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Susitna-Watana Hydroelectric Project Document
ARLIS Uniform Cover Page
Title:
Draft Susitna River productivity study implementation plan
SuWa 26
Author(s) – Personal:
Author(s) – Corporate:
R2 Resource Consultants, Inc.
AEA-identified category, if specified:
January 31, 2013 Filing
AEA-identified series, if specified:
Series (ARLIS-assigned report number):
Susitna-Watana Hydroelectric Project document number 26
Existing numbers on document:
Published by:
[Anchorage, Alaska : Alaska Energy Authority, 2013]
Date published:
January 2013
Published for:
Prepared for Alaska Energy Authority
Date or date range of report:
Volume and/or Part numbers:
Attachment D
Final or Draft status, as indicated:
Draft
Document type:
Pagination:
viii, 79, [32] p.
Related work(s):
Cover letter (SuWa 22), Attachments A-C, E (SuWa 23-25, 27)
Pages added/changed by ARLIS:
Added cover letter
Notes:
All reports in the Susitna-Watana Hydroelectric Project Document series include an ARLIS-
produced cover page and an ARLIS-assigned number for uniformity and citability. All reports
are posted online at http://www.arlis.org/resources/susitna-watana/
1
January 31,2013
Ms. Kimberly Bose
Secretary
Federal Energy Regulatory Commission
888 First Street, NE
Washington, DC 20426
Re: Susitna-Watana Hydroelectric Project, FERC Project No. 14241-000
Dear Secretary Bose:
By letter dated January 17, 2013, Staff of the Federal Energy Regulatory
Commission (Commission) issued a modified schedule for its April 1, 2013 study plan
determination (SPD)for 13 of the individual studies contained in the Alaska Energy
Authority’s (AEA) Revised Study Plan (RSP) for the Susitna-Watana Hydroelectric
Project, FERC Project No. 14241.1 Among other milestones, Staff’s modified schedule
required AEA to file specified information related to these 13 individual studies by
January 31, 2013, and to convene public meetings on February 14-15, 2013, to discuss
these materials with federal and state resource agencies and other licensing participants.
In accordance with Staff’s modified schedule, the purposes of this filing are to: (1)
submit all information specified by Staff for filing by January 31; and (2) provide details
of the public meetings to be held in Anchorage, Alaska, on February 14-15, 2013.
Description of Attached Information
Commission Staff’s January 17 modified schedule required AEA to file the
following information by January 31, 2013:
results of 2012 open-water flow routing model and habitat mapping; draft
implementation plans for the Fish Distribution and Abundance in the
Upper Susitna River (study 9.5), the Fish Distribution and Abundance in
the Lower and Middle Susitna River (study 9.6), and River Productivity
1 See Letter from Jeff C. Wright, Federal Energy Regulatory Commission, to Wayne Dyok, Alaska
Energy Authority, Attachment A, Project No. 14241-000 (issued Jan. 17, 2013)[hereinafter, Schedule
Modification Letter]. The 13 individual studies scheduled for Staff’s April 1 SPD consist of the following:
(1) Baseline Water Quality (RSP 5.5); (2) Water Quality Modeling Study (RSP 5.6); (3) Mercury
Assessment and Potential for Bioaccumulation Study (RSP 5.7); (4) Geomorphology Study (RSP 6.5); (5)
Fluvial Geomorphology Modeling Below Watana Dam Study (RSP 6.6); (6) Groundwater Study (RSP 7.5);
(7) Ice Processes in the Susitna River Study (RSP 7.6); (8) Fish and Aquatics Instream Flow Study (RSP
8.5); (9) Riparian Instream Flow Study (RSP 8.6); (10) Study of Fish Distribution and Abundance in the
Upper Susitna River (RSP 9.5); (11) Study of Fish Distribution and Abundance in the Middle and Lower
Susitna River (RSP 9.6); (12) River Productivity Study (RSP 9.8); and (13) Characterization and Mapping
of Aquatic Habitats (RSP 9.9).
2
(study 9.8) studies; all proposed focus areas; and a description of habitat
units within the focus areas for all aquatic studies to be implemented in the
middle Susitna River.2
In response to Staff’s request, and in furtherance of its efforts to finalize study reports
associated with its 2012 early licensing studies, AEA has prepared several study reports
and technical memoranda containing all the requested information. The information
requested by Commission Staff appears in the attachments as follows:
Requested Information Attachment
Results of 2012 Open-Water Flow Routing Attachment A, Open Water HEC-RAS
Flow Routing Model (January 2013)
Results of 2012 Habitat Mapping Attachment B, Middle Susitna River
Segment Remote Line Habitat Mapping
Technical Memo (January 2013)
Draft Implementation Plan for Study of
Fish Distribution and Abundance in the
Upper Susitna River (RSP 9.5)
Attachment C, Draft Susitna River Fish
Distribution and Abundance
Implementation Plan (January 2013)
Draft Implementation Plan for Study of
Fish Distribution and Abundance in the
Middle and Lower Susitna River (RSP 9.6)
Attachment C, Draft Susitna River Fish
Distribution and Abundance
Implementation Plan (January 2013)
Draft Implementation Plan for River
Productivity Study (RSP 9.8)
Attachment D, Draft Susitna River
Productivity Study Implementation Plan
(January 2013)
Proposed Focus Areas Attachment E, Selection of Focus Areas
and Study Sites in the Middle and Lower
Susitna River for Instream Flow and Joint
Resource Studies –2013 and 2014
(January 2013)
Description of Habitat Units within Focus
Areas for All Aquatic Studies to Be
Implemented in the Middle Susitna River
Attachment E, Selection of Focus Areas
and Study Sites in the Middle and Lower
Susitna River for Instream Flow and Joint
Resource Studies –2013 and 2014
(January 2013)
Details of Public Meetings
Commission Staff’s modified schedule directed AEA to hold meetings on
February 14-15, 2013, “to discuss the study results, proposed implementation plans, and
selected focus areas in the middle and lower Susitna River.”3 These Technical
Workgroup (TWG) meetings, which are open to federal and state resource agencies, other
licensing participants, and interested members of the public, will begin each day at 8:30
a.m. (Alaska Standard Time), and will be held in the Public Conference Room of the Z.J.
2 Schedule Modification Letter, Attachment A.
3 Id.
3
Loussac Public Library, located at 3600 Denali Street, Anchorage, Alaska. Additional
information regarding these TWG meetings—including instructions for participating
online and via teleconference for those unable to attend in person—appear at AEA’s
licensing website, http://www.susitna-watanahydro.org/meetings/. More detailed
information regarding these TWG meetings, including a draft agenda, will be posted to
the website in the coming days.
AEA looks forward to discussing these materials in the upcoming TWG meetings.
These discussions will inform and assist AEA in its development of the final
implementation plans for the Study of Fish Distribution and Abundance in the Upper
Susitna River (RSP 9.5), Study of Fish Distribution and Abundance in the Middle and
Lower Susitna River (RSP 9.6), and River Productivity Study (RSP 9.8). As provided in
Commission Staff’s modified schedule, AEA will file these final implementation plans
with the Commission by March 1, 2013.
AEA acknowledges and greatly appreciates the participation and commitment to
this licensing process of Commission Staff, federal and state resource agencies, and other
licensing participants. AEA is particularly appreciative of all participants’ efforts to date
to work efficiently and collaboratively in developing a robust study plan that can be
approved by Commission Staff in accordance with the modified schedule and
implemented beginning with the 2013 field season.
If you have questions concerning this submission please contact me at
wdyok@aidea.org or (907) 771-3955.
Sincerely,
Wayne Dyok
Project Manager
Alaska Energy Authority
Attachments
cc: Distribution List (w/o Attachments)
Attachment D
Draft Susitna River Productivity Study
Implementation Plan (January 2013)
Susitna-Watana Hydroelectric Project
(FERC No. 14241)
Draft Susitna River Productivity Study
Implementation Plan
Prepared for
Alaska Energy Authority
Prepared by
R2 Resource Consultants, Inc.
January 2013
DRAFT REPORT RIVER PRODUCTIVITY IMPLEMENTATION PLAN
Susitna-Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page i January 2013
TABLE OF CONTENTS
1. Introduction ........................................................................................................................1
1.1. Study Goals and Objectives ...............................................................................2
1.2. Study Area .........................................................................................................3
1.3. Background ........................................................................................................3
1.3.1. Historic Data Collection Efforts ..................................................... 3
1.3.2. Life History Summary of Susitna Target Fish Species ................... 5
1.3.3. Middle River Mainstem Habitat Delineation Results ................... 18
1.3.4. Documentation of TWG input to site selection protocol .............. 19
2. Methods .............................................................................................................................20
2.1. Sampling Site Selection Protocols ...................................................................20
2.1.1. Middle River Segment Stations / Focus Areas ............................. 20
2.1.2. Upper Segment Stations ................................................................ 21
2.1.3. Talkeetna Station .......................................................................... 21
2.2. Benthic Macroinvertebrate Sampling ..............................................................22
2.2.1. Field Sampling Protocols .............................................................. 22
2.2.2. Sample Processing Protocols ........................................................ 26
2.2.3. Data Analysis Methods ................................................................. 26
2.3. Benthic Algae Sampling ..................................................................................27
2.3.1. Field Sampling Protocols .............................................................. 27
2.3.2. Processing Protocols ..................................................................... 28
2.3.3. Data Analysis Methods ................................................................. 30
2.4. Organic Matter Sampling .................................................................................30
2.4.1. Field Sampling Protocols .............................................................. 31
2.4.2. Processing Protocols ..................................................................... 31
2.4.3. Data Analysis Methods ................................................................. 32
2.5. Invertebrate Drift Sampling .............................................................................32
2.5.1. Field Sampling Protocols .............................................................. 33
2.5.2. Processing Protocols ..................................................................... 35
2.5.3. Analysis Protocols ........................................................................ 35
2.6. Adult Insect Emergence Sampling ...................................................................35
DRAFT REPORT RIVER PRODUCTIVITY IMPLEMENTATION PLAN
Susitna-Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page ii January 2013
2.6.1. Field Sampling Protocols .............................................................. 35
2.6.2. Processing Protocols ..................................................................... 36
2.6.3. Data Analysis Methods ................................................................. 36
2.7. Fish Scale Sampling .........................................................................................36
2.7.1. Field Sampling Protocols .............................................................. 36
2.7.2. Processing Protocols ..................................................................... 37
2.7.3. Data Analysis Methods ................................................................. 37
2.8. Fish Gut Content Sampling ..............................................................................38
2.8.1. Field Sampling Protocols .............................................................. 38
2.8.2. Processing Protocols ..................................................................... 38
2.8.3. Data Analysis Methods ................................................................. 38
2.9. Macroinvertebrate Colonization Sampling ......................................................39
2.9.1. Field Sampling Protocols .............................................................. 39
2.9.2. Processing Protocols ..................................................................... 41
2.9.3. Data Analysis Methods ................................................................. 41
2.10. Trophic Modeling ............................................................................................41
2.10.1. Data Analysis Methods ................................................................. 41
2.11. Stable Isotope Analysis ....................................................................................43
2.11.1. Field Sampling Protocols .............................................................. 43
2.11.2. Processing Protocols ..................................................................... 43
2.11.3. Data Analysis Methods ................................................................. 44
2.12. Data Management ............................................................................................44
2.12.1. Established QA/QC Protocol ........................................................ 44
2.12.2. Relational Database ...................................................................... 45
3. Schedule ............................................................................................................................45
4. Field Equipment List .......................................................................................................46
5. References .........................................................................................................................47
6. Tables ................................................................................................................................58
7. Figures ...............................................................................................................................63
DRAFT REPORT RIVER PRODUCTIVITY IMPLEMENTATION PLAN
Susitna-Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page iii January 2013
LIST OF TABLES
Table 1.2-1. Locations and descriptions of proposed Focus Areas selected for the River
Productivity study in the Middle River Segment of the Susitna River. Focus Area
identification numbers (e.g., Focus Area 184) represent the truncated Project River Mile
(PRM) at the downstream end of each Focus Area. ............................................................. 59
Table 2.2-1. Descriptive metrics commonly used in aquatic ecological studies to describe
benthic macroinvertebrate (BMI) communities. ................................................................... 60
Table 2.8-1. Itemized listing of the number of fish gut content samples to collect for the River
Productivity Study in each study year. ................................................................................. 61
Table 2.11-1. Itemized listing of sample components to collect for Stable Isotope Analysis at the
two sampling stations (6 sites total) in each study year in the Middle Segment of the Susitna
River for the River Productivity Study. ................................................................................ 61
Table 3.1-1. Preliminary schedule for River Productivity Study................................................. 62
LIST OF FIGURES
Figure 1.2-1. Upper Susitna River Segment, with the two proposed River Productivity sampling
stations selected for the River Productivity Study. ............................................................... 64
Figure 1.2-2. Middle Susitna River Segment, with the four proposed River Productivity sampling
stations /Instream Flow Focus Areas selected for the River Productivity Study. ................. 65
Figure 1.3-1. Total catch of juvenile coho salmon by sample period and gear type at DFH sites
in 1982. Source: Estes and Schmidt 1983 ............................................................................ 66
Figure 1.3-2. Seasonal distribution and relative abundance of juvenile coho salmon on the
Susitna River between the Chulitna River confluence and Devil Canyon, May through
November 1983. Source: Dugan et al. (1984). .................................................................... 67
Figure 1.3.3. Density distribution and juvenile coho salmon by macrohabitat type on the Susitna
River between the Chulitna River confluence and Devil Canyon, May through November
1983. Percentages are based on mean catch per cell. Source: Dugan et al. (1984). ............. 68
Figure 1.3-4. Total catch of juvenile Chinook salmon by sample period and gear type at DFH
sites in 1982. Source: Estes and Schmidt 1983 .................................................................... 69
Figure 1.3-5. Seasonal distribution and relative abundance of juvenile Chinook salmon on the
Susitna River between the Chulitna River confluence and Devil Canyon, May through
November 1983. Source: Dugan et al. (1984). .................................................................... 70
Figure 1.3-6. Density distribution and juvenile Chinook salmon by macrohabitat type on the
Susitna River between the Chulitna River confluence and Devil Canyon, May through
November 1983. Percentages are based on mean catch per cell. Source: Dugan et al. (1984).
............................................................................................................................................... 71
Figure 1.3-7. Total catch of rainbow trout by sample period and gear type at DFH sites in 1982.
Source: .................................................................................................................................. 72
DRAFT REPORT RIVER PRODUCTIVITY IMPLEMENTATION PLAN
Susitna-Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page iv January 2013
Figure 2.1-1. Map showing Focus Area 184 that begins at Project River Mile 184.7 and extends
upstream to PRM 185.7. The Focus Area is located about 1.4 miles downstream of the
proposed Watana Dam site near Tsusena Creek. .................................................................. 73
Figure 2.1-2. Map showing Focus Area 173 beginning at Project River Mile 173.6 and extends
upstream to PRM 175.4. This Focus Area is near Stephan Lake and consists of main
channel and a side channel complex. .................................................................................... 74
Figure 2.1-3. Map showing Focus Area 141 beginning at Project River Mile 141.8 and extends
upstream to PRM 143.4. This Focus Area includes the Indian River confluence and a range
of main channel and off-channel habitats. ............................................................................ 75
Figure 2.1-4. Map showing Focus Area 104 beginning at Project River Mile 104.8 and extends
upstream to PRM 106. This Focus Area covers the diverse range of habitats in the Whiskers
Slough complex. ................................................................................................................... 76
Figure 2.1-5. Map showing Focus Area 144 beginning at Project River Mile 144.4 and extends
upstream to PRM 145.7. This Focus Area is located about 2.3 miles upstream of Indian
River and includes Side Channel 21 and Slough 21. ............................................................ 77
Figure 2.1-6. Map showing the River Productivity Upper Segment sampling station located in
the proximity of the mouth of the Oshetna River beginning approximately at Project River
Mile 232.4 and extends upstream to approximately PRM 233.6. ......................................... 78
Figure 2.1-7. Map showing the River Productivity Upper Segment sampling station located
upstream of the Tyone River beginning approximately at Project River Mile 428.2 and
extends upstream to approximately PRM 249.5. .................................................................. 79
Figure 2.2-1. Sampling equipment used to collect benthic macroinvertbrates in streams and
rivers. Top left: Hess stream sampler. Top right: drift net. Middle: examples of floating
aquatic insect emergence traps. Bottom: Hester-Dendy multiplate sampler. ..................... 80
APPENDICES
Appendix 1. Major and Barbour 2001. Standard Operating Procedures Processing for the
Alaska Stream Condition Index: Method 002 – Laboratory
Appendix 2. Field Data Forms
Appendix 3. Susitna Data Standards
Appendix 4. Draft Database Templates
DRAFT REPORT RIVER PRODUCTIVITY IMPLEMENTATION PLAN
Susitna-Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page v January 2013
LIST OF ACRONYMS AND SCIENTIFIC LABELS
Abbreviation Definition
ADF&G Alaska Department of Fish and Game
ADNR Alaska Department of Natural Resources
AEA Alaska Energy Authority
Anadromous Fishes that migrate as juveniles from freshwater to saltwater and then return as
adults to spawn in freshwater.
APA Alaska Power Authority
APA Project APA Susitna Hydroelectric Project
Baseline
Baseline (or Environmental Baseline): the environmental conditions that are the
starting point for analyzing the impacts of a proposed licensing action (such as
approval of a license application) and any alternative.
Benthos (benthic) Defining a habitat or organism found on the streambed or pertaining to the
streambed (or bottom) of a water body.
Braided streams
Stream consisting of multiple small, shallow channels that divide and recombine
numerous times. Associated with glaciers, the braiding is caused by excess
sediment load.
Cascade
The steepest of riffle habitats. Unlike rapids, which have an even gradient,
cascades consist of a series of small steps of alternating small waterfalls and
shallow pools.
cfs cubic feet per second
Channel A natural or artificial watercourse that continuously or intermittently contains water,
with definite bed and banks that confine all but overbank stream flows.
Cross-section A plane across a river or stream channel perpendicular to the direction of water
flow.
Depth Water depth at the measuring point (station).
Devils Canyon
Located at approximately Susitna River Mile (RM) 150-161, Devils Canyon contains
four sets of turbulent rapids rated collectively as Class VI. This feature is a partial
fish barrier because of high water velocity.
Distribution (species) The manner in which a biological taxon is spatially arranged.
et al. “et alia”; and the rest
FERC Federal Energy Regulatory Commission
Flood Any flow that exceeds the bankfull capacity of a stream or channel and flows out on
the floodplain.
Floodplain
1. The area along waterways that is subject to periodic inundation by out-of-bank
flows. 2. The area adjoining a water body that becomes inundated during periods of
over-bank flooding and that is given rigorous legal definition in regulatory programs.
3. Land beyond a stream channel that forms the perimeter for the maximum
probability flood. 4. A relatively flat strip of land bordering a stream that is formed by
sediment deposition. 5. A deposit of alluvium that covers a valley flat from lateral
erosion of meandering streams and rivers.
Focus Area Areas selected for intensive investigation by multiple disciplines as part of the AEA
study program.
Geomorphic reach Level two tier of the habitat classification system. Separates major hydraulic
segments into unique reaches based on the channel’s geomorphic characteristic.
Geomorphology The scientific study of landforms and the processes that shape them.
GIS Geographic Information System. An integrated collection of computer software and
data used to view and manage information about geographic places, analyze
DRAFT REPORT RIVER PRODUCTIVITY IMPLEMENTATION PLAN
Susitna-Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page vi January 2013
Abbreviation Definition
spatial relationships, and model spatial processes.
Glide An area with generally uniform depth and flow with no surface turbulence. Low
gradient; 0-1 % slope.
GPS global positioning system. A system of radio-emitting and -receiving satellites used
for determining positions on the earth.
Groundwater (GW) In the broadest sense, all subsurface water; more commonly that part of the
subsurface water in the saturated zone.
Habitat
The environment in which the fish live, including everything that surrounds and
affects its life, e.g. water quality, bottom, vegetation, associated species (including
food supplies). The locality, site and particular type of local environment occupied
by an organism.
ILP Integrated Licensing Process
Instream flow The rate of flow in a river or stream channel at any time of year.
Juvenile A young fish or animal that has not reached sexual maturity.
licensing participants; Participants Agencies, ANSCA corporations, Alaska Native entities and other licensing
participants
Lower segment Susitna The Susitna River from Cook Inlet (RM 0) to the confluence of the Chulitna River at
RM 98.
Main channel For habitat classification system: a single dominant main channel. Also, the primary
downstream segment of a river, as contrasted to its tributaries.
Main channel habitat
Level four tier of the habitat classification system. Separates main channel habitat
types including: tributary mouth, main channel, split main channel, multiple split
main channel and side channel into mesohabitat types. Mesohabitat tyes include
pool, glide, run, riffle, and rapid.
Mainstem
Mainstem refers to the primary river corridor, as contrasted to its tributaries.
Mainstem habitats include the main channel, split main channels, side channels,
tributary mouths, and off-channel habitats.
Mainstem habitat
Level three tier of the habitat classification systems. Separates mainstem habitat
into main channel, off-channel, and tributary habitat types. Main channel habitat
types include: tributary mouth, main channel, split main channel, multiple split main
channel and side channel. Off-channel habitat types include: side slough, upland
slough, backwater, and beaver complex. Tributary habitat is not further categorized.
Major hydraulic segment
Level one tier of the habitat classification system. Separates the River into three
segments: Lower River (RM 0-98), Middle River (RM 98-184), and Upper River (RM
184-233).
Mesh size The size of holes in a fishing net.
Mesohabitat
A discrete area of stream exhibiting relatively similar characteristics of depth,
velocity, slope, substrate, and cover, and variances thereof (e.g., pools with
maximum depth <5 ft, high gradient rimes, side channel backwaters).
Middle segment Susitna The Susitna River from the confluence of the Chulitna River at RM 98 to the
proposed Watana Dam Site at RM 184.
Migrant (life history type) Some species exhibit a migratory life history type and undergo a migration to from
rivers/lakes/ocean.
Migration Systematic (as opposed to random) movement of individuals of a stock from one
place to another, often related to season.
Minnow trap Normally composed of small steel mesh with 2-piece torpedo shape design, this
trap is disconnected in the middle for easy baiting and fish removal.
N/A not applicable or not available
Non-native Not indigenous to or naturally occurring in a given area.
DRAFT REPORT RIVER PRODUCTIVITY IMPLEMENTATION PLAN
Susitna-Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page vii January 2013
Abbreviation Definition
ºC degrees Celsius
ºF degrees Fahrenheit
Off-channel Those bodies of water adjacent to the main channel that have surface water
connections to the main river at some discharge levels.
Off-channel habitat Habitat within those bodies of water adjacent to the main channel that have surface
water connections to the main river at some discharge levels.
Outmigrant trap Several types of trapping equipment that can be used to estimate the abundance of
downstream migrating anadromous salmonid smolts.
Overwintering
Freshwater habitat used by salmonids during the winter for incubation of eggs and
alevin in the gravel and for rearing of juveniles overwintering in the stream system
before migrating to saltwater the following spring.
pH A measure of the acidity or basicity of a solution.
PIT Passive Integrated Transponder tags used to individually identify animals and
monitor their movements.
PM&E protection, mitigation and enhancement
Pool Slow water habitat with minimal turbulence and deeper due to a strong hydraulic
control.
PRM
Project River Mile(s) based on the digitized wetted width centerline of the main
channel from 2012 Matanuska-Susitna Borough digital orthophotos. PRM 0.0 is
established as mean lower low water of the Susitna River confluence at Cook Inlet.
Project Susitna-Watana Hydroelectric Project
Radiotelemetry Involves the capture and placement of radio-tags in adult fish that allow for the
remote tracking of movements of individual fish.
Rapid
Swift, turbulent flow including small chutes and some hydraulic jumps swirling
around boulders. Exposed substrate composed of individual boulders, boulder
clusters, and partial bars. Lower gradient and less dense concentration of boulders
and white water than Cascade. Moderate gradient; usually 2.0-4.0% slope.
Resident Resident fish as opposed to anadromous remain in the freshwater environment
year-round
Riffle
A fast water habitat with turbulent, shallow flow over submerged or partially
submerged gravel and cobble substrates. Generally broad, uniform cross-section.
Low gradient; usually 0.5-2.0% slope.
Riparian Pertaining to anything connected with or adjacent to the bank of a stream or other
body of water.
River A large stream that serves as the natural drainage channel for a relatively large
catchment or drainage basin.
River corridor
A perennial, intermittent, or ephemeral stream and adjacent vegetative fringe. The
corridor is the area occupied during high water and the land immediately adjacent,
including riparian vegetation that shades the stream, provides input of organic
debris, and protects banks from excessive erosion.
River mile The distance of a point on a river measured in miles from the river's mouth along
the low-water channel.
RM River Mile(s) referencing those of the APA Project.
RSP Revised Study Plan
Run (habitat)
A habitat area with minimal surface turbulence over or around protruding boulders
with generally uniform depth that is generally greater than the maximum substrate
size. Velocities are on border of fast and slow water. Gradients are approximately
0.5 % to less than 2%. Generally deeper than riffles with few major flow
obstructions and low habitat complexity.
DRAFT REPORT RIVER PRODUCTIVITY IMPLEMENTATION PLAN
Susitna-Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page viii January 2013
Abbreviation Definition
Run (migration)
Seasonal migration undertaken by fish, usually as part of their life history; for
example, spawning run of salmon, upstream migration of shad. Fishers may refer to
increased catches as a “run” of fish, a usage often independent of their migratory
behavior.
Side channel
Lateral channel with an axis of flow roughly parallel to the mainstem, which is fed by
water from the mainstem; a braid of a river with flow appreciably lower than the
main channel. Side channel habitat may exist either in well-defined secondary
(overflow) channels, or in poorly-defined watercourses flowing through partially
submerged gravel bars and islands along the margins of the mainstem.
Side slough Off-channel habitat characterization of an Overflow channel contained in the
floodplain, but disconnected from the main channel. Has clear water,
Slope The inclination or gradient from the horizontal of a line or surface.
Slough
A widely used term for wetland environment in a channel or series of shallow lakes
where water is stagnant or may flow slowly on a seasonal basis. Also known as a
stream distributary or anabranch.
Spawning The depositing and fertilizing of eggs by fish and other aquatic life.
Split main channel Main channel habitat characterization where three of fewer distributed dominant
channels.
Stratified sampling
A method of sampling from a population. In statistical surveys, when
subpopulations within an overall population vary, it is advantageous to sample each
subpopulation (stratum) independently. Stratification is the process of dividing
members of the population into homogeneous subgroups before sampling.
Three Rivers Confluence
The confluence of the Susitna, Chulitna, and Talkeetna rivers at Susitna River Mile
(RM) 98.5 represents the downstream end of the Middle River and the upstream
end of the Upper River.
Tributary A stream feeding, joining, or flowing into a larger stream (at any point along its
course or into a lake). Synonyms: feeder stream, side stream.
TWG Technical Workgroup
Upland slough
Off-channel habitat characterization feature that is similar to a side slough, but
contains a vegetated bar at the head that is rarely overtopped by mainstem flow.
Has clear water.
Upper segment Susitna The Susitna River upstream of the proposed Watana Dam Site at RM 184.
Watana Dam
The dam proposed by the Susitna-Watana Hydroelectric project. The approximately
750-foot-high Watana Dam (as measured from sound bedrock) would be located at
river mile (RM) 184 on the Susitna River. The dam would block the upstream
passage of Chinook salmon, possibly other salmon species, and resident fish that
migrate through and otherwise use the proposed Watana Dam site and upstream
habitat in the Susitna River and tributaries.
DRAFT REPORT RIVER PRODUCTIVITY IMPLEMENTATION PLAN
Susitna-Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 1 January 2013
1. INTRODUCTION
The Alaska Energy Authority (AEA) is preparing a License Application that will be submitted to
the Federal Energy Regulatory Commission (FERC) for the Susitna-Watana Hydroelectric
Project (Project) using the Integrated L ice nsing Process (ILP). The Project is located on the
Susitna River, an approximately 300-mile-long river in Southcentral Alaska. The Project’s dam
site will be located at river mile (RM) 184, corresponding to Project RM (PRM) 187.1 of the
updated GIS-based hydrography.
AEA filed the Revised Study Plan with FERC on December 14, 2012, which included a River
Productivity Study (RSP Section 9.8). The overarching goal of the River Productivity Study is to
collect baseline data to assist in evaluating the effects of Project-induced changes in flow and the
interrelated environmental factor upon the benthic macroinvertebrate and algal communities in
the Middle and Upper Susitna River. This implementation plan fulfills portions of the River
Productivity Plan.
As described in RSP Section 9.8.1, the production of freshwater fishes in a given habitat is
constrained both by the suitability of the abiotic environment and by the availability of food
resources (Wipfli and Baxter 2010). Algae are an important base component in the lotic food
web, being responsible for the majority of photosynthesis in a river or stream and serving as an
important food source to many benthic macroinvertebrates. In turn, benthic macroinvertebrates
are an essential component in the processes of an aquatic ecosystem due to their position as
consumers at the intermediate trophic level of lotic food webs (Hynes 1970; Wallace and
Webster 1996; Hershey and Lamberti 2001). Macroinvertebrates are involved in the recycling of
nutrients and the decomposition of terrestrial organic materials in the aquatic environment,
serving as a conduit for the energy flow from organic matter resources to vertebrate populations,
namely fish (Hershey and Lamberti 2001; Hauer and Resh 1996; Reice and Wohlenberg 1993;
Klemm et al. 1990). ). In turn, nutrients and energy provided by spawning salmon have the
potential to increase freshwater and terrestrial ecosystem productivity (Wipfli et al. 1998;
Cederholm et al. 1999; Chaloner and Wipfli 2002; Bilby et al. 2003; Hicks et al. 2005) and may
subsidize otherwise nutrient-poor ecosystems (Cederholm et al. 1999). Recent studies have
demonstrated the important role benthic macroinvertebrates play in processing salmon carcasses
of coastal streams (Cederholm et al. 1999, Chaloner and Wipfli 2002).
The significant functional roles that macroinvertebrates and algae play in food webs and energy
flow in the freshwater ecosystem make these communities important elements in the study of a
stream’s ecology. The operations of the proposed Project would likely shift one or more
environmental factors that can affect the abundance and distribution of benthic algae and benthic
macroinvertebrate populations, with an upward food chain effect on fish growth and productivity
in the ecosystem. The degree of impact on the benthic communities and fish resulting from
hydropower operations will necessarily vary depending on the magnitude, frequency, duration,
and timing of flows, as well as potential Project-related changes in geomorphology, ice
processes, temperature, and turbidity. By investigating the current condition of algal
populations, benthic macroinvertebrates, and fish in the Susitna River and the trophic
relationships between them, this study will provide a better understanding how changes in
environmental factors might affect the availability and utilization of food resources at each
trophic level in the system. In addition, by applying what is known about the effects of river
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regulation and hydropower operation on these populations in riverine ecosystems, AEA can
begin to assess the potential impacts of Project operations on river productivity in the Susitna
River, as well as provide information to inform development of any necessary protection,
mitigation, and enhancement (PM&E) measures, as appropriate.
The River Productivity Study (RSP Section 9.8) includes the description of the sampling scheme.
However, decisions regarding specific site locations, timing, sampling devices, processing, and
analyses were dependent upon recent results from 2012 data collection efforts.
A limited review of these 2012 results was used as a guide for a more detailed plan. This River
Productivity Implementation Plan includes specific details for methods that will be used to
conduct elements of this River Productivity Study.
Consistent with the RSP Section 9.8.4, this implementation plan includes: (1) a summary of
relevant macroinvertebrate and algal studies in the Susitna River (Section 1.3.1), (2) an overview
of the life-histories of the target fish species in the Susitna River that are selected for the trophic
analysis (Section 1.3.2), (3) a review of the preliminary results of habitat characterization and
mapping efforts and “Focus Areas” (Section 1.3.3), (4) a description of site selection protocols
(Section 2.1), (5) a description of sampling protocols (Sections 2.2 through 2.11), (6) a
description of sample processing protocols (Sections 2.2 through 2.11, and Appendix 1), (7) a
discussion of data analysis methods (Sections 2.2 through 2.11), (8) development of field data
collection forms (Appendix 2), and (9) development of database templates that comply with
2012 AEA QA/QC procedures (Section 2.12, and Appendices 3 and 4).
This implementation plan includes a level of detail sufficient to instruct field crews in data
collection efforts. In addition, the plan includes protocols that will be used in the field, specific
sampling locations, details about the choice and use of sampling techniques and equipment. The
implementation plan will ensure that field collection efforts are consistent and repeatable among
field crews and between river segments.
1.1. Study Goals and Objectives
To review, the overarching goal of the River Productivity study is to collect baseline data to
assist in evaluating the potential Project-induced changes in flow and effects on environmental
factors (e.g., temperature, substrate, water quality), and benthic macroinvertebrate and algal
communities in the Middle and Upper Susitna River. Individual objectives that will accomplish
this are as follows:
1. Synthesize existing literature on the impacts of hydropower development and operations
(including temperature and turbidity) on benthic macroinvertebrate and algal
communities.
2. Characterize the pre-Project benthic macroinvertebrate and algal communities with
regard to species composition and abundance in the Middle and Upper Susitna River.
3. Estimate drift of benthic macroinvertebrates in selected habitats within the Middle and
Upper Susitna River to assess food availability to juvenile and resident fishes.
4. Conduct a feasibility study in 2013 to evaluate the suitability of using reference sites on
the Talkeetna River to monitor long-term Project-related change in benthic productivity.
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5. Conduct a trophic analysis to describe the food web relationships within the current
riverine community within the Middle and Upper Susitna River.
6. Develop habitat suitability criteria for Susitna benthic macroinvertebrate and algal
habitats to predict potential change in these habitats downstream of the proposed dam
site.
7. Characterize the invertebrate compositions in the diets of representative fish species in
relationship to their source (benthic or drift component).
8. Characterize organic matter resources (e.g., available for macroinvertebrate consumers)
including coarse particulate organic matter, fine particulate organic matter, and
suspended organic matter in the Middle and Upper Susitna River.
9. Estimate benthic macroinvertebrate colonization rates in the Middle Susitna Segment
under pre-Project baseline conditions to assist in evaluating future post-Project changes
to productivity in the Middle Susitna River.
1.2. Study Area
The Study Area for this implementation is described in RSP Section 9.8.3. The River
Productivity Study will entail field sampling throughout the Upper Segment and Middle Segment
on the Susitna River (Table 1.2-1; Figures 1.2-1 and 1.2-2).
1.3. Background
1.3.1. Historic Data Collection Efforts
A number of evaluations of the benthic macroinvertebrate community were conducted on the
Susitna River in the 1970s and in the 1980s for the original Alaska Power Authority (APA)
Susitna Hydroelectric Project (Friese 1975; Riis 1975, 1977; ADF&G 1983a; Hansen and
Richards 1985; Van Nieuwenhuyse 1985; Trihey and Associates 1986). ADF&G studies in the
1970s included sampling of macroinvertebrates using artificial substrates (i.e., rock baskets)
deployed for a set period of time to allow for colonization. Friese (1975) set a total of eight rock
baskets in Waterfall Creek and Indian River in various habitats (e.g., deep and shallow pool,
deep and shallow riffle, quiet water) to determine species composition of the insect population in
tributary streams. Rock baskets returned extremely low numbers of invertebrates, which were all
aquatic insects, largely due to inadequate time allowed for colonization, as well as survey timing.
The most common insects were Isoperla stonef1ies (P1ecoptera: Perlodidae) and "no-see-ums"
(Diptera: Ceratopogonidae), with simuliid blackfly larvae (Diptera: Simuliidae), flat-headed
mayfly nymphs (Ephemeroptera: Heptageniidae), and some predaceous caddisfly larvae also
present (Friese 1975). Stomach content analysis of coho salmon fry was also collected at
Sloughs 9, 11, and 15 on the Susitna River (August and September), and at Slough Number 2 on
the Talkeetna River (June) to provide comparative data on food availability. Results
demonstrated the importance of insect larvae, particularly Trichoptera and Diptera, in the diets of
rearing fish. Salmon eggs were also an important food source. A larger variety of insects were
present in the Talkeetna River stomach samples, probably due to the earlier time of year at which
those fry were collected.
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Riis (1975) used a total of eight rock baskets, colonized for 30 days during summer (July –
September), to sample the mainstem Susitna River and Waterfall Creek in the Middle Susitna
River segment. Mainstem Susitna River sites included points just upstream of the Deshka River
and Willow Creek in the Lower Segment and above Gold Creek in the Middle Segment. Fourth
of July Creek was also sampled using a kick screen. Numbers of organisms collected per site
were low; the most common insects were stonef1ies (P1ecoptera: Perlodidae), mayfly nymphs
(Ephemeroptera: Heptageniidae and Baetidae), and caddisfly larvae (Trichoptera:
Rhyacophilidae and Sericostomatidae). Riis (1977) later deployed rock baskets in the Susitna
River at several locations near the mouth of Gold Creek for a colonization period of 75 days;
however, only two of seven baskets were retrieved. The two baskets collected a total of 118
organisms, comprised of 77 Plecoptera, 66 Ephemeroptera, and 55 Diptera.
Studies conducted in the 1980s for the original APA Susitna Hydroelectric Project focused on
benthic macroinvertebrate communities in the sloughs, side channels, and tributaries of the
Middle Segment of the Susitna River from RM 125 to RM 142 during the period from May
through October. Efforts included direct benthic sampling with a kick screen or a Hess bottom
sampler, and drift sampling. Alaska Department of Fish and Game (ADF&G) efforts in 1982
and 1984 also involved collection of juvenile salmon in these side channels and sloughs, and an
analysis was conducted to compare gut contents with the drift and benthic sampling results
(ADF&G 1983a; Hansen and Richards 1985). In addition, Hansen and Richards (1985)
collected water velocity, depth, and substrate-type data to develop habitat suitability criteria
(HSC), which were used to estimate weighted usable areas for different invertebrate community
guilds, based on their behavioral type (swimmers, burrowers, clingers) in slough and side
channel habitats. Efforts in 1985 (Trihey and Associates 1986) expanded to include sampling at
nine sites in the Middle Susitna River Segment: three side channels, two sloughs, two tributaries,
and two mainstem sites. Results presented are data in tabular format, by site and date, of
samples processed to that point in time, and are not expanded or summarized, so limited
conclusions can be made.
Algal communities were periodically sampled and analyzed for chlorophyll-a (chl-a) at Susitna
Station from 1978 to 1980. In the 1980s, algae samples were collected as part of the APA
Susitna Hydroelectric Project water quality studies, with sampling conducted at Denali, Cantwell
(Vee Canyon), Gold Creek, Sunshine, and Susitna Station gage sites on the Susitna River, as
well as on the Chulitna and Talkeetna rivers (Harza-Ebasco 1985 as cited in AEA 2011).
Analysis showed low productivity (less than 1.25 mg/m3 chl-a) and indicated algal abundance
was most likely limited by high concentrations of suspended sediment and turbidity (AEA 2011).
Baseline field data for estimating benthic primary and secondary production was also collected
in 1985, as part of the Primary Production Monitoring Effort (Van Nieuwenhuyse 1985).
Chlorophyll-a and macroinvertebrates were collected from early April to late October 1985 from
a variety of off-channel and mainstem habitat sites. Early April sampling took place in an open-
water lead in Slough 8A and revealed high macroinvertebrate densities (averaging 17,600
individuals/m2) comprised almost entirely of chironomid larvae and chlorophyll-a densities
averaging 34.4 mg/m2. Sampling in early May in Slough 8A revealed macroinvertebrate
densities averaging 2,950 individuals/m2, dominated by chironomids, with chl-a densities
averaging 37mg/m2. Results from five mainstem habitat sites showed similar macroinvertebrate
numbers, with densities ranging from 393 to 8,820 individuals/m2 in May 1985, but with
considerably more diversity; chironomids accounted for an average of 53 percent of the density
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and only 8 percent of the macroinvertebrate biomass. Algae samples beyond May 1985 had not
been analyzed; therefore, no data were available for summer or fall. No sampling results were
given for summer macroinvertebrate sampling (June and July). August and September 1985
sampling showed low average densities at mainstem sites (44 – 164 individuals/m2), with large
increases occurring in October 1985 (1,729 – 7,109 individuals/m2). Average densities in Slough
8A in August 1985 remained similar to spring levels (2,851 individuals/m2), with a surge in
September 1985 (13,964 individuals/m2); again, chironomids represented over 80 percent of the
numbers. No further information or reports were available concerning the Primary Production
Monitoring Effort task.
Benthic macroinvertebrate information from the 1980s is largely focused on a limited number of
mainstem, side channel, and slough habitats located within a 17-mile reach of the Middle Susitna
River. Additional information is needed on mainstem benthic communities, as well as those in
side channel and slough habitats, within both the Middle and Upper Susitna River segments.
Benthic algae information needs to be collected in conjunction with the macroinvertebrates,
particularly with functional feeding groups, to define their relationship in the river’s trophic
system. To assess potential impacts of future hydropower operations on the benthic communities
within the Susitna River, additional information must be collected through an increased sampling
effort, including more sampling sites along the river in relation to the distance both downstream
from the proposed dam site and upstream from the proposed Project reservoir area.
1.3.2. Life History Summary of Susitna Target Fish Species
1.3.2.1. Coho salmon (Oncorhynchus kisutch)
1.3.2.1.1. General Life History
Coho salmon are widely distributed throughout the North Pacific basin. Their distribution ranges
from the Sea of Japan north to Point Hope, Alaska, and south to the Sacramento River in
California (Sandercock 1991). Along the Pacific coast of Alaska, coho salmon are native to
coastal rivers and streams in the Southeast, Southcentral and Southwestern regions of the state.
Coho salmon have been documented in the mainstem and several Susitna River tributaries,
including the Yentna, Talkeetna, and the Chulitna rivers (ADF&G 2012).
Like other Pacific salmon species, coho salmon are anadromous. North American coho salmon
typically spawn from October to March, although entry into freshwater and spawning time varies
among populations and with environmental conditions (Morrow 1980, Sandercock 1991). In
northwestern Canada and Alaska, adult coho salmon may begin their upstream migrations as
early as late June and July; however, most of the spawning in these areas occurs in November. In
Southcentral Alaska, adult returns to freshwater peak in August and September (McPhail and
Lindsey 1970) and spawning continues through the fall. Coho salmon adults die after spawning.
The duration of incubation for coho salmon ranges from 35 to 101 days (Laufle et al. 1986) and
is temperature dependent. Specific to Alaska coho salmon, the incubation period ranges from 42
to 56 days (McPhail and Lindsey 1970). After hatching, larval fish typically spend 2 to 3 weeks
in the gravel before emerging between early March and mid-May (Laufle et al. 1986, McMahon
1983). Juvenile coho salmon rearing time in freshwater is typically about 15 months, although
some juveniles will remain in freshwater for up to 2 years (Sandercock 1991). Smolt
outmigration begins in February and may continue into June; however, in more northern
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populations, outmigration is likely to occur later and extend into July or August. While the
majority of coho salmon reach maturity and return from the sea to reproduce in their natal
tributaries as 3-year olds, precocious males that reach maturity during their first (referred to as
“jacks”) or second year are a natural component of many Alaska coho salmon populations
(Sandercock 1991).
1.3.2.1.2. Periodicity
During studies conducted in the 1980s, adult coho salmon migration timing in the main channel
areas of the Lower Segment of the Susitna River occurred from early July through early October,
with peak passage in late July and early August (Roth and Stratton 1985, Roth et al. 1986).
Migration into Lower Segment spawning tributaries was estimated to start in mid- or late-July
and peak during the month of August (Roth and Stratton 1985, Roth et al. 1986). Upstream
spawning migration of adult coho salmon into the Middle Segment of the Susitna River typically
began in late July and continued through early October based on studies conducted during the
1980s, with peak movement during early and mid-August (Jennings 1985, Thompson et al.
1986). Adult coho salmon primarily used main channel areas for migration to access tributary
spawning sites (Jennings 1985). Upstream migration into Middle River spawning tributaries was
delayed due to holding and milling behavior in the lower extent of the Middle Segment and in
areas proximal to spawning tributaries (ADFG 1981-APA324, ADFG 1982-APA588). Based on
observed milling and/or delay between date of radio-tagging and tributary entry, the timing of
tributary entry and upstream migration was estimated to occur from early August through early
October, with peak movement in late August and early September.
Coho salmon spawning in the Middle Susitna River occurred from mid-August through early
October and peaked during mid- and late September (Jennings 1985). The timing of main
channel spawning was assumed to be the same as tributary spawning due to sparse main channel
spawning data. Primary spawning tributaries in the Middle Segment were Indian River, Gash
Creek, Chase Creek, and Whiskers Creek (Jennings 1985, Thompson et al. 1986). Spawn timing
in Lower Segment tributaries was slightly earlier relative to Middle Segment streams and
occurred from early or mid-August through early October, with peak spawning in late August
and early September (Roth et al. 1986). Coho salmon spawning in the Lower River Segment
occurred almost entirely in tributary habitats during the 1980s studies, though approximately 13
percent of adult coho salmon tagged in a 2009 study utilized Lower River Segment mainstem
areas for spawning (Roth and Stratton 1985, Roth et al. 1986, Merizon et al. 2010).
The timing and duration of coho salmon egg incubation and fry emergency is not well defined in
the Susitna River due to sparse winter data. The incubation period begins with the start of
spawning in mid-August and continues through fry emergence in the following spring. Coho
salmon fry emergence began prior to the start of outmigrant trap operation in mid-May 1983 and
1985, though ice cover precluded trap operation prior to this point (Schmidt et al. 1983, Roth et
al. 1986). Salmon egg incubation time depends on water temperature and the duration necessary
for coho salmon egg development from the point of fertilization to fry emergence can range from
228 days at water temperatures of 2° C to 139 days at 5° C (Murray and McPhail 1988 cited in
Quinn 2005). Based on these data and approximate timing of coho salmon emergence in similar
areas, coho salmon fry emergence in the Susitna River is thought to begin in early March (Scott
and Crossman 1973). Among age-0 coho salmon captured in June and July of 1981, 1982, and
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1983, the lower extent of the length range was less than 35 mm, which suggests that emergence
may continue through May or beyond (Jennings 1985).
Age-0+ coho salmon utilized natal tributaries for nursery habitats immediately following
emergence, but many emigrated from tributaries soon after emergence to mainstem habitats
between early May through October (Jennings 1985). Within the Susitna River mainstem, age-
0+ salmon primarily used upland sloughs and side sloughs during the open water season.
Juveniles also moved downstream to the Lower River Segment based on outmigrant trap catch
data. Downstream movement of age-0 coho salmon to the Lower River Segment appeared to
begin in early May, prior to outmigrant trap operation each year, and continued through October,
with peak movement from late June to late August (Jennings 1985, Roth et al. 1986). Movement
by age-0+ coho salmon observed in September and October may have been dispersal into
suitable winter nursery habitats, which were side sloughs and upland sloughs in the Middle
Segment (Jennings 1985, Roth et al. 1986). Within the Lower Segment mainstem, age-0+ coho
salmon primarily used tributary mouths as nursery habitats, with comparatively little use of side
channel or side slough habitats (Suchanek et al. 1985). A portion of age-0+ coho salmon may
have emigrated to marine or estuarine areas during September and October based on capture data
at the Flathorn Station (RM 22) outmigrant trap (Roth and Stratton 1985).
Ages-1+ and 2+ coho salmon primarily utilized natal tributaries, side sloughs, and upland
sloughs as nursery habitat in the Middle River Segment (Dugan et al. 1984). Historic data
indicates that juvenile coho salmon remained in the Susitna Basin as age-1+ parr but some
portion of this age group dispersed from natal habitats in the Middle River, as suggested by few
age-2+ coho salmon captures in the Middle River during the 1980s (Stratton 1986). These
researchers surmised that these juvenile coho salmon had dispersed to the Lower River.
Dispersal from nursery habitats occurred during winter and early spring, although the timing and
pattern of this movement is not well understood. Limited data collected during the winter of
1984-1985 suggested that juvenile coho salmon parr exhibit movements similar to juvenile
Chinook salmon, with downstream migration between November and February (Stratton 1986).
Age-1+ coho salmon in the Lower Segment redistributed to suitable habitats throughout the open
water season, while a portion emigrated as smolts to estuarine areas (Roth et al. 1986). Based on
limited data collected during winter in the Middle River Segment, age-1+ and age-2+ coho
salmon were believed to have begun emigration from nursery habitats in early winter, and the
peak of mainstem downstream movement likely occurred during the open water season (Stratton
1986, Roth et al. 1986). Age-2+ coho salmon emigration from the Lower Segment was
estimated to have occurred between early January through mid-July, with movement in June
(Roth et al. 1986).
1.3.2.1.3. Distribution
Coho salmon distribution in the Susitna River Basin extends from Portage Creek (RM 148.9) to
Cook Inlet (RM 0.0; Jennings 1985, Thompson et al. 1986). Coho salmon counted at the Yentna
Station represented 16 to 46 percent (average 35 percent) of the combined escapement estimated
at the Yentna and Sunshine Stations (ADF&G 1981, ADF&G 1982C, ADF&G 1984, Barrett et
al. 1985). Merizon et al. (2010) radio-tagged 300 coho salmon at Flathorn during 2009 and
assigned a spawning location to 275 of the tagged fish based on tag detections and movement
patterns. Coho salmon were strongly oriented toward the east or west banks. Consequently, fish
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captured and tagged on the west side of the river primarily entered the Yentna River, while those
captured on the east side tended to migrate up the Susitna River. Of the 275 coho salmon tagged
at Flathorn and assigned a spawning location, four (1.5 percent) spawned in the Middle Susitna
River, and none entered associated tributaries (Merizon et al. 2010). For the Lower Susitna
River, 130 coho salmon (47.3 percent of those assigned a spawning location) spawned in the
Yentna drainage, 39 (14.2 percent) spawned in the Lower Susitna River, and 102 (37.1 percent)
spawned in other tributaries to the Lower Susitna River, primarily the Talkeetna, Deshka, and
Chulitna drainages. Caution is warranted when considering the results of Merizon et al. 2010 as
these researches based spawning on movement patterns and tag locations determined from the air
and did not confirm spawning activity or the presence of redds in presumed spawning locations.
Spawning surveys were conducted each year from 1981 to 1985, but the level of intensity varied
from year to year. In contrast to the 2009 radio tracking, spawning surveys conducted at 811
sites in the Lower Susitna River in 1982 did not identify any coho salmon spawning locations in
the mainstem river (Barrett et al 1983). However, Barrett et al. (1985) and Thompson et al.
(1986) conducted intensive surveys in 1984 and 1985 and identified coho salmon in tributaries of
the Middle Susitna River. During 1984, Barrett et al. (1985) identified two non-slough and one
slough spawning areas in the mainstem of the Lower Susitna River. They also identified 11 of
17 tributary mouths that were used as holding habitat, but not for spawning. Based on these
historic data, Whiskers Creek, Indian River, and Chase Creek (RM 106.9) accounted for the
majority of the tributary spawning in the Middle Susitna River. Thompson et al. (1986)
observed coho salmon milling in five sloughs of the Middle Susitna River during 1985, and
Barrett et al. (1985) observed milling in three sloughs during 1984, but no spawning activity was
observed in sloughs during either year. In 1984, Barrett et al. (1985) identified one non-slough
spawning area with two coho salmon in the mainstem of the Middle Susitna River.
While there is some uncertainty regarding the precise proportional distribution of coho salmon
among the different Susitna River spawning areas due to annual variability, the tributaries
associated with the Lower Susitna River are the major coho salmon production areas. In addition,
adult coho salmon appeared to use mainstem channels and sloughs; however, actual
documentation of spawning in these habitats has been very rare. The Middle Susitna River
tributaries account for a small portion of the total Susitna River coho salmon production.
1.3.2.1.4. Adult Escapement and Juvenile Relative Abundance
Coho salmon are the least abundant anadromous salmon returning to the Susitna River Basin yet
are important components for commercial and sport fisheries. From 1966 to 2006, an annual
average of 313,000 coho salmon were caught for the commercial fishery in the Upper Cook Inlet
(UCI) Management Area (Merizon et al. 2010). Next to Chinook salmon, coho salmon are the
second highest contributor to the sport fishery with an annual average of 40,767 fish captured
from 1998 to 2007 (Merizon et al. 2010). Average combined escapement for coho salmon in the
Yentna Basin and Susitna Basin upstream of RM 80 from 1981 to 1984 was 61,400 fish; annual
escapement was not estimated for the Susitna Basin downstream of RM 80 from 1981 to 1983,
except for in the Yentna Basin (Jennings 1985). During 1981-1984, average escapement at the
Talkeetna Station (RM 103) fishwheel was 5,700 fish, while escapement estimates at the
Sunshine Station (RM 80) and Yentna River Station (Susitna RM 28.0; Yentna RM 4.0)
fishwheels were 43,900 and 19,600 fish, respectively (Jennings 1985). Total coho salmon
escapement in the Susitna Basin was estimated to be 663,000 in 2002 (Willette 2003).
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Based upon sonar counts of fish returning to the Yentna River and Peterson estimates of returns
to the Sunshine Station, minimum coho salmon returns to the Susitna River averaged 61,986 fish
annually from 1981 through 1985 and ranged from 24,038 to 112,874 fish (ADF&G 1981,
ADF&G 1982c, ADF&G 1984, Barrett et al. 1985, Thompson et al. 1986). These values
represent minimum estimates, because sonar counts at the Yentna River station underestimate
the total returns to the Yentna River (Jennings 1985). The average annual return to Talkeetna
Station from 1981 to 1984 was 5,666 coho salmon. However, this may be an overestimate
because coho salmon adults may enter the Middle Susitna River, and then migrate back
downstream to spawn in other areas, as suggested by previous tracking studies. The Talkeetna
Station was not operated in 1985. Average returns to Curry Station were 1,613 fish and ranged
from 761 to 2,438 fish from 1981 to 1985.
From June through September of 1982, a total of 1,857 juvenile coho salmon were captured by
all gear types at Designated Fish Habitat (DFH) sites from Goose Creek 2 upstream to Slough 21
(Estes and Schmidt 1983). Total juvenile coho salmon catch from this effort is shown by gear
type and site in Figure 1.3-1. Juvenile coho salmon were present for at least one of the eight
sampling periods in roughly 90 percent of the 17 DFH sites sampled.
Sampling in 1983 at Juvenile Anadromous Habitat Study sites captured 2,023 juvenile coho
salmon between the Chulitna River (RM 98.6) and Portage Creek (RM 148.8; Dugan et al.
1984). Relative abundance determined from this effort is shown in Figure 1.3-2, both seasonally
and by site. Age composition consisted of 97 percent age 0+, 3 percent age 1+, and less than one
percent age 2+ fish. In general, juvenile coho salmon were widely distributed in low densities at
many sites in the Middle Segment of the Susitna River, although high tributary densities were
observed in early July and August. Juvenile coho salmon CPUE estimates were frequently
highest at sites located in the lower portion of the Middle Segment.
1.3.2.1.5. Habitat Associations
Adult coho salmon spawn almost exclusively in tributary habitats, although adults have been
documented in main channel, side channel and side slough habitats during the 1980s and in 2009
(ADFG 1984-APA 1450, Barrett et al. 1985, Merizon et al. 2010). During 1984, coho salmon
were recorded spawning at one side channel location in the Middle River Segment and in two
side channels and one side slough site in the Lower River Segment (Barrett et al. 1985). No
spawning was observed by coho salmon in surveyed slough or tributary mouth habitats (Barrett
et al. 1985, Jennings 1985). Radio tracking studies conducted in 2009 indicated that 14 percent
of all tagged coho salmon (n = 275) spent time in mainstem (i.e., main channel and off-channel)
habitats in the Middle and/or Lower Susitna River segments (Merizon et al. 2010). Primary
spawning tributaries for coho salmon based on the 1980s and 2009 data are Indian River and
Whiskers Creek in the Middle Segment and the Chulitna, Deshka, and Yentna rivers in the
Lower River Segment (Jennings 1985, Thompson et al. 1986, Merizon et al. 2010).
Based on scale analysis of returning adults, most juvenile coho salmon in the Susitna Basin
reside in nursery habitats for 1 or 2 years prior to emigrating as age-1+ and age-2+ smolts to
marine areas (ADF&G 1984, Barrett et al. 1985). The proportions of coho salmon that emigrate
as age-1+ and age-2+ varied among years during the 1980s, though approximately equal
proportions of adults exhibited each life history; a small portion (i.e., < 5 percent) of juvenile
coho salmon emigrated as age-3+ smolts (ADF&G 1984, Barrett et al. 1985). During the open-
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water period, age-0 and age-1 juveniles in the Middle River Segment primarily utilized clear
water habitats associated with natal tributaries and upland sloughs (Figure 1.3-3), whereas those
in the Lower River Segment used clear water tributaries and tributary mouths more consistently
than side slough or side channel habitats, which were often more turbid (Schmidt and Bingham
1983, Dugan et al. 1984, Suchanek et al. 1985). Catch of age-0 juvenile coho salmon fry at
tributary mouths peaked in July and August (Delany et al. 1981). These authors suggest that
juvenile coho salmon movement in late summer may have been in response to declining water
temperature and relocation to overwintering habitats. Coho salmon overwintered in side sloughs
and upland sloughs in the Middle River Segment and tributary mouths and side channels in the
Lower River Segment, though the distribution and intensity of fish sampling was reduced by ice
cover and weather conditions (Delaney et al. 1981, Stratton 1986). Age-2 coho salmon were
believed to rear primarily in Lower River Segment habitats during winter, based on low capture
rates of age-2 fish in the Middle River Segment during winter (Stratton 1986).
1.3.2.2. Chinook salmon, (Oncorhynchus tshawytscha)
1.3.2.2.1. General Life History
Chinook salmon are distributed from northern Hokkaido, Japan, to the Anadyr River in Siberia
and from the San Joaquin River in Central California to the Coppermine River in the Canadian
Arctic (Healey 1991). In Alaska, Chinook salmon occur in large coastal rivers from the southern
tip of Alaska’s panhandle northward to Point Hope (Mecklenburg et al. 2002). The Chinook
salmon stock of the Susitna River is the fourth largest in Alaska (Ivey et al. 2009).
As with other Pacific salmon, Chinook salmon are anadromous. Chinook salmon mature and
begin their spawning migration between 3 and 6 years of age, but most spawning adults are ages
4 and 5 (Healey 1991). In northwestern Canada and Alaska, adults migrate to freshwater
spawning grounds between late May and July, although this period may extend from April to
September in some locations (Healey 1991). While spawning generally takes place from July to
November, spawning time varies regionally and depends on the distance and duration of river
migration (Morrow 1980, Scott and Crossman 1973). Northern populations, such as those in
Alaska, tend to spawn from July through September (Healey 1991). Adults die following
reproduction and egg deposition into one or more gravel nests known as redds.
Chinook salmon egg incubation varies with temperature, with lower temperatures resulting in
increased time to hatching (Healey 1991). After hatching in the spring, the young remain in the
gravel for 2 to 3 weeks and then emerge as free-swimming, feeding fry (Morrow 1980). While
some juvenile Chinook salmon may rapidly disperse to sea, this life history pattern tends to be
absent in locations north of 56 degrees North latitude, such as Alaska (Quinn 2005). In these
northern locations, most juvenile Chinook salmon remain in freshwater streams for 1 year before
beginning their outmigration to sea, but some will remain in freshwater for 2 years (Morrow
1980, Quinn 2005).
Owing to their large body size, adult Chinook salmon require deep holding water and sufficient
stream flow to successfully complete their upstream migration. Spawning depths vary widely,
from 5 to 720 centimeters (cm), with average spawning depths starting at 30 cm (Healey 1991).
The large body size of Chinook salmon also enables them to use large gravel and cobble
substrates for spawning (Raleigh et al., 1986). Successful incubation requires clean water
percolating through spawning gravels at temperatures less than 16 °C (Healey 1991).
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Juvenile Chinook salmon occupy a variety of habitats during their stay in freshwater. Younger,
smaller fry inhabit stream margins, eddies, backwaters, and side channels and are often
associated with fallen trees, root wads, and areas with bank cover. As they increase in size,
juvenile Chinook salmon move into stream and river habitats with increasing velocities (i.e., up
to 1.2 meters per second). This movement is associated with a shift from predominantly sandy
substrates to those with larger-sized gravel and boulders (Healey 1991).
1.3.2.2.2. Periodicity
In the Susitna River, adult Chinook salmon begin their upstream migration in late-May to early
June (Jennings 1985, ADF&G 1984). Although a few Chinook salmon may pass Susitna Station
(RM 26.7) as late as mid-August, nearly all Chinook salmon (95 percent) have passed the station
by the first week of July (ADF&G 1981, Jennings 1985). Peak run timing is generally later at
Talkeetna Station (RM 103) compared to Sunshine Station. However, peak run timing at Curry
Station appears to be similar or earlier than at Talkeetna Station, suggesting that upriver fish (i.e.,
Chinook salmon bound primarily for Indian and Portage creeks) enter and migrate during the
early portion of the overall Chinook salmon migration period in the Susitna River Basin.
Spawning generally begins in mid-July and is finished by the end of August (Barrett 1985,
Jennings 1985). Peak spawning is during the last week of July and first week of August
(Jennings 1985). Run timing may be affected by high flow levels, as indicated by decreased
fishwheel catch rates; however, this pattern was not consistent across all years (Jennings 1985).
The timing of Chinook salmon fry emergence in Susitna River tributaries is poorly understood
due to the difficulty of early and mid-spring sampling in the Susitna River Basin. Sampling for
outmigrating fish following ice-out can seldom occur prior to mid-May and frequently cannot
begin until early June. Delaney et al. (1981) reported that Chinook salmon fry were collected in
Indian River in April during 1981 as part of a winter sampling effort. In 1982, sampling did not
begin until early June, and fry were already present by this time (Schmidt et al. 1983). During
1985, sampling in Portage Creek and the Indian River began on July 9, and Chinook salmon fry
were captured at relatively high rates with lengths ranging from 36 to 64 mm (Roth et al. 1986),
suggesting that emergence was primarily completed by that time. Schmidt and Bingham (1983)
reported that Chinook salmon fry emerge in April and March, while Stratton (1986) reported that
emergence occurs in April; however, neither of these authors provides any supporting field
sampling data for these conclusions.
Nearly all Chinook salmon juveniles outmigrate to the ocean as age-1+ fish. The bulk of
Chinook salmon fry outmigrate from the Indian River and Portage Creek by mid-August and
redistribute into sloughs and side channels of the Middle Susitna River or migrate to the Lower
River (Roth and Stratton 1985, Roth et al. 1986). Outmigrant trapping occurred at Talkeetna
Station (RM 103) during open water periods from1982 to 1985 and demonstrated that Chinook
salmon fry were migrating to the Lower Susitna River throughout the time traps were operating
(Schmidt et al. 1983, Roth et al. 1984, Roth and Stratton 1985, Roth et al. 1986). Peak catch
often occurred during periods of high flows. Outmigrant traps were also fished at Flathorn
Station (RM 22.4) in 1984 and 1985 and demonstrated peak periods of Chinook salmon fry
movement during early July; however, many of these fry may have originated from the Deshka
River (Roth and Stratton 1985, Roth et al. 1986). Roth and Stratton (1986) suggested that some
Chinook salmon fry either overwinter in the Lower Susitna River between the mouth and
Flathorn Station or outmigrate to the ocean as fry. They also suggested that outmigration as fry
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is a relatively unsuccessful life history pattern for Chinook salmon in the Susitna River, because
scale pattern analysis indicates that few adults return.
Based on the capture of a small number of age-1+ Chinook salmon juveniles in the Indian River
during winter sampling (Stratton 1986), it is thought that some Chinook salmon fry remain in
natal tributaries throughout their first year of life and overwinter in any available suitable habitat.
In 1984, sampling in the Indian River to cold brand juvenile salmon failed to capture any
Chinook salmon age-1+ fish during July, yet was successful during May and June, suggesting
that age-1+ Chinook salmon juveniles emigrate from tributary streams shortly after ice-out (Roth
and Stratton 1985). The cumulative frequency of age-1+ Chinook salmon captured in 1985 at
Talkeetna and Flathorn stations reached 90 percent by early July and late-July, respectively
(Roth et al. 1986). These data indicate that outmigrating age-1+ smolts are generally in estuarine
or near-shore waters by mid-summer.
1.3.2.2.3. Distribution
Based upon observations of juveniles, Chinook salmon are distributed in the Susitna River up to
at least the Oshetna River (RM 225) (Buckwalter 2011). During the 1980s two spawning
Chinook salmon were observed in Fog Creek (RM 176.7) during 1984 (Barrett 1985). More
recently Buckwalter (2011) observed adult Chinook salmon in Fog Creek (RM 176.7) and
Tsusena Creek (RM181.3) during 2003 and in Kosina Creek (RM 201) during 2011. Juvenile
Chinook salmon were also observed in Fog Creek, Kosina Creek, and Oshetna River during 2003
and a Fog Creek tributary during 2011. In addition, adult Chinook salmon were observed in
Cheechako Creek (5), Chinook Creek (5), Devil Creek (7), Fog Creek (1), and Kosina Creek (16)
during 2012, with evidence of spawning documented in Kosina Creek, as well (AEA
unpublished data).
A series of three partial velocity barriers are present in Devils Canyon, restricting access to
upstream habitat. Chinook salmon are the only known anadromous salmon that can pass all
three barriers (AEA unpublished data). The lower two barriers appear to be passable by Chinook
salmon at a relatively broad range of flows while the upper barrier, located downstream of Devil
Creek, can only be passed under a narrow range of flows.
Chinook salmon spawn exclusively in tributary streams (Thompson et al. 1986, Barrett 1985,
Barrett 1984, Barrett 1983). Consequently, the mainstem Susitna River primarily provides a
migration corridor and holding habitat for adult Chinook salmon. Apportionment of Chinook
salmon among the major Susitna River subbasins from peak spawning surveys is somewhat
confounded by inconsistent surveys, in part because of poor visibility and partly due to annual
differences in surveying priorities. Nevertheless, major patterns in the distribution of Chinook
salmon spawning during the late 1970s and early 1980s are discernible based upon data
summarized by Jennings (1985). Important spawning tributaries in the Lower River included the
Deshka River and Alexander Creek, the Yentna, Talkeetna, and Chulitna Rivers. The Yentna
River and Talkeetna R/Chulitna subbasins are big producers and typically accounted for about 20
percent and 15 percent, respectively, of the Chinook salmon spawning for the entire Susitna
River. There was proportionally much less spawning in the Middle River tributaries, which
typically accounted for about 5 percent of the total Chinook salmon spawning. When focusing in
on the Middle River spawning habitats, Portage Creek and Indian River accounted for nearly all
of the Chinook salmon spawning at approximately 90 percent or greater. Other tributaries, such
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as Fourth of July Creek and Whiskers Creek, accounted for minor amounts of spawning,
generally with no more than about 2.5 percent of the spawning in the Middle River.
1.3.2.2.4. Adult Escapement and Juvenile Relative Abundance
Of the five salmon species returning to the Susitna River, Chinook salmon have had the smallest
run size, but have been the most important sport fish (Jennings 1985). Long-term escapement
trend data from 1974 to 2009 was available for a number of index streams in the Susitna River
Basin monitored by ADF&G, but comparisons among streams were unreliable because of
different survey methods (weirs, foot, or aerial; Fair et al. 2010). Most index streams were
tributaries to the mainstem in the Lower Susitna River or tributaries in the Chulitna and
Talkeetna subbasins (Fair et al. 2010). The Deshka River (RM 40.6) had the highest escapement
of all tributaries with a median of 35,548 fish. ADF&G installed a counting weir in the Deshka
River prior to the 1995 season to improve the accuracy of salmon escapement counts (Fair et al.
(2010). All other index streams generally had fewer than 5,000 fish spawning during peak
surveys.
Total peak counts of Chinook salmon spawning in Middle River tributaries between 1981 and
1985 ranged from 1,121 to 7,180 fish, with a median of 4,179 fish; Jennings 1985, Thompson et
al. 1986). Generally, over 90 percent of the Chinook salmon that returned to the Middle River
spawned in Indian River or Portage Creek. Peak spawner counts from 1976 to 1984 ranged from
114 to 1,456 fish (median 479.5 fish) in Indian River and 140 to 5,446 fish (median 680.5 fish)
in Portage Creek (Jennings 1985).
ADF&G used mark-recapture techniques to estimate escapement to various fishwheel stations.
Total escapement, as estimated from point estimates, to Sunshine Station ranged from 52,900 to
185,700 fish, with a median 103,614 fish, from 1982 to 1985 (Barrett 1984, Barrett 1985,
Thompson et al. 1986). Escapement to Talkeetna Station ranged from 10,900 to 24,591 fish
(median 14,400 fish). However, this has been considered an overestimate, because many
Chinook salmon tagged at the Talkeetna Station were found to have spawned in tributaries
downstream of Talkeetna Station (Jennings 1985). The large difference between these two
stations, especially considering the overestimate at Talkeetna Station, reflects the large number
of fish that return to the Deshka River.
Declines in returns of Chinook salmon have prompted the Alaska Board of Fisheries to list some
Susitna River tributary stocks as Stocks of Concern. These include the Alexander Creek stock,
which was listed as a “Management Concern” in 2011, and the Willow Creek and Goose Creek
stocks, where were listed as “Yield Concern” in 2011. Low returns to the Deshka River in 2007
through 2009 have also prompted concern, and in 2012, low returns resulted in an early closure
to the sport fishery.
From June through September of 1982, a total of 963 juvenile Chinook salmon were captured by
all gear types at DFH sites from Goose Creek 2 upstream to Slough 21 (Estes and Schmidt
1983). Total juvenile Chinook salmon catch from this effort is shown by gear type and site in
Figure 1.3-4.
Sampling from May 1 to November 15, 1983 at Juvenile Anadromous Habitat Study sites
resulted in the capture of 4,443 juvenile Chinook salmon between the Chulitna River (RM 98.6)
and Portage Creek (RM 148.8; Dugan et al. 1984). Relative abundance by season and site
determined from this effort is shown in Figure 1.3-5. Juvenile Chinook salmon were captured at
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all study sites that were surveyed at least four times. Peak densities of 26.4 fish per cell were
recorded at tributary sites.
1.3.2.2.5. Habitat Associations
Adult Chinook salmon in the Upper, Middle and Lower Segments were observed to spawn
almost exclusively in tributaries during the 1980s, with some occasional use of tributary mouths
(Barrett et al. 1983, Jennings 1985, Thompson et al. 1986). Chinook salmon spawning was not
documented in main channel habitats from 1981 to 1985, although this may be due to the fact
that surveys conducted from 1983 to 1985 did not specifically target Chinook salmon (Barrett et
al. 1983, ADF&G 1984, Jennings 1985, Thompson et al. 1986). In 1981, mainstem surveys were
performed from July 15 to August 15 and covered 37 and 280 sites in the Middle and Lower
River segments, respectively (Barrett et al. 1983). In 1982, mainstem spawning was monitored
at 397 sites in the Middle River Segment and at 811 sites in the Lower River Segment from
August 1 to October 7, which was later than most observed spawning in tributaries (Barrett et al.
1983). Chinook salmon spawning was observed at tributary mouths in 1982 in the Middle
Susitna at Cheechako Creek (RM 152.4) and Chinook Creek (RM 157) but was not documented
at similar habitats elsewhere in the Upper, Middle, or Lower Segments (Barrett et al. 1983,
Barrett et al. 1985, Thompson et al. 1986).
Most juvenile Chinook salmon in the Susitna River typically exhibit either of two freshwater life
history patterns. One group of Chinook salmon fry rear in their natal tributary for nearly one
year prior to emigrating to the ocean as age-1+ smolts, while a second group of Chinook salmon
disperse from natal tributaries throughout the spring and summer to the Susitna River’s main
channel, side channel, and slough habitats in the Middle and Lower River segments (Roth and
Stratton 1985, Stratton 1986). Winter studies during the 1980s suggest that most Chinook
salmon fry utilize the Lower River Susitna as winter nursery habitat (Stratton 1986). A third
freshwater life history pattern, in which juvenile Chinook salmon emigrate to the ocean as age-
0+ smolts, was exhibited by very few juvenile Chinook salmon during the 1980s studies and was
associated with high ocean mortality rates based on adult scale analyses (Barrett et al. 1985, Roth
and Stratton 1985, Suchanek et al. 1985). Age analysis of adult Chinook salmon scales in 1985
indicated that 5 percent of the fish sampled had emigrated as age-0+ smolts (Thompson et al.
1986).
Primary nursery habitats in the Middle Susitna River for juvenile Chinook salmon during the
open water season were tributaries, tributary mouths, side channels, and side sloughs (Dugan et
al. 1984). Clearwater side channels and sloughs influenced by groundwater sources provided
juvenile overwintering habitat (Roth and Stratton 1985). Middle Susitna River sites with high
juvenile Chinook salmon use were: Portage Creek (RM 148.8), Indian River (RM 138.6), side
channels 10 (RM 133.8) and 10A (RM 132.1), and Whiskers Creek Slough (RM 101.2; Figure
1.3-6; Dugan et al. 1984). In the Lower Susitna River, tributary mouths and side channels were
the primary nursery habitats used by juvenile Chinook salmon, and there appeared to be a
preference for low-turbidity (i.e., 10-20 NTU) sites (Suchanek et al. 1986).
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1.3.2.3. Rainbow Trout (Oncorhynchus mykiss)
1.3.2.3.1. General Life History
Rainbow trout are native to both Asia and North America but have been widely introduced
throughout the world. Their distribution in North America ranges from northwest Mexico to the
Kuskokwim River in Alaska (Mecklenburg et al. 2002). In Alaska, native populations extend
from the Alaska panhandle along the coastline north to the Kuskokwim River and west to the
Point Moller region of the Alaska Peninsula (Mecklenburg et al. 2002). Rainbow trout have been
introduced in several lakes located in the interior of Alaska near Fairbanks, including Big Delta
and Summit Lake (Morrow 1980). Rainbow trout inhabiting the Susitna River represent one of
the northernmost naturally-occurring populations of the species (Morrow 1980).
Resident rainbow trout are spring spawners. Spawning takes place between mid-April and late
June when adults deposit eggs and milt into redds. Unlike other Pacific salmon species, rainbow
trout are iteroparous (i.e., able to breed multiple times) and do not die shortly after spawning.
Repeat spawning is common for resident rainbow trout (Quinn 2005), and annual spawning may
occur for up to 5 consecutive years for some fish (Morrow 1980).
Incubation typically lasts from 4 to 7 weeks, depending on water temperature. Fry emergence
occurs within 3 to 7 days, usually between mid-June and mid-August (Morrow 1980). After
emergence, rainbow trout fry may quickly disperse to lake habitats or remain in natal streams for
up to 3 years (McPhail and Lindsey 1970; Scott and Crossman 1973). Rainbow trout mature at
an age of 3 to 5 years and may live for up to 9 years (Morrow 1980).
Rainbow trout can be either stream- or lake-resident fish. When in rivers and streams, rainbow
trout are commonly found near lake outlets or below waterfalls and rapids (McPhail and Lindsey
1970). Tributary streams are used as spawning habitat by both stream- and lake-resident
populations (Morrow 1980). Redds are often constructed in fine gravel substrates of riffles
located adjacent to pools. Preferred water temperatures for spawning and incubation are between
10°C and 13°C, and groundwater upwelling and dissolved oxygen concentrations are important
in determining egg survival rates (McPhail and Lindsey 1970; Morrow 1980). Juveniles from
stream-resident populations occupy riffles during summer months and tend to shift into pools for
autumn and winter months (McPhail and Lindsey 1970).
Rainbow trout are opportunistic predators that feed on a wide variety of prey items, including
various insects (e.g., dipteran larvae and adults), plankton, crustaceans, snails, leeches, fish eggs,
smaller fishes, and adult salmon carcasses (Morrow 1980, Quinn 2005, Scott and Crossman
1973).
1.3.2.3.2. Periodicity
Rainbow trout spawning migrations typically begin in March prior to ice breakup when adults
move from main channel holding areas to spawning tributaries (Sundet 1986). Migration timing
into clear, non-glacial tributaries used for spawning was observed in April and early May during
the 1980s studies, while most spawning occurred during late May and early June (Schmidt et al.
1983; Suchanek et al. 1984; Sundet and Pechek 1985). Migration and spawn timing for rainbow
trout appears to be similar between the Middle and Lower Susitna River segments, although
timing of upstream migration into tributary habitats was noted to occur up to 10 days earlier in
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the Lower Segment (Sundet and Pechek 1985). Rainbow trout located upstream of the Chulitna
River confluence (RM 98.6) begin to migrate to tributary habitats to spawn in late May and early
June (Schmidt et al 1984).
Adult rainbow trout reside primarily in tributary habitats during the open water season, but they
may also use tributary mouths and clearwater side sloughs throughout the Middle River Segment
for holding and feeding during summer (Schmidt et al. 1983). In 1983 and 1984, adult migration
from tributary habitats occurred during late August and September, such that many individuals
had moved to tributary mouths by mid-September, and few remained in tributaries by early
October (Suchanek et al. 1984; Sundet and Wenger 1984; Sundet and Pechek 1985). Migration
timing to overwintering areas in main-channel and side channel habitats occurred from mid-
September through early February, with peak movement in October and late December (Schmidt
and Estes 1983; Sundet 1986). October movement was in response to freeze-up as fish sought
winter holding habitats in the main channel (Sundet 1986). By December, most adult rainbow
trout were in main channel areas apart from spawning tributaries (Sundet and Wenger 1984).
There is minimal information related to rainbow trout incubation and emergence timing in the
Susitna River; however, incubation is assumed to begin in May based on observed spawn timing
(Schmidt et al. 1983; Suchanek et al. 1984; Sundet and Pachek 1985). Based on generalized
incubation times for rainbow trout in cold water temperature regimes (e.g., 5-8° C), the start of
rainbow trout fry emergence in the Susitna River’s tributary habitats is estimated to occur in
early July and continue through mid-August (Quinn 2005; Crisp 1988, 1991). After emergence,
juvenile rainbow trout primarily reside in natal tributary habitats throughout the year, though
occasional use of tributary mouths and clear sloughs has been documented (Schmidt et al. 1983).
1.3.2.3.3. Distribution
Within the Susitna River, rainbow trout populations are found up to and including Portage Creek
at RM 148.8 (ADF&G 1983m). No rainbow trout have been identified upstream of Devils
Canyon in the impoundment zone (FERC 1983). These results are consistent between the 1980s
and 2012 studies. Rainbow trout in the Susitna River are distributed throughout tributary and
mainstem areas downstream of Devils Canyon (RM 152; Schmidt et al. 1983). Upstream of the
Chulitna River confluence (RM 98.6), Whiskers Creek (RM 104.4), Lane Creek (RM 113.6), and
Fourth of July Creek (RM 131.1) are the major spawning areas, whereas the larger tributaries
(e.g., Indian River and Portage Creek) are of lesser importance (Schmidt et al. 1984). Primary
spawning tributaries in the 1980s were Fourth of July and Portage creeks in the Middle Susitna
River Segment and the Talkeetna River (RM 97.2), Montana Creek (RM 77.0), and Kashwitna
River (RM 61.0) in the Lower Susitna River Segment (Sundet and Pechek 1985). Primary
holding and feeding locations for rainbow trout were the Fourth of July Creek (RM 131.1) and
Indian River (RM 138.6) tributary mouths, Slough 8A (RM 125.1), and Whiskers Creek Slough
(RM 101.2; Schmidt et al. 1983).
1.3.2.3.4. Relative Abundance
Data collected in the 1980s indicate that adult rainbow trout are more abundant in the Middle
Segment of the Susitna River than in the Lower Segment (Schmidt et al. 1983). Based on a tag-
recapture study conducted from 1981 to 1983, the estimated abundance of rainbow trout greater
than 150 mm in FL in the Middle Segment was approximately 4,000 fish (Sundet and Wenger
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1984). In the Lower River in 1984, a total of 155 rainbow trout were captured using multiple
capture methods (Sundet and Wenger 1984). The highest number of rainbow trout captures (i.e.,
62 fish) occurred in the Deshka River. Relatively high catches were made by boat electrofishing
in the mainstem Susitna River between RM 30.0 and RM 98.5 in early September (31 fish
captured) and at the mouth of Little Willow Creek (RM 50.3) in late September (14 fish
captured). Only nine rainbow trout were captured in the upper reaches of east side tributaries
during early September (Sundet and Pechek 1985).
Sampling at the DFH sites in 1982 resulted in the captured of 207 rainbow trout (Figure 1.3-7;
Schmidt et al. 1983). The largest number of rainbow trout captured (n=43) was at the Fourth of
July Creek site. Other DFH sites where more than 20 rainbow trout were captured included
Whiskers Creek and Slough, Slough 8A, and Indian River. Whitefish Slough was the only DFH
site sampled in 1982 at which no rainbow trout were caught.
From May to October 1983, sampling at 12 selected sites between the Chulitna River confluence
and Devils Canyon captured 163 rainbow trout (Sundet and Wenger 1984). The highest catches
were at Fourth of July Creek (RM 131.1) and Indian River (RM 138.6), where 46 and 45 fish
were caught respectively. Other sites with relatively high catches included Whiskers Creek
Slough (RM 101.2), Lane Creek (RM 113.6), and Portage Creek (RM 148.8). Sampling at
locations other than the twelve selected DFH sites resulted in the capture of 228 rainbow trout,
with 78 percent of these fish captured in the lower 1.5 miles of Fourth of July Creek. The
highest catches of rainbow trout in tributary streams of the Susitna River were recorded in Fourth
of July Creek, where significant spawning activity was documented (Sundet and Wenger 1984).
Rainbow trout were also documented in lakes within the Susitna River basin; a total of 390 fish
were captured in six lakes surveyed in 1984, comprising 86 percent of the total fish catch
(Sundet and Pechek 1985). Lakes in which rainbow trout were abundant in 1984 include those
that flow into Fourth of July and Portage creeks (Sundet and Pechek 1985).
1.3.2.3.5. Habitat Associations
Rainbow trout in the Susitna River are distributed throughout tributary and mainstem areas
downstream of Devils Canyon (RM 152; Schmidt et al. 1983). Upstream of the Talkeetna River,
they mainly use tributaries for spawning and rearing, while overwintering occurs primarily in the
mainstem (Schmidt et al. 1984). Upstream of the Chulitna River confluence (RM 98.6), the
major spawning areas are Whiskers Creek (RM 104.4), Lane Creek (RM 113.6), and Fourth of
July Creek (RM 131.1); larger tributaries (e.g., Indian River and Portage Creek) appear to be of
less importance with regard to rainbow trout spawning (Schmidt et al. 1984).
Adult rainbow trout utilize clearwater tributary habitats to spawn following ice breakup each
spring (Schmidt et al. 1983). After spawning, adults primarily hold and feed during the open
water period in tributary and tributary mouth habitats, although some utilization of clearwater
side slough habitat was observed during the 1980s (Schmidt et al. 1983). Holding and feeding
areas during the open water period were closely associated with Chinook, chum and pink salmon
spawning areas (Sundet and Pechek 1985). Primary holding and feeding locations for rainbow
trout were the Fourth of July Creek (RM 131.1) and Indian River (RM 138.6) tributary mouths,
Slough 8A (RM 125.1), and Whiskers Creek Slough (RM 101.2; Schmidt et al. 1983).
Prior to ice formation on the Susitna River, adult rainbow trout move from tributaries to main
channel or side channel habitats to hold during winter (Schmidt and Estes 1983, Sundet and
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Pechek 1985). In the Middle Segment, rainbow trout were found to utilize main channel areas,
but in the Lower Segment, they typically used side channel habitat (Sundet and Pechek 1985).
Movement from spawning or feeding tributaries to overwintering habitat is commonly in a
downstream direction (Sundet and Pechek 1985). Many adults overwinter relatively close (i.e.,
<4 miles) to spawning tributaries, while others exhibit long-distance migrations that typically
range from 10 to 20 miles downstream but can extend over 76 miles (Schmidt and Estes 1983,
Sundet 1986). Winter holding areas include main channel and side channel habitat (Schmidt and
Estes 1983, Sundet 1986). Specific habitat features of winter holding areas during the 1980s
were difficult to ascertain, though upwelling and ice cover appeared to be common in fish habitat
(Schmidt et al. 1983, Sundet and Pechek 1985, Sundet 1986). No tagged fish were observed in
areas with anchor ice (Sundet 1986). Limited observations of tagged rainbow trout suggest the
Susitna River between RM 78.0 and Talkeetna may also be an important overwintering area for
Talkeetna River stocks (Sundet and Wenger 1984).
Juvenile rainbow trout generally utilize natal clearwater tributaries as nursery habitats (Schmidt
et al. 1983). Some juveniles also rear in the mainstem and sloughs, but the use of these habitats
appears to be limited (ADF&G 1983b, Schmidt et al. 1984). Fourth of July Creek (RM 131.1) is
an important rearing area for juvenile rainbow trout (Schmidt et al. 1984). Capture of juvenile
rainbow trout in main channel areas was low, though use of tributary mouths and clearwater
sloughs was observed (Sundet and Pechek 1985). Lake systems associated with the Fourth of
July and Portage creeks were believed to possibly supplement rainbow trout production in each
basin based on analysis of juvenile scale patterns; however, no direct evidence of juvenile
rearing in these lakes was recorded (Sundet and Pechek 1985). Winter rearing for juvenile
rainbow trout occurred primarily in tributaries with occasional use of clear side slough habitats
(Schmidt et al. 1983).
1.3.3. Middle River Mainstem Habitat Delineation Results
In winter 2012-2013, the frequency and proportion of habitat in the mainstem Middle River was
delineated using geo-rectified aerial imagery in combination with available aerial videography.
The objective of Middle River mainstem mapping was to characterize and classify river habitat
in the Middle River mainstem from the Chulitna River confluence to the proposed Watana Dam
site. These data were used to support the selection of representative focus areas for instream flow
studies and the approach for fish distribution and abundance site selection.
A hierarchical and nested classification system developed specifically for the Susitna River with
input from the Fish and Aquatics Technical Working Group was used to classify habitat to the
mainstem habitat level. The geo-rectified imagery in combination with aerial videography was
sufficient to map the Middle Susitna River mainstem habitat to the mesohabitat level. However,
the imagery was not suitable for mapping off-channel or tributary habitats to this level. Thus,
these habitats were delineated only to the level of mainstem habitat types in 2012(HDR 2013).
A summary of these results can be found in the Middle Susitna River Segment Remote Line
Habitat Mapping Technical Memorandum (HDR 2013).
Main channel habitat varied by geomorphic reach within the Middle River Segment and
generally increased in complexity from upstream to downstream locations. Mesohabitat in the
main channel was generally dominated by a mixture of run and glide habitats. Glide and run
habitats, which were not distinguished from each other at this level of classification, included
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smooth-flowing, low-turbulence reaches as well as areas with some standing or wind waves and
occasional solitary protruding boulders. Run-glide mesohabitat dominated all reaches except
MR-4, where Devils Canyon is located. Riffle habitat was most prevalent in MR-4. Riffle
habitat was lacking or found in very small amounts in the other Middle River geomorphic
reaches.
Side channels were predominantly glide or run, with some riffle areas in the lower reaches.
Many side channels were not completely inundated with flowing water and so identification of
riffle or run habitat was not possible; these were classified as unidentified and were most
prevalent in MR-6.
Cascade habitat was not found within any of the geomorphic reaches of the Middle River
Segment. The geomorphic reach through Devils Canyon (i.e., MR-4) contained the only rapids
in the Middle River, which accounted for 38 percent of the mainstem habitat in that reach. Only
3 pools were found in the Middle River, and all were located in MR-4 between rapids in Devils
Canyon.
The habitat associated with the confluence of tributaries with the main channel river was
documented as tributary mouth and clear water plume. Not all tributaries that entered the Middle
River had tributary mouth habitat. Small tributaries where the vegetation line was close to the
mainstem did not fan out and create the areas classified as tributary mouth habitat. In addition,
small tributaries or tributaries that flowed into fast moving or turbulent sections of the mainstem
did not produce clear water plume habitats. Clear water plume habitats were located in reaches
MR-2, MR-3, MR-5, and MR-7, with the highest number in reach MR-2.
Off-channel habitat was assigned to one of three habitat types observed: upland sloughs, side
sloughs, and backwaters. Upland and side sloughs were prevalent throughout the Middle River
reaches outside of Devils Canyon and downstream of the uppermost reach at MR-1. Side
sloughs were most abundant in MR-5, followed by MR-6. Upland sloughs were most abundant
in MR-8, and generally increased in abundance towards the downstream reaches (Table 5).
Backwater habitat was relatively rare and found in a few areas in the lower reaches from MR-6
through MR-8. A single backwater was also delineated in MR-2 and in MR-4, but each
accounted for less than 1 percent of the linear habitat within their respective reaches. The
greatest total area of backwater habitat was in MR-7, but the greatest frequency was found in
MR-6.
Beaver complexes were consistently associated with slough habitats and as such were not
categorized as a habitat type but were noted as a characteristic of that slough habitat unit. Beaver
dams were rarely present in side slough habitat, and slightly more prevalent in upland sloughs.
Beaver dams were only observed in reaches MR-6 and MR-7.
1.3.4. Documentation of TWG input to site selection protocol
This section will be provided in Final Implementation Plan, following February 2013
consultation.
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2. METHODS
2.1. Sampling Site Selection Protocols
Sampling for the River Productivity Study will be stratified by river segment and mainstem
habitat type, as defined in the Project-specific habitat classification scheme (e.g., main channel,
tributary mouth, side channel, side sloughs). Sampling will occur at six stations on the Susitna
River, and one station on the Talkeetna River, each station with three sites (one main channel site
and two different macrohabitat sites associated with the main channel site), for a total of 18 sites.
Two stations will be located in the Upper Segment, above the proposed dam and reservoir area
(upstream of RM 223) (Table 1.2-1; Figure 1.2-1). In the Middle River Segment, two stations
will be located between the dam site and the upper end of Devils Canyon, and two stations will
be located between Devils Canyon and Talkeetna (Table 1.2-1; Figure 1.2-2). All stations
established within the Middle River Segment will be located at Focus Areas established by the
Instream Flow Study (RSP Section 8.5.4.2.1.2), in an attempt to correlate macroinvertebrate data
with additional environmental data (flow, substrates, temperature, water quality, riparian habitat,
etc.) collected by other studies (e.g., RSP Section 5.5, Baseline Water Quality), for uses in
statistical analyses, and HSC/HSI development. Many of these Focus Areas are also highly
utilized by the target fish species selected for this study’s trophic analysis (RSP Section
9.8.4.5.1). Station and site locations are discussed below.
2.1.1. Middle River Segment Stations / Focus Areas
Within the Middle Segment of the Susitna River, the River Productivity Study will establish four
study stations, each one located at a proposed Focus Area (Table 1.2-1; Figure 1.2-2 and Figures
2.1-1 through 2.1-4). For sampling between the proposed dam site and Devils Canyon, Focus
Areas 184 and 173 have been selected for River Productivity Study activities. Between Devils
Canyon and Talkeetna, Focus Areas 141 and 104 have been selected as stations for the River
Productivity Study. In addition, two side sloughs are required for proposed storm event
sampling. After review of historic data (ADF&G 1983c; Hale et al. 1984) regarding the
mainstem discharge required to overtop various sloughs in the Middle Segment, sloughs in Focus
Areas 104 and 144 have been selected for storm event sampling.
Focus Areas 184 and 173 have been selected due to their proximity to the location of the
proposed dam site. Any effects on the benthic macroinvertebrate population due to Project
operations would be most pronounced at these upper locations. Therefore, monitoring this area
during pre-Project operations is critical for establishing baseline conditions. Focus Area 184 is
located approximately 1.4 miles downstream of the proposed dam site and will provide a
mainstem site and a side channel site within its 1-mile extent (Figure 2.1-1). In order to establish
a third site with an additional habitat type, it will be necessary to move outside of the Focus Area
to sample the mouth of Tsusena Creek. Focus Area 173 is located approximately 11.7 miles
downstream from the proposed dam site and contains a complex of main channel and off-channel
habitats within a wide floodplain, thus representing the greatest channel complexity within its
geomorphic reach (MR-2; Figure 2.1-2). Focus Area 173 will provide a mainstem site, a side
channel site, and a side slough site within its 1.8-mile extent.
Below Devils Canyon, Focus Areas 141 and 104 have been selected because of the diversity of
main channel and off-channel habitats that they contain, and documented fish use in and nearby
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these Focus Areas. Focus Area 141 includes the Indian River confluence, which is a primary
Middle Susitna River tributary with documented high fish use. Focus Area 141 offers a range of
main channel and off-channel habitat types and will thus provide a mainstem site, a tributary
mouth site, and a side channel site within its 1.6-mile extent (Figure 2.1-3). Focus Area 104 is
located approximately 3.3 miles upstream of the confluence of the Chulitna and Susitna rivers,
making it the downstream-most station in the Middle Segment for the River Productivity Study.
This Focus Area contains the confluence of Whiskers Creek, side channels, and side slough
habitats that have been documented as supporting juvenile and adult fish use. Focus Area 104
will provide a mainstem site, a side slough site, and a side-channel site within its 1.2-mile extent
(Figure 2.1-4).
For storm event sampling, Focus Area 104 was retained for study, and Focus Area 144 was
additionally selected. Focus Area 144 is located approximately 2.3 miles upstream of the Indian
River confluence, and features a side channel and a side slough complex (Figure 2.1-5). Both
Focus Areas feature side sloughs that require similar levels of mainstem discharge for
overtopping (ca. 22,000-25,000 cfs), and both side sloughs maintain at least some of wetted
habitat during the summer months (ADF&G 1983c; Hale et al. 1984).
2.1.2. Upper Segment Stations
Two stations will be established in the Upper Segment of the Susitna River and above the upper
limit of the proposed Project’s maximum reservoir pool. After review of the results of 2012 data
collection efforts, as well as information collected from ADF&G fish inventories in the Upper
Susitna River (Buckwalter 2011), few details on habitat types present in the Upper Segment of
the Susitna River are available. The data that is available is limited to habitats within the
Oshetna River and downstream.
As a result, the two stations in the Upper Segment of the Susitna River have been selected using
existing topographic maps and available orthographic imagery to review river features. A site
reconnaissance trip will be used to confirm the selected stations (Table 1.2-1, Figures 2.1-6 and
2.1-7). The downstream-most station (tentatively designated RP-233) is a 1.5-mile reach
containing the mouth of the Oshetna River, in which ADF&G has recently documented the
presence of adult and juvenile Chinook salmon (Buckwalter 2011; ADF&G 2011). Station RP-
233 will provide a mainstem site, a tributary mouth site, and a possible side channel or slough,
although this will need to be confirmed during site reconnaissance (Figure 2.1-6). In the event
that no additional habitat types are available, the study will set up two main channel sites, with
one above the confluence with the Oshetna River, and another below. The second station
established in the Upper Segment (RP-248) will be located within a 1.3-mile reach beginning
approximately 1.25 miles upstream of the Tyone River confluence. Imagery and maps indicate
this area is complex, with split channels, side channels, and possibly side sloughs (Figure 2.1-7).
Station RP-248 will provide a mainstem site, side channel site, and a side slough site, and will be
confirmed with site reconnaissance.
2.1.3. Talkeetna Station
One task within the River Productivity Study assesses the feasibility of the Talkeetna River as a
reference site for post-Project monitoring activities at these stations. Because the Talkeetna
River is outside of the Project area, results from 2012 study efforts and historic information from
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the 1980s are limited. Review of the literature has revealed a single USGS study which reports
on water quality and benthic macroinvertebrate data collected from the Talkeetna River,
approximately 5 miles upstream from its mouth near a USGS gaging station (Frenzel and Dorava
1999). The USGS sampling reach was limited to the main channel, with benthic
macroinvertebrate sampling taken off a cobble point bar.
The ideal station on the Talkeetna River for the feasibility study will be a match with physical
conditions similar to one of the Focus Areas selected in the Middle Segment of the Susitna
River. The Talkeetna station will feature both main channel and off-channel habitat types to
allow for the establishment of a main channel site, a side channel site, and a side slough site.
Habitat types have not been identified for the Talkeetna River, so station selection for the
feasibility study will be limited to an initial review of topographic maps and available
orthographic images. Final site selection will be made with a site reconnaissance trip.
2.2. Benthic Macroinvertebrate Sampling
Three sampling periods (also known as Index Periods) will occur from April through October in
both study years (2013-2014) to capture seasonal variation in community structure and
productivity. These seasonal periods are tentatively scheduled for April through early June for
Spring, late June through August for Summer, and September through October for Autumn. In
addition, benthic sampling will be conducted both before and after storm events that increase
flows to levels similar to pulse flow increases from the proposed Project (ca., 5,000 cfs) at two
side slough sites, located in Focus Areas 104 and 144. Specific details on timing of sampling are
provided in Section 3 below.
2.2.1. Field Sampling Protocols
Benthic macroinvertebrate sampling will be conducted in fast-water mesohabitats (typically
riffles/runs) within main channel (i.e., main channel, side channels, and tributary mouths) and
off-channel macrohabitat types (i.e., side sloughs). Measurements of depth, mean water column
velocity, mean boundary layer velocity (near bed), and substrate composition will be taken
concurrently with benthic macroinvertebrate sampling at the sample location. While a benthic
macroinvertebrate sample is being collected by one crew member, two other crew members will
be collecting the associated benthic algae samples (Section 2.3) and associated habitat
measurements (e.g., depths, velocities, etc.).
Water temperatures will be monitored using submerged temperature loggers at hourly intervals
and deployed throughout the ice-free season. Temperature and flow monitoring will be
coordinated with the Baseline Water Quality Study (RSP Section 5.5) and the Instream Flow
Study (RSP Section 8.5), and supplemental temperature loggers will be deployed, if necessary, at
all River Productivity Study sites.
Higher flows may inundate new shoreline substrates, which present a risk of sampling in areas
that are not fully colonized. The shoreline bathymetry for each site will be evaluated such that
changes in water level due to increasing or decreasing flows must remain constant enough that
the substrates accessible for sampling will be continually inundated for a period of at least one
month to facilitate colonization of those substrates. At each sampling location (see Section
2.2.1.1), a basic transect will be established, perpendicular to the shoreline. A stake or pin will
be hammered into the riverbank at the high water mark. Measurements of depth and velocity
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will be taken every meter, out to the sampling location, and up to 5 meter past it or up to a depth
of 1 meter, whichever occurs closest to the shoreline. This localized transect information will be
used in conjunction with multiple remote cameras and staff gages installed along the Susitna
River, along with the USGS gage at Gold Creek, to closely monitor for conditions that indicate
adequate inundation levels for sampling. Depth and velocity measurements will also be taken at
1-meter intervals both upstream and downstream of the Hess sample location, out to a distance of
5 meter or a depth of 1 meter. All depth and velocity information will be recorded on the field
data sheet for the sample entry.
2.2.1.1. Hess Samples
Sampling will be conducted using a modified Hess sampler (0.086 m²-area) with a 243
micrometer (µm) mesh net (Canton and Chadwick 1984; Klemm et al. 1990). The modified
Hess sampler is commonly used in benthic macroinvertebrate studies (Barbour et al. 1999;
Klemm et al. 1990; Klemm et al. 2000; Carter and Resh 2001) including previous Susitna River
studies from the 1980s (Hansen and Richards 1985, Trihey 1986). The modified Hess sampler is
an enclosed cylinder 40 cm in height and 33 cm in diameter, with a screened opening in the
front, and receiving mesh net bag opposite it (Figure 2.2-1). The cylinder is forcibly pushed and
rotated into the substrate to depths of 7.5-15 cm, and all substrate within the enclosed 0.086 m2
area is cleaned of macroinvertebrates. Water flows in through the upstream window and out the
downstream window into the collecting net and bucket. The modified Hess sampler is easy to
use, yet also prevents escape of organisms, which is an issue with other sampling devices, such
as the Surber sampler and kick nets. The sampler also prevents drifting organisms and materials
from entering the sample, which is an important factor in sampling the organic matter
components for this study (Section 2.4). Replicate samples (n=5) will be collected to allow for
statistical testing of results for short- and long-term monitoring. The following is the procedure
for collecting Hess samples.
1. Walk the length of the sampling reach, identifying all locations that would be suitable for
sampling. A suitable sampling area will be in fast-water habitat, offering coarse
substrates at water depths of approximately 40 cm or less and which have been inundated
for at least 30 days. The most ideal locations are likely to be shoreline reaches that offer
larger areas of large gravel and cobble substrates. Select five of the suitable locations,
spacing them as equidistantly as possible, to be representative of the site. If five unique
and separate locations are not available, it will be necessary to collect more than one
sample within the same location. If this is the case, space the sample locations out as far
as possible. For example, if conditions require two samples in one riffle area, sample at
the downstream end and then the upstream end. As a general rule, samples should not be
taken within 10 m of each other. Selected locations at each site should be sampled in a
downstream-to-upstream direction.
2. After selecting a sample’s location, measure and record the depth, mean water column
velocity (60 percent of depth), mean boundary layer velocity (near bed), and a visual
estimate of substrate composition using the Wentworth scale, to the nearest 5 percent,
where the sample is taken.
3. Position the Hess sampler securely on the river substrate at the chosen location, and
slowly twist the bottom of the frame into the substrate. For streambeds comprised of
larger cobbles, this may not be possible. As a general rule, larger substrates that are more
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than 50 percent inside the sampling area should be lifted and moved into the sampler, and
those less than 50 percent inside should be excluded. If complete containment of the
sampling area cannot be accomplished, a neoprene skirt may be to be used along the
bottom of the sampler.
4. Ensure the screened opening is facing into the current and the net portion is trailing
downstream. Hold the sampler in position between your legs, applying pressure with
your knees. Do not to disturb the substrate upstream from the sampler, as that area will
supply the algal samples (Section 2.3) to associate with this Hess sample.
5. Reach into the cylinder and carefully turn over and lightly hand-scrub all large substrates,
which will dislodge macroinvertebrates clinging to the stones and wash them into the net
bag. Examine each rock for organisms, including larval or pupal cases that may be
attached to it before removing it from the sampler.
6. Stir remaining finer substrate with your hands to a depth of 5 to 10 cm, to dislodge all
remaining organisms, which will be collected in the mesh net.
7. To prevent the contents of the mesh net bag from washing out, slowly lift the sampler out
of the substrate and the water, tilting the sampler so that the net bag’s opening is oriented
up.
8. Wash any debris and organisms clinging to the net bag down into the cod-end collection
bucket by splashing river water on the outsides of the bag, or by lowering the bag into the
stream and quickly removing it.
9. Return to shore and carefully remove the cod-end collection bucket from the sampling
net over a 250-µm sieve, and empty the contents into the sieve.
10. Carefully examine the mesh net bag of the Hess sampler for any clinging organisms and
remove them with forceps, and place them with the rest of the sample in the sieve.
11. Examine the contents in the sieve. Closely inspect all large materials for attached
invertebrates. Keep all organic matter; it will be needed for assessment of organic matter
content (Section 2.4). Discard all larger inorganic materials.
12. Rinse the sample in the sieve, consolidating the material to one side of the sieve, and
transfer the material into a storage container. Efforts should be taken to minimize the
amount of water retained with the sample to prevent too much dilution of the ethanol
used to preserve the sample. Next, scoop out the material with a spoon or spatula and
place it in the sample container, and then rinse the sieve to consolidate the remaining
material to one side of the sieve. Wash the remaining sample into the container with a
wash bottle containing 95 percent ethanol.
13. A paper label (standard label hereafter) defining the station, site, sample number, date,
collector, and unique sample identification code is added to the sample. Adhesive
standard labels are also applied to the outside of the sample jars.
14. Preserve the sample with additional 95 percent ethanol, enough to completely cover the
sample, and place the labeled lid on the container, making sure it is secured tightly and
does not leak.
15. Rinse the Hess sampler net and cod-end collection bucket and reassemble.
16. Move the sampler upstream to the next riffle/run identified, and repeat this process.
Continue until five replicate samples have been sampled, each upstream from the last.
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2.2.1.2. Snag Samples
Due to the prevalence of large woody debris in the Susitna River, woody snags, if present at a
sampling site, also will be sampled as a substrate stratum for benthic macroinvertebrates.
Sampling methods for woody snags will be semi-quantitative, based upon protocols established
by the USGS (Moulton et al. 2002). Moulton et al. (2002) defines wood snags as “submerged
sections of wood (branch or log) having a minimum diameter of 1 cm and are colonized by
aquatic organisms.” The following is the procedure for sampling wood snags.
1. Identify five (if present) woody snag locations throughout the site area. Suitable woody
snags will have been submerged for an extended period of time so as to be clearly
colonized.
2. At each wood snag location, identify a woody snag piece to remove from the water. Ideal
snag pieces should be at least 5 cm in diameter. Sections of larger branches may need to
be removed, using a hand saw. Ideally, each snag section will originate from a separate
snag, and therefore count as a separate, replicate sample.
3. Measure and record: the depth of the snag piece, both from the water surface and from
the stream bed; the current velocity at the snag piece and in the water column (60 percent
of depth); and visually estimate the substrate composition using the Wentworth scale, to
the nearest 5 percent, where the woody snag is positioned. This information is written on
the field data collection worksheet for the site.
4. Place a collection net downstream of the woody snag piece, to capture and minimize loss
of mobile or loosely attached invertebrates.
5. Remove the woody snag piece from the water, using a saw or lopping shears. Each
woody snag piece removed from the river should be closely inspected for evidence of
colonization and discarded if it appears to have recently fallen into the river.
6. Place the woody snag piece, lengthwise, over a plastic bin (e.g., a 10-Gal Rubbermaid
storage container) to delineate the sampling area. Initially, loosely attached insects are
rinsed from the surface of branches with a wash bottle or pump sprayer. The snags will
be allowed to dry for a period of time (usually 1 hour), insects will begin moving from
retreats and dropping into the container. Meanwhile, specimens should be picked from
attached detritus, retreats, and cracks using fine-tipped forceps.
7. As desiccation begins to hinder insect movement, rather than encourage it, the woody
snag piece should be lightly rinsed. The total amount of time spent collecting specimens
from each sample is approximately 1 -1.5 hours.
8. The invertebrates, associated debris, and water within the sample containers are agitated
and poured through a 125-µm sieve. The container should be rinsed, agitated, and sieved
several times and any remaining specimens should be picked from the container by hand.
The contents of the sieve are then washed into a 500-ml wide-mouth plastic jar with a
wash bottle containing 95 percent ethyl alcohol. Any insects clinging to the sieve are
transferred to the sample jar with forceps before filling the container with alcohol to
completely cover the sample material.
9. A standard label defining the station, site, sample number, date, collector, and unique
sample identification code is added to the sample. Adhesive standard labels are also
applied to the outside of the sample jars. Samples from each site are numbered
consecutively, 1-5.
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10. After final inspection, snag sections sampled will be measured for length and average
diameter to determine surface area sampled. The length of branch, or section of branch,
within the containers is measured, as is the circumference at both ends, to estimate the
surface area for each woody snag sample. This information is written on the field data
collection worksheet for the site.
2.2.2. Sample Processing Protocols
Benthic macroinvertebrate samples from both Hess and snag samples will be sent to one or more
accredited contract laboratories for subsampling, sorting, and taxonomic identification.
Laboratories should have taxonomists on staff that are certified by the Society for Freshwater
Science for taxonomic identifications of specific groups (EPT taxa, chironomids, etc.). Sample
processing protocols should follow those established by the USEPA for the Rapid Bioassessment
Protocols (Barbour et al. 1999) and modified for use in Alaska (Major and Barbour 2001; see
Appendix 1).
A gridded subsampling tray (Caton 1991) will be used to acquire a 300-organism fixed-count
(±20 percent) subsample. All invertebrates are removed from debris with the aid of a dissecting
microscope (7-45x) and sorted into major taxonomic groups. As specified in Major and Barbour
(2001), benthic macroinvertebrates should be identified to the lowest practical level. For aquatic
insects, identifications are to the genus level, with exceptions for damaged or immature
specimens. Non-insect taxa are identified to family or order.
Sorted debris is retained in a labeled, 60-ml bottle and stored for later for QA/QC assessment
and, for Hess samples, organic matter analysis (Section 2.4). At the conclusion of the
subsampling effort, a large-rare organism sort is performed on the unsorted portion of the sample
to identify taxa that were not accurately represented in the sorted grids. All large organic
material removed from the tray prior to subsampling should also be retained for organic matter
analysis (Section 2.4).
Biomass estimates will be taken for invertebrate taxa collected for benthic sampling. The fresh
blotted wet mass of invertebrate taxa in samples will be recorded. The samples will be oven
dried at 60˚C until reaching constant mass, and the dry mass will be recorded.
2.2.3. Data Analysis Methods
The end result of benthic macroinvertebrate sampling after the collection, processing, sorting,
and identification of the various taxa, is the creation of a matrix of abundances. Those
abundances can then be transformed into a variety of quantitative measures, called metrics,
which represent different attributes of the structure, composition, or function of the benthic
macroinvertebrate assemblage (Wang and Lyons 2003). Results generated from the collections
will include several descriptive measures commonly used in aquatic ecological studies (Table
2.2-1). Each measure will have the mean and variability (95-percent confidence intervals)
calculated. Comparisons for these measures will be made among sites, to look for differences
between habitat types, as well as spatial trends along the length of the river (upstream versus
downstream sites). Comparisons will also be made over time, examining both the interannual
(seasonal) and annual variability in the benthic macroinvertebrate community. Statistical tests
(ANOVA, MANOVA) will be performed on each measure to look for an overall significant
difference among sites, seasons, and years. If a difference is significant (p ≤ 0.05) for the
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measure, then a multiple comparison test will be used to describe the significant differences in
the data. Assumptions of normality and equal variance will also be tested with each ANOVA.
In the event data does not meet distribution assumptions, it may be transformed (i.e., log+1 or
square root) prior to analysis. If the data does not pass a test for normality, then a non-
parametric test, like the Kruskal-Wallis one-way ANOVA on ranks, followed by a Kruskal-
Wallis multiple comparison z-value test will be used. If the data fails the modified-Levene-
equal-variance test, a series of unequal-variance-two-sample t-tests can be utilized to test for
significant differences.
In addition, multivariate ordination procedures, such as principle components analysis (PCA)
and canonical correspondence analysis (CCA), may be utilized to explain the relative
contribution of different measures, taxa, and environmental variables to observed grouping
patterns that best explain variability in the data. The goal of ordination is to preserve differences
between samples, to reduce the dimensionality of the data, and to create a set of independent
covariates from a set of correlated variables. The general approach is to define a new set of axes
that describe the majority of the variability in the multivariate data. The first axis is a vector
fitted to the direction of maximum variability in the data. Successive axes are orthogonal
(perpendicular) to the existing axes, with each additional axis explaining a smaller portion of the
total variation in the data. PCA is probably the most widely known type of ordination. CCA is a
procedure to analyze two (or more) data tables simultaneously and is the preferred method for
analyzing species and environmental data, and is particularly well suited to ecosystem-species
questions (ter Braak 1986). Cluster analyses using the Bray-Curtis measure of dissimilarity may
be used to group sites or stations by the similarity of their community structure.
2.3. Benthic Algae Sampling
2.3.1. Field Sampling Protocols
Benthic algae (also referred to as periphyton) will be sampled in conjunction with benthic
macroinvertebrate sampling with the Hess sampler (Section 2.2). Rock surfaces in fast-water
habitats are sampled, based on the methods utilized by the USGS for the NAWQA program
(Moulton et al. 2002), the USEPA for the Rapid Bioassessment Protocol (Barbour et al. 1999),
and the USEPA for the Environmental Monitoring and Assessment Program (EMAP; Lazorchak
et al. 2000; Peck et al 2006). Methods employ an area-delimiting sampling device that is pressed
to a smooth rock or cobble substrate to consistently sample a defined surface area For the
purposes of this study, a PVC pipe area delimiter with a rubber collar at one end, as
recommended by the EPA methods, will be adopted (Barbour et al. 1999; Lazorchak et al. 2000;
Peck et al 2006). In the event that the PVC pipe method proves unsuitable for use, other
sampling approaches may be adopted (Moulton et al. 2002; Fetscher et al. 2009). Moulton et al.
(2002) describe the SG-92, a modified syringe-sampling device, which performs best on smooth
cobble surfaces with moderate-to-dense coverage of microalgal periphyton. Other approaches
are the plastic frame of a 35-mm or medium format slide and a rubber mat with an opening. The
slide frame is preferred by some, because it is more flexible and form-fitting than a section of
PVC pipe or the barrel of a syringe. The rubber mat is likewise flexible with the added feature of
covering the area outside of that delineated and when rinsed, reduces the potential for sample
contamination (Fetscher et al. 2009). .
The following is the procedure for sampling benthic algae.
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1. Randomly collect five rock substrates distributed in the undisturbed area located
upstream of each Hess sample being collected. At each location where a cobble or rock
substrate is collected, measurements of depth, mean water column velocity, mean
boundary layer velocity, and area substrate composition will be taken. Light availability
will be measured at each sample location with an underwater light sensor to measure the
photosynthetically-active radiation (PAR) available to the algal community. PAR
readings will be taken from just below the water surface to the stream bottom at regular
10-cm intervals. A turbidity measurement, using a portable turbidity meter, will also be
taken at the sample site to determine water clarity. Record all measurements on the field
data sheet for the sampling site.
2. Place substrates in a plastic dishpan and transport them to the shoreline, in a shaded area
if possible, to collect algae from each cobble.
3. Place the area-delimiting sampler on a substrate surface. Press down on the gasket/o-ring
and rotate slightly to create a tight seal. Maintain this seal while the collection is made.
4. Using a pipette, squirt approximately 5 ml of filtered stream water into the sampler on the
cobble. If the water leaks from the barrel, select another place on the substrate and try
again. If the water does not leak, insert a small brush into the barrel and scrub the
enclosed area on the substrate to remove the algae.
5. Remove the algae and water mixture with a pipette and dispense it in a 100-ml graduated
cylinder. [Note: dispensing into a graduated cylinder instead of a 500-ml sample bottle is
recommended in case the sampler seal fails while collecting the sample, thereby causing
the collector to start over. If the seal fails, then only the contents of the graduated
cylinder are discarded.] Repeat this process several times until all of the visible
periphyton is removed. Pour the contents of the graduated cylinder into a 500-ml sample
bottle. Alternatively, an aspirator device (Bouchard and Anderson 2001) can be used to
remove algae materials from the area delimiter.
6. Repeat the sampling procedure for a single area on each of the cobbles selected; the
composited sample is composed of 5 discrete collections taken from 5 cobbles. Ensure
that the sample volume does not exceed 475 ml. Place the bottle on ice inside a cooler
and keep in the dark until the sample is processed.
7. Measure the diameter of the area sampled by the sampler at the beginning and end of
sampling. Record these diameters on the field data sheet to establish an average diameter
from which the sampling area can be calculated.
8. Calculate the total sampling area by using the following formula:
9. Total sampling area (cm2) = (n)(π)(d/2)2
10. Where, n = number of discrete collections, π = 3.1416, and d = average diameter of the
sampled areas, in centimeters. [note: if using the inside diameter of a 5-cm PVC pipe,
then the total surface area sampled for 5 cobbles will be about 98 cm2.]
11. Process the periphyton sample following the steps described in section 2.3.2. Processing
(below).
2.3.2. Processing Protocols
Benthic algae samples will be initially prepared and processed for additional laboratory analyses
by subsampling. Processing can take place immediately in the field, or after coming out of the
field later that day. In either case, care should be taken to avoid sample exposure to direct
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sunlight. Procedures for processing are taken directly from the Quantitative Microalgae
processing procedures detailed in Moulton et al. (2002). Moulton et al. (2002) state:
“The goal of processing a composited algal sample in the field is to prepare subsamples
for various laboratory analyses. Successful execution of the processing procedures
described here to produce high-quality subsamples for analysis is dependent on
measuring and tracking various volumes as the sample is processed.”
Two subsamples are taken from each benthic algae composite sample for the purpose of
determining chlorophyll-a and ash free dry mass (AFDM) in the laboratory. The remaining
volume of the sample component is preserved, and archived for additional analyses, if needed.
The following is the procedure for processing benthic algae samples for chl-a and AFDM.
1. Measure the sample volume to the nearest milliliter. Record on field data sheet.
2. Calibrate the pipette. [Note: the calibration is important, especially if the tip has been
trimmed to enlarge the opening for extracting dense algal material.]
3. Assemble the chlorophyll filtration apparatus by attaching the filter base with rubber
stopper to the filtering flask. Join the flask and a hand-operated vacuum pump (with
gage) using a section of tubing
4. Place a 47-mm glass fiber filter (e.g., Whatman™ GF/F) on the filter base and wet with
deionized water. [Note: wetting the filter will help keep it in place in windy weather.
Attach the filter funnel to the base.]
5. Homogenize the composite algae sample. Invert the sample bottle 10 times and use a
battery powered stirrer to break up the clumps. Cut algal filaments, if present, into pieces
about 2 mm in length.
6. Shake the sample component vigorously for about 30 seconds to ensure that it is well
mixed before extracting subsamples.
7. Extract two 5-mL aliquots of homogenized sample using the pipette and dispense onto
the wetted glass-fiber filter.
8. Filter the aliquots by using 7-10 psi to avoid rupturing the algal cells.
a) Examine the filter. An adequate amount of microalgal biomass for analysis is
indicated by the green or brown color of material retained on the filter. Extract
additional 5.0-mL aliquots and filter until the desired level of biomass is obtained.
b) Determine the number of 5.0-mL aliquots filtered, and record the subsample volume
on the field data sheet (e.g., 2 aliquots x 5.0 mL/aliquot = 10 mL subsample volume).
c) Rinse the funnel sides with deionized water; allow the water to be vacuumed
completely before releasing the vacuum from the filtering apparatus.
d) Remove the filter from the funnel base with forceps.
e) Rinse the filter funnel, filter holder, filter chamber, and graduated cylinder thoroughly
with deionized water.
f) Repeat the filtering steps for each subsample (either Chl-a or ADFM) collected.
9. Prepare the filtered subsamples (Chl-a and AFDM) for storage and shipping
a) Fold each filter into quarters with filtered biomass inside. Wrap each filter in a small
piece of aluminum foil and place in separate labeled resealable plastic bags.
b) Label the bag with the following required information: site, collection date, total
sample area, sample volume, subsample volume, sample type (Chl-a or AFDM), and
sample identification code.
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c) Place the labeled resealable plastic bags in a cooler containing dry ice. About 4.5 kg
(10 pounds) of dry ice is needed for subsamples packed in a small cooler (< 2 gal).
Insulate the cooler with newspaper to minimize sublimation of the dry ice.
10. Measure the volume of the remaining benthic algae sample component. This represents
the subsample volume of the remaining subsample to be archived.
11. Preserve the archive subsample with a sufficient volume of buffered formaldehyde to
obtain a final concentration of 3 to 5 percent buffered formalin. Record the preservative
volume on the field data sheet.
Volume (mL)
Sample 25 50 100 125 200 250 300 350 400 450 475
Buffered
formaldehyde
1 2 4 6 8 11 14 16 18 22 23
12. Place a completed sample label on the sample bottle.
13. Filtered subsamples should be stored in freezers (at -20°C) as soon as possible.
14. Samples should be shipped to the laboratory as soon as possible, because of a 25-day
holding-time limit on the subsamples.
15. Complete a Chain of Custody form provided by the accredited contract laboratory for
listed samples that indicates which laboratory analyses are to be performed. Contact the
contracted laboratory to make them aware of plans to ship (via overnight shipping
service) coolers containing dry ice and frozen subsample filters.
2.3.3. Data Analysis Methods
Results generated from the collections would include both AFDM and chlorophyll-a. Each
measure will have the mean and variability (95-percent confidence intervals) calculated.
Comparisons for AFDM and chl-a will be made among sites, to look for differences between
habitat types, as well as spatial trends along the length of the river (upstream versus downstream
sites). Comparisons will also be made over time, examining both the interannual (seasonal) and
annual variability in algal biomass and chl-a. Statistical tests (ANOVA, ANCOVA, MANOVA)
will be performed on each measure to look for an overall significant difference among sites,
seasons, and years. If a difference is significant (p ≤ 0.05) for the measure, then a multiple
comparison test will be used to describe the significant differences in the data. Results may also
be used as covariates in the analyses of benthic macroinvertebrate data, especially in regards to
the functional feeding group compositions in the community. Multivariate ordination
procedures, such as principle components analysis (PCA) and canonical correspondence analysis
(CCA), may be utilized to explain the relative contribution of AFDM and chlorophyll-a to
observed grouping patterns of sites, stations, times, and in relation to macroinvertebrate taxa,
their distributions, and the functional feeding groups of the benthic macroinvertebrate
community.
2.4. Organic Matter Sampling
Organic matter materials serve as an important food resource to benthic macroinvertebrates,
serving as a conduit for the energy flow from organic matter resources to vertebrate populations,
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such as fish (Hershey and Lamberti 2001; Hauer and Resh 1996; Reice and Wohlenberg 1993;
Klemm et al. 1990). This organic matter exists as both fine particulate organic matter (FPOM)
and coarse particulate organic matter (CPOM). FPOM includes particles ranging from 0.45 to
1000 µm in size and can occur in the water column as seston or can be deposited in lotic habitats
as fine benthic organic matter (FBOM; Wallace and Grubaugh 1996). CPOM is defined as any
organic particle larger than 1 mm in size (Cummins 1974).
Given the dominant characteristics of the Susitna River system (i.e., large, cold, and turbid
during the growing season), secondary productivity is likely to be driven by allocthonous inputs
of organic material from the terrestrial environment. Benthic organic material is one of the most
important “interrelated environmental factors” influencing the macroinvertebrate community,
and damming the river is likely to have significant consequences for the transport of organic
matter from the upper watershed. Therefore, to address the importance of organic matter to
productivity in this type of system, this study will quantify benthic organic matter as it is related
to the benthic macroinvertebrates being collected.
2.4.1. Field Sampling Protocols
In order to quantify the amounts of organic matter available in the Susitna River for river
productivity, CPOM and FPOM will be collected directly from all benthic macroinvertebrate
sampling, in Hess samples and drift net samples. (RSP Objective 2, Section 9.8.4.2.1.; RSP
Objective 3, Section 9.8.4.3.).
2.4.1.1. Benthic
In order to streamline the collection efforts, Hess sampling devices will possess a net mesh size
of 250 µm in order to retain FBOM in the 250–1,000 µm size range for analysis, as well as
CPOM particles. All organic debris collected within each Hess sample collected will be retained
with the sample and preserved with the entire portion in 95 percent ethanol. Organic materials
too large to fit within the sample jar (i.e., sticks) will be thoroughly examined for attached
organisms and broken down enough to fit within the sample jar or in a large resealable plastic
bag. A standard internal label will be placed within the bag, including the same information as
the benthic sample jar. An additional note will be made on the field data sheet for that specific
sample indicating that additional organic matter was collected and stored in the plastic bag.
2.4.1.2. Seston
Suspended FPOM (seston) will be collected from material in invertebrate drift samples, utilizing
drift nets with a 250-µm mesh size in order to retain FBOM in the 250–1,000 µm size range for
analysis, as well as CPOM particles (RSP Objective 3, Section 9.8.4.3). All organic debris
collected within each drift sample collected will be retained with the sample and preserved with
the entire portion in 95 percent ethanol.
2.4.2. Processing Protocols
Processing of benthic macroinvertebrates involves subsampling to acquire a 300-organism fixed-
count (±20 percent) subsample. All invertebrates are removed from debris with the aid of a
dissecting microscope (7-45x), and sorted debris is retained in a labeled, 60-ml bottle and stored
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for later for QA/QC assessment and, for Hess samples, organic matter analysis. Organic matter
retained from subsampling after organism sorting and processing will be separated from
inorganic material, rinsed through 1-mm and 250-µm nested sieves, to separate CPOM and
FPOM components of the detritus, oven-dried (60°C), and weighed. Results will be expanded
according to the subsample factor, and calculated as amounts of CPOM and FPOM per unit area
(g/m2).
Processing of drift samples will require full sorting. After the detritus has been sorted and
benthic invertebrates removed, the sample material should be rinsed through 1 mm and 250 µm
nested sieves to separate CPOM and FPOM components of the detritus. Components will then
be oven-dried (60°C), and weighed. Results will be calculated as amounts of CPOM and FPOM
per unit area (g/m3).
2.4.3. Data Analysis Methods
Results generated from the collections would include amounts of CPOM and FPOM per unit area
(g/m2 for benthic samples and g/m3 for drift samples). Each measure will have the mean and
variability (95-percent confidence intervals) calculated. Comparisons for these measures will be
made among sites, to look for differences in organic matter content between habitat types, as
well as spatial trends along the length of the river (upstream versus downstream sites).
Comparisons will also be made over time, examining both the interannual (seasonal) and annual
variability in the amounts of organic matter within the sampled substrates. Statistical tests
(ANOVA, ANCOVA, MANOVA) will be performed on each measure to look for an overall
significant difference among sites, stations, seasons, and years. If an effect is significant (p ≤
0.05) for the measure, then a multiple comparison test will be used to describe the significant
differences in the data. Results may also be used as covariates in the analyses of benthic
macroinvertebrate data, especially in regards to the functional feeding group compositions in the
community. Multivariate ordination procedures, such as principle components analysis (PCA)
and canonical correspondence analysis (CCA), may be utilized to explain the relative
contribution of organic matter to observed grouping patterns of sites, stations, times, and in
relation to macroinvertebrate taxa and distributions, and the functional feeding groups in the
benthic macroinvertebrate communities.
2.5. Invertebrate Drift Sampling
Stream dwelling invertebrates are often transported downstream in the water column, which is
referred to as “drift”. Several categories have been used in the literature to describe drift:
behavioral, constant, and catastrophic (Waters 1972). Behavioral drift occurs when organisms
actively enter the water column, for example to escape predators or search for food. Behavioral
drift has been found to show a diurnal pattern for many species. Many studies have reported
increased drift densities during the night, peaking twice: one just after sunset, and a smaller peak
just before sunrise (Brittain and Eikeland 1988). Constant drift, also called background drift, is
drift that occurs in steady, low numbers, regardless of the time of day, because of accidental
dislodgement from the substrate. Catastrophic drift is usually associated with flow-related
disturbances but can also be due to disturbances involving pollution or changes in the
temperature regime (Brittain and Eikeland 1988). Catastrophic drift can result from both flow
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increases and decreases, either due to natural occurrences such as floods or spates and droughts
or due to river regulation.
Regarding behavioral drift, it is unclear whether the benthic community in the Susitna River
would exhibit the typical strong diel patterns. While many studies show that drift is
characterized by a distinct diel periodicity, with greater drift in the night than during the daytime,
such diel patterns are usually exhibited by Ephemeroptera, Plecoptera, Trichoptera, (EPT taxa)
and Simuliidae taxa (Brittain and Eikeland 1988). Chironomidae are usually reported to be
aperiodic, showing either no diel variation in drift densities, maximum drift during daylight
hours, or a maximum drift at night (Brittain and Eikeland 1988). Measures of drift in a glacial
river and its non-glacial tributary in Western Norway found that Chironomidae were the most
abundant in drift and showed significant peaks in drift density at mid-day sampling (Saltveit et
al. 2001). Light level serves as a signal for behavioral drift (Allan 1995). Müller (1973) found
that the reaction of stream invertebrates to the long photoperiods of summers in higher latitudes
is much different in that it extinguishes drift rhythm entirely.
In addition to aquatic invertebrates, terrestrial invertebrates often enter streamflows and drift
from riparian vegetation, can comprise a significant proportion of drift, and may be an important
food subsidy for salmonids (Elliott 1973; Cada et al. 1987; Wipfli 1997; Nakano et al. 1999;
Kawaguchi and Nakano 2001; Allan et al. 2003) particularly in unproductive streams
(Romaniszyn et al. 2007). This terrestrial component of drift does not display any diurnal
patterns.
In Alaskan streams and rivers, the benthic community is dominated by Chironomidae, with EPT
taxa together accounting for less than 25-percent of the fauna (Oswood 1989). Given that
several studies have shown that chironomids do not necessarily adhere to the typical patterns of
diurnal drift, and that such diel periodicity is disrupted by long photoperiods of summers in
higher latitudes, invertebrate drift sampling conducted during daylight hours can be considered a
valid approach under this study plan. Collecting drift samples concurrently with benthic
macroinvertebrate sampling at all sites within the six established sampling stations will allow for
comparisons between the drift component and the benthic macroinvertebrate community, as well
as revealing the availability of terrestrial invertebrates to fish predation.
2.5.1. Field Sampling Protocols
Sampling will be conducted in fast-water habitats within the established mainstem sites, and
associated off-channel habitat sites. Invertebrate drift sampling will be conducted based on the
USEPA’s EMAP drift net sampling protocols (Klemm et al. 2000). Drift sampling will be
conducted during daylight hours, preferably beginning shortly after arrival at a site in the
morning, and will involve collecting duplicate samples (Klemm et al 1990; Klemm et al. 2000).
Drift nets with a 250-µm mesh size will be utilized (Figure 2.2-1). Water velocity will be
recorded with an in-net flow meter. The following is the procedure for sampling invertebrate
drift.
1. Locate the area to install the drift net pair for the site. Do not use drift nets in areas with
currents less than 0.05 meters per second (m/s). Drift nets should always be deployed
above the sampling reach to avoid the unintentional introduction of macroinvertebrates to
the drift by disturbance of the stream substrate by the crew’s other sampling efforts.
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Ideally, the nets should be installed at the downstream end of a fast-water habitat
(typically a riffle or run).
2. Install the net in an area of river that is receiving part of the main channel flow, but that
can be safely accessed by wading. Depths of 1 m or less are preferred.
3. Drive steel rods or rebar into the substrate. Drift nets should be oriented perpendicular to
and facing the stream flow and secured to the rods with cable clamps. The bottom of the
net mouth should be suspended at least 2 cm above the stream bed to deter invertebrates
from crawling into the net mouth. Position the net so that the top of the net is above the
water surface at least 2 cm, such that drifting terrestrial invertebrates and debris are
collected. Note on the field data sheet the distance from the bottom of the net (from the
inside margin of the frame) to the water surface. This will be used to calculate the area of
the net mouth receiving flow.
4. Install the in-net flow meter into one of the nets. Record the starting counter number and
the start time of sampling on the field data sheet. In addition, measure the current
velocity at the entrance of the net and at 60 percent of the depth using a flow meter, and
record the measured velocity and depth, as well as a measure of turbidity and
temperature, on the field data sheet.
5. Avoid walking upstream of the drift net during drift net deployment.
6. Leave the drift net assembly in the river for at least 1 hour, and as long as 3 hours,
checking the nets often for signs of clogging. Drift nets can become clogged with
suspended material, causing nets to back up water at the net mouth, and resulting in an
inaccurate estimate of the total volume of water sampled by a net. If a net is filling
rapidly and beginning to clog in less than one hour, sample for the shorter duration.
7. Before removal at the end of the allotted sampling time (1-3 hours), measure the current
velocity at the entrance of the net and at 60 percent of the depth using a flow meter, and
record the measured velocity and depth, as well as a measure of turbidity and
temperature, on the field data sheet.
8. Record the end time counter number and the end time of sampling on the field data sheet.
9. Remove the nets from the water, holding the net vertically and taking care not to disturb
the bottom upstream of the net. Concentrate the material in each net by swishing up and
down in the stream or river.
10. Empty the contents of one drift net into a 250-µm mesh sieve. Closely inspect all large
materials for attached invertebrates. Keep all organic matter; it will be needed for
assessment of organic matter content (Section 2.4). Discard all larger inorganic
materials.
11. Rinse the sample in the sieve, consolidating the material to one side of the sieve, and
transfer the material into a storage container. Efforts should be taken to minimize the
amount of water retained with the sample to prevent too much dilution of the ethanol
used to preserve the sample. Next, scoop out the material with a spoon or spatula and
place it in the sample container, and then rinse the sieve to consolidate the remaining
material to one side of the sieve. Wash the remaining sample into the container with a
wash bottle containing 95 percent ethanol.
12. A standard label defining the station, site, sample number, date, collector, and unique
sample identification code is added to the sample. Adhesive standard labels are also
applied to the outside of the sample jars.
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13. Preserve the sample with additional 95 percent ethanol, enough to completely cover the
sample, and place the labeled lid on the container, making sure it is secured tightly and
does not leak.
14. Repeat steps 10-13 for the 2nd drift net. Do not combine the contents of separate drift net
samples.
15. Rinse the drift nets out completely.
2.5.2. Processing Protocols
Invertebrate drift samples will be processed in an accredited contract taxonomic laboratory,
using methods similar to those used for benthic samples (Barbour et al. 1999; Major and Barbour
2001; see Appendix 1). Laboratories should have taxonomists on staff that are certified by the
Society for Freshwater Science for taxonomic identifications of specific groups (EPT taxa,
chironomids, etc.). Processing of drift samples will likely require full sorting; however, if a
sample is too large (i.e., it will require greater than 3 hours to process), subsampling may be
warranted, either by a sample splitter or a gridded tray. After the sample has been sorted and
invertebrates removed, the organic debris must be retained for processing (Section 2.4.2).
Biomass estimates will be taken for invertebrate taxa collected for benthic sampling. The fresh
blotted wet mass of invertebrate taxa in samples will be recorded. The samples will be oven
dried at 60˚C until reaching constant mass, and the dry mass will be recorded.
2.5.3. Analysis Protocols
Results generated from these collections will include drift density, drift rate, and drift
composition. For a select subsample of the collection, energy density (J / g wet weight) will be
estimated from the percent dry mass (dry mass / wet mass) of each sample (Ciancio et al. 2007;
James et al. 2012). Energy density will be determined separately for the aquatic and terrestrial
life stages of each primary invertebrate taxon for use in the trophic modeling efforts.
Data collected as part of this study will be compared to data from the benthic macroinvertebrate
collections (RSP Section 9.8.4.2.1) and the fish dietary analysis (RSP Section 9.8.4.7). In
addition, drift results will be compared to the results of 1980s drift studies (ADF&G 1983a;
Hansen and Richards 1985; Trihey and Associates 1986) to evaluate any differences between the
historic and current drift components of the macroinvertebrate communities.
2.6. Adult Insect Emergence Sampling
2.6.1. Field Sampling Protocols
To measure insect emergence, floating emergence trap samplers will be deployed, with one trap
per site. The emergence traps will be based on previous designs of floating aquatic emergence
traps (LeSage and Harrison 1979; Cushman 1983; Davies 1984; Walton et al. 1999). The
emergence trap design will be a low-profile trap with a floating base (Figure 2.2-1), with a
collection bottle or tray with alcohol preservation attached to the trap to collect adult specimens.
The trap will be anchored to rebar stakes driven into the stream bed by a length of chain, cable,
or rope. Ethanol (95 percent) with glycerol added will be placed into the trap collection bottle or
tray. Samples will be collected from deployed traps approximately every 2 weeks by field
crews. The collected adult insects will be removed from the trap, washed into a sample
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container, preserved with ethanol with glycerol added, and labeled with information about the
site, date collected, time collected, and the collectors’ initials. This information will also be
entered onto a field data sheet. The trap will be reassembled, with fresh ethanol added to the
collection bottle or tray. The collected sample container will be sent to the contract laboratory
for processing and analysis.
2.6.2. Processing Protocols
Adult aquatic insect samples will be sent to one or more contract taxonomic laboratories for
identification. A dissecting microscope will be used to sort, identify, and enumerate collected
specimens at the family level. If feasible, chironomid should be separated into ‘morphospecies’
with select reference organisms slide mounted and identified under a compound microscope to
genus. If specimen counts are high, subsampling may be necessary, either by sample splitting, or
a gridded tray approach. Biomass estimates will be taken for all identified taxa. The fresh
blotted wet mass of each identified taxa in samples will be recorded, the samples will be oven
dried at 60˚C until reaching constant mass, and the dry mass will be recorded.
2.6.3. Data Analysis Methods
Results generated from these collections will include taxonomic composition, densities
(numbers/m2/time period), and biomass (dry weight/m2/time period), which will be described
qualitatively through graphical depictions for emergent insect families and chironomid genera.
Adult aquatic insect emergence results will also be compared to data from the benthic
macroinvertebrate collections (RSP Section 9.8.4.2.1), drift collections (RSP Section 9.8.4.3),
and the fish dietary analysis (RSP Section 9.8.4.7). Comparisons of results from emergence
traps with species composition of benthic community sampling will describe timing in the
aquatic phase and time of emergence. This information will be useful in assessing how the
timing of emergence may be altered due to Project operations.
For a select sub-sample of the collection, energy density (J / g wet weight) will be estimated
from the percent dry mass (dry mass / wet mass) of each sample (Ciancio et al. 2007; James et al.
2012). Energy density will be determined separately for each primary invertebrate taxon for use
in the trophic modeling efforts.
2.7. Fish Scale Sampling
2.7.1. Field Sampling Protocols
To support the fish stomach content analysis (Section 2.8) and trophic modeling (Section 2.10),
fish scales for aging juvenile Chinook salmon, juvenile coho salmon, and juvenile and adult
rainbow trout (DeVries and Frie 1996) will be collected in conjunction with fish abundance and
distribution sampling in the Upper River (RSP Section 9.5.4.3.1) and Middle River (RSP Section
9.6.4.3.1). Scales will be collected from the first five fish of each species and age group captured
at each sampling site, in conjunction with stomach content sampling (Section 2.8). For field
sampling purposes during 2013, rainbow trout will be provisionally categorized as “juveniles”
(ages 0 and 1) at less than or equal to 120 mm fork length, or “adults” (ages 2 and above) at
greater than 120 mm fork length (ADF&G 1983b, pp. G-8, G-14; Sundet and Wenger 1984, part
5, pp. 69, 70). The length cutoff will be adjusted if necessary for the 2014 field season based on
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the length-age relationship determined from the scale analysis. Scales will be collected after
stomach contents are collected from anaesthetized fish and before fish are placed in the river
water recovery tote (see Section 2.8). Scales will be collected from specific areas of each fish
using forceps; those areas are below and posterior to the dorsal fin (Scarnecchia 1979). Multiple
scales (approximately six) will be collected from each fish to increase the likelihood that at least
one non-regenerated scale is available for aging. Scales will be stored dry in small paper
envelopes individually labeled with a specimen number and transported to a laboratory for
analysis.
2.7.2. Processing Protocols
The age and growth of juvenile Chinook salmon, juvenile coho salmon, and rainbow trout will
be determined using scales and temporal length distribution data (DeVries and Frie 1996; Isely
and Grabowski 2007). Seasonal length-frequency distributions will be examined for juvenile
Chinook salmon, juvenile coho salmon, and juvenile rainbow trout, stratified by sampling
season. If any species displays distinct length modes, suggesting that age-0 and age-1 fish are
distinguishable from each other and from older fish based on length and sampling date alone
(e.g., Daum and Flannery 2011), this method will be validated by aging scales from a random
subset of 80 fish per size group. If seasonal length distributions do not contain distinct modes or
if the length-frequency analysis fails to correctly assign at least 95 percent (76 of the 80 fish) to
the correct age based on the scale analysis, then all scales from that species will be aged. Age
classes of rainbow trout aged 2 years and older are expected to overlap in length, so all fish will
be aged by scale analysis only.
Ages will be assigned to fish using scale annuli (DeVries and Frie 1996). Scales of juvenile fish
will be removed from envelopes in the lab, soaked in water in a petri dish, and cleaned of any
slime and foreign material. One suitable scale (neither regenerated nor damaged) from each fish
will be identified under a dissecting microscope. Scales will be aged using one of two methods.
First, scales will be mounted on microscope slides and directly examined under a dissecting
microscope. Second, if direct microscopy does not yield consistent ages, scales will be aged
from acetate impressions. Clean scales will be placed on a gummed card, sculptured side up.
Gummed cards containing multiple labeled scales will be impressed into acetate slides, and the
slides will examined under a dissecting microscope. In each method, every scale will be aged
independently by two readers, with the final age assigned by consensus. Images of a subset of
scales will be captured and archived with a microscope-mounted digital camera interfaced with a
desktop computer.
2.7.3. Data Analysis Methods
Growth rates of juvenile Chinook salmon, juvenile coho salmon, and rainbow trout will be
characterized in terms of mean weight at age based on field data from all specimens sampled,
stratified by sampling period and reach. To test whether size-selective mortality or migration
introduces bias into these growth rate estimates, seasonal growth rates will also be estimated for
individual fish that are recaptured during the PIT tag studies in the Upper River (RSP Section
9.5.4.3.2) and Middle River (RSP Section 9.6.4.3.2). The adopted growth relationships will
serve as inputs for the bioenergetics models for each species (Section 2.10).
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2.8. Fish Gut Content Sampling
2.8.1. Field Sampling Protocols
Fish stomach contents will be sampled by nonlethal gastric lavage in conjunction with fish
abundance and distribution sampling in the Upper River (RSP Section 9.5.4.3.1) and Middle
River (RSP Section 9.6.4.3.1). Stomach contents will be sampled from juvenile coho salmon,
juvenile Chinook salmon, and juvenile and adult rainbow trout to provide input data for the
trophic model (RSP Section 9.8.4.5.1). Stomach contents will be collected from the first eight
fish per species and age class that are captured at each sampling site. A fish that is lavaged and
found to have an empty stomach will be replaced by the next fish of that species and age class
that is captured. Rainbow trout will be provisionally classified as juvenile (age 0 and 1) or adult
(age 2 and older) for field purposes using the method described in the fish scale collection
section (Section 2.7). Fish will be anesthetized with clove oil, measured for fork length (mm),
weighed (g), and their stomach contents will be flushed with a 10-mL syringe assembly (Meehan
and Miller 1978). Water will be gently pumped into fish stomachs to force stomach contents out
of fishes’ mouths. Stomach contents and associated water will be flushed into a small plastic bag
and an equal volume of 95 percent ethanol will be added as a preservative for transport to the
laboratory (Wipfli 1997). Fish will be held in a plastic tote filled with river water until they
recover their ability to maintain an upright orientation. After recovery, fish will be returned to
the river near the original place of capture.
This sampling effort will target a maximum of 1,728 stomach content samples over each of the
two field seasons, allocated according to the detailed sampling protocol provided in Table 2.8-1.
If this protocol cannot be achieved because not all target taxa are captured from all sites during
all sampling periods, then a portion of the sampling effort may be reallocated to match the
distribution of organisms encountered in the field, with the goal of achieving the study objectives
most effectively.
2.8.2. Processing Protocols
Stomach content samples will be examined under a dissecting microscope in the laboratory
(Bowen 1996). Invertebrate prey will be identified to life stage (i.e., aquatic or terrestrial) and
family when possible, or otherwise the lowest possible taxonomic level. Fish prey will be
identified to species when possible, or otherwise the lowest possible taxonomic level. The
blotted wet weight of each prey category will be recorded to the nearest 0.1 g using an electronic
balance. A representative subset of prey items in each category will be measured to the nearest
millimeter and weighed to the nearest 0.01 g. All stomach contents will be archived in 95
percent ethanol for future verification.
2.8.3. Data Analysis Methods
The diet composition of each fish species and age class will be calculated in terms of diet
proportions by weight (Chipps and Garvey 2007). Diet composition will be compared along an
upstream-downstream gradient and among habitat types and seasons for each fish species and
age class using multivariate statistics. In the event data does not meet distribution assumptions,
it may be transformed (e.g., arcsine-transformed) prior to analysis. Multivariate analysis of
variance of diet proportions, two-dimensional Kolmogorov-Smirnov tests, or alternative tests
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equivalent to these statistical analyses will be used to make comparisons (Chipps and Garvey
2007). Potential ontogenetic shifts in diet will be identified graphically for each fish species by
plotting the taxon and length of individual prey against the length of the associated fish predator
(Beauchamp et al. 2007). The onset of piscivory in rainbow trout will be identified graphically
by plotting the proportion of fish in each stomach content sample against the length of each
rainbow trout. Data collected during this study will also be compared to the results of fish diet
studies conducted on the Susitna River during the 1980s (ADF&G 1983a; Hansen and Richards
1985) to evaluate any differences between the historic and current fish diets.
2.9. Macroinvertebrate Colonization Sampling
In order to assess the influences of turbidity and temperature on the benthic community
colonization rates, a field study will be conducted for both study years (i.e., 2013 and 2014) to
estimate potential benthic macroinvertebrate colonization rates for four different habitat types
that reflect these conditions in the Susitna River. Due to the difficulty of isolating each of these
conditions under natural conditions, colonization will be examined under turbid/warm,
clear/warm, turbid/cold, and clear/cold conditions. Locating and establishing appropriate
sampling sites for colonization study will require an extensive review of all studies done in the
segment, along with discussions with other research teams conducting field studies in the Middle
Segment of the Susitna River to locate areas that display these conditions over an eight-week
period. This effort will also require site reconnaissance trips to assess candidate sites.
Hester-Dendy multiplate samplers (Hester and Dendy 1962; Fullner 1971; Tsui and Breedlove
1978) will be used as the artificial substrates for the study of colonization rates in the Middle
Segment of the Susitna River. The Hester-Dendy multiplate sampler consists of 14 tempered
hardboard plates, either square or circular, which are spaced apart by smaller, circular hardboard
spacers and mounted on a central eyebolt (Figure 2.2-1). The top nine plates are separated by
one spacer, and the remaining plates are separated by 2, 3, and then 4 spacers, thus providing a
simulated complexity of surfaces and interstitial spacing (Klemm et al. 1990). This version of
the Hester-Dendy sampler offers 0.16 m2 of surface area. Hester-Dendy multiplates are
frequently suspended in the water column but can be deployed along the bottom with a heavy
anchor weight (Klemm et al. 1990).
Multiplate samplers were selected, because each unit has the same surface area and the same
microhabitat to offer potential colonizers. This permits standardized sampling in both the
sampling effort, thus eliminating sampling error, and in surface area sampled. They also have a
calculated surface area, which allows for more quantitative results to be collected. Multiplate
samplers are also small and more easily transported when accessing remote areas, as opposed to
rock baskets, which are bulky. Hester-Dendy samplers are also the most common type of
artificial substrate samplers used today by several state and federal monitoring programs and
have been successfully used on many large rivers, notably as part of standard programs in
Florida, Wisconsin, and Ohio (Johnson et al. 2006).
2.9.1. Field Sampling Protocols
All Hester-Dendy samplers will be pre-conditioned prior to deployment by being placed for 4
weeks in the Susitna River (preferably at a project base camp) and then air-dried. Sets of three
pre-conditioned artificial substrates will be deployed incrementally for set periods of
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colonization time (e.g., 8, 6, 4, 2, and 1 week[s]) and then pulled simultaneously at the
conclusion of the colonization period. Artificial substrates will be deployed at two depths at
fixed sites along the channel bed. Depths at which to set the substrates should take into account
the river stage fluctuations. Crew members deploying the multiplate samplers should attempt to
set the shallower set of samplers during the lowest river stage and/or at locations that will ensure
that the substrates are not dewatered during their time in the water (for up to 8 weeks). This will
require consulting the real-time flow and stage gage data available to make an informed decision.
Progressive sets for each new exposure period should be installed downstream of those
previously installed, so as to minimize disturbances to the previous set(s). For example, the sets
exposed for 4-weeks should be installed a short distance downstream from the 6-week sets,
which, in turn, are located downstream from the 8-week sets.
For each set deployed, three multiplate samplers will be equidistantly attached to a 2-foot section
of light chain. A two-foot rebar spike with an eyebolt will be driven into the riverbed at the
appropriate location and depth, and the chain of multiplates then laid out upon the river bottom,
in direct contact with the cobble/gravel substrates and attached to the spike with a quick link.
The location, depth, velocity (both 60 percent of depth and near-bed measurements), PAR levels,
and turbidity should be measured at the deployment of each set, and recorded on the field data
sheet for the current deployment. If previous sets have been deployed, those sets should be
checked, to see if they have been lost, vandalized, damaged, or exposed since the last
deployment at the site.
The following is the procedure for the retrieval of multiplate sampler sets and collection of
benthic macroinvertebrates.
1. Locate the shallow depth set of multiplate samplers deployed for the downstream-most
set. At the beginning, this should be those sets deployed for 1 week.
2. Take measurements of depth, velocity (both 60 percent of depth and near-bed
measurements), PAR levels, and turbidity, and record the data on the field data sheet,
making sure to note which set of multiplate samplers is being retrieved (e.g., 1 week,
shallow).
3. Place a D-net directly downstream of the multiplate set. Detach the chain from the rebar
spike, and then remove the chain and multiplate samplers from the water.
4. Multiplates are quickly brought to shore, and placed in three separate wash-buckets.
Each multiplate sampler is disassembled, and cleaned of colonizing macroinvertebrates in
its wash-bucket. Cleaned parts are set aside for reassembly later.
5. Pour the contents of the wash bucket through a 250-µm sieve. Rinse the bucket with
water to ensure all material and invertebrates are washed into the sieve.
6. Rinse the sample in the sieve, consolidating the material to one side of the sieve, and
transfer the material into a storage container. Efforts should be taken to minimize the
amount of water retained with the sample to prevent too much dilution of the ethanol
used to preserve the sample. Next, scoop out the material with a spoon or spatula and
place it in the sample container, and then rinse the sieve to consolidate the remaining
material to one side of the sieve. Wash the remaining sample into the container with a
wash bottle containing 95 percent ethanol
7. A standard label defining the station, site, sample number, date, collector, and unique
sample identification code is added to the sample. Adhesive standard labels are also
applied to the outside of the sample jars.
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8. Preserve the sample with additional 95 percent ethanol, enough to completely cover the
sample, and place the labeled lid on the container, making sure it is secured tightly and
does not leak.
9. Reassemble the multiplate sampler, so as not to lose any parts.
10. Repeat steps 1-9 with the deep depth set of multiplate samplers deployed at that exposure
time.
11. Continue upstream to the next set of multiplate samplers. Repeat steps 1-10.
2.9.2. Processing Protocols
Benthic macroinvertebrate processing protocols will be identical to those used for benthic
macroinvertebrate sampling (Section 2.2).
2.9.3. Data Analysis Methods
Results generated from the collections will include a variety of descriptive metrics commonly
used in aquatic ecological studies (Table 2.2-1). Comparisons will be made among exposure
times, depths, and conditions to examine trends of benthic macroinvertebrate colonization.
Colonization information will be compared with colonization results from other river systems
and, in the future, with post-Project colonization results. In addition, results will be utilized in
HSC/HSI development (RSP Section 9.8.4.6) and in the varial zone modeling task of the
Instream Flow Study (RSP Section 8.5.4.6.1.6) to assist in determining potential Project effects
of short-term flow fluctuations on benthic macroinvertebrates.
2.10. Trophic Modeling
2.10.1. Data Analysis Methods
To determine how water temperature, food availability, and food quality influence the growth
performance of juvenile Chinook salmon, juvenile coho salmon, and juvenile and adult rainbow
trout, field data from the Instream Flow Study (RSP Section 8.5), Fish Abundance and
Distribution Studies in the Upper and Middle Rivers (RSP Sections 9.5 and 9.6), and the River
Productivity Study will be analyzed using a bioenergetics approach. This analysis will allow
comparisons of observed growth rates, estimated consumption rates, and estimated growth
efficiency (i.e., the grams of growth achieved per gram of food consumed) among different
habitats under the environmental conditions observed during 2013 and 2014. Consumption and
growth efficiency will be estimated using Wisconsin bioenergetics models (Hanson et al. 1997)
with species-specific physiological parameters for Chinook salmon (Stewart and Ibarra 1991;
Madenjian et al. 2004), coho salmon (Stewart and Ibarra 1991), and rainbow trout/steelhead
(Rand et al. 1993). Simulations for each species will encompass the full range of age classes for
which sufficient field data are collected; at a minimum, these are expected to include ages 0-1 for
Chinook salmon, 0-2 for coho salmon, and 0-8 for rainbow trout. Simulations will run on a daily
time step from emergence from the gravel through smolting (or senescence for resident rainbow
trout). Model inputs will include field data on growth rate, water temperature, diet composition,
and the energy density of prey. Growth rates will be determined from seasonal mean weight at
age data (Section 2.7.3). Water temperatures will be measured using temperature loggers (RSP
Section 9.8.4.2.1). Diet composition will be determined from stomach contents (Section 2.8).
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The energy density of prey will be estimated based on laboratory measurements of the percent
dry matter of prey organisms (Ciancio et al. 2007; James et al. 2012) collected during sampling
of macroinvertebrates, as described in Sections 2.1.2 and 2.1.5, and fishes (RSP Sections 9.5 and
9.6). Based on these inputs, the bioenergetics models will estimate consumption rates and
growth efficiency on a daily basis. These metrics will be compared among habitats and seasons
to determine whether growth is currently limited primarily by water temperature, food
consumption, or food quality in the study area, and whether these limiting factors differ among
habitats (McCarthy et al. 2009).
In addition to the descriptive bioenergetics analysis described above, a growth rate potential
(GRP) analysis will be developed and evaluated as a potential prospective approach for
predicting fish growth rates under changing environmental conditions. Detailed foraging
parameters for juvenile coho salmon and juvenile rainbow trout have been published (e.g.,
Dunbrack and Dill 1984; Berg and Northcote 1985; Piccolo et al. 2007; Piccolo et al. 2008a,
2008b), enabling the development of well-supported drift foraging models for both species. The
necessary bioenergetics model parameters are also available for these fishes (see above).
Mechanistic drift foraging models are not available for juvenile Chinook salmon, so the growth
rate potential approach will not be applied to this species.
Species-specific GRP models for juvenile coho salmon and juvenile rainbow trout will link a
drift foraging model (Fausch 1984; Hughes and Grand 2000; Hayes et al. 2007) to a Wisconsin
bioenergetics model (Kitchell et al. 1977; Hanson et al. 1997). The foraging models will
estimate a consumption rate based on stream flow, turbidity, and prey density input data. The
bioenergetics models will predict a growth rate from inputs of consumption, body size, water
temperature, diet composition, and the energy density of prey.
Preliminary GRP models for each species will be developed using data from the 2013 field
season as well as from prior Susitna Basin studies. Initial model predictions of the growth
potential of particular sites will be tested by comparison with the observed growth and
distribution of fish captured in those sites. A sensitivity analysis will be conducted to identify
the most important parameters for further refinement (e.g., Beaudreau and Essington 2009).
Field sampling during 2014 will focus on improving estimates for these parameters. Preliminary
growth models will simulate GRP assuming that fish remain within a given habitat; however,
final GRP models, developed after the 2014 field season, will allow simulated fish to move
among habitats within a sampling location to enhance growth rates. Optimal simulated
movement patterns will be estimated and compared with the observed movements documented
by the biotelemetry components of the Fish Distribution and Abundance Studies of the Upper
River (RSP Section 9.5.4.3.2) and Middle River (RSP Section 9.6.4.3.2). Final GRP models will
also allow for inter- and intraspecific competition among juvenile coho salmon and rainbow trout
(Hughes and Grand 2000).
The suitability of the GRP models for predicting the growth rates of each species will be tested
using an information theoretic model selection approach (Burnham and Anderson 2002). For
each species, a full model will be fit to the observed growth data using the observed water
temperature, stream flow, turbidity, prey density, prey quality (energy density), and competitor
density as explanatory variables. A set of simplified growth models will also be constructed
using every possible subset of those variables. The full suite of candidate growth models will be
fit to the data, and the most parsimonious models will be identified using AICc (Burnham and
Anderson 2002). This analysis will evaluate whether the GRP approach or simpler approaches
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may serve as useful tools for future predictive analyses of the effects of future environmental
changes on fish growth in the Susitna River.
2.11. Stable Isotope Analysis
2.11.1. Field Sampling Protocols
Stable isotope samples will be collected from algae, OM, spawning salmon, aquatic and
terrestrial macroinvertebrates, and focal salmonid fishes. Isotope samples will be collected from
two of the River Productivity Study sampling stations in the Middle Susitna River, with three
habitat-specific sampling sites per station, for a total of six sampling sites. To account for
temporal variability in isotopic signatures (Post 2002), all sample types will be collected during
three seasonal periods, with the exception of salmon carcasses, which will be collected only
during the spawning run. Algae, OM collected by benthic sampling, and OM collected by drift
sampling will each be collected in separate composite samples of approximately 10 g wet mass.
Tissue from the carcasses of spawned out salmon will be collected during spawning runs in
composite samples of approximately 10 g wet mass. Aquatic macroinvertebrates will be
collected by benthic sampling in composite samples of approximately 20 g wet mass. Terrestrial
macroinvertebrates will be collected by drift and emergence sampling in separate composite
samples of approximately 5 g wet mass. In conjunction with fish abundance and distribution
sampling in the Middle River (RSP Section 9.6.4.3.1), stable isotope samples will be collected
non-lethally from fish by clipping a small portion of the caudal fin (Sanderson et al. 2009;
Hanisch et al. 2010). Fin clips will be collected after stomach contents (Section 2.8) and scales
(Section 2.7) are collected from anaesthetized fish and before fish are placed in the river water
recovery tote (see Section 2.8). Fin clip sampling may cause a reduction in survival for fishes
smaller than 50 mm in fork length (Sanderson et al. 2009), so any fish of this size that are
selected for sampling will be sacrificed. These fish will be sacrificed with an overdose of
buffered MS-222 and filleted to provide stable isotope samples.
This sampling effort will target a maximum of 1,246 total stable isotope samples over each of the
two field seasons, allocated according to the detailed sampling protocol provided in Table 2.11-
1. If this protocol cannot be achieved because not all target taxa are captured at all sites during
all sampling periods, then a portion of the sampling effort may be reallocated to match the
distribution of organisms encountered in the field, with the goal of achieving the study objectives
most effectively. All samples will be stored in small plastic bags on ice in the field and
subsequently frozen.
2.11.2. Processing Protocols
Stable isotope samples will be oven dried at 50-60˚C to a constant weight and ground to a
homogenous powder using a mortar and pestle. Aquatic macroinvertebrate samples will be
separated into four subsamples by functional group (i.e., grazers, collectors, shredders, and
predators), and caddisfly larvae will be removed from their cases before drying and grinding.
Subsamples of approximately 3-4 mg for algae, 4-6 mg for OM, and 1 mg for animal tissue will
be weighed to the nearest 0.001 mg on a micro-analytical balance and placed into tin capsules.
Samples will be combusted and analyzed in an isotope-ratio mass spectrometer interfaced with
an elemental analyzer. Data will be normalized using isotope reference standards, and analytical
precision will be estimated by analyzing a subset of samples in duplicate.
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2.11.3. Data Analysis Methods
The stable isotope analysis will be conducted to determine the relative contributions of
freshwater, terrestrial, and marine nutrients to focal salmonid species along an upstream-
downstream gradient and among habitat types in the river (Wipfli and Baxter 2010). Stable
isotope signatures are conventionally reported in δ units, which indicate the ratio of heavy to
light atoms in a sample, relative to a standard. Stable isotope signatures of C and N will be
calculated as δ13C or δ15N = [(R sample /R standard) – 1]1000, where R is 13C/12C or 15N/14N
(Peterson and Fry 1987). Spawning salmon are expected to exhibit an enriched signature of δ15N
relative to freshwater or terrestrial energy sources (Bilby et al. 1996; Chaloner et al. 2002;
Satterfield and Finney 2002), and the combination of the δ15N and δ13C signatures may
additionally allow all three sources to be distinguished (Fry 2006).
To evaluate whether differences in lipid content among samples might influence isotopic
signatures, variability in the elemental ratio of C:N will be examined after the samples collected
during 2013 have been analyzed (Post et al. 2007). This ratio is measured and reported as part of
the δ13C and δ15N analysis. If variability in C:N ratios is great enough to potentially influence
the study conclusions (i.e., if the range of values exceeds approximately 4 percentage points),
then mathematical lipid normalization approaches (Kiljunen et al. 2006; Post et al. 2007) will be
evaluated to correct for this variability.
Variability in the diet composition of each focal salmonid species and age class will be evaluated
with respect to sampling location (i.e., upriver vs. downriver) and habitat type. Broad patterns of
energy flow within the riverine food web will be examined graphically by plotting δ13C vs. δ15N
for all samples. For each focal salmonid species and age class, diet composition will be
estimated and compared among locations and habitats using stable isotope mixing models, if the
final dataset meets the assumptions of these techniques, including adequate sample sizes,
contrast in isotopic signatures, and suitable geometry of the δ13C vs. δ15N plot (Moore and
Semmens 2008; Semmens et al. 2009). Alternatively, if the mixing model approach is not well
suited to the dataset, variability in the δ13C and δ15N signatures of the focal salmonids relative to
other taxa may be evaluated directly using MANOVA, 2-dimensional Kolmogorov-Smirnov
tests, or the most appropriate analytical approach given the distributional characteristics of the
data.
2.12. Data Management
The goals of data management are to establish a data QA/QC protocol to be applied by study
teams at logical stages of data collection and processing and to ultimately create a relational
database including all finalized river productivity data collected for the Susitna-Watana Project.
2.12.1. Established QA/QC Protocol
• There will be 5 levels of data QC, named QC1 to QC5, each of which is tracked either
within tabular datasets (as for Excel and database tables), or within file path names (as for
raw field data files). This allows for quick determination of the QC status of all data.
• Details for the QC Protocol are found in Appendix 3: Susitna Field Data Standards.
• The QC levels, briefly, are as follows:
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QC1 – Field Review: Review of field forms before leaving the field, or the QC level of
raw data collected via field equipment such as thermistors, cameras, GPS units,
etc.
QC2 – Data Entry: Data from paper forms are entered into an electronic format and
verified.
QC3 – Senior Review: Final review by senior professional before submitting field data
to AEA, or the QC level of raw data cleaned up for delivery to AEA.
QC4 – Database Validation: Tabular data files are verified to meet project database
standards.
QC5 – Technical Review: Data revision or qualification by senior professionals when
analyzing data for reports.
2.12.2. Relational Database
A database template is being designed to store the river productivity data from all consultants
and studies, providing a centralized data tool for users. The final database will be maintained in
MS Access software and will include data collected in 2012, and new data from future studies in
2013 and 2014. It may include data submitted from other entities, such as ADF&G, UAF , and
other contracted processing labs. The database will be available for querying and analysis by
parties assigned by AEA.
A data dictionary describing the database entities and attributes will be compiled, to accompany
the database and to provide an understanding of data elements and their use by anyone querying
or analyzing the data.
See Appendix 4 for a template of the River Productivity database.
3. SCHEDULE
The preliminary schedule for the river productivity study elements is presented in Table 3.1-1
Field sampling at the Susitna River sites and the Talkeetna River test reference sites for benthic
macroinvertebrates, algae, organic matter, drift, fish diet analysis, and stable isotopes will be
conducted for three seasonal sampling periods from April through October in both study years
(2013 and 2014). These seasonal periods are tentatively scheduled for April through early June
for Spring, late June through August for Summer, and September through October for Autumn
(Table 3.1-1), due to annual variability in the timing of seasons. In addition, seasonal sampling
must be conducted within select flow ranges and stages. Higher flows may inundate new
shoreline substrates, which present a risk of sampling in areas disturbed by periodic inundation
and dewatering and will not be fully colonized. Therefore, changes in water level due to
increasing or decreasing flows must remain constant enough that the substrates accessible for
sampling will be continually inundated for a period of at least one month, to facilitate
colonization of those substrates prior to sampling. Based on the criteria for sampling, the
schedule will be determined within a window of several weeks. Multiple remote cameras and
staff gages have been installed along the Susitna River, and these, along with the USGS gage at
Gold Creek, will be closely monitored for target sampling conditions based on indicators such as
flow and river stage conditions.
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Two additional sampling events are planned for benthic macroinvertebrates, algae, and organic
matter under storm conditions and will occur sometime during April through October. Specific
dates are determined by criteria previously mentioned that will trigger storm event sampling.
Sample processing of organisms and materials collected in the 2013 field efforts will require
extensive laboratory taxonomic analysis, and will continue throughout the remainder of 2013 and
into the first quarter of 2014. Trophic analysis efforts will be initiated during the latter half of
the first quarter of 2013 and continue throughout the rest of 2013 and into 2014.
Second-year field sampling efforts, adhering to the same tentative scheduling as in 2013, will
resume in the latter half of the first quarter of 2014, with sample processing, data analysis,
trophic analysis research continuing through the fourth quarter.
4. FIELD EQUIPMENT LIST
To be provided in Final Implementation Plan.
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Sanderson, B.L., C.D. Tran, H.J. Coe, V. Pelekis, E.A. Steel, and W.L. Reichert. 2009.
Nonlethal Sampling of Fish Caudal Fins Yields Valuable Stable Isotope Data for
Threatened and Endangered Fishes. Transactions of the American Fisheries Society
138(5):1166-1177.
Satterfield, F. R., and B. P. Finney. 2002. Stable isotope analysis of Pacific salmon: insight into
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Scarnecchia, D.L. 1979. Variation of scale characteristics of coho salmon with sampling
location on the body. The Progressive Fish-Culturist 41(3):132-135.
Schmidt, D., and C. Estes. 1983. Aquatic Habitat and Instream Flow Studies, 1982. Prepared
by Alaska Department of Fish and Game, Susitna Hydro Aquatic Studies for the Alaska
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Schmidt, D., and A. Bingham. 1983. Synopsis of the 1982 Aquatic Studies and Analysis of Fish
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6. TABLES
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Table 1.2-1. Locations and descriptions of proposed Focus Areas selected for the River Productivity study in the Middle River Segment of the Susitna River. Focus Area
identification numbers (e.g., Focus Area 184) represent the truncated Project River Mile (PRM) at the downstream end of each Focus Area.
Focus Area ID / RivProd
ID
Common
Name
River Productivity
Study Use Description
Geomorphic
Reach
Location (PRM)
Area Length
(mi)
Habitat Types Present
Fish use in 1980s Main Channel, Single Main Channel, Split Side Channel Tributary Mouth Side Slough Upland Slough Beaver Complex Upstream Downstream Spawning Rearing RP- 248 Complex
Area 248
Study Station
(3 sites)
Area with channel
complex approximately
1.7 miles upstream of
Tyone River
UR-1 250.1 248.8 1.3 X X X X N/A N/A
RP-233 Oshetna
River
Study Station
(3 sites)
Area covering Oshetna
River mouth and
downstream
UR-2, 3 235.4 233.9 1.5 X X N/A N/A
Focus
Area-184
Watana
Dam
Study Station
(3 sites)
Area approximately 1.4
miles downstream of
dam site
MR-1 185.7 184.7 1.0 X X X N/A N/A
Focus
Area-173
Stephan
Lake,
Complex
Channel
Study Station
(3 sites)
Wide channel near
Stephan Lake with
complex of side
channels
MR-2 175.4 173.6 1.8 X X X X N/A N/A
Focus
Area-144
Side
Channel 21
Storm Event
Site
Side channel and side
slough complex
approximately 2.3 miles
upstream Indian River
MR-6 145.7 144.4 1.3 X X X X X X X X
Focus
Area-141
Indian
River
Study Station
(3 sites)
Area covering Indian
River and upstream
channel complex
MR-6 143.4 141.8 1.6 X X X X X X X X
Focus
Area-104
Whiskers
Slough
Study Station
(3 sites), Storm
Event Site
Whiskers Slough
Complex MR-8 106.0 104.8 1.2 X X X X X X X X
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Table 2.2-1. Descriptive metrics commonly used in aquatic ecological studies to describe benthic macroinvertebrate
(BMI) communities.
Biological Metrics Description
Predicted
Response to Impairment
Abundance Measures
Density The total number of individuals collected in a unit area (m2) variable
Richness Measures
Taxa Richness Total number of individual taxa decrease
Ephemeroptera Taxa Number of mayfly taxa decrease
Plecoptera Taxa Number of stonefly taxa decrease
Trichoptera Taxa Number of caddisfly taxa decrease
Shannon-Weiner Diversity Index Summary metric that combines taxa richness and abundances, calculated with
the natural logarithm (ln) decrease
Composition Measures
Percent Composition: Major Taxa Relative abundances of: Ephemeroptera, Plecoptera, Trichoptera, Coleoptera,
Chironomidae, non-chironomid Diptera, other Insect taxa, and non-insect taxa variable
Percent Dominant Taxa Percent composition of the three most abundant taxa increase
EPT:Chironomid Ratio Ratio of EPT abundance to Chironomidae abundance, ranging from 0 to 1, with
scores below 0.5 indicating more Chironomidae. decrease
Tolerance/Intolerance Measures
Biotic Index Value between 0 and 10 weighted for abundance of individuals designated as
pollution tolerant (higher values) and intolerant (lower values) increase
Intolerant Taxa Number of taxa in sample that are highly intolerant to impairment (tolerance value
≤ 4) decrease
Percent Tolerant Organisms Percent of organisms in sample that are highly tolerant to impairment (tolerance
value ≥ 7) increase
Functional Feeding Groups
Percent Collector-Gatherers Percent of macrobenthos that gather fine particulate matter increase
Percent Collector-Filterers Percent of macrobenthos that filter fine particulate matter increase
Percent Scrapers (Grazers) Percent of macrobenthos that graze upon periphyton variable
Percent Predators Percent of macrobenthos that feed on other organisms variable
Percent Shredders Percent of macrobenthos that shreds coarse particulate matter decrease
Percent Other Groups Percent of macrobenthos that are either omnivorous, macrophyte or piercer
herbivores, or parasites variable
Habits /Life History Measures
Clinger Taxa Number of taxa with physical adaptations that allow them to hold onto smooth
substrates in fast water decrease
Long-lived Taxa Number of taxa that require more than 1 year to complete their life-cycles (semi-
voltine) decrease
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Table 2.8-1. Itemized listing of the number of fish gut content samples to collect for the River Productivity Study in each
study year.
Target Species / Lifestage Sites Seasons Samples Total
Chinook salmon - juveniles 18 3 8 432
Coho salmon - juveniles 18 3 8 432
Rainbow trout - juveniles 18 3 8 432
Rainbow trout - adults 18 3 8 432
Total 1,728
Table 2.11-1. Itemized listing of sample components to collect for Stable Isotope Analysis at the two sampling stations (6
sites total) in each study year in the Middle Segment of the Susitna River for the River Productivity Study.
Category Taxon Sites Seasons Samples Total
Endmembers
Benthic Algae 6 3 5 90
Organic Matter - benthic 6 3 5 90
Organic Matter - drift 6 3 2 36
Salmon carcass 2 1 20 40
Invertebrates
Benthic- grazers 6 3 5 90
Benthic- collectors 6 3 5 90
Benthic- shredders 6 3 5 90
Benthic- predators 6 3 5 90
Terrestrial Drift 6 3 2 36
Emergents 6 3 1 18
Fish
Chinook salmon - juveniles 6 3 8 144
Coho salmon - juveniles 6 3 8 144
Rainbow trout - juveniles 6 3 8 144
Rainbow trout - adults 6 3 8 144
Total 1,246
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Table 3.1-1. Preliminary schedule for River Productivity Study.
Activity 2013 2014 2015
1Q 2Q 3Q 4Q 1Q 2Q 3Q 4Q 1Q
Literature Review on Hydropower Impacts
Sampling benthic macroinvertebrate
communities, algal communities, and
organic matter.
Invertebrate drift sampling
Sampling Talkeetna for Reference Site
Feasibility Study
Trophic analysis with bioenergetics and
stable isotope analysis
Generate habitat suitability criteria
Conduct a fish gut analysis
Establish baseline colonization rates
Data Analysis and Reporting
Initial Study Report ∆
Updated Study Report
Legend:
Planned Activity
Tentatively scheduled sampling event
∆ Initial Study Report
▲ Updated Study Report
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7. FIGURES
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Figure 1.2-1. Upper Susitna River Segment, with the two proposed River Productivity sampling stations selected for the River Productivity Study.
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Figure 1.2-2. Middle Susitna River Segment, with the four proposed River Productivity sampling stations /Instream Flow Focus Areas selected for the River
Productivity Study.
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Figure 1.3-1. Total catch of juvenile coho salmon by sample period and gear type at DFH sites in 1982. Source: Estes and Schmidt 1983
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Figure 1.3-2. Seasonal distribution and relative abundance of juvenile coho salmon on the Susitna River between the
Chulitna River confluence and Devil Canyon, May through November 1983. Source: Dugan et al. (1984).
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Figure 1.3.3. Density distribution and juvenile coho salmon by macrohabitat type on the Susitna River between the
Chulitna River confluence and Devil Canyon, May through November 1983. Percentages are based on mean catch per
cell. Source: Dugan et al. (1984).
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Figure 1.3-4. Total catch of juvenile Chinook salmon by sample period and gear type at DFH sites in 1982. Source: Estes and Schmidt 1983
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Figure 1.3-5. Seasonal distribution and relative abundance of juvenile Chinook salmon on the Susitna River between the
Chulitna River confluence and Devil Canyon, May through November 1983. Source: Dugan et al. (1984).
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Figure 1.3-6. Density distribution and juvenile Chinook salmon by macrohabitat type on the Susitna River between the
Chulitna River confluence and Devil Canyon, May through November 1983. Percentages are based on mean catch per
cell. Source: Dugan et al. (1984).
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Figure 1.3-7. Total catch of rainbow trout by sample period and gear type at DFH sites in 1982. Source:
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Figure 2.1-1. Map showing Focus Area 184 that begins at Project River Mile 184.7 and extending upstream to PRM 185.7. The Focus Area is located about 1.4 miles
downstream of the proposed Watana Dam site near Tsusena Creek.
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Figure 2.1-2. Map showing Focus Area 173 beginning at Project River Mile 173.6 and extending upstream to PRM 175.4. This Focus Area is near Stephan Lake and
consists of main channel and a side channel complex.
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Figure 2.1-3. Map showing Focus Area 141 beginning at Project River Mile 141.8 and extending upstream to PRM 143.4. This Focus Area includes the Indian River
confluence and a range of main channel and off-channel habitats.
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Figure 2.1-4. Map showing Focus Area 104 beginning at Project River Mile 104.8 and extending upstream to PRM 106. This Focus Area covers the diverse range of
habitats in the Whiskers Slough complex.
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Figure 2.1-5. Map showing Focus Area 144 beginning at Project River Mile 144.4 and extending upstream to PRM 145.7. This Focus Area is located about 2.3 miles
upstream of Indian River and includes Side Channel 21 and Slough 21.
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Figure 2.1-6. Map showing the River Productivity Upper Segment sampling station RP-233, located near the mouth of the Oshetna River beginning approximately at
Project River Mile 233.9 and extending upstream to approximately PRM 235.4.
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Figure 2.1-7. Map showing the River Productivity Upper Segment sampling station RP-248, located upstream of the Tyone River beginning approximately at Project
River Mile 248.8 and extending upstream to approximately PRM 250.1.
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Figure 2.2-1. Sampling equipment used to collect benthic macroinvertbrates in streams and rivers. Top left: Hess stream
sampler. Top right: drift net. Middle: examples of floating aquatic insect emergence traps. Bottom: Hester-Dendy
multiplate sampler.
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APPENDIX 1. MAJOR AND BARBOUR (2001). STANDARD
OPERATING PROCEDURES FOR THE ALASKA STREAM CONDITION
INDEX: METHOD 002 – LABORATORY PROCESSING
ASCI Method 002, 5th Edition • ENRI • Page 1 of 10
Rapid Bioassessment Protocols: Technical Level
Method 002 – Laboratory Processing
Macroinvertebrate samples are subsampled, sorted, and identified in the laboratory under controlled con-
ditions. All samples are recorded upon receipt by the laboratory. Information from the sample container
label should be included on the login sheet. The number of containers should be indicated and equal those
indicated on the label. All samples should be sorted in a single laboratory for quality control. Dates and
types of sample processing should be recorded in the sample login sheet for each sample.
Laboratory Equipment and Supplies
• Two standardized 350 m gridded subsampler trays (5.5 cm x 5.5 cm grids)
• 350 m sieve
• Forceps
• White plastic or enamel sorting trays
• Specimen vials with rubber-lined caps or stoppers
• Sample labels
• Dissecting microscope
• Fiber optic light source
• Ethanol for storage of specimens
• Taxonomic keys
• Taxonomy validation notebook
• Compound microscope
• Microscope slides and cover slips
• Head mount medium (CMC-10)
Record Keeping (See pages 6–9 of Method 002.)
• Sample Login Sheet
• Laboratory Bench Sheet-Subsampling
• Laboratory Bench Sheet-Identification
• Laboratory Bench Sheet-Chironomidae Identification
Subsampling/Sorting Procedures
The protocol is used for a 300-organism subsample. The entire sample is processed and a 300-organism
subsample (+/- 20%) is randomly selected, sorted, and preserved separate from the remaining sample.
SS-1.Note the total number of jars recorded on the login sheet and retrieve the jars. Pour the contents
of all jars into the 350 m mesh sieve or tray and thoroughly rinse the entire sample to remove preser-
vative and fine sediment. Large organic material (whole leaves, twigs, algal or macrophyte mats,
etc.) not removed in the field should be rinsed, visually inspected, and discarded. If the samples have
been preserved in ethanol, soak the sample contents in water for about 15 minutes to hydrate the or-
ganisms. This will prevent them from floating on the water surface during sorting. Gently mix the
sample by hand while rinsing to homogenize.
ASCI Method 002, 5th Edition • ENRI • Page 2 of 10
SS-2.Spread the sample evenly across a subsampling pan marked with 5.5 cm grids after washing. Put
some water in the tray to distribute the contents evenly and then slowly pull the inside tray up to drain
off the water to begin subsampling.
SS-3.Use random numbers representing the grids and select four numbers corresponding to squares
within the gridded pan. Note the grids selected on the Laboratory Bench Sheet-Subsampling on the
level 1 section (see page 7). Using a spatula, remove all material (organisms and debris) from the
four grid squares and place the material into a shallow white sorting pan. Add water to facilitate
sorting. If there appears to be 300 ± 20% organisms (cumulative of four grids) from a visual inspec-
tion, then subsampling is complete and sorting can begin. Consider any organism that is lying over a
line separating two grids to be on the grid containing its head. In those instances where it is not
possible to determine the location of the head (worms for instance), consider the organism to be in the
grid containing most of its body.
If the density of organisms is high enough that many more than 300 organisms are contained in the
first four grids, transfer the contents of the first four grids to a second gridded subsampling pan and go
to the second level of subsampling. Randomly select grids for the second level of sorting as was done
for the first, sorting grids one at a time until 300 ± 20% organisms are found. Mark the grids sampled
on the table for level 2. If picking through the entire first grid of level two subsampling is likely to
result in more than 300 ± 20% organisms, then that grid may be subsampled in the same manner as
before. Continue to pick grids one at a time until the desired number is reached. Record the total
number of grids sampled on the level 3 table.
Complete the laboratory bench sheet for the subsampling procedures. Record the date that the
subsampling was completed and the sorters initials on the login sheet. All organisms should be picked
from the subsample and the material from the sorting pans disposed of after quality control checks are
complete.
SS-4.As the organisms are sorted, put them into glass vials and preserve in 70% ethanol. Label the
vials inside with the sample identifier, sampling date, water body name, sample collectors, and ini-
tials. If more than one vial is needed, label and number each (e.g., 1 of 2, 2 of 2) to identify the total
number of vials for the taxonomist. Insert the labels left-edge first so they can be easily read.
SS-5.Finally, inspect the entire sample for large and rare organisms that were not identified during the
subsampling procedure. Pick out the types of organisms that were not collected in the original
subsample and place them in a vial labeled “5-minute pick” with the sample identifier, sampling date,
and stream name. This procedure is used to ensure that representative taxa are collected for identifi-
cation. When the 5-minute pick procedure is completed, record the resulting data on the appropriate
sections of the login sheet, subsampling sheet, and identification sheet. Record the total numbers of
organisms to be identified by the taxonomist from the subsample on the identification sheet.
SS-6.After subsampling is complete, if it is necessary to save the unsorted debris residue, add the words
“processed sample” to the outside label, put the contents of the subsampling tray back in the jar(s),
and again preserve it in ethanol. The inside label should also indicate that the sample has been pro-
cessed. Length of storage and archival time are determined by the program manager. If there is no
reason to archive the material, discard the remainder of the sample.
SS-7.Turn the vials of organisms and subsampling and identification sheets over to the taxonomist for
identification. Qualified taxonomists complete the identification process.
ASCI Method 002, 5th Edition • ENRI • Page 3 of 10
Identification
ID-1.Record on the Laboratory Bench Sheet-Identification (see pages 8 and 9) the station identification
code, sample collector initials, collection date, stream location, sorter, date sorted, taxonomist initials,
identification date, total number in subsample, and type of subsample. Begin the identification pro-
cess and list the taxa identified and numbers of each found in the subsample. Insects are identified to
genus level by a qualified taxonomist using a dissecting microscope.
Chironomidae (midges) tend to predominate biological communities in Alaska. Characterizing
Chironomidae to genus level is a labor-intensive technical process but is important to accurately as-
sess biological condition. Midge larvae are identified primarily by head capsule and mouthpart char-
acteristics and generic identification requires specimens be slide-mounted for examination under a
compound microscope (see ID-2 for details). Chironomidae are subsampled to identify them to genus
level and yet gain generic-level information.
Non-insect taxa (e.g. Hydrachnidia, Oligochaeta, Amphipoda, etc.) are identified to family or order.
These organisms are incorporated in the metrics based on the relative abundance to the total. Also,
note in the Taxonomic Certainty Rating (TCR) column any suspect identifications (e.g., very small
organisms or those with missing parts) and include the number from 1–5 that indicates the taxonomist’s
certainty that the identification is correct. Identification of organisms collected from the 5-minute
pick procedure are used only to calculate taxa richness measures and are noted in a separate column
on the laboratory bench sheet.
ID-2. Chironomidae Subsampling. Identify approximately
20% of the midges for each sample. (This number is de-
rived from the number of Chironomidae recorded on the
laboratory data sheet). Separate the midges out of the 300-
organism subsample and spread them randomly in a petri
dish divided into ten equal sections. (See figure at right.)
Choose two sections of the dish to randomly collect ap-
proximately 20% of the organisms. Place them in a sepa-
rate petri dish labeled “Chironomidae 20% subsample.”
If necessary, continue to remove midges from a third quad-
rant until you reach the 20% number.
Sort the midge subsample, using a dissecting microscope,
into distinct groups based on physical characteristics (mor-
pho-taxa) including:
• General body appearance – shape and color, length, density, and placement of setae;
• Head capsule – shape, color or markings (stripes, spots, bars, or darkened posterior margin), shape
of mentum;
• Antennae – shape, length, presence of elongated bases, presence and shape of Lauterborn organs,
and ability to retract antennae.
Complete a separate visual pick using the dissecting microscope to ensure that all taxa are represented
in the 20% random subsample by scanning the remaining 80% of the sample. Label a second vial
with “Chironomidae visual pick” and place a representative of each taxon found in the visual pick.
Head Capsule Mounting. Slide-mount the organisms collected from both the 20% subsample and
visual-pick to prepare for generic identification. Label the slides to clearly show whether it is from
Petri Dish Marked for 20%
Chironomidae Subsampling
ASCI Method 002, 5th Edition • ENRI • Page 4 of 10
the subsample or the visual pick. Those organisms identified for the visual pick are used for taxa
richness calculations only. Label slides to include study designation, slide number, study site, sample
type (i.e., a, b, or q), and subsample type (i.e., 20% subsample or visual pick). Slides with frosted
glass labels are recommended.
Use small cover slips (10 ml) to allow mounting multiple midges on each slide and to minimize the
number of slides and storage boxes needed for storage. This will accommodate mounting four midges
on each slide. Place a drop or two of mounting medium to position each midge on the slide. Use a
fast-drying, self-clearing medium such as CMC-10. Place one midge larva in each drop of medium.
Use a dissecting microscope for the rest of the mounting process to position the larvae and cover slip.
It is critical that the head capsule be positioned ventral-side-up, which may necessitate the decapita-
tion of larger larvae. It is also helpful (but not necessary) to point the anterior of the head capsule
toward the bottom of the slide. Positioned thus, the head capsule will appear right side up when viewed
through a compound microscope for identification.
Add the cover slip after the midge is in position by holding it with forceps. Place one edge of the
cover slip on the slide and then allow the opposite edge to fall. This will prevent air bubbles from
being trapped beneath the cover slip. Gently press the tip of the forceps to the top of the cover slip in
order to fine-tune the specimen and cover slip into position. Press the cover slip onto the head cap-
sule with sufficient pressure to spread the mandibles. Mounting groups of taxa with similar morpho-
logical characteristics sequentially will speed the identification process.
Identification. A compound microscope, preferably with phase-contrast lighting and 4x, 10x, 40x, and
100x (oil immersion) objectives, is necessary for generic identification. Taxonomic keys used for
midge larvae include Wiederholm (1983) or Merritt and Cummins (1996). The diagnoses and draw-
ings in Wiederholm (1983) are very helpful to confirm identifications. Record final identifications on
the Laboratory Bench Sheet-Chironomidae Identification (see page 9). Remember to multiply the
abundance of each genus by five to extrapolate the number of Chironomidae in the entire sample.
ID-3.Refill the specimen vials with ethanol, label, and group by station and date for archival. Make
sure the vials are tightly capped. Periodically examine the ethanol level in these jars and replenish as
needed. Maintain archived samples in the laboratory.
ID-4.Refer to Merritt and Cummins (1996) for feeding group and habit designations.
Quality Control
QC-1. Sorting. Examine 10% of the sorted samples in each lot. This will be done by the person desig-
nated responsible for laboratory quality control. (A lot is defined as a special study, basin study, index
period, or individual sorter.) Examine the material in the sorting tray to look for organisms missed by
the sorter. Any organisms found are added to the vials for that sample. The sample passes if less than
30 organisms (10% of the subsample) are found; the sample fails if more than 30 (10%) are found.
Check 100% of the samples sorted by new personnel until samples pass consistently. Complete ran-
dom sort checks after this time.
QC-2. Identification. Maintain a voucher collection of all samples and subsamples. Label, preserve,
and store these samples in the laboratory for future reference. Samples should be spot checked by a
second taxonomist and differences in identification recorded in a taxonomy validation notebook. If
no consensus can be reached as to the identification of the organism, send it out to a third taxonomist.
ASCI Method 002, 5th Edition • ENRI • Page 5 of 10
Add labels with specific taxa names to the specimen vials as they are identified. Extract individual
specimens as necessary to develop a reference collection or for identification verification by a second
taxonomist. The identifying taxonomist initials slides for Chironomidae identification. Keep these in
a slide file.
Maintain a reference collection of each identified taxon that is verified by a second taxonomist. Add
the word “validated” and the first initial and last name of the person validating the identification to
the vial label. Record the date specimens are sent out for taxonomy validations in a taxonomy valida-
tion notebook and include the label information. Record the date received, the results, and the name
of the person who performed the validation in the notebook upon return of the specimens.
QC-3. Tracking. Record information on laboratory progress of the samples (i.e., subsampling, sorting,
and taxonomy) on the login sheet to track the progress of each sample within the sample lot.
QC-4. Cleaning Equipment. Rinse thoroughly all sieves, pans, trays, etc., that have come into contact
with the sample after laboratory processing is complete. Examine the equipment carefully and pick
off any organisms or debris; add any organisms found to the sample residue.
QC-5. Reference Resources. Maintain and update as necessary taxonomic literature (see list below).
These resources are essential for identification of specimens. As possible, support taxonomists to
participate in periodic training of specific taxonomic groups to ensure accurate identifications.
Taxonomic References
Clifford, H.F. 1991. Aquatic invertebrates of Alberta. The University of Alberta Press, Edmonton, Alberta,
Canada. 538 pp.
Edmunds, G.F., Jr., S.L. Jensen, and L. Berner. The mayflies of North and Central America. University
of Minnesota Press, Minneapolis, MN. 330 pp.
Merritt, R.W., and K.W. Cummins, eds. 1996. An introduction to the aquatic insects of North America.
3rd ed. Kendall/Hunt Publishing Company, Dubuque, IA. 862 pp.
Peckarsky, B.L., et al. 1990. Freshwater macroinvertebrates of northeastern North America. Cornell
University Press, Ithaca, NY. 442 pp.
Pennak, R.W. 1989. Fresh-water invertebrates of the United States: Protozoa to mollusca. 3rd ed. John
Wiley and Sons, NY. 628 pp.
Stewart, K.W., and B.P. Stark. 1993. Nymphs of North American stonefly genera (Plecoptera). Univer-
sity of North Texas Press, Denton, TX. 457 pp.
Wiederholm, T. 1983. Chironomidae of the Holarctic region: keys and diagnoses. Part 1-Larvae.
Entomologica Scandinavica. Supplement 19.
Wiggins, G.B. 1996. Larvae of the North American caddisfly genera (Trichoptera). 2nd ed. University
of Toronto Press, Toronto, Canada. 457 pp.
ASCI Method 002, 5th Edition • ENRI • Page 6 of 10Sample Processing QCCollect Samplers# Jars SS 5' Pick Sorting ID Chiro Processing IDSample ID Stream Name Date IDY/N Y/N Date/Init Date/Init Date/Init Date/Init Date/InitSAMPLE LOGIN SHEET
ASCI Method 002, 5th Edition • ENRI • Page 7 of 10
LABORATORY BENCH SHEET: Subsampling
Station ID___________Stream Name ____________________Sample Date _________
Processing Date __________ Sorter Init._______________
Circle appropriate type of subsample processing: 300 5' Pick QC Other
Please check the appropriate subsampling levels used
and the number of grids picked in each:
Final SS: No. level 1 grids____ x No. level 2 grids _____ x No. level 3 grids _____
Level 1. Note random grids selected. T No. Of Grids _____
123456
A
B
C
D
E
Level 2. Note random grids selected. T No. Of Grids _____
123456
A
B
C
D
E
Level 3. Note random grids selected. T No. Of Grids _____
123456
A
B
C
D
E
Total Number of organisms in final subsample __________
ASCI Method 002, 5th Edition • ENRI • Page 8 of 10
LABORATORY BENCH SHEET – Identification
Station ID ________________Collected by ________________Date __________ Stream______________________
Sorted by_____________ Date Sorted____________ Subsample (underline): 300 (+/-20%) 5’ Pick QC 5' Pick Other
Taxonomist Init. _________ Date ID ______________
Organisms No. Found in TCR* Organisms No. Found in TCR*
5' pick 5' pick
Trichoptera
Apataniidae - Apatania
Brachycentridae - Brachycentrus
Glossosmatidae - Glossosoma
Hydroptilidae - Ochrotrichia
- Oxyethira
Hydrosychidae - Hydropsyche
- Arctopsyche
Lepidostomatidae - Lepidostoma
Leptoceridae - Ceraclea
Limnephilidae -unid
- Ecclisomyia
- Eocosmoecus
- Grensia
- Hesperophylax
- Limnephilus
- Onocosmoecus
- Psychoglypha
Polycentropodidae - Polycentropus
Rhyacophilidae - Rhyacophila
Uenoidae - Neophylax
Diptera
Ceratopogoniidae - unid
- Bezzia
- Ceratopogon
- Probezzia
Chironomidae - unid
Empididae - unid
- Chelifera
- Clinocera
- Oreogeton
Psychodidae - Pericoma
Sciomyzidae - unid
Simuliidae - Simullium
Tipulidae - unid
- Dicranota
- Hesperoconopa
- Hexatoma
- Tipula
Coleoptera
Other
Other
Ephemeroptera
Ameletidae - Ameletus
Baetidae - unid
- Acentrella
- Baetis
Ephemerellidae - unid
- Drunella
- Ephemerella
Heptageniidae - unid
- Cinygmula
- Epeorus
- Rithrogena
Leptophlebiidae - Paraleptophlebia
Plecoptera
Capniidae - unid
- Capnia
Capniidae/Leuctridae - unid
Leuctridae - unid
- Despaxia
Chloroperlidae - unid
- Neaviperla
- Plumiperla
- Suwallia
- Sweltsa
Nemouridae - Nemoura
- Zapada
Perlodidae - unid
- Isoperla
- Diura
Pteronarcyidae - Pteronarcella
Taeniopterygidae - Taenionema
Turbellaria
Gastropoda
Lymnaeidae - Lymnaea
Physidae - Physa
Planorbidae - unid
Valvatiidae -Valvata
Bivalvia - Sphaeriidae
Arachnoidea - Hydracarina
Crustacea
Amphipoda - unid
Gammaridae - unid
Ostracoda - unid
Oligochaeta
Nematoda
*Taxonomic certainty rating (TCR): 5 = most certain, 1 = least certain.
If rating is 3–1, give reason (e.g., missing gills).
Total No. Organisms _______ Total No. Taxa _______
Page 8 of 10 • ENRI • ASCI Method 002, 5th Edition
ASCI Method 002, 5th Edition • ENRI • Page 9 of 10
Chironomidae — unid Orthocladiinae — unid
Chironomini — unid - Brillia
- Chironomus - Cardiocladius
- Cryptochironomus - Chaetocladius
- Dicrotendipes - Corynoneura
- Einfeldia - Cricotopus
- Glypotendipes - Diplocladius
- Kiefferulus - Doithrix
- Omisus - Eudactylcladius
- Parachironomus - Eukiefferiella
- Paracladopelma - Euorthocladius
- Paralauterborniella - Heterotrissocladius
- Paratendipes - Hydrobaenus
- Phaenopsectra - Krenosmittia
- Polypedilum - Limnophyes
- Stenochironomus - Metriocnemus
- Stictochironomus - Nanocladius
Diamesinae — unid - Oliveridia
- Diamesa - Orthocladius
- Diamesinae - Paracricotopus
- Lappodiamesa - Parakiefferiella
- Odontomesa - Parametriocnemus
- Pagastia - Paraphaenocladius
- Potthastia - Paratrichocladius
- Prodiamesa - Parorthocladius
- Sympotthastia - Psilometriocnemus
Tanypodinae — unid - Rheocricotopus
- Brundiniella - Rheosmittia
- Coelotanypus - Smittia
- Conchapelopia - Stilocladius
- Helopelopia - Symposiocladius
- Krenopelopia - Synorthocladius
- Larsia - Thienemanniella
- Macropelopia - Tvetenia
- Natarsia - Zalutschia
- Nilotanypus Tanytarsini — unid
- Oliveridia - Cladotanytarsus
- Paramerina - Constempellina
- Rheopelopia - Micropsectra
- Tanypodinae - Paratanytarsus
- Telmatopelopia - Radotanytarsus
- Thienemannimyia - Rheotanytarsus
- Xenopelopia - Stempellina
- Zavrelimyia - Stempellinella
Podonominae - Boreochlus - Tanytarsini
- Tanytarsus
- Zavrelia
LABORATORY BENCH SHEET – Chironomidae Identification
Station ID ________________Collected by ________________Date __________ Stream______________________
Sorted by____________ Date Sorted__________ Subsample (underline): (20%) 5’ Pick Other
Taxonomist Init. _________ Date ID ______________ Total No. of Slides ___________
Tribe-Genus No. Found in TCR* Tribe-Genus No. Found in TCR*
5' pick 5' pick
*Taxonomic certainty rating (TCR): 5 = most certain, 1 = least certain.
If rating is 3–1, give reason (e.g., young specimen).
Total No. Chironomidae _______ Total No. Taxa _______ASCI Method 002, 5th Edition • ENRI • Page 9 of 10
ASCI Method 002, 5th Edition • ENRI • Page 10 of 10
DRAFT REPORT RIVER PRODUCTIVITY IMPLEMENTATION PLAN
Susitna-Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 January 2013
APPENDIX 2. FIELD DATA FORMS
To be provided prior to initiation of field data collection
DRAFT REPORT RIVER PRODUCTIVITY IMPLEMENTATION PLAN
Susitna-Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 January 2013
APPENDIX 3. SUSITNA DATA STANDARDS
~ 1 ~
AEA Susitna Project 2012 – Water Resources Programs
Field Data Collection, Processing, and Delivery Standards
version Jan. 31, 2013 DRAFT
Contents
A. Data Collection, Backup, and Delivery ...................................................................................................... 3
QC Protocol – Briefly................................................................................................................................. 3
File Paths / Names .................................................................................................................................... 4
Field Data Collection Guidelines................................................................................................................ 5
Raw Data Delivery .................................................................................................................................... 5
Final Data Delivery .................................................................................................................................... 6
B. Data Attributes and Databases ................................................................................................................ 7
Data Attributes ............................................................................................................................................. 7
Attribute Naming Standards ..................................................................................................................... 7
Attribute Naming - Names Not Allowed .................................................................................................... 7
Too Generic .......................................................................................................................................... 7
Database Reserved Words .................................................................................................................... 7
Attribute Data Values ............................................................................................................................... 8
Case ...................................................................................................................................................... 8
Comment, Note .................................................................................................................................... 8
Coordinates .......................................................................................................................................... 8
Dates and Times ................................................................................................................................... 8
Derived and Calculated Fields ............................................................................................................... 9
Downstream / Upstream Orientation.................................................................................................... 9
Location / Site Identifiers ...................................................................................................................... 9
Measurements: Numeric, Estimates, and Descriptive ........................................................................... 9
Measurements Units (UM).................................................................................................................. 10
Person / Staff Names .......................................................................................................................... 11
Special characters and symbols ........................................................................................................... 11
Waypoint names ................................................................................................................................. 11
Relational Databases .................................................................................................................................. 11
Database Object Names ......................................................................................................................... 11
Attribute Data Types............................................................................................................................... 12
~ 2 ~
Unique Record Identifiers (Primary Keys).................................................................................................... 13
Appendix A: Data QC Protocol ................................................................................................................... 14
Appendix B: Letter of Transmittal .............................................................................................................. 17
~ 3 ~
A. Data Collection, Backup, and Delivery
In general, the process for preparing and submitting field data includes the following steps:
1. Create field forms and mobile device entry screens and review with R2 (Dana Stewart and
Judy Simon) 2 weeks before field trip.
2. In the field, record data on field forms or in mobile devices and do QC1 and QC2.
3. Backup field forms and books and mobile devices (ArcPad, Trimble, cameras, GPS,
thermistors, etc) nightly.
4. Submit these raw deliverables to AEA at least monthly, via AEA SharePoint or to AEA IT on
external drives/DVDs with large files. AEA conside rs these to be interim deliverables.
5. Process the raw data to prepare for the AEA project database: convert raw file to a
submittal format, perform remaining QC levels 1 to 3, assign site IDs, flag unusable records,
apply database naming and codes, perform data reduction, etc.
6. Submit final processed (QC3) data files to AEA SharePoint or via hard drive, as done for raw
data. (Refer to the GIS User Guide for delivery of GIS data.)
7. For data being delivered for storage in the project database, data must be accompanied by
a data dictionary.
8. The project’s data resource manager will perform QC4 review and coordinate revisions
with the consultant’s Data Coordinator.
9. Data and dictionary are incorporated into the Susitna project relational database. No more
revisions can be made in the data by consultants, as the data is considered Final for the
study year.
10. If data revisions are needed later, such as for QC5, they’ll be coordinated by the project’s
data manager. The appropriate QC columns will be updated, which will serve as adequate
documentation.
QC Protocol – Briefly
• There will be 5 levels of data QC, named QC1 to QC5, each of which is tracked either within
tabular datasets (as for Excel and database tables), or within file path names (as for raw
field data files). This allows for quick determination of the QC status of all data.
• Details for the QC Protocol are found in Appendix A: Data QC Protocol.
• The QC levels, briefly, are as follows:
QC1 – Field Review: Review of field forms before leaving the field, or the QC level of raw
data collected via field equipment such as thermistors, cameras, GPS units, etc.
QC2 – Data Entry: Data from paper forms are entered into an electronic format and
verified.
QC3 – Senior Review: Final review by senior professional before submitting field data to
AEA, or the QC level of raw data cleaned up for delivery to AEA.
~ 4 ~
QC4 – Database Validation: Tabular data files are verified to meet project database
standards.
QC5 – Technical Review: Data revision or qualification by senior professionals when
analyzing data for reports.
File Paths / Names
• All delivered files should be named to clearly identify the source and type of data within.
These file names may include folder names to group files together by field event and data
type.
• The maximum filename length is 250 characters, including folder names and the file
extension.
• All delivered files must be accompanied by a Letter of Transmittal which will include the
information below, expanding on codes / shorthand as needed to clearly identify the
deliverable. The template for the Letter of Transmittal is provided in the Appendices.
• Include the following information within file path / names, in the order below:
Descriptor Format / Example
project name SuWa
submitting comp./agency HDR, LGL, ADFG, R2, etc.
study subject ChanMorph, AqHabitat, FishRadioTelem, ButterflyCollection, etc.
beginning study date YYYYMMDD
study area/location MidRiver , DevilCanyon, RM180.4
deliverable type Photo, FieldBk, FieldFrm, HoboDump, GPSDump, etc.
field form name (if applicable) Title of the field form included
QC level QC1, QC2, or QC3
equipment name (if applicable) GPS name, thermistor serial number, camera name, etc.
Data Coordinator staff initials
date submitted YYYYMMDD
sequential file name (if applicable) photo numbers, etc.
Original camera photo names are ok, IF unique within the folder.
A catalog with more descriptive info is expected for photos.
file type .xls, .mdb, .pdf, .jpg, etc
Examples:
SuWa LGL\FishRadioTelem\20120601 MidRiver\GPS dump QC1\GPS12 MB 20120610.txt
SuWa R2\ISFRiparian\20120731 RM98\Photos QC1 JZ 20120831 \IMGP2041.jpg
SuWa R2\ISFRiparian\20120731 MidRiver\Photo Catalog QC3 JZ 20120930
\RiparianPhotoCatalog.xls
~ 5 ~
Field Data Collection Guidelines
• Field forms and field books should be backed up after each day’s field work, either by
scanning to PDF and storing on a laptop or external drive (hard drive, thumb drive, or DVD),
OR making a photocopy, OR taking pictures with digital camera and storing the images on a
laptop or external drive.
• If equipment isn’t available for backup, then a new field book should be used each day, or
new loose leaf field book pages in a binder. Do not take used field books into the field if
they haven’t been backed up.
• Each field book should have the following information on the front cover: Study,
consultant, date range.
• Each field book page should have a header of waypoint name, streamcode (if known), date,
crew (if first page for the day), and page #.
• Each field form page should have a header of study name, waypoint name, streamcode (if
known), date, and page # of #. The crew should be recorded on the first form of each
site/date.
• Once the river miles and site identifiers have been identified for the project, these may be
recorded in addition to or instead of waypoints.
• Photo descriptions can be included in field notes, then entered into the photo catalog later,
so that anyone looking at a photo knows what they are looking at.
Raw Data Delivery
• Raw data should be delivered on the first day of each month for all field events occurring
in the previous 30 days. Special considerations for delivery schedules and requirements
can be worked out for each study if needed.
• The table below lists general raw data deliverable requirements:
Data Source QC Level Delivery Schedule Delivery
Format
Field book scans QC1 First day of each month. .PDF
Field form scans QC1 First day of each month. .PDF
GPS dumps QC1 – raw dump, no data
cleanup
First day of each month. .TXT
Lab reports QC1 – as received from lab First day of each month. .PDF
Mobile data collector
(ArcPad, etc)
QC1 – raw dump, no
cleanup
First day of each month. .TXT or .CSV
Photos QC1 – raw dump from
camera, before cleanup
First day of each month. .JPG
Telemetry dumps QC1 – raw dump, no
cleanup
First day of each month. .TXT or .CSV
Thermistor dumps QC1 – raw dump, no
cleanup
First day of each month. .TXT or .CSV
• Photos should be accompanied by photo catalogs to enable users to find applicable photos
as needed in the future.
~ 6 ~
• Data submittals can be posted to the AEA SharePoint site, Library “SUWADATA”, folder
“2012 Field Data Deliverables”, in the appropriate folder for the study. Upon posting, a
Letter of Transmittal (Appendix B) should be emailed to the data managers listed on the
Letter template to notify them of the delivery, so they may maintain a catalog of all
deliveries for AEA.
• Upload times to AEA SharePoint have been tested; expect a 10 MB file to upload in less
than 2 minutes, and a 30 MB file to upload in 4 minutes. If an upload exceeds 100 MB,
please notify AEA IT (Sara Nogg) before posting to plan transmission and storage space.
• Once raw data have been archived, external hard drives may be returned upon request.
Final Data Delivery
• Data collected in the field will be processed and submitted to AEA, constituting final data
delivery. Delivery schedules and final data forma t for each study will be agreed on by AEA,
the consultant Data Coordinator, and the project Data Manager. Tabular data may be MS
Excel or Access relational format, or a GIS database.
• Processed data should follow the Susitna QC protocol (refer to “Appendix A: Data QC
Protocol”). All raw data intended for the Susitna project relational database must be
processed: equipment dumps are not intended for database imports.
• Photos selected for final delivery should be delive red with a catalog providing further
details on specific location, date, etc. The catalog can be an MS Excel or MS Access table.
• The table below lists final data deliverable requirements:
Data Source QC Level Delivery
Schedule
Delivery Format
DIDSON data QC1 Study due date
Field tabular data QC3 – loaded from field forms and
equipment dumps, processed,
cleaned up, senior review
Study due date .XLS or .MDB
Lab tabular data QC3 – loaded from lab format,
standardized, senior review
Study due date .XLS or .MDB
Modeling data QC3 – data used to feed into a
modeling application
Study due date .XLS or .MDB
Photos QC3 – renamed if desired, bad
photos removed
Study due date .JPG
Photo Catalog QC3 Study due date .XLS or .MDB
Videography QC3 – processed and compressed Study due date contact UAF GINA
manager Dayne
Broderson
• All deliverables should be accompanied by a transmittal letter (Appendix B).
• Once data files are delivered to AEA, they should be archived at the consultant’s office for
2 years.
~ 7 ~
B. Data Attributes and Databases
Data Attributes
Standards are being established for the Susitna project for some data attributes, whether stored on field forms, MS
Excel sheets, database tables, etc. These standards should be considered as much as is practical.
Attribute Naming Standards
(see Excel file “SuWa - Field Data Standards - Attributes DES20120511.pdf” posted on SharePoint Library
SUWADATA, folder “Field Data Standards and Database Domains”)
Attribute Naming - Names Not Allowed
Too Generic
These field names are not allowed as standalone and need clarification within the name, usually with
a subject prefix or initials. Some of these are also reserved words in database software, so mustn’t be
used alone.
Too Generic Better Example
Class AqHabClass
Code FishSpecCd
Comment FishCtCom
Date RTTrackDat
Desc, Description, Note TurbidDesc
End TransectED
File GPSFile
ID RTTrackID
Name SiteName
Parameter LabParam, Analyte
Sample SampleID
Start TransectST
Temp WaterTemp
Time FloatTime1
Type RosgenType
Unit AqHabUnit
UOM AnalyteUM
Database Reserved Words
Some words have special meaning within database engine software; some of these “reserved
words” should be avoided as full names for attributes. For example, DATE and COUNT are
database function names, so are disallowed as attribute names unless they are qualified with
descriptors, such as SurvDate or FishCount.
~ 8 ~
AEA currently uses MS Access 2010 and Alaska Department of Natural Resources uses Oracle,
so reserved words for these platforms should be considered in attribute naming. Some
reserved words are found in the generic names list, but others to avoid include:
Current, Float, Group, Index, Key, Label, Limit, Memo, Nested, Note, Range, Recover, Report,
Reset, Resource, Return, Set, Size, Table, Text, Us er, Value, Year, Zone.
Complete lists of reserved words can be found on Microsoft and Oracle websites, but those
listed above seemed the most likely to be encountered in the Susitna project.
Attribute Data Values
Case
• Values may be upper or lower case or a mixture, for readability and reporting.
• Case should be applied consistently within a field.
• Some data systems can accommodate case sensitivity while others can’t, so values should
be assumed to be equivalent for upper and lower case. For example, a units code of M or
m represents meters.
• Coded values should be upper case; this helps identify them as codes from lookup tables.
Comment, Note
• Field names don’t need to reflect the entity, as these fields are not commonly included in
output. If they do get reported, unique display na mes can be assigned in the query.
Coordinates
• All coordinates must be WGS84 and in units decimal degrees NNN.NNNNN (5-6decimals).
• Degree decimal minutes dumped from GPS are not allowed in final data. Consultants will
convert coordinates before delivery.
Dates and Times
• All dates are Text data type, format YYYYMMDD. (The DateTime type is problematic in GIS,
so is not used.)
• Times should be stored in separate attributes from dates.
• Times are Text data type, 24-hour time
o Time of Day format = HH:MM or HH:MM:SS, specified in the data dictionary.
o Duration Time format = HH:MM or HH:SS, specified in the data dictionary
• If a time is for duration, try to reflect that in the attribute name.
o Consider using a units field for durations, which can read as HH:MM or MM:SS.
• Field names should reflect the entity, so they are easily distinguished from other dates and
times in reports and query output. For example: fish wheel dates might be FWLogDate
and FWCatchDat.
• A time zone qualifier must be included in any tables that have time-of-day attributes. Use
codes:
~ 9 ~
• AST = Alaska Standard Time
• ADT = Alaska Daylight Time.
Derived and Calculated Fields
• Data tables may contain calculated and derived fields. The formula must be provided in
the data dictionary, as well as any other fieldnames used in the calculation.
• Calculated fields must be named to show their status, using a “Calc” as a name suffix, such
as AvgWidCalc.
• At this point, the MS Access 2010 data type of Calculated is not used for Susitna.
Downstream / Upstream Orientation
• Any attributes that are specific to a left bank (LB) or right bank (RB) feature should be
orientated as “looking downstream”.
• Whereas some disciplines may normally orientate as “looking upstream”, the Susitna
project has chosen a downstream orientation for all applications with deliverables to AEA.
Location / Site Identifiers
• A linear route layer has been developed for the Susitna River mainstem for the current
project. River miles along this route are name “PRM” (project river mile). Some studies
and historic data may include “HRM” (historic river mile), calculated in the 1980s studies.
When HRM is present, the historic source should be noted in the data dictionary and
possibly a field in a site table. A cross-reference table of PRM and HRM may be created by
the GIS team.
• As of this document version (Jan 2013), streamcodes and project river miles have been
generated only for the Susitna River mainstem main channel and certain river features. Off
channel and tributary sites are making use of lat/long for location identifiers, but naming
conventions for them are being considered.
• Location names must be meaningful, and at least include a project river mile (PRM).
• No cryptic site codes. Codes used in the field must be converted to site names in the GIS
site domain before submittal. (As of Jan. 9, 2013 there is no site domain available.)
• There will be a separate document for the geospatial reference.
Measurements: Numeric, Estimates, and Descriptive
• Attributes of a numeric nature should be NUMBER data type and cannot contain
characters.
• Number fields are typically measurements such as count, width, velocity, etc. However,
some measurement results require alphanumeric values, which can be accommodated in
various ways.
• If estimated measurements must be stored, they go into the numeric field, with a TEXT flag
to describe the nature of the estimate, such as Est Flag.
Example:
~ 10 ~
Count values that are not allowed: “~10”, “>20”, “many”, “5-10”
Use the following instead:
FishCount CntEstFlag
10 this means exactly 10
10 ~ this means about 10
20 > this means >20
• If counts of “5-10” and “many” need to be allowed for some reason, we can employ a
count description (CountDesc) field,TEXT datatype.
• Other descriptive measurements, such as some Turbidity, use a TEXT field named with
“Desc”, such as TurbidDesc. The domain for a field like this should be defined and enforced
to allow for reporting.
• Queries and reports may need to include EstFlags and Desc fields, if they exist. Users need
to know how to deal with measurements like this, so it should be documented in the
dictionary.
• Use caution that the default value for numeric fields isn’t set to zero (0). This will be
checked during QC4 verification.
Measurements Units (UM)
• Attributes with units can be stored in one of two ways: units indicated in the field name, or
units stored in a separate units of measurement (UM) field. These will be decided when
reviewing draft field forms.
• Units will be included in field names where practic al.
• Some attributes use varying units based on discipline, or the units can’t be denoted within
a 10-character field name. These will need a separate UM field. Examples may include:
WetWid and WetWidUM
RelatCond and RelCondUM
SpecCond and SpecCondUM
• Some parameters will have standard measurement units for the project. These can be
identified when reviewing field forms, but at least include:
water temperature degrees C
fish distribution metric units
Instream Flow (ISF) English units
Habitat Suitability Criteria (HSC) English units
(others to be determined)
• Unit values should never include special characters, as the Unicode character set could be
misinterpreted during data imports and exports. For example, the Unicode symbol for
micron “µ” should be represented with an ASCII “u”.
~ 11 ~
Person / Staff Names
• Avoid using a person’s initials, to avoid an additional lookup and confusion of acronyms.
• Use first initial and last name (FLastname), such as DStewart.
• Exception: Authors in the Bibliographic Database are Last, First M.
Special characters and symbols
• ASCII special characters are allowed within values. These are common in:
long text fields like Comments
streamcodes with periods (SU 1.120.10)
multiple values separated by commas or semicolon (WeatherDes = wind, light rain)
• Values should never contain Unicode symbols, only ASCII characters.
Waypoint names
• Waypoints may typically be assigned sequential numbers within a GPS unit. If the
waypoints are to be delivered to AEA for the final project database, they should be
renamed using the following standard:
GPS unit ID + YYYYMMDD collection date + original sequential waypoint #
(GPS unit ID = the consultant’s equipment inventory ID, not a manufacturer name)
Relational Databases
If MS Access databases will be delivered as part of the final data deliveries, the following
guidelines should be used.
Database Object Names
The Leszynski (Hungarian) naming convention is commonly used by MS Access developers and is
adopted for the Susitna project, with some minor customization. Note that this convention isn’t
enforced by MS Access; it is implemented by the database administrator for easier maintenance
and programming in Visual Basic for Access (VBA), where reference to an object name may not
indicate its data type.
Attributes (no prefix)
tbl Table: data
tlu Table: lookup, valid value, code
tmp Table: temporary, can be deleted without adverse effect
qry Query, view
(The next ones aren’t typically delivered with a da tabase by consultants.)
frm Form
rpt Report
mcr Macro
mod Module
~ 12 ~
Other naming rules:
• Table names are restricted to a 30-character maximum, as required to meet GIS
standards for this project.
• Attribute names are restricted to a 10-character maximum to accommodate GIS shapefile
users.
• Attribute names must start with a capital letter.
• Contain only letters and numbers.
• Underscores may be allowed if necessary, but no spaces.
• Symbol fonts are never allowed in names.
• Name using Pascal case (camel case with the first letter capitalized). This is a mix of
upper and lower case, where each new element of the name is capital, and is encouraged
for readability.
The naming convention may be addressed if the database is later moved to another platform
with case sensitivity issues between Oracle, MS Access, and SQL Server.
Attribute Data Types
The following field data types will be utilized in the Susitna database and are permitted in
deliverables:
Boolean (True/False, Yes/No)
Hyperlink
Number
Text (make sure zero-length string properties are disabled)
Data types that aren’t permitted at this time in de liverables:
Attachment (OLE, BLOB)
AutoNumber (change to Text or LongInt for delivery)
Calculated (MS Access 2010 data type)
DateTime (dates and times must be Text)
Memo
Multi-valued (MS Access accdb format)
A naming convention for attributes to show the data type won’t be implemented for the Susitna
project, as we need to accommodate the shapefile attribute name limit of 10 characters. For
example, we won’t use prefix “int” for integer type attributes.
~ 13 ~
Unique Record Identifiers (Primary Keys)
• A logical / natural primary key must be identified for each datset, whether MS Access table
or MS Excel data sheet.
• If a synthetic / surrogate key is also desired, or in some situations required, then the key
name must be descriptive; the name “ID” alone (a default name created by MS Access) is
not allowed. Refer to the Susitna project Data Naming Conventions for descriptors.
• Surrogate keys may be text, numeric, or MS Access AutoNumber data types. Text keys
should be upper case for portability to another platform.
• If the key contains information, it should be noted in the data dictionary so users can
interpret it correctly. For example, SurveyID is year + study method + sequential number
(2012RTTAG2).
C. Data Dictionary
The Program Lead team is tasked with compiling a comprehensive data dictionary document for all
water resources studies. Ideally, a data dictionary utility with reporting capabilities will be
employed, although this has not been decided yet. This may provide a more detailed and
descriptive document than the GIS metadata, which is needed to meet GIS project standards.
For the Susitna project, we make a distinction between the terms “metadata” (refers to the GIS)
and data dictionary” (refers to the relational data base). The metadata has standards that the GIS
team and ADNR establish and enforce for the GIS. The relational database will be documented
differently from the GIS, and its template doesn’t resemble GIS metadata.
• (This item is in progress and will be updated.)
• When field data is submitted to the Program Lead team for level QC4, it should be
accompanied by a data dictionary. This will provide a detailed, descriptive document to
compliment the GIS metadata project standards.
• The dictionary will be reviewed for table naming and descriptions, identification of keys,
field names, data types, and descriptions.
• Descriptions should not typically be terse, but rat her detailed with an eye to being useful to
scientists years later and without access to current scientists for explanation. Special
handling of anomalies within tables or fields shoul d also be described.
• The format for data descriptions can be MS Excel or MS Word until further notice. Storing
field descriptions within MS Access table designs won’t fulfill the dictionary requirements.
~ 14 ~
Appendix A: Data QC Protocol
Introduction
The F&A Program Lead team is tasked with implementing a standardized QA/QC protocol,
intended for use in all environmental field studies in 2012, including fish and aquatic, water
quality, river ice, terrestrial wildlife and botany, ISF, and others. This document will be presented
to the leader and appointed Data Coordinator of each of these study teams.
Members of the Program Lead team can be contacted with questions and comments:
Dana Stewart – Data Resources Management
Judy Simon – Program Coordination
Joetta Zablotney – GIS-related QC
QC Levels
There will be 5 levels of data QC, named QC1 to QC5, each of which is tracked within the data.
This allows for quick determination of the QC status of every data record. The first three levels are
to be completed by the study team, the fourth level by the Program Lead team, and the final level
by senior professionals during analysis and reporting.
QC1 – Field Review: QC review performed by the person collecting field data, whether recorded
on paper field forms or directly into electronic data collection tools, and then by the field
team leader. This is also the QC level of raw data collected via field equipment such as
thermistors, cameras, GPS units, etc.
The goal of QC1 is to identify errors and omissions and correct them under similar field
conditions prior to leaving the field.
Review is done on 100% of data and includes completeness, legibility, codes, and logic on
all information recorded. This is typically completed in the field daily. Once completed,
QC1 notations are made directly on the field form in an entry named “QC1”, containing
the date and responsible staff and formatted as “YYYYMMDD FLastname” (example:
“20120631 JDoe”).
QC2 – Data Entry: Data from paper forms are entered into an electronic format, then data entry
is verified by a second party against the field forms.
The goal of QC2 is to verify correct, complete, and consistent data entry.
Verification is done on 100% of data entered and includes extrapolation of shorthand
codes that might be used in the field into longhand or standard codes during data entry.
Data entry errors are corrected at this time, then QC is recorded in a column named
“QC2”, containing the date and responsible staff and formatted as “YYYYMMDD
FLastname” (example: “20120631 JDoe”).
~ 15 ~
QC3 – Senior Review: Data are reviewed by a senior professional on the consultant team,
checking for logic, soundness, and adding qualifiers to results if warranted. Calculated
results can also be added at this time (formulas must be documented in the data
dictionary). This is the final review before submitting field data to the Program Lead, and is
recorded in the “QC3” column in the same format as QC2. This is also the QC level of raw
files that have been “cleaned up” or otherwise processed for delivery to AEA, such as
photos.
QC4 – Database Validation: Electronic data files are submitted to and verified by the Program
Lead’s data resources manager. The deadline for this delivery is negotiated with the
team Data Coordinator in consideration of the study due date.
Data are verified for completeness, project standards (codes, field name conventions,
date formats, units, etc.), calculated and derived fields, QC fields, etc. The data files are
incorporated into the project database schema, splitting into normalized tables as
necessary and all primary and foreign keys checked. An error report is generated for the
study consultant, who is expected to make corrections and resubmit data. The process is
repeated until verification is clean and records are marked in column “QC4” (such as
“20121001 DStewart”).
QC5 – Technical Review: Data revision and qualification may be applied by senior professionals
when analyzing data for reports, trends, and FERC applications. Data calculations may be
stored with the data. Some data items may get corrected or qualified within the
database, while others are only addressed in report text. QC5 may be iterative, as data
are analyzed in multiple years.
If a data item is revised directly, it’s recorded in 2 columns, QC5 (date and staff) and
QC5Edit (what is revised and why). This will serve as adequate documentation of the
revisions, so maintenance of additional documentation isn’t usually necessary. QC5
revisions will be physically made by the Data Resource Manager, directed by the senior
professional.
Data Collection Devices (e.g. ArcPad, Trimble)
Field forms should be reviewed and approved by the Program Lead team before use in the
field. If mobile data devices (ArcPad and Trimble) are used to record field data directly, they must
be accompanied by backup paper field forms in case of equipment failure, and both the paper
forms and device entry screens should be approved by the Program Lead team.
Both paper and electronic field forms should be backed up nightly in the field by scanning and
downloading to a storage unit or photocopy to paper.
Data Revisions
~ 16 ~
Once the processed field data (QC3) have been submitted by a consultant to AEA via R2, and
and it has been validated as ready for incorporation into the Susitna project database (QC4), the
data are considered to reside with AEA, and subsequent revisions will only be made by the
Program Lead team on their behalf. If a study team discovers that data require revisions, their
Data Coordinator can send a formal, written request (i.e. email) to the Data Resources Manager.
Revisions will be made and the appropriate QC columns updated, which will serve as adequate
documentation.
~ 17 ~
Appendix B: Letter of Transmittal
(next page)
~ 18 ~
LETTER OF
TRANSMITTAL
To: Dana Stewart, R2 Date:
Dani Evenson, R2 Project:
Sara Nogg, AEA Subject:
Transmitted via AEA SharePoint DVD Thumb drive External hard drive
Other______________________________________________
are the following: **Please specify file names and folder/file paths and include a brief description
As: Raw / QC1 Final/ QC3 Other _______________________________________
Remarks:
Please notify us if the enclosures are not received.
Submitted by:
Name:
Company
cc:
DRAFT REPORT RIVER PRODUCTIVITY IMPLEMENTATION PLAN
Susitna-Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 January 2013
APPENDIX 4. DRAFT DATABASE TEMPLATES
Relationships for River Prod ERDWednesday, January 16, 2013tblCaptureEventtblFishObservationtblGutContenttblSurgeryDetailtblSiteEventtblSitetluStudytblMacroinvSampletblAlgeaSampletblFishTissueSampletblRiverProductivityEventtblSnagSampletblDriftSampletblAdultEmergentSampletblColonizationEventtblLabResulttblStationCapture Event KeyFish Observ KeyEvent KeyObserv SiteSpeciesLifestageSizeBehaviorCountGear TypeFish Observ KeyGut contents from labFish Observ KeySurgery detailsEvent KeyStudy KeySite KeySite KeySegment (Level 1)Geomorphic Reach (Level 2)Channel TypeMS Hab Category (Level 3)MC Hab Type (Level 3)OCH Type (Level 3)Mesohab Type (Level 4)Edge Hab Length (Level 5)Feature TypeStreamcodePRMPRM CriteriaTrib Channel TypeDimensionsFocus AreaHydro Layer KeyFeature Layer KeyStudy KeyStudy detailsSegmentRiverProd Event KeyMacroinv Sample KeyReplicate parentPosition in streamSurface areaSample grid squaresLat & LongRiverProd Event KeyAlgae Sample KeyLat & LongSample detailsFish Observ KeyTissue Sample KeyRiverProd Event KeyLat & LongRiverProd Event KeySnag Sample KeyLat & LongRiverProd Event KeyDrift Sample KeyLat & LongSample detailsRiverProd Event KeyAdult Emerg Sample KeyLat & LongSample detailsRiverProd Event KeyColonization Sample KeyLat & LongDeployment detailsRetrieval detailsSample detailsRiverProd Event KeySample KeyLab resultsStation KeySite Key