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Title:
Bat distribution and habitat use, Study plan Section 10.13 : Initial study
report SuWa 207
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Draft initial study report
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Susitna-Watana Hydroelectric Project document number 207
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[Anchorage : Alaska Energy Authority, 2014]
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February 2014
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Study plan Section 10.13
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Susitna–Watana Hydroelectric Project
(FERC No. 14241)
Bat Distribution and Habitat Use
Study Plan Section 10.13
Initial Study Report
Prepared for
Alaska Energy Authority
Prepared by
ABR, Inc.—Environmental Research & Services
Forest Grove, Oregon
February 2014 Draft
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page i February 2014 Draft
TABLE OF CONTENTS
Executive Summary ...................................................................................................................... v
1. Introduction ....................................................................................................................... 1
2. Study Objectives................................................................................................................ 1
3. Study Area ......................................................................................................................... 2
4. Methods and Variances in 2013 ....................................................................................... 2
4.1. Acoustic Surveys .................................................................................................... 2
4.1.1. Variances......................................................................................... 3
4.2. Roost Surveys ......................................................................................................... 3
4.2.1. Natural Roosts ................................................................................. 3
4.2.2. Artificial Roosts .............................................................................. 4
4.2.3. Variances......................................................................................... 5
4.3. Data Management and Analysis ............................................................................. 5
4.3.1. Variances......................................................................................... 6
5. Results ................................................................................................................................ 6
5.1. Acoustic Surveys .................................................................................................... 6
5.1.1. General Bat Activity ....................................................................... 6
5.1.2. Temporal Comparisons ................................................................... 7
5.1.3. Spatial Comparisons ....................................................................... 7
5.2. Roost Surveys ......................................................................................................... 9
5.2.1. Natural Roosts ................................................................................. 9
5.2.2. Artificial Roosts .............................................................................. 9
6. Discussion........................................................................................................................... 9
6.1. Acoustic Monitoring ............................................................................................... 9
6.1.1. Temporal Comparisons ................................................................. 10
6.1.2. Spatial Comparisons ..................................................................... 11
6.2. Roost Surveys ....................................................................................................... 12
6.2.1. Natural Roosts ............................................................................... 12
6.2.2. Artificial Roosts ............................................................................ 13
7. Completing the Study ..................................................................................................... 13
8. Literature Cited .............................................................................................................. 14
9. Tables ............................................................................................................................... 17
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page ii February 2014 Draft
10. Figures .............................................................................................................................. 17
LIST OF TABLES
Table 4.1-1. Categorization of Acoustic Detector Stations by Habitat and Forest Structure Types,
2013. ...................................................................................................................................... 17
Table 4.2-1.Quality Scores for Potential Cliff-Roosting Habitat. ................................................ 18
Table 5.1-1. Number and Percentage of Nights Surveyed by Acoustic Detector Stations in 2013.
............................................................................................................................................... 19
Table 5.1-2. Bat Activity (Bat Passes per Detector-Night) by Station and Month, 2013. ............ 20
Table 5.1-3. Elevation and Minimum Distances to Water Bodies and Cliffs, by Station, 2013. . 22
Table 5.1-4. Bat Activity (Bat Passes per Detector-Night) by Month and Habitat Type, 2013. .. 23
Table 5.1-5. Bat Activity (Bat Passes per Detector-Night) by Month and Forest Structure Type
for Non-Pond Habitats, 2013. ................................................................................................ 24
Table 5.1-6. Acreage of Habitat and Forest Structure Types in Bat Study Area, 2013. ............... 24
Table 5.2-1. Results of Building Searches for Artificial-Roost Surveys, 2013. ........................... 25
LIST OF FIGURES
Figure 3-1. Bat Study Area for the Susitna–Watana Hydroelectric Project, 2013. ...................... 27
Figure 4.1-1. Acoustic Detector Sites Monitored for the Bat Study in 2013................................ 28
Figure 5.1-1. Distribution of Bat Activity Among Acoustic Detector Stations, 2013.................. 29
Figure 5.1-2. Representative Sonogram from Little Brown Bat Recorded during Current
Study, 2013. .......................................................................................................................... 30
Figure 5.1-3. Bat Activity by Date, 2013 (error bars indicate SE). .............................................. 31
Figure 5.1-4. Bat Activity by Hour in Relation to Sunset, 2013 (error bars indicate SE). ........... 32
Figure 5.1-5. Bat Activity by Station in 2013 (error bars indicate SE; asterisks indicate
that no bats were detected). ................................................................................................... 33
Figure 5.1-6. Bat Activity by Month and Habitat Type, 2013 (error bars indicate SE). .............. 34
Figure 5.1-7. Bat Activity by Month and Forest Structure Type for Non-Pond Habitats,
2013 (error bars indicate SE). ............................................................................................... 35
Figure 5.1-8. Distribution of Habitat Types in Bat Study Area, in Relation to Acoustic
Detector Sites, 2013. ............................................................................................................. 36
Figure 5.1- 9. Distribution of Forest Structure Types in Bat Study Area, in Relation to
Acoustic Detector Sites, 2013. .............................................................................................. 37
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page iii February 2014 Draft
Figure 5.2-1. Cliff Habitats Surveyed in Bat Study Area, in Relation to Acoustic Detector
Sites, 2013. ............................................................................................................................ 38
Figure 5.2-2. Locations of Buildings Searched on Artificial-Roost Surveys, in Relation to
Acoustic Detector Sites, 2013. .............................................................................................. 39
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page iv February 2014 Draft
LIST OF ACRONYMS, ABBREVIATIONS, AND DEFINITIONS
Abbreviation Definition
ADF&G Alaska Department of Fish and Game
AEA Alaska Energy Authority
AKNHP Alaska Natural Heritage Program
APA Alaska Power Authority
cm centimeter
CF compact flash
CIRWG Cook Inlet Region Working Group
FERC Federal Energy Regulatory Commission
ft feet
GB bravel bar
GIS geographic information system
ILP Integrated Licensing Process
ISR Initial Study Report
km Kilometer
m Meter
mi mile
PRM Project River Mile
Project Susitna-Watana Hydroelectric Project
QA/QC quality assurance and quality control
RSP Revised Study Plan
SPD study plan determination
USNO United States Naval Observatory
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page v February 2014 Draft
EXECUTIVE SUMMARY
Bat Distribution and Habitat Use 10.13
Purpose The purpose of this study is to assess the occurrence of bats, as well as the
distribution of habitats used by bats, and to document roosting locations used
by bats in the study area. These data will enable estimation of the potential
loss and modification of habitat likely to result from Project development.
Status Data collection and analysis for 2013 were completed as planned. Planning for
the second year of study is underway.
Study
Components
The study has two major components: (1) assess the occurrence of bats and the
distribution of habitats used by bats in the study area, using acoustic
monitoring; (2) identify potential roosting locations of bats in the study area
through literature review and conduct ground-based searches to locate roosts
of bats in the study area.
2013 Variances Acoustic monitoring and ground-based roost searches could not be conducted
as planned on CIRWG lands due to lack of access in 2013 (RSP Section
10.13.4.1). The search effort for artificial roosts (RSP Section 10.13.4.1) was
expanded to include nearby buildings outside of the study area.
Steps to
complete the
Study
As explained in the cover letter to this draft ISR, AEA’s plan for completing
this study will be included in the final ISR filed with FERC on June 3, 2014.
Highlighted
Results and
Achievements
The study team documented widespread occurrence of bats throughout the
study area (85 percent of monitoring sites), including areas of seasonal
concentration, using acoustic monitoring. The study team visited 26 structures
at 11 sites during the artificial-roost search and characterized 102 cliff sections
during the natural-roost search. No roosting bats were discovered during either
the artificial- or natural-roost searches, however.
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 1 February 2014 Draft
1. INTRODUCTION
On December 14, 2012, Alaska Energy Authority (AEA) filed with the Federal Energy
Regulatory Commission (FERC or Commission) its Revised Study Plan (RSP) for the Susitna-
Watana Hydroelectric No. 14241 (Project), which included 58 individual study plans (AEA
2012). Section 10.13 of the RSP described the Bat Distribution and Habitat Use Study (Bat
Study). On February 1, 2013, FERC staff issued its study determination (February 1 SPD) for 44
of the 58 studies, approving 31 studies as filed and 13 studies with modifications. The Bat Study
was one of the 31 studies approved with no modifications.
This study evaluates the occurrence of bats and the distribution of habitats used by bats in the
study area. Project biologists deployed ultrasonic acoustic detectors and conducted searches for
evidence of roosting sites, maternity colonies, and hibernacula to better understand how bats
might be affected by the Project. RSP Section 10.13 described the goals, objectives, and
proposed methods of data collection regarding bats.
Following the first study season, FERC’s regulations for the Integrated Licensing Process (ILP)
require AEA to “prepare and file with the Commission an initial study report describing its
overall progress in implementing the study plan and schedule and the data collected, including an
explanation of any variance from the study plan and schedule.” (18 CFR 5.15(c)(1)). This Initial
Study Report (ISR) on the Bat Study has been prepared in accordance with FERC’s ILP
regulations and details AEA’s status in implementing the study, as set forth in the FERC-
approved RSP (referred to herein as the “Study Plan”).
2. STUDY OBJECTIVES
The goal of the Bat Study is to collect baseline data on bats in the Project area to enable the
assessment of potential impacts on bats from development of the proposed Project.
The Bat Study objectives are established in RSP Section 10.13.1:
• Assess the occurrence of bats and the distribution of habitats used by bats within the
proposed reservoir inundation zone and associated infrastructure areas for the Project.
• Review geological and topographical data to assess the potential for roosting, maternity,
and hibernacula sites in the study area.
• Examine suitable geological features (caves, crevices) and human-made structures
(buildings, mines, bridges) for potential use by bats as roosting sites, maternity colonies,
and hibernacula.
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 2 February 2014 Draft
3. STUDY AREA
As established by RSP Section 10.13.3, the bat study area (Figure 3-1) encompasses the
proposed reservoir inundation zone, the proposed dam and powerhouse locations, and the
associated camp facilities area, but not the access and transmission corridors.
4. METHODS AND VARIANCES IN 2013
The methods for each of the Bat Study components are presented in this section.
4.1. Acoustic Surveys
During the 2013 study season, AEA implemented the acoustic survey methods described in RSP
Section 10.13.4 with the exception of variances explained below (Section 4.1.1).
Acoustic surveys of bats employed the use of echolocation detectors to assess bat activity
patterns and habitat associations across the study area during May 25–October 7, 2013. Twenty
Anabat® SD1 broadband acoustic detectors (Titley Electronics, Ballina, New South Wales,
Australia) were deployed to record the ultrasonic sounds produced by echolocating bats (Figure
4.1-1). Scientists use these detectors commonly for passive detection of free-ranging,
echolocating bats (O’Farrell et al. 1999). Each detector had a detection range of approximately
20 m (66 ft), with the actual range depending on air temperature, humidity, elevation, and the
frequency and intensity of echolocation calls. A sensitivity setting of 6 was used on each detector
to minimize reception variability among all detectors. Microphones were housed in waterproof
“bat-hats” (EME Systems, Berkeley, California) and were secured to a section of rebar or tree,
approximately3–5 ft (~1–1.5 m) above ground level. All associated electronic equipment for the
detectors was enclosed in waterproof plastic cases (Pelican Products, Inc., Torrance, California)
located below each microphone and a photovoltaic system (GoGreenSolar.com, Placentia,
California) was connected to each detector to provide solar power for recharging the batteries.
Sampling sites for the detectors were selected using random points (20 primary and 40
alternative) generated within the study area with a geographic information system (GIS). The
random points were stratified by broad habitat type (pond, stream, cliff, upland) based on
preliminary water body mapping and cliff mapping prepared for other wildlife and botanical
studies (Study 10.14, Surveys of Eagles and Other Raptors, and Study 11.5, Vegetation and
Wildlife Habitat Mapping in the Upper and Middle Susitna Basin). The non-pond habitat types
were stratified further by forest structure type (closed, open, dwarf, shrub; Table 4.1-1) using the
existing vegetation map prepared for the Alaska Power Authority (APA) Susitna Hydroelectric
Project in the 1980s (Kreig and Associates 1987) because an updated vegetation map for the
current Project was not available in 2013. The forest structure types used in this study were
based on the original vegetation classification system created by Viereck et al. (1980) and were
adapted to be biologically relevant to bats by recognizing the potential importance of structural
complexity on bat activity. Closed structure types were forests with 60–100 percent canopy
cover; open structure types included open (25–60 percent) and woodland (10–25 percent) forest
types; the dwarf structure had at least 10 percent canopy cover of dwarf forest [defined as trees
under 5 m (16 ft) at maturity]; and the shrub structure type comprised at least 25 percent shrub
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
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FERC Project No. 14241 Page 3 February 2014 Draft
cover and <10 percent forest canopy cover. Within each habitat type, the study team selected one
site in each of four vegetation structure types (closed, open, dwarf, shrub). Among habitat types,
sampling points were selected within 200 m (656 ft) of a pond for pond habitat; within 200 m
(656 ft) of a perennial stream for stream habitat; within 200 m (656 ft) of a cliff for cliff habitat;
and all other remaining land as upland habitat. The area of each habitat and forest structure type
was measured using GIS. The final sampling locations included eight pond sites, four stream
sites, three cliff sites, and five upland sites. Detector stations were placed as close as possible to
the primary random points. In several cases, alternative random points were chosen because of
inaccurate vegetation classifications or difficult helicopter access at primary points.
At each site, the study team positioned the detector and oriented the microphone to maximize the
probability of recording echolocation call sequences (bat passes), based on the specific site
characteristics. Data were recorded on 1-GB compact flash (CF) data cards. Detectors were
programmed to monitor the period from approximately 1 hour before sunset to 1 hour after
sunrise, adjusting the duty cycle periodically, to cover the crepuscular and nocturnal periods
when bats are most active (Hayes 1997). The sunset and sunrise times were calculated from the
United States Naval Observatory website (USNO 2013) for Talkeetna, where extensive periods
of twilight occur after sunset and before sunrise. The study team exchanged the CF cards and
checked equipment on June 3–4, 14–15, 26–27; July 16–17, 31; August 11–13, 29; and
September 10 and 24, 2013. Sampling covered the spring, summer, and fall seasons,
encompassing the periods of parturition, lactation, volancy of young, copulation, and possibly
hibernation or migration (Gotthardt and Coray 2005).
4.1.1. Variances
No variances from the acoustic survey methods described in the Study Plan were necessary in
2013. However, the Study Plan implicitly assumed that all lands in the bat study area would be
available for sampling in 2013. The lack of ground access to Cook Inlet Regional Working
Group (CIRWG) lands in the western portion of the study area prevented acoustic sampling in
some areas that would otherwise have been included in the random allocation of sampling points.
The study team plans to meet study objectives by sampling on CIRWG lands during the next
study season, if available.
4.2. Roost Surveys
AEA implemented the methods for natural and artificial roosts described in the Study Plan with
the exception of the variances explained below (Section 4.2.3).
4.2.1. Natural Roosts
The research team used a variety of literature-based and field methods to assess the occurrence
of natural structures (caves, cliffs, trees) and their suitability as roost sites, maternity colonies, or
hibernacula in the study area. The potential occurrence of caves in the study area was assessed
by reviewing geological literature regarding the presence of suitable bedrock (e.g., limestone)
conducive to the formation of caves.
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FERC Project No. 14241 Page 4 February 2014 Draft
During June 28–30, 2013, the survey team conducted an aerial survey by helicopter to examine
potential roosting habitats in cliffs and other rock structures. The team evaluated discrete cliff
sections that had been identified for Study 10.14, Surveys of Eagles and Other Raptors, by using
GIS analysis of aerial photography, digital elevation models, and remote-sensing data on plant
biomass (Normalized Difference Vegetation Index, or NDVI). Qualitative suitability scores
(Table 4.2-1) were assigned to each cliff section in the field. Where possible, cliff habitats were
examined from the ground.
Ground searches of potentially suitable tree roosts (large-diameter snags) also were conducted
during June 28–30, 2013. The tree-roost search targeted areas near inactive nests of Bald Eagles
(Haliaeetus leucocephalus) in the study area and opportunistically surveyed other possible roost
trees identified in the field. Forest inventory information was not available to assess the presence
of large-diameter dead trees as roosting habitat.
In the fall (October 4–6, 2013), additional areas were surveyed for tree roosts, including areas
near previously active Bald Eagle nests that were not accessible earlier in the season. The area
between Jay Creek and Watana Creek was surveyed to search for the potential presence of caves
in a limestone formation reported by Chapin (1918).
4.2.2. Artificial Roosts
The research team used a combination of office-based and field methods to evaluate human-
made structures (buildings, mines, bridges) as roost sites, maternity colonies, and hibernacula in
the study area. No bridges were present in the study area, so the search concentrated on
buildings. Before beginning the search, permission was requested via letters, emails, and
telephone calls for access to building sites on private, federal, and state lands in and near the
study area. Permission was obtained for access to 11 of the 16 sites identified.
During August 11–13, 2013, the research team examined 25 structures (e.g., cabins, sheds,
outhouses) at those 11 sites for the presence of bats and any signs of use as roost sites or
maternity colonies. All structures were examined externally and some were examined internally,
but not all structures were accessible because they were locked or barricaded. The building
search was coordinated with the historical property surveys for the Cultural Resources Study (see
ISR Study 13.5). Several mining claims were identified within the bat study area; however, all of
those claims involved surface-mining methods (e.g., placer), which do not directly provide
roosting habitat, so they were not inspected if no structures were present.
During the fall roost search (October 4–6, 2013), all of the structures surveyed in mid-August
were reexamined, along with another site for which permission had not been granted previously.
The fall search was focused on potential use of the structures as hibernation sites.
Both artificial roost searches included structures (summer = 19, fall = 20), that were located
outside of, but near, the study area. Those additional structures were included because artificial
structures potentially suitable for bat roosting were scarce in the study area and permission could
not be obtained to examine all of the buildings in the study area.
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 5 February 2014 Draft
4.2.3. Variances
Access to CIRWG lands, which encompassed most of the western end of the study area, was not
possible in 2013. The lack of ground access to CIRWG lands prevented searches of potential
roosting habitat (both natural and artificial) that would otherwise have been included in the roost
surveys, resulting in a variance from the Study Plan. The research team was unable to perform
ground searches on CIRWG lands at four Bald Eagle nest trees and one limestone area near the
northern flank of Mount Watana. The research team was also unable to search two artificial
structures on CIRWG lands, both of which were located outside of the Project area. Although
the access restrictions resulted in a variance of these methods in 2013, AEA will meet study
objectives by conducting these searches on CIRWG lands in the next study season, if access to
CIRWG lands is granted.
Additionally, the study team expanded roost searches to include nearby areas outside of the study
area due to the scarcity of suitable roosting structures within the study area. This additional
search effort expanded the scope proposed in the Study Plan and constitutes a variance.
4.3. Data Management and Analysis
AEA implemented the data management and analysis methods as described in the Study Plan
with no variances.
To maintain quality assurance and quality control (QA/QC), acoustic monitoring equipment was
checked and data cards were downloaded into a database approximately every 1–2 weeks to
minimize data loss from equipment failures or other factors, such as damage by other animals.
The study lead checked the database periodically for inconsistencies and errors and the entire
database was proofed again for errors before data analysis began. All data is stored on a network
server with frequent backups to prevent loss of data.
Interpretation of bat acoustic data is subject to several important caveats. The number of “bat
passes” recorded is an index of relative activity, but may not correlate directly with numbers of
individual bats in the area being monitored (i.e., 10 bat passes may represent a single bat
recorded 10 different times or 10 different bats recorded, each with a single pass; Hayes 1997).
Activity also may not be proportional to abundance because of variability attributable to (1)
detectability (loud vs. quiet species); (2) species call rates; (3) migratory vs. foraging call rates;
and (4) attraction to or avoidance of the sampling area by bats (Kunz et al. 2007; Hayes et al.
2009). However, interpreted properly, the index of relative activity can provide useful
information on bat use by characterizing temporal (hourly, nightly, and seasonal) and spatial
(location) patterns of bat activity (Parsons and Szewczak 2009).
The echolocation sequences recorded by the detectors were analyzed using Anabat CFC Read
and AnalookW software (Corben 2011) to detect and quantify bat passes. A bat pass was defined
as a search-phase echolocation sequence of ≥2 echolocation pulses with a minimum pass
duration of 10 milliseconds (ms) within each sequence, separated by >1 second (Gannon et al.
2003). The standard metric for quantifying bat activity is the number of bat passes/detector-night
(Kunz et al. 2007). The within-night activity rates (hours relative to sunset) observed in this
study were compared with a probability distribution generated from 5,000 bootstrap simulations
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
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FERC Project No. 14241 Page 6 February 2014 Draft
(Varian 2005). For each simulation, the observed hourly activity rate was recorded randomly
within each night and a new average was calculated for each hour. Calls in May and October
were so few that they were excluded from the hours-relative-to-sunset analysis. Nonparametric
(Kruskal–Wallis) tests were used for statistical comparison of the spatial and habitat differences
among detectors. Kruskal–Wallis tests also were used to compare activity rates among stations
and months for periods when all 20 detectors were operational. Only June–September data were
used for monthly comparisons because of the short duration of sampling conducted in late May
and early October. GIS software was used to measure the minimum distances from each detector
station to seven landscape features: ponds, streams, rivers, cliffs, and cliffs with roost quality
index scores of 1, 2, and 3. Correlation between the mean number of bat passes and the minimum
distances to these landscape features was tested using Spearman’s rank correlation. SPSS version
18.0 analytical software was used for all statistical comparisons, assuming statistical significance
at α = 0.05 (SPSS 2009).
4.3.1. Variances
No variances from the data management and analysis methods described in the Study Plan
occurred in 2013.
5. RESULTS
Data developed in support of this study are available for download at
http://gis.suhydro.org/reports/isr:
• ISR_10_13_BAT_Data_ABR.gdb/ISR_10_13_BAT_Detector_Sites;
• ISR_10_13_BAT_Sonogram.jpg;
• ISR_10_13_BAT_Acoustic_Data.xlsx;
• ISR_10_13_BAT_Station_Locs.xlsx;
• ISR_10_13_BAT_Acoustic_and_Habitat.xlsx;
• ISR_10_13_BAT_Data_ABR.gdb/ISR_10_13_BAT_Habitat_Buffers;
• ISR_10_13_BAT_Data_ABR.gdb/ISR_10_13_BAT_Cliff_Habitat;
• ISR_10_13_BAT_Artificial_Roost.xlsx.
5.1. Acoustic Surveys
5.1.1. General Bat Activity
In 2013, acoustic monitoring at all 20 detector stations resulted in a total of 2,767 potential
detector-nights (number of detectors multiplied by number of nights; Table 5.1-1). Across all 20
detector stations, usable data were recorded on 2,660 detector-nights (96.1 percent). Data losses
resulted from CF card failures (G7, August 20–28; G9, May 25–June 2 and June 12–26),
flooding during breakup of river ice (G18, May 25–June 12), an electrical problem (G1, July 9–
14), and damage caused by bears (G7, September 18–October 6; G15, September 16–24; G18,
August 6–10; G19, September 20–28) and porcupines (G7, September 5–11).
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FERC Project No. 14241 Page 7 February 2014 Draft
Bat activity was detected at 17 (85 percent) of the 20 locations sampled (Figure 5.1-1). Overall,
621 bat passes were recorded during the entire sampling period. All calls were identified as
having been made by little brown bats (Myotis lucifugus) based on their acoustic characteristics
(Figure 5.1-2), which were similar to those described by Ober (2006). Activity across all stations
and seasons averaged 0.23 ± 0.04 (mean ± SE) bat passes/detector-night (Table 5.1-2).
5.1.2. Temporal Comparisons
5.1.2.1. Seasonal Activity
Bat activity varied substantially throughout the sampling period (Figure 5.1-3; Table 5.1-2).
Despite the variability in monthly activity, statistical differences were not detected among entire
months (June–September; H = 2.51; df = 3; P = 0.474), probably because of low statistical
power. Bat activity was recorded only sporadically until the end of June, then peaked in July
(0.47 ± 0.14 mean passes/detector-night; Table 5.1-2), declined in August (0.22 ± 0.04 mean
passes/detector-night), and increased again in September (0.29 ± 0.10 mean passes/detector-
night). Most stations recorded the greatest amount of activity in July (8 of 20 stations; 40
percent), followed by August (5 of 20 stations; 25 percent) and September (3 of 20 stations; 15
percent). Very little activity was detected in late May and early October (0.01 ± 0.01 mean
passes/detector-night for each). The spatial distribution of bat activity (number of stations with
any activity across the study area) by month followed a slightly different trend, with the most
widespread detections occurring in August (15 of 20 stations; 75 percent), followed by July (11
of 20 stations; 55 percent), and September (7 of 20 stations; 35 percent).
5.1.2.2. Nightly Activity
Bat activity within nights (expressed as mean number of bat passes per station per hour) varied
substantially among hours of the night during all months (Figure 5.1-4), with peak activity
generally occurring between 1 and 3 hours after sunset. No bat activity was recorded in the hour
before sunset or the hour after sunrise. In June, activity peaked 1–2 hours after sunset, when
significantly greater activity occurred (mean passes/site/hour = 0.05; P < 0.01). In July, activity
peaked 2–3 hours after sunset, with significantly less activity in the first hour after sunset (mean
passes/station/hour = 0; P < 0.05), and significantly more activity 2–3 hours after sunset (mean
passes/station/hour = 0.27; P < 0.01). In August, activity peaked 1–2 hours after sunset, when
significantly more activity occurred (mean passes/station/hour = 0.08; P < 0.01). In September,
activity peaked within 2–3 hours after sunset, with significantly more activity during that time
period (mean passes/station/hour = 0.09; P < 0.01), and significantly less activity in the middle
of the night, 4–5 hours after sunset (mean passes/station/hour = 0.002; P < 0.05) and 7–8 hours
after sunset (mean passes/station/hour = 0.002; P < 0.05).
5.1.3. Spatial Comparisons
5.1.3.1. Activity Among Stations
Bat activity differed significantly among sampling stations (H = 274.16; df = 19; P < 0.001).
Station G6 recorded the greatest total amount of activity (2.02 ± 0.54 mean passes/detector-
night), more than twice as much activity as the next most active stations (G3, 0.78 ± 0.38 mean
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passes/detector-night; G16, 0.74 ± 0.32 mean passes/detector-night; Table 5.1-2). The next three
stations in descending order of activity were G13 (0.24 ± 0.13 mean passes/detector-night), G10
(0.21 ± 0.06 mean passes/detector-night), and G19 (0.19 ± 0.05 mean passes/detector-night). No
bat activity was detected at three stations during the entire sampling period (G5, G15, G20;
Figures 5.1-1 and 5.1-4).
The elevation of detector stations above sea level ranged from 1,680 ft to 2,425 ft (Table 5.1-3).
Bat activity was not correlated with elevation (Spearman’s ρ = –0.008, P = 0.972), but bat
activity tended to peak at higher elevations later in the sampling period. Although the test
statistic for correlation of elevation with the month of peak activity did not meet the criterion for
statistical significance of α = 0.05, it was very close (Spearman’s ρ = 0.474, P = 0.054),
indicating a strong relationship.
5.1.3.2. Activity in Relation to Habitat and Forest Structure
Bat activity varied significantly among the four broad habitat types sampled (pond, stream, cliff,
and upland; H = 8.58; df = 3; P = 0.035). Detector stations in stream habitats recorded the
greatest level of activity (0.59 ± 0.16 mean passes/detector-night; Table 5.1-4), followed by pond
habitats (0.24 ± 0.07 mean passes/detector-night), cliff habitats (0.15 ± 0.05 mean
passes/detector-night), and upland habitats (0.004 ± 0.003 mean passes/detector-night). Bat
activity at both stream and cliff sites peaked in July, whereas activity at pond sites peaked in
September (Figure 5.1-6).
Bat activity did not differ among the four types of forest structure sampled (open, closed, dwarf,
and shrub; H = 5.00; df = 3; P = 0.175). Detector stations in closed forest-structure types
recorded the greatest level of activity (0.77 ± 0.19 mean passes/detector-night; Table 5.1-5),
followed by shrub (0.08 ± 0.02 mean passes/detector-night), open (0.03 ± 0.01 mean
passes/detector-night), and dwarf (0.002 ± 0.002 mean passes/detector-night). Activity levels in
the closed and shrub types peaked in July, whereas activity in open forests remained consistently
low during the entire study (Figure 5.1-7).
The bat study area totaled 33,280 acres (Table 5.1-6). Stratified according to the broad habitat
types sampled, the study area comprised these proportions: Upland = 65.8 percent; Cliff = 22.9
percent; Stream = 8.2 percent; and Pond = 3.1 percent (Figure 5.1-8). Stratified by forest-
structure type, the non-water-body portion of the study area comprised these proportions: Open =
44.5 percent; Closed = 19.5 percent; Shrub = 15.1 percent; and Dwarf = 5.8 percent (Figure 5.1-
9).
None of the minimum distances measured to the seven landscape features (ponds, perennial
streams, rivers, any cliff, and cliff-roost quality scores of 1, 2, and 3; Table 5.1-3) were
significantly correlated with mean bat passes per detector-night (Spearman’s ρ; P> 0.05).
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5.2. Roost Surveys
5.2.1. Natural Roosts
The 102 discrete cliff sections identified before the field season as potential cliff-roosting habitat
were categorized into four groups during the June 28–30 aerial survey: four sections were not
suitable, 49 sections were of low suitability (quality score = 1), 33 sections were of moderate
suitability (quality score = 2), and 16 sections were of high suitability (quality score = 3) (Table
4.2-1; Figure 5.2-1). Besides cliffs, four areas near Bald Eagle nests were examined for large-
diameter snags suitable for use by roosting bats. Project researchers searched for natural caves in
a limestone formation reported by Chapin (1918) between Jay Creek and Watana Creek, but no
caves were found. Despite the widespread presence of bats revealed by acoustic monitoring, the
study team was not successful in locating any roosting locations, maternity colonies, or
hibernacula in natural sites during the surveys in 2013.
5.2.2. Artificial Roosts
The study team obtained permission for access to 10 sites during the August roost search and to
11 sites during the October search, but was unable to secure permission to visit five other sites of
interest (Table 5.2-1; Figure 5.2-2). The study team obtained permission for access to 11 of the
16 sites of interest, including the two sites within the study area (RS 04 and RS 09; Table 5.2-1).
During August 11–13, 2013, the team investigated 25 structures (e.g., cabins, sheds, outhouses)
at 10 sites for the presence of bats and any sign of use as roost sites or maternity colonies. During
October 4–6, 2013, the team searched the same sites and structures as in August, plus one
additional site and structure (RS 16; Table 5.2-1) for the presence of bats and any signs of use as
hibernacula. Of the 26 structures surveyed, 15 were considered to be suitable for roosting by
bats; however, no roosting bats or sign of roosting bats were found at any of the sites or within
any of the structures during either survey. Two of the 16 sites visited were located within the bat
study area (Table 5.2-1). The potential pool of candidate sites was expanded outside the study
area because of the rarity of suitable structures in the study area. Despite the widespread
presence of bats revealed through acoustic monitoring, no roosting locations, maternity colonies,
or hibernacula were located in artificial sites during the surveys in 2013.
6. DISCUSSION
The ecology of bats in Alaska remains largely unknown, especially in the Interior (Parker et al.
1997, AKNHP 2013). Bats were not included in the APA Project studies in the 1980s, so data on
the occurrence of bats in the upper Susitna River drainage were lacking and their status in the
Project area was essentially unknown at the time this study began. Kessel et al. (1982) reported a
single observation of a bat during their bird and mammal surveys in the early 1980s.
6.1. Acoustic Monitoring
Activity of little brown bats was widespread across the study area, occurring from the western
end of the Dam and Camp Facilities Area almost all the way to Goose Creek near the eastern
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edge of the proposed reservoir inundation zone. Only three of the 20 detector stations in the
study area did not record any bat activity between late May and early October 2013.
The overall activity rates found in this study would be considered low for locations outside of
Alaska (compared to the Lower 48 states) and no other studies are available for comparison in
Interior Alaska. Parker et al. (1996) documented highly variable acoustic rates (average calls per
night) of bat activity in riparian (81.0), old-growth (6.0), clearcut (2.0) and second-growth (0.03)
habitats in Southeast Alaska. Those rates are difficult to compare with the data from this study
because of timing differences (their study monitored during June–August), the presence of four
additional species in their study, and habitat differences between Southeast Alaska and the study
area.
Similarly, Lausen (2006) conducted acoustic monitoring in the Northwest Territories, Canada,
but those rates also are difficult to compare with this study because Lausen only sampled during
the peak of bat activity for 22 total days in July and August; four additional species were present
in that study area; and the study design and objectives of that study differed from this study.
Nevertheless, an approximate mean of 20 bat passes per detector- night over the duration of that
study was derived from their data (Table 6 in Lausen 2006). Assuming that each of the five
species in Lausen’s study was equally represented, the activity rates in that study would be
similar to the most active station in this study.
Slough and Jung (2008) conducted extensive bat research, including acoustic monitoring, over a
12-year period in the Yukon, Canada. The acoustic activity they documented included three
additional species and they only reported total bat passes from sporadic, single-night surveys (not
including nights with zero detections). Similar to this study, they found tremendous variability
among detector sites, with up to 454 total bat passes in a single night (Table 2 in Slough and
Jung 2008). The greatest total activity from a single station in a single night in this study was 63
bat passes, recorded at station G6.
6.1.1. Temporal Comparisons
6.1.1.1. Seasonal Activity
Bats were detected during every month of this study, from late May to early October. Parker et
al. (1997) observed a similar pattern in bat activity near Fairbanks and suggested that bats in
Interior Alaska may not travel far to hibernate. Substantial variability was evident in the monthly
activity rates in this study, but those differences were not statistically significant, probably
because of low statistical power. More stations peaked in July than in any other month and
overall bat activity in that month was roughly twice the activity detected in August and 1.5 times
the activity in September. The periodic pulses of bat activity in June suggested that, although
bats were present, foraging conditions may not have been favorable until late June or July. Insect
prey would have to be abundant during the few dark hours available for foraging in June or else
the animals would be forced to save energy by remaining in torpor. Alternatively, the lack of
consistent activity until late June and July may reflect the arrival of migrant bats.
From July to August, bat activity decreased by more than half before increasing again near the
end of September. McGuire et al. (2009) documented hyperphagia (greatly increased feeding)
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that occurred in early August during prehibernation swarming to build energy stores for
reproduction and hibernation at a site in southern Canada (45 degrees North latitude). The
difference in latitude may account for an earlier onset of increased activity in the Bat Study Area
(62 degrees North latitude) in July. It is also possible that the increased activity in July was
related to the compressed period of darkness available for foraging, forcing bats to search for and
consume prey constantly and efficiently. The pulse of activity near the end of September may
indicate prehibernation behavior, premigratory behavior, or migrating bats moving through the
study area.
Activity at four of the bat stations peaked in September, including station G3, which also
recorded bat activity in October. Those four stations were also among the higher elevation sites,
ranging from 240 ft to 562 ft higher than the lowest site. Although this difference in elevation
may not seem great, the effect of elevation on bat distribution is more pronounced at high-
latitude locations such as Alaska (Parker et al. 1997). Mean activity rates tended to peak later in
the year at higher elevation sites. Although not significant in a strictly statistical sense, the
difference may be biologically significant. Bats may have been active at higher elevation sites
later in the year to take advantage of cooler temperatures to maximize energy savings during
torpor or simply to follow the availability of insect prey.
6.1.1.2. Nightly Activity
Bat activity was recorded between sunset and sunrise. Most of the activity likely occurred during
periods of low light or darkness, but the study team did not specifically measure the amount of
light and the calculation of sunset time did not account for topography. Some bat activity was
detected within the first hour after sunset during relatively bright periods, as has been observed at
more northerly latitudes in Alaska (Parker et al. 1997). The majority of bat activity observed in
this study occurred within 2–4 hours after sunset, likely the darkest hours of the night, for most
months (June – August). The limited data recorded in June, when the fewest hours of darkness
were available, suggested that bats were most active 1–2 hours after sunset, when darkness can
minimize predation risk from avian species (Rydell and Speakman 1995) and reduce competition
from avian competitors (Speakman et al. 2000). Significantly fewer bat calls were detected in the
first hour after sunset in July, also suggesting an avoidance of foraging during times during
relatively light periods. With increasing hours available for foraging in September, a bimodal
distribution (two peaks) in the pattern of activity became evident, which also has been
documented in other studies (Kunz 1973, Erkert 1982, Taylor and O’Neil 1988, Maier 1992,
Hayes1997).
6.1.2. Spatial Comparisons
6.1.2.1. Activity Among Stations
Bat activity recorded among stations varied considerably. Station G6 recorded three times more
activity than the station with the next greatest activity (G3). This station (G6) was located
adjacent to a pool of slow-moving water in an unnamed stream course between Deadman and
Watana creeks, which appeared to provide excellent foraging opportunities. In addition, Station
G6 was located less than 1,500 ft upstream from a “highly suitable” section of cliff. Some of the
metrics generated from this study were certainly affected by the large number of bat calls
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recorded at this site, but this single station did not exert undue influence on the overall trends
observed across all 17 detector stations at which bats were detected, except in the habitat and
forest structure analyses. The results of those analyses appeared to be driven by station G6, due
to the small sample size (n = 20; df = 3).
6.1.2.2. Activity in Relation to Habitat and Forest Structure
The greatest amount of bat activity in this study occurred in habitat types associated with water
(streams and ponds). Similarly, Slough and Jung (2008) documented the highest activity in
riparian and lacustrine habitats in the Yukon. This result is expected because riparian habitats are
known to provide important foraging and drinking areas for insectivorous bats (Grindal et al.
1999). It is likely that cliff habitats provide the major source of roosting opportunities in the
study area, due to the paucity of other roost structures (caves, trees, human-made structures).
Detectors located in and near cliff habitats recorded an intermediate level of bat activity, while
detectors located in upland habitat types recorded the least amount of bat activity among habitat
types. In view of the apparent lack of suitable roost trees, upland habitats probably do not
provide many resources needed by bats.
The mean activity levels of bats detected among the habitat types sampled in this study were
inversely proportional to their extent on the landscape. Pond and stream habitats composed only
11.3 percent of the total study area acreage, but represented 84.3 percent of all recorded bat
activity. Most of the remaining activity (15.2 percent) occurred in cliff habitats, which
constituted 22.9 percent of the study area acreage.
The mean activity rates of the little brown bats detected in this study were not influenced
significantly by forest structure type. Little brown bats are considered to be foraging generalists
because they have the ability to glean insects from slow-moving water, to fly at intermediate
speeds through forested habitats, and also to employ aerial pursuit (Adams 2003). Studies of
little brown bats and morphologically and ecologically similar species have produced mixed
results when evaluating the effect of habitat structural complexity (i.e., clutter) on bat activity.
Brigham et al. (1997) reported lower bat activity rates in highly cluttered habitats, whereas Jung
et al. (2012) found increased bat activity in more structurally heterogeneous (i.e., more cluttered)
environments and Brigham and Sleep (2003) reported no significant relationship between bat
activity and clutter. In this study, bats were most active in the closed forest structure type, which
was the most complex or cluttered habitat. The rate in that forest structure type was driven
largely by the single station that recorded the most bat activity during the entire study (G6).
Dwarf forest provided few resources needed by bats within the study area, judging from the
lowest activity rate recorded among all habitat and forest structure types. Despite the high
acreage of the open forest structure type (44.5 percent) in the study area, detectors located in
open forests recorded only 3.4 percent of the overall bat activity.
6.2. Roost Surveys
6.2.1. Natural Roosts
The most likely natural roosting habitats available in the bat study area are the cracks and
crevices in the extensive cliffs along the Susitna River. Almost half (48 percent) of the 102 cliff
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sections mapped along the Susitna River and its major tributaries in the study area were
classified as moderately or highly suitable roosting habitat. Little brown bats are widely known
to use rock crevices as day roosts (Barbour and Davis 1969; Adams 2003; Lausen and Barclay
2006; Foresman 2012) in the Lower 48 states. A study of bats in the Yukon documented only a
few natural roosts in trees or rock crevices, including a rock crack in Miles Canyon on the Yukon
River near Whitehorse, which served as a maternity colony for little brown bats; rock crevices
above Pine Lake; and behind the exfoliating bark of a fire-killed white spruce (Picea glauca)
(Slough and Jung 2008). Few trees were found in the bat study area in 2013 that were considered
to provide suitable roosting habitat and no bats were found roosting behind the bark of those
trees.
In addition to cliffs and trees, the study team searched for limestone formations in and near the
study area in an attempt to locate caves, but none were found. The available sources of geologic
data for the study area contained conflicting information about the presence of limestone, which
has not been resolved at this writing. The preliminary geologic map being produced for the
Project (see ISR Study 4.5, Geology and Soils Study) may provide new insights regarding
potential cave locations (M. Bruen, Geology and Soils Study Lead, personal communication).
6.2.2. Artificial Roosts
The structures searched in and near the bat study area included buildings associated with
seasonal mining or hunting camps, old trapper cabins from the 1930s, and modern, well-
maintained cabins. Although more than half (58 percent) of the structures examined were
considered to have potential as roost sites, no bats or bat sign were found at any of the structures.
Several owners of cabins above tree-line (at Clarence Lake) stated that they had never seen bats
at their cabins in the decades they have owned those properties. While it is possible that bats
escaped detection during the artificial roost searches in this study, nearly all structures were
surveyed twice. Hence, given the paucity of buildings in the bat study area and their apparent
lack of use as roosts, it is probable that bats are using natural roost sites in the study area.
Most roost sites documented in the Yukon by Slough and Jung (2008) were maternity colonies in
buildings and the vast majority of roosts reported to the Alaska Department of Fish and Game
(ADF&G) in Southcentral Alaska have been in buildings (D. Tessler, ADF&G, personal
communication). Because of the much greater likelihood of detecting bats in structures visited
frequently by humans, however, it is difficult to evaluate the proportional use of artificial roosts
in relation to natural roosts.
7. COMPLETING THE STUDY
[As explained in the cover letter to this draft ISR, AEA’s plan for completing this study will be
included in the final ISR filed with FERC on June 3, 2014.]
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8. LITERATURE CITED
Adams, R. A. 2003. Bats of Rocky Mountain Ecosystems. In Bats of the Rocky Mountain West:
natural history, ecology, and conservation. University Press of Colorado, Boulder, CO.
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Project FERC Project No. 14241. December 2012. Prepared for the Federal Energy
Regulatory Commission by the Alaska Energy Authority, Anchorage, Alaska.
http://www.susitna-watanahydro.org/study-plan.
AKNHP (Alaska Natural Heritage Program). 2013. Alaska bat monitoring project. Available
online: http://aknhp.uaa.alaska.edu/zoology/citizen-science/alaska-bat-project/ (accessed
November 2013).
Barbour, R. W., and W. H. Davis. 1969. Bats of America. The University of Kentucky Press.
Lexington.
Brigham, R. M., S. D. Grindal, M. C. Firman, and J. L. Morrisette. 1997. The influence of
structural clutter on activity patterns of insectivorous bats. Canadian Journal of Zoology
75: 131–136.
Chapin, T. 1918. The Nelchina–Susitna region. U.S. Geological Survey Bulletin 668,
Washington, DC. 67 pp. + map appendices.
Corben, C. 2011. Anabat system software. Available online at http://users.lmi.net/corben/
anabat.htm#Anabat Contents (accessed March 2012).
Crampton, L. H., and R. M. R. Barclay. 1998. Selection of roosting and foraging habitat by bats
in different-aged aspen mixed-wood stands. Conservation Biology 12:1347–1358.
Erkert, H. G. 1982. Ecological aspects of bat activity rhythms. In T. H. Kunz, editor. Ecology of
bats. Plenum Publishing Corporation, New York, NY.
Foresman, K. R. 2012. Mammals of Montana. Mountain Press Publishing Company. Missoula.
Gannon, W. L., R. E. Sherwin, and S. Haymond. 2003. On the importance of articulating
assumptions when conducting acoustic studies of bats. Wildlife Society Bulletin 31: 45–
61.
Gotthardt, T.A., and C.A. Coray. 2005. Little brown bat. Alaska Natural Heritage Program,
Anchorage. Available online : http://www.adfg.alaska.gov/static/species/speciesinfo/
_aknhp/Little_brown_bat_2008.pdf(accessed September 2013).
Grindal, S. D., J. L. Morissett e, and R. M. Brigham. 1999. Concentration of bat activity in
riparian habitats over an elevational gradient. Canadian Journal of Zoology 77: 972–977.
Hayes, J. P. 1997. Temporal variation in activity of bats and the design of echolocation-
monitoring studies. Journal of Mammalogy 78: 514–524.
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Hayes, J. P., H. K. Ober, and R. E. Sherwin. 2009. Survey and monitoring of bats. In T. H. Kunz
and S. Parsons (eds.),Ecological and Behavioral Methods for the Study of Bats. Second
edition. Johns Hopkins University Press, Baltimore, MD.
Jung, K., S. Kaiser, S. Bohm, J. Nieschulze, and E. K. V. Kalko. 2012. Moving in three
dimensions: effects of structural complexity on occurrence and activity of insectivorous
bats in managed forest stands. Journal of Applied Ecology 49: 523–531.
Kessel, B., S. O. MacDonald, D. D. Gibson, B. A. Cooper, and B. A. Anderson. 1982. Susitna
Hydroelectric Project environmental studies, Phase I final report—Subtask 7.11: Birds
and non-game mammals. Report prepared by University of Alaska Museum, Fairbanks,
and Terrestrial Environmental Specialists, Inc., Phoenix, NY, for Alaska Power
Authority, Anchorage. 149 pp.
Kreig and Associates. 1987. Susitna Hydroelectric Project, vegetation mapping final report and
user guide. Report prepared by Ray A. Kreig and Associates, Inc., Anchorage, for Harza–
Ebasco Susitna Joint Venture, Anchorage. 92 pp. [APA Doc. No. 3509]
Kunz, T. H. 1973. Resource utilization: temporal and spatial components of bat activity in
central Iowa. Journal of Mammalogy 54: 14–32.
Kunz, T. H., E. B. Arnett, B. A. Cooper, W. P. Erickson, R. P. Larkin, T. J. Mabee, M. L.
Morrison, M. D. Strickland, and J. M. Szewczak. 2007. Assessing impacts of wind-
energy development on nocturnally active birds and bats: A guidance document. Journal
of Wildlife Management 71: 2449–2486.
Lausen, C. 2006. Bat survey of Nahanni National Park Reserve and surrounding areas,
Northwest Territories. Unpublished report prepared for Parks Canada, Nahanni National
Park Reserve; and Canadian Parks and Wilderness Society, NWT Chapter. Available
online: http://cpawsnwt.org/uploads/Bat_SurveyReport_Lausen_26NovemberFINAL.pdf
(accessed November 2013).
Lausen, C. L., and R. M. R. Barclay. 2006. Winter bat activity in the Canadian prairies.
Canadian Journal of Zoology 84:1079–1086.
Maier, C. 1992. Activity patterns of pipistrelle bats (Pipistrellus pipistrellus) in Oxfordshire.
Journal of Zoology (London) 228:69–80.
McGuire, L. P., and C. G. Guglielmo. 2009. Effect of age on energy storage during
prehibernation swarming in little brown bat (Myotis lucifugus). Canadian Journal of
Zoology 87:515–519.
Ober, H. K. 2007. Functional relationships among vegetation, nocturnal insects, and bats in
riparian areas of the Oregon Coast Range. Ph.D. dissertation, Oregon State University,
Corvallis.
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bats using the Anabat detector. Journal of Mammalogy 80: 1–23.
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Parker, D. I., J. A. Cook, and S. W. Lewis. 1996. Effects of timber harvest on bat activity in
southeastern Alaska’s temperate rain forests. Paper presented at the Bats and Forests
Symposium, October 19–21, 1996, Victoria, British Columbia, Canada.
Parker, D. I., B. E. Lawhead, and J. A. Cook. 1997. Distributional limits of bats in Alaska. Arctic
50: 256–265.
Parsons, S., and J. M. Szewczak. 2009. Recording and analyzing the vocalizations of bats. In T.
H. Kunz and S. Parsons, editors. Ecological and Behavioral Methods for the Study of
Bats. Second edition. Johns Hopkins University Press, Baltimore, MD.
Rydell, J., and Speakman, J.R. 1995. Evolution of nocturnality in bats: Potential competitors and
predators during their early history. Biological Journal of the Linnean Society 54: 183–
191.
Slough, B. G., and T. S. Jung. 2008. Observations on the natural history of bats in the Yukon.
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article/viewFile/114/59 (accessed November 2013).
Speakman, J. R., J. Rydell, P. I. Webb, J. P. Hayes, G. C. Hays, I. A. R. Hulbert, and R. M.
McDevitt. 2000. Activity patterns of insectivorous bats and birds in northern Scandinavia
(69 degrees N), during continuous midsummer daylight. Oikos 88: 75–86.
SPSS. 2009. SPSS for Windows, version 18.0. SPSS, Inc., Chicago, IL.
Taylor, R. J., and M. G. O’Neill. 1988. Summer activity patterns of insectivorous bats and their
prey in Tasmania. Australian Wildlife Research 15: 533–539.
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9. TABLES
Table 4.1-1. Categorization of Acoustic Detector Stations by Habitat and Forest Structure Types, 2013.
Station Habitat Type Forest Structure Type
G1 Pond –
G2 Pond –
G3 Pond –
G4 Pond –
G5 Upland Shrub
G6 Stream Closed
G7 Pond –
G8 Upland Dwarf
G9 Stream Open
G10 Pond –
G11 Upland Open
G12 Pond –
G13 Cliff Closed
G14 Cliff Open
G15 Upland Dwarf
G16 Pond –
G17 Upland Closed
G18 Stream Shrub
G19 Cliff Shrub
G20 Stream Dwarf
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Table 4.2-1.Quality Scores for Potential Cliff-Roosting Habitat.
Quality Score Description
Number (%) of Cliff Sections Identified in Study Area
0 Not suitable: no potential for bat roosts; e.g., unvegetated mud slope
with no holes, cracks, or crevices.
4 (3.9%)
1
Low suitability: no or few vertical and/or horizontal cracks or
crevices, shallow cracks approximately <2 cm deep1, vegetation
may block access.
49 (48.0%)
2
Moderate suitability: moderate number of vertical and/or horizontal
cracks or crevices present, cracks approximately 2 cm–0.5 m deep,
no vegetation blocking access.
33 (32.4%)
3
High suitability: large numbers of vertical and/or horizontal cracks or
crevices present, cracks >0.5 m deep, no vegetation blocking
access.
16 (15.7%)
Notes:
1. Similar size requirement for roost site in trees from Crampton and Barclay (1998).
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 19 February 2014 Draft
Table 5.1-2. Number and Percentage of Nights Surveyed by Acoustic Detector Stations in 2013.
Station
Number of Nights in Sampling Period
Number of Nights Actually Surveyed
Percentage of Nights Surveyed
G1 139 133 95.7
G2 139 139 100
G3 139 139 100
G4 139 139 100
G5 139 139 100
G6 142 142 100
G7 136 101 74.3
G8 140 140 100
G9 137 113 82.5
G10 140 140 100
G11 138 138 100
G12 140 140 100
G13 140 140 100
G14 139 139 100
G15 140 131 93.6
G16 136 136 100
G17 136 136 100
G18 136 112 82.4
G19 136 127 93.4
G20 136 136 100
Total 2,767 2,660 96.1
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (STUDY 10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 20 February 2014
Table 5.1-2. Bat Activity (Bat Passes per Detector-Night) by Station and Month, 2013.
May June July August September October Total
Station 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3
G1 0 – 11 0 – 30 0 – 25 0.10 0.07 31 0 – 30 0 – 6 0.02 0.02 133
G2 0 – 11 0 – 30 0 – 31 0.03 0.03 31 0 – 30 0 – 6 0.01 0.01 139
G3 0 – 11 0 – 30 0.03 0.03 31 0.10 0.05 31 3.43 1.68 30 0.17 0.17 6 0.78 0.38 139
G4 0 – 11 0 – 30 0 – 31 0.19 0.11 31 0 – 30 0 – 6 0.04 0.02 139
G5 0 – 11 0 – 30 0 – 31 0 – 31 0 – 30 0 – 6 0 – 139
G6 0 – 11 0.20 0.14 30 5.84 2.23 31 2.23 0.72 31 1.03 0.36 30 0 – 9 2.02 0.54 142
G7 0 – 8 0 – 30 0.23 0.09 31 0.05 0.05 22 0 – 10 – – 0 0.08 0.03 101
G8 0 – 10 0 – 30 0 – 31 0 – 31 0.03 0.03 30 0 – 8 0.01 0.01 140
G9 – – 0 0 – 13 0.10 0.07 31 0.03 0.03 31 0 – 30 0 – 8 0.04 0.02 113
G10 0 – 10 0 – 30 0.03 0.03 31 0.26 0.13 31 0.67 0.23 30 0 – 8 0.21 0.06 140
G11 0 – 10 0 – 30 0 – 31 0.03 0.03 31 0 – 30 0 – 6 0.01 0.01 138
G12 0 – 10 0 – 30 0.13 0.08 31 0 – 31 0.03 0.03 30 0 – 8 0.04 0.02 140
G13 0 – 10 0.03 0.03 30 0.71 0.55 31 0.32 0.13 31 0 – 30 0 – 8 0.24 0.13 140
G14 0 – 9 0 – 30 0.03 0.03 31 0.06 0.04 31 0.07 0.07 30 0 – 8 0.04 0.02 139
G15 0 – 10 0 – 30 0 – 31 0 – 31 0 – 21 0 – 8 0 – 131
G16 0.11 0.11 9 0.83 0.64 30 1.55 1.25 31 0.65 0.20 31 0.20 0.12 30 0 – 5 0.74 0.32 136
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FERC Project No. 14241 Page 21 February 2014
May June July August September October Total
Station 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3
G17 0 – 9 0 – 30 0 – 31 0.03 0.03 31 0 – 30 0 – 5 0.01 0.01 136
G18 0 – 2 0.06 0.06 18 0.10 0.05 31 0.04 0.04 26 0 – 30 0 – 5 0.04 0.02 112
G19 0 – 9 0 – 30 0.48 0.13 31 0.29 0.14 31 0 – 21 0 – 5 0.19 0.05 127
G20 0 – 9 0 – 30 0 – 31 0 – 31 0 – 30 0 – 5 0 – 136
Total 0.01 0.01 181 0.06 0.03 571 0.47 0.14 614 0.22 0.04 606 0.29 0.10 562 0.01 0.01 126 0.23 0.04 2,660
Notes:
1. 𝑥̅ = Mean bat activity
2. SE = Standard error of mean
3. n = Number of detector-nights used in analysis
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 22 February 2014
Table 5.1-3. Elevation and Minimum Distances to Water Bodies and Cliffs, by Station, 2013.
Minimum Distance (ft)
Station Elevation
(ft) Pond Stream1 River
Cliff Quality Score > 0
Cliff Quality Score = 12
Cliff Quality Score = 23
Cliff Quality Score = 34
G1 2,362 0 1,086 2,408 6,724 9,988 6,724 7,629
G2 2,425 97 3,478 3,487 10,384 13,065 10,384 10,655
G3 2,242 140 1,589 3,568 8,961 12,198 8,961 10,364
G4 2,230 31 1,856 3,170 1,676 8,460 1,676 8,777
G5 2,388 1,477 4,004 7,432 3,506 5,787 3,506 3,517
G6 1,829 2,899 12 5,906 1,417 1,417 7,380 6,910
G7 2,047 441 1,657 4,447 2,309 2,309 7,874 7,787
G8 2,042 4,651 1,519 10,663 5,694 5,694 18,765 10,108
G9 1,869 3,010 2 21,533 4,715 7,468 4,715 21,353
G10 2,031 0 3,542 3,276 2,903 2,903 10,371 8,622
G11 1,748 7,334 685 293 1,931 1,931 4,025 4,113
G12 1,795 20 928 1,490 626 626 668 2,416
G13 1,680 6,523 1,688 210 603 3,231 603 7,594
G14 1,920 3,072 141 10,406 103 1,083 103 13,275
G15 1,711 8,790 1,069 618 1,560 1,560 4,477 2,792
G16 1,751 33 232 724 5,267 5,267 6,112 17,729
G17 1,827 8,405 4,131 740 4,882 4,882 6,468 24,487
G18 1,876 2,501 475 50 472 12,392 1,596 472
G19 1,968 9,331 72 131 336 25,377 14,501 336
G20 1,716 7,749 2,452 811 1,452 1,452 6,233 2,146
Notes:
1. Perennial Stream.
2. Cliff Quality Score 1 = “Low Suitability.”
3. Cliff Quality Score 2 = “Moderate Suitability.”
4. Cliff Quality Score 3 = “High Suitability.”
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 23 February 2014
Table 5.1-4. Bat Activity (Bat Passes per Detector-Night) by Month and Habitat Type, 2013.
Pond Stream Cliff Upland Total
Month 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3
May 0.01 0.01 81 0 – 22 0 – 28 0 – 50 0.01 0.01 181
June 0.10 0.08 240 0.08 0.05 91 0.01 0.01 90 0 – 150 0.06 0.03 571
July 0.25 0.16 242 1.51 0.59 124 0.41 0.19 93 0 – 155 0.47 0.14 614
August 0.18 0.04 239 0.60 0.21 119 0.23 0.07 93 0.01 0.01 155 0.22 0.04 606
September 0.59 0.24 220 0.26 0.10 120 0.02 0.02 81 0.01 0.01 141 0.29 0.10 562
October 0.02 0.02 45 0 – 27 0 – 21 0 – 33 0.01 0.01 126
Total 0.24 0.07 1,067 0.59 0.16 503 0.15 0.05 406 0.004 0.003 684 0.23 0.04 2,660
Notes:
1. 𝑥̅ = Mean bat activity
2. SE = Standard error of mean
3. n = Number of detector-nights used in analysis
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 24 February 2014
Table 5.1-5. Bat Activity (Bat Passes per Detector-Night) by Month and Forest Structure Type for Non-Pond Habitats,
2013.
Open Closed Dwarf Shrub Total
Month 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3 𝒙�1 SE2 n3
May 0 – 19 0 – 30 0 – 29 0 – 22 0 – 100
June 0 – 73 0.08 0.05 90 0 – 90 0.01 0.01 78 0.02 0.01 331
July 0.04 0.03 93 2.18 0.80 93 0 – 93 0.19 0.05 93 0.60 0.21 372
August 0.04 0.02 93 0.86 0.26 93 0 – 93 0.11 0.05 88 0.26 0.07 367
September 0.02 0.02 90 0.34 0.13 90 0.01 0.01 81 0 – 81 0.10 0.04 342
October 0 – 22 0 – 22 0 – 21 0 – 16 0 – 81
Total 0.03 0.01 390 0.77 0.19 418 0.002 0.002 407 0.08 0.02 378 0.23 0.05 1,593
Notes:
1. 𝑥̅ = Mean bat activity
2. SE = Standard error of mean
3. n = Number of detector-nights used in analysis
Table 5.1-6. Acreage of Habitat and Forest Structure Types in Bat Study Area, 2013.
Habitat Type
Forest Structure
Type Pond Stream Cliff Upland Total
Closed 9 622 2,212 3,647 6,490
Open 309 1,531 2,727 10,254 14,821
Dwarf 3 90 421 1,426 1,940
Shrub 432 269 273 4,067 5,041
Water 267 135 1,966 2,175 4,543
Unclassified 3 87 13 342 445
Total 1,023 2,734 7,612 21,911 33,280
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 25 February 2014 Draft
Table 5.2-1. Results of Building Searches for Artificial-Roost Surveys, 2013.
Site ID Number of Structures Searched Number of Structures with Roost Potential Bat Sign Observed?
RS 011 – – –
RS 02 1 0 No
RS 03 1 0 No
RS 042 1 0 No
RS 051 – – –
RS 061 – – –
RS 07 1 0 No
RS 08 1 1 No
RS 092 5 4 No
RS 10 4 2 No
RS 111 – – –
RS 12 5 4 No
RS 13 5 3 No
RS 14 1 0 No
RS 151 – – –
RS 163 1 1 No
Total 26 15
Notes:
1. Access permission not received.
2. Within Bat Study Area.
3. Searched in fall only.
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 26 February 2014 Draft
10. FIGURES
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
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FERC Project No. 14241 Page 27 February 2014 Draft
Figure 3-1. Bat Study Area for the Susitna–Watana Hydroelectric Project, 2013.
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
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FERC Project No. 14241 Page 28 February 2014 Draft
Figure 4.1-1. Acoustic Detector Sites Monitored for the Bat Study in 2013.
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
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FERC Project No. 14241 Page 29 February 2014 Draft
Figure 5.1-1. Distribution of Bat Activity Among Acoustic Detector Stations, 2013.
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
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FERC Project No. 14241 Page 30 February 2014 Draft
Figure 5.1-2. Representative Sonogram from Little Brown Bat Recorded during Current Study, 2013.
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
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FERC Project No. 14241 Page 31 February 2014 Draft
Figure 5.1-3. Bat Activity by Date, 2013 (error bars indicate SE).
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
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FERC Project No. 14241 Page 32 February 2014 Draft
Figure 5.1-4. Bat Activity by Hour in Relation to Sunset, 2013 (error bars indicate SE).
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 33 February 2014 Draft
Figure 5.1-5. Bat Activity by Station in 2013 (error bars indicate SE; asterisks indicate that no bats were
detected).
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 34 February 2014 Draft
Figure 5.1-6. Bat Activity by Month and Habitat Type, 2013 (error bars indicate SE).
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 35 February 2014 Draft
Figure 5.1-7. Bat Activity by Month and Forest Structure Type for Non-Pond Habitats, 2013 (error bars
indicate SE).
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 36 February 2014 Draft
Figure 5.1-8. Distribution of Habitat Types in Bat Study Area, in Relation to Acoustic Detector Sites, 2013.
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 37 February 2014 Draft
Figure 5.1- 9. Distribution of Forest Structure Types in Bat Study Area, in Relation to Acoustic Detector Sites, 2013.
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
Susitna–Watana Hydroelectric Project Alaska Energy Authority
FERC Project No. 14241 Page 38 February 2014 Draft
Figure 5.2-1. Cliff Habitats Surveyed in Bat Study Area, in Relation to Acoustic Detector Sites, 2013.
INITIAL STUDY REPORT BAT DISTRIBUTION AND HABITAT USE (10.13)
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FERC Project No. 14241 Page 39 February 2014 Draft
Figure 5.2-2. Locations of Buildings Searched on Artificial-Roost Surveys, in Relation to Acoustic Detector Sites, 2013.