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HomeMy WebLinkAboutA Model for the Movement and Distribution of Fish in a Body of Water 1978ORNL/TM-6310 .S~5 ~t~.)>- A Model for the lViol!ement 2nd Distribution of Fish in a Body of W"ter D.L.DeAngelis ENI!IRON~iENTAL SCIENCES DIVISION Publication No.1173 _.------= !"-Y•.--lL",::r\A AAC'TIC ......_:..INFORMATION AN:.>L'"...\..';;NTER 707 Ito SUlfET • NDtClIAIl«.Nt.ioool '.,..'.' --_.._- .-.....'.'''::.'............"..' ; I''1 • I. · II I, In~I I ~ • :I ;I f ' ~ • I.i -(I''(i ." d:l~i \';"1l~I I, I,• Contract No.W-74DS-eng-26 A MODEL FOR THE MOVEMENT AND DISTRIBUTION OF FISH IN A BODY OF WATER O.L.DeAngelis ENVIRONMENTAL SCIENCES DIVISION Publication No.1173 DATE PUBLISHED -JUNE,197B ORNL/TM-631O OAK RIDGE NATIONAL LABORATORY Oak Ridge.Tennessee 37830 operated by UNION CARBIDE CORPORATION for the DEPARTMENT OF ENERGY ACKNOWLEDGEMENTS I wish to thank Dr.C. C.Coutant for his encouragement and help in this work.I also thank Drs.J.S.Suffern and R.H.Gardner,who have offered many useful criticisms.This work.was sponsored by the Division of Biological and Environmental Research,U.S.Department of Energy.under contract W-740S-eng-26 with Union Carbide Corporation. iii ABSTRACT DEANGELIS.O.L.1978.A model for the movement and distribution of fish in a body of water.ORNL/TM-6310.Oak Ridge National Laboratory,Oak Ridge.Tennessee.78 pp. A Monte Carlo mathematical model tracks the movement of fish in a body of water (e.g.,a pond or reservoir)which is represented by a two-dimensional grid.For the case of a long.narrow reservoir,depth and length along the reservoir are the logical choices for coordinate axes.In the model,it is assumed that the movement of fish is influenced by gradients of temperature and dissolved oxygen.as well as food availability and habitat preference.The fish takes one spatial "step"at a time,the direction being randomly selected,but also biased by the above factors. In trial simulations,a large number of simulated fish were allowed to distribute themselves in a hypothetical body of water. Assuming only tamperature was influencing the movements cf the fish, the resultant distributions are compared with experimental data on temperature preferences. v TABLE OF CONTENTS ACKNOWLEOGl'iNTS ABSTRACT ••• LI ST OF TABLES LIST OF FIGURES GENERAl DESCRIPTION OF THE MODEL MATHEMATICAl DESCRIPTION OF THE MODEL COMPUTER PROGRAM • • • • Part A.Input Cards . Part 8.Output . Part C.Computer program listing TRIAl SIMULATIONS ••••••• Fish movements . .. . . . Fish distribution patterns S~1t'lARY • • REFERENCES APPENDIX • vii Page iii v ix xi 4 9 16 19 24 24 2B 2B 2B 37 43 45 Table 1 2 3 LI ST OF TABLES The Program Variables . Parameter Values Used in the Example shown in Figure 7 Changes in parameter values from Table 2 relevant to the example shown in Fig.11 . 1x Page 29 34 41 LIST OF FIGURES Figure Page 1 A hypothetical reservoir.The vertical dimensioo 15 depth in meters (disproportionately scaled),and the horizontal dimension 1s length along the reservoir in kilometers,with the downstream dam at the left. Isotherms in degrees Centrigrade (solid lines)and dissolved oxygen isobars in parts per thousand (dotted lines)are sketched In.The shaded region denotes high food ava i lab i 1ity.A power p hnt is assumed loeated at the upstream end of the reservoir.. . . . . . . . . . 5 2 The point (iii)in a grid of points,w'th the adjacent points to which the fish can move in one step.. . . . 7 3 A grid of points representing a portion of the reservoir. The shaded circles are water,while the open circles are above the water surface.The shaded circles surrounded by larger circles represent points along the preferred tempera- ture isotherm.. • • • . • . . • • . . . . . . . . . . . • • 8 4 A plot of food availability to fish in a hypothetical reservoir.The peaks and plateaus represent the regions of high food availability.• • . . • • • . . . . . ...18 5 Input data for a sample trial simulation as it appe~rs on the data cards . . . . . . . . . . . • ...20 6 Input data for a sample trial ~imulation as it is printed out by the computer program ••. . . .••..•••.....25 7 Plot of simulated motions of two fish initially placed at points A and 8.The assumed preferred temperature is TEMP p =29.0°C and the force of temperature attraction, PT'is 1.0 for case A and SO.O for case B . • • • • . .26 8 The distribution of 500 fish influenced only by temperature in the reservoir after 200 steps.The assumed preferred temperature is 29.0°C.Other parameters of the model are given in Table 2 • . . • • . . . . ...• .27 xi Figure Page 9 Histogram of percent distribution of fish in Fig.8 about the preferred temperature of 29.0°C .•.....•..38 10 Histogram of relative frequency of largemouth bass in ambient water temperatures during daytime (from Reynolds and Caster lin 1977)••••••....•..•39 11 The distribution of sao fish influenced by temperature. dissolved oxygen.food availability and habitat favorability in the reservoir after 200 steps.Parameter values are givE!f'l in Table 3 ••....•...••40 xll INTRODUCTION The distribution of fish populations in bodies of water is interesting to sportsmen,conmercial fishermen.and ecologists aliKe. Several factors that may influence fish movements and spatial popula- tion distribution have been proposed,including temperature,dissolved oxygen in the water,pH values.the availability of food,the presence of cover for protection from predators,and the occurrence of compe· titors.These are not all independent.Dissolved oxygen is to some extent related to water temperature,as is the availability of certain types of prey.If the locomotor responses of fish to each of the factors were known in detail,then one could feasibly predict the average motions of a fish in a given body of water.The task of identifying and quantifying all the influences on fish locomotor behavior will not be easy,but significant progress has been made, th~nks to ingenious laboratory experiments and telemetry methods useful for the field. As the factors involved in the spatial behavior of fish begin to be understood,it can be applied to a host of practicll matters.For example,one would like to know where in a body of water fish popula- tioo densities will be highest at a given time of year.Also,htw will the pop.dation distribution ~n space respond to sl(lll or rapid changes in the conditioo of the water,either through natural processes such as seasonal variations,or artificial changes such as those induced by power plant operations? Both basic research and practiFal applications in the area of fish movements will rely on techniques of mathematical modeling.Models incorporating specific hypotheses will form a framework far experi- mental research,from which the data can be used to test the hypotheses. When the fundamental parameters of the models have been quantified,the model can be used predictively.This report describes a mathematical model capable of being used in conujuncticn with laboratory experiments and field studies,and later,for predictive purposes. iPS·' 2 Much experimental research has gone into the study of the effects of temperature on locomotor behavior in fishes.Temperature has been called the most i~ortant influence on the behavior of many freshwater fish (e.g.,Coutant 1975).It has long been noticed that fish move to different areas of a body of water as water te~erature changes.For exa~le,largemouth bass overwinter in deep water,~here the temperature is warmest.Using underwater telemetry,Warden and Lorio (1973)found that largemouth bass tend to move great distances to new home ranges in spring and fall,when water temperature is changing most rapidly.In winter.the population of largemouth bass congregate around the ttlermal discharge!.of power plants (Gibbons,Hook and Forney 1972).In a Texas cooling reservoir,it was noticed that largemouth bass sought out the cooler shoreline zones in summer mornings when the remainder of the reservoir had temperatures exceeding 37.8°C (Smith 1972). Laboratory studies have been performed to refine the data on temperature selection of several centrarchid species (Reynolds and Casterlin 1976,Stuntz and Magnuson 1976).Researchers have also sought to relate temperature preferenda with thermoregulation and tht! optimization of physiological processes (e.g.,McCauley and Huggins 1976,Reynolds and Casterline 1976).Growth rates of largemouth bass usually seem to be optimal near their temperature preferenda (Coutant and Cox 1976),although this does not seem to be the case for bluegills in thermal discharge areas during the sumner months (Kitchell et !!. 1974).81uegills were shown to actively avoid lethal temperatures (Peterson and Schutsky 1976),and to vary their temperature preferenda according to their daily rations (Stl6ltz and Magnuson 1976). A question that has bearing on attempts to model fish movements is what is the precise mechanism by which fish tend to center around their preferred temperatures?Neill (1976)discusses different mechanisms in detail and describes one·dimensional computer models based on some of these mechanisms.Thermoregulatory movements can be broadly categorized as predictive or reactive.In the former case,the fish is assumed to have some knowledge,by prior experience or instinct,of the 3 temperature distribution in the body of water,and will use this knowledge to move toward the desired temperature range.For example, since lower water-strata are normally cooler than upper layers,the fish should automatically move downwards when it feels too warm. Reactive behavior presupposes no prior knowledge of the temperature distribution,but only that the fish responds to different temperature regimes by altering its locomotory behavior.Several models of reac· tive movements have been developed.One type of model has been termed orthokinetic by Fraenkel and Gunn (1961).According to this model, fish slow their movements when in the preferred temperature range. increasing their chances of staying there.Both Fraenkel and Gunn (1961)and Neill (1976)have pointed out the inefficiency of this model for producing aggregation about the preferred temperature.Fish whose direction of motion was originally oriented away from the preferred temperature would continue to move away from it.Neill was able to obtain realistic aggregation only when his model specified a high probability of changing directions when the fish was moving away from the preferred temperature range.This form of behavior is called klinokinesis. Dissolved oxygen and pH in the water are important to the health of the fish and,therefore,presumably influence its movements.While fish have not been shown to exhibit dissolved oxygen and pH preferenda, they might be expected to avoid unfavorable conditions.For example, at 25°C the minimum oxygen requirement of small largemouth bass is almost 0.92 ppm (Moss and Scott 1961);it would be advantageous for such fish to preferentially move away from areas with dissolved oxygen levels below this minimum. The movement of fish in response to food availability and habitat preference probably involve learning where favorable conditions exist in a body of water.It is harder to develop models for response to these factors than it is for motion in temperature gradients,since it is difficult to know the extent of learning in the fish. The model described in this report assumes that the fish acts as if it can sense temperature gradient~and will move along a temperature 4 gradient 1n the direction of its oreferred temperature.We do not specify whether the fish acts this way because it actually can perceive temperature gradients or because its k.linokinl?tic activity increases as it moves into less preferrable temperature ranges.On the scale length we are dealing with (meters vertically and kilometers horizontally)~---.-._------------.-----_._--- the precise mechanisms of motion on the small scale may be unimportant. We alsoassume·thati~fi;h~Tl-;;o~~-away from dissolved o~ygen levels below that which is the minimum tolerable.and that they will have a general tendency to move toward areas of greater available food and more favorable habitat.These sevl!ral influences can either rein- force each other or.to some extent.cancel each other under particular circumstances.Aside from these basic assumptions.the model is very general and can be parameterized to suit a variety of situations. The present model is offered not as a ~~~tion of the way fish behave.but as a device bL'itlich-uarjetL.of .l!iP~the.!.ica!-_c!escriQ.t!~2.s of''-oc-omotor behavior can be tested.A few examples are given to i;lustrate the wa-Y-i~whic~h~-~odel is used.More thorough explora- tion of the model will be undertaken later.in combination with field studies. GENERAL DESCRIPTION OF THE MODEL The intent of this model is to predict the average spatial distri- bution of a fish population in a closed body of water.To do this we simulate the movements of individual fish,allowing a large number of fish to start from random positions in the body of water,and to move for a certain period of time.We assume that a small number of factors influence the movements of the fish;temperature,dissolved oxygen. food availability and habitat preference. The rr.odel is designed to apply to a two-dimensional representation of a hypothetical reservoir (Fig.1).The two dimensions are depth and either length along the reservoir or width across a cross section.A three-dimensional representation would be preferable,but would pose J 5 Fig.1.A hypothetical reservoir.The vertical dimension is depth in meters (disproportionately scaled),and the horizontal dimension is length along the reservoir in kilometers,with the downstream dam at the left.Isotherms in degrees Centrigrade (solid lines)and dissolved oxygen isobars in parts per thousand (dotted lines)are sketched in. The shaded region denotes high food availability.A power plant is assumed located at the upstream end.of the reservoir. - 6 problems both computationally and graphically.It is hoped that this model will eventually be extended to three dimensions.but the present two-dimensional model is useful.Note that the scaling 1n the vertical (depth)dimension is greatly exaggerated relative to the horizontal coordinate.Typical temperature and dissolved oxygen isoclines are sketched in.and the area in which food availability is greatest (usually the shallow water along shore lines)is shaded.We assume that the position of those factors are stable over the time scale in which a fish can move considerable distances.A typical fish will have a preferred range of temperatures.will tend to avoid very low levels of dissoh'ed oxygen,wi 11 be attracted by high food availability,and will prefer ~~bitats that give it sufficient cover f~predators.On this basis.~he avel"age distribution of a model fish population may be reliably predicted.though ".he path of a given fish is unique. For modeling purposes.it is necessary to represent the two-dimensional space by a grid of points.Consider a fish located at some point (i.J)in the grid points (Fig.2).The fish can move to one of eight adjacent points (i+o,j+E),where 0 and E take on the values -1,0 and +1 {but both cannot be 0 simultaneously}.It is assumed that the following factors influence the next location of the fish: 1.The tendency of the fish to continue moving in the general direction in which it is already moving.This can be termed the "forward inertia"of motion. 2.The preferred temperature of the fish and the temperature at the presen~location of the fish,(i,i),and the eig~t surrounding points. 3.The location of food supplies and cover. 4.The boundary of the water body,which sets limits on the motion of the fish. These factors can be elucidated to some extent by examination of Fig.3.Assume the fish is located at point (i,J)and has just moved from the point (i,j-l).The black points in this figure are those in the body of water while the white dots are above its surface.The isotherm of the preferred temperature is represented by black dots 7 ORNL-DWG 77-2861 (i-l,j+1l• (i -1,jl• (i -1,j-ll• (i,j+ll• (i ,jl• (i;j-ll• (i+1,j +1)• (i +1 J)• (1+1,j-1l• Fig.2.The point (i.j)in a grid of points,with the adjacent points to which the fish can move in one step. 8 ORNL-OWG 78-1682 0 0 0 0 0 0 0 0 0 0 (i+,.j-'Hi.,.jHi+',j+t) 0 0 0 0 0 0 0 0 0 SURFACE_. U,j-tl (i,j)(i,j +1)• • •• • l!>••• (i-l,j+tl• • • •• • @ • •• •• • • • •••• • • • • ••• • • •• • • •••@ •• ••• •••••• I I'•••• ••• •• •• •• • • •••• Fig.3.A grid of points representing a portion of the reservoir. The shaded circles are water.while th&open circles are above the water surface.The shaded circles surrounded by larger circles represent points along the preferred temperature isotherms. 9 surrounded by a circle.The most likely next "step"of the fish is to the point (i.j+l),since this is in its direction of preferred tempera- ture as well as its direction of inertia.The fish also has a high probability of moving to point (i-l.j+l).Of course.the fish cannot move to points (i>l,j-l),(i>l,j);or (i>l,j>l)because these lie above the surface of the water. It is conceptually and mathematically advantageous to discuss fish movements in terms of the four factors listed above.but these factors have not been quantified in detail (except for factor 4;the fish we are dealing with cannot normally leave the wat~r).Data are available on the response of some fish species to temperature and dissolved oxygen variations,but other factors,such as food availability and habitat preferences.complicate the situation in natural bodies of water.making predictions based on mathematical models less reliable. MATHEMATICAL DESCRIPTION OF THE MODEL It is cO.lVenient to represent the probability of a fish moving one step from a point (i.j)to another (k.m)in a two-dimensional grid as an element of a transition matrix.po.k.Since the fish can movelJ.m from one grid point only to an adjacent one in a single step.k and m are constrained as follows: I I.j I k =>6 (6 =-1,0,>1) m =j +C (c =-1.0,+1), (la) (1 b) (see Fig.1).In all future discussion.k and m will be implicitly subject to the limitations (la,lb). The sum over all probabilities for direction of motion must equal un ity: ..._.~~~~..Jo, 1+1 E k=1-1 j+l E m=j-l 10 =1.0 (2 ) The model is event-oriented,where an event is a step in space. This means that.given a fish initially at point (i,j),the next moment of interest occurs only when the fish has moved to an adjacent grid point.Therefore,the probability of the fish being in its same posi- tion at the next locomotory event in the model is identically zero.or =0.0.(3) All of the transition elements together define a transition matrix. f..Let !(l)be the probability vector for the position of the fish at a given moment.The elements of !(l),which are Xij(I),represent the probabilities of the fish being located at any given point (i,j). The condition ...ri=-<lO ... .rJ=_<XI (4) must hold since the fish must be somf"oolhere in the water body.Then m+l f(2)=r j=m-l k+lr1=k-l !(1l (5) 11 is the probability matrix for the position of the fish after its next movement to a new grid point. If the movement of the fish from one grid point to the next is purely random (i.e.,"random walk"),then Pij,km =1.0/8.0 =0.125 (6) that is,there is an equal probability of 0.125 of the fish going to any of the eight adjacent points.However,the motion of the fish is biased by its forward inertia,temperature and dissolved oxygen gradients,the location of food and favored habitat,and boundaries of the body of water. Consider first only the influence of forward inertia.It intro- duces a directional bias on top of random motion.The transition probability can be written P ..k •(l.0 +l(k,m)}/(lJ.m where (is the normalization factor, (7) r and i+1 (=~ k=1-1 j+l m=I-1 P'..k ''J.m (8) P'ij.ij :0:0.0 (9a) Pij,km =1.0 +I(k,m)(m ~j.if k i).(9b) Pij,km ={1.0 +l(k,m)+T(k,m)+OO(k,m)+F(k,m)+H(k,m»)/<(10) Pij,km ={l.0 +l(k,m)+T(k,m)+DO(k,m)+F(k,m)+H(k,ml)B(k,m)/<,(12) where ~is defined by Eq.(8)and now (13) (11 ) {l.0 +I(k,m)+T(k,m)+DO(k,m)+F(k,m)+H(k,m»)B(k,m), The term Ifk..m)is a measure of the strength of forward inertia relative to random effects in determining the next grid point in the fish's course of movement.If I(k.m)«1.0,then the random effects dominate the movement.On the other hand,if,say.I(i+l.j+l):»1.0 and I(i+l.j+l}»I(k,m)for all seven other pertinent values of k and m. then the fish is likely to move upward and to the right on its next step.The magnitude of I(k,m)for particular values of k and m depends on the past motion of thp.fish.For this reason,f.is not a Markov process matrix. In a similar manner,the effects of temperature and dissolved oxygen can be incorporated into this mathematical scheme.If T(k,m), OO(k ,m},Fek .m)and H(k ,m)represent the strengths with which temp(~ra­ ture grad"ients.dissolved oxygen gradients and gradients in distribution of food availability and habitat desirability.respectively.then one can write 12 p'..k =1.0 +l(k,m)+T(k,m)+OO(k,m)+F(k,m)+H(k,m)lJ.m where ~is defined by Eq.(8)and now The effects of the boundary of the body of water on fish movement is incorporated as follows.Define 8(k.m)as the boundary factor.and now write Pij.km as P'ij.km I-,, i II I 13 where O.(k ,m)outside the body of water (17) (16) (15a) (15b) =;'+6' j=j'+('. I(k.m)=Probability (6,<given 6',<'), c =16-6'1 +1<-<'1· B(k,m)(14) where this probability is higher the more positive the correlation between (o,e)and (6',(').In the model,a quantity,C.is defined, where. 1.(k,m)in the body of water Inertia of forward movement,I{k.m) Assume the fish is at point (i.j)and its preceding location was (i',j').where and where 6'and c'have the same ranges of values as 6 and (;[see Eqs. (1a,lb)).Then I(k,m),where k and m are given by Eqs.(la,lb),is a conditional probability, It is now appropriate to discuss the detailed formulations of I(k,m),T(k,m),D)(k,m),F(k,m)and H(k,m).These are developed in as simple and practical a manner as possible in the absence of definitive field measurements.Subsequent studies may require alterations of these formulations. 2) ) 14 The bars represent absolute values of the enclosed differences.The quantity C can take on one of five different integer values,for each of which I(k,m)is assigned a different value.e p as represented in Eq.(l8), e 1 (C •0) e 2 (C =1) [(k .m)=e 3 (C =2)(18) e 4 (C =3) e 5 (C =4), where the constants e i are chosen so that e 1 >e Z >e 3 >e 4 > eS 'The model fish is likely to continue in the same general direc- tioo because I(k.m)is greatest when 6 '"6'and e:'"£'. Temperature term,T(k,m) Assume the fish has a preferred temperature,TEMP p'The tempera- ture at point (i,i)is defined as TEMP(i,i).Oefine the absolute difference between the temperature at (i,j)and the optimal temperature by dT(i,i)=ITEMP(i,i)-TEMPpl.Then,if (k,m)is a neighboring point of (i.i).we define the temperature effect.T{k,m}.by T(k,m) ={ST >0.0 0.0 (1g) The quantita~ive value of the constant sr is assigned to reflect strength of the effect of the temperature gradient on the fish. mates of values might be obtained from experiments in which only perature effects are present. the Esti- tem- 15 Dissolved oxygen term,OO(k.m) We have no information on the existence of a "preferred"00 level. but there is evidence on minimum tolerable levels.Define by DISOX min the minimum tolerable level and by OISOX(i.j)the dissolved oxygen at point (i,j).Then if the fish is in a spatia~region in which the dissolved oxygen is below the minimum tolerable limit,(i.e., DISOX(i.j)<.OISOX min ).then define the dissolved oxygen effect, OO(k,m),by OO(k,m)= SOD >0.0 OISOX(k,m)>OISOX(i,j) (20) 0.0 OISOX(k,m)<OISOX(i,j). If the fish is in a region in which the amount of dissolved oxygen in the water is above the m1n'mum tolerable limit.then DO(k.m)=0 for all values of k and m.The constant Soo is a measure of the strength of avoidance by fish of low dissolved oxygen levels. Food availability terms.Fq(k,m) Assume that there are q regicns in the body of water that are attractive to fish because of high food availability.We assume that the closest of these to the current position of the fish will exert some attraction on the fish.Define by dF (i.j)the level of food,q availability at point (i,j).Then if (k,m)is a point neighboring (i.j).the force of attraction of the food is =jSF,q >0.0 l 0.0 (21) 16 Habitat preference terms,H (k,m) Assume that there are ~regions in the body of water that are attractive to 'fish because of their favorability as habitat.We assume that the closest of these to the current position of the fish will exert some attraction on the fish.Define by dH,p(i,j)the level of habitat favorability at point (i.j).Then if (k.m)is a point ne;gh~ boring (i,j).the force of attraction of habitat is SH >0.0,p dH (k,m)<dH (i ,j).P ,p 0.0 dH p(k,m)>dH (i,j).,,p COMPUTER PROGRAM (22) The computer program consists of a MAIN PROGRAM and three subrou- tines,SUBROUTINE RANSET,FUNCTION URANO,SUBROUTINE PLOTT and SUBROUTINE HIST. The MAIN PROGRAM first reads in the input data.which is described in Part A below,and then prints it Qut (see Part B.below).There are two ways in which data on temperature and dissolved oxygen can be entered;either by splcifying each grid point values.or by using mathematical functions to express their spati 1 variation.As an example of the latter.temperature might be given by the f"--;ction TEMP 40000'/{10000 .•(i _B5.)2 •5.0(j -55.)2 1 ,(23) which leads to the isotherms shown in Fig.1.Similar functions are used for dissolved oxygen.Food distribution might be modeled by functions of the form =(24) 17 which are plotted in Fig.4.The peaks and plateaus in this figure represent regions of high food availability.Similar functions are used to describe habit::t preferences. In the input data,the user specifies how many fish are released at random locations in the body of water and how many spatial steps they are allowed to take.The user also chooses whether or not the paths of the fish are to be plotted.If they are not,only the final positions of the fish will be shown by a dot.The user can also have the computer print out the isotherms,if desired. The program first randomly selects,using a pseudo-random number generator,the position and direction of motion of the fish.There- after.the movement of the fish from point to point on the grid is determined by the pseudo-random number generator.in combination with the transition probabilities.Pij.km'which are computed at each step. Information on the paths and final positions of the fish is stored for later printing. The only purpose of SUBROUTINE RANSET and FUNCTION URANO is to generate pseudo-random numbers on the interval (0,1).These subrou- tines have been described elsewhere (HcGarth and Irving,1975)and so will not be discussed here.The type of simulation that uses a pseudo- random number generator is commonly referred to as a Monte Carlo simula- tion.SUBROUTINE PLOTT handles the plotting of the outline of the body of water,while SUBROUTINE HIST plots a histogram of the final tempera- ture distribution of the fish. The computer program is meant to be very general.If changes in the program are necessary.however"the documentation of the program below should be complete enough to enable the user to make these changes. The r~mainder of this section consists of a description of the data input cards 'Part A).the printed output of the program (Part B). and a listing o~the computer program (Part C).In the next section. the use of the program is demonstrated by means of some trial simula- tions. I 18 ~.."-0 so -0 ..LON~1 TUDt:.0 fig-4_~plot of food availa~ilitY to reservoir-1he pea's and plat. aus represent alla l1ab "ity. 90-0 fish ,n a hypotnetiCal the regiOnS of high food 19 Part A.Input Cards Figure 5 is a listing of the input cards relevant to an example given in the next section.These input cards are described below: Card A Input parameters:NHOR.NVER.NREG Fonnat:415 NHOR ::number of horizontal grid points NVER ::number of vertical grid points ilREG ::number of environmental regions (usually there will be only two; (1)the body of water,and (2)the surrounding air and land Card B Input parameters:NREGP Format:15 NREGP ::the number of points on the line to be drawn to define the boundary of the body of water Card Set C Input parameters:(ARRAYX(I),l'l,NREGP) Fonnat:7EI0.0 ARRAYX(I)::the horizontal coordinates of points on the line defining the boundary of the body of water Card Set 0 Input parameters:(ARRAYY(I),I=l,NREGP) Fonnat:7EI0.0 ARRAYY(I}=the vertical coordinates of points on the line defining the boundary of the body of water Card Set E Input paramete:-s:NVER cards containing the information IREG. (IBEG(I),lENO(I),TYPE(I),1-I,IREG) Format:12,ex,6(212,F5.1,IX) I .' 20 .. ..•"•2.D.•••01'.0 ,~.O 10.0 l~.O ~.., )5."'1.11 ".0 10.0 ".0 'l.~n.",.....,..,..,,..'..0.'••••••'"'••••10.0 16.(1 n.1l ~o.o n.o 11.0 }•.o •n."",0 0.'••0"0 ... •''''0 '.',..'O?...O)~S ,..06'0 ...,"'''1 •••~J"",..01_0 ...,"'Ill ...IHIl ,..tno •••,"",..."'lI ~..."'I'...,"'"..."122 ,..2)_,...,o HI;'"'I'll'•••n"'.',"'01 '.'OJH ,..~o,o ...,.....,...O}.·,..,~....,0101 ...!!n....",..•••,0102 ...01'~•••"'"•••,Ill1l1 '.'n',,..'Ull ...,"'01 '.."H'o.'.0.0 '.',0'''''.'"J'~•••"'0 ...,1)101 '.'Ill.,,..'J'O '.',"'01 ..."'"...nto •••,"'01 ...Il}.,,.......'.',"'01 '.'OUt 0.'U'G ...,"""...,,'u ,..50'0 ...,0102 ..."H'..."'0 ...•,"'D2 ...Il}"...•••0 ...•,"'02 ..."1",..·nll ...•,"'01 '.'01"'..•uo ...•,0101 ...0'"...foO·O ...•,"'D''.'OJ'",..nta '.'•,"'Ol '.'OHl ,..'""...•,"'01 ...IU'"•••~uo '.'•,1"'"'.'In_,,..17"...•,"'"''.'llJ'~'..•••0 '.'•,0'02 ...Illf'~.0 '""0 '.'0,OlU ...'llH ,..'1"·..•,0'12 ..•OJ'l ...11'\1 ...•,"'('1 1.~IlJ')•••""0 '.'•,I'.'n ...Il)l''.'"'"••••,.....,•••01"'.'"'0 ...0,0102 ...O)l6 '..'HO ·..•,Il •.".......0 ..."'0 ·..•,01nl '..OJ"'..u.,'.'•,..,,,,'"'"l'"o••..no ...•,"'01 ...IlJIl"...81'0 ...•,0""...II}"..."'0 ·..•,0'111 ...OH'...ano ...•,D.Il,...01'"..."'0 '.'•,",1)1 '.'Il,"'.,"I'"·..•,0'01 '.'"'0 ,'.'8100 ...•,"'01 ...018'...~na ...•,0'01 ...r1.''.'88tO ...•,0'01 ...n).,,.....0 ...•,0'01 ...nUl •••...0 ...•,~,n,...n18',..8 ••0 ...,0'02 ..."18'...noo •••,ftlO1 '.'0)8'...•..0 ·..,0'01 ...~,.,o •••,.0 ...,"101 ...r18'•••"00 ••••n,o,.... •o,.n ,.~ •nlOO ... •ft ..O ...•0100 ...•, 19.0 ...,..'.',•••••,••'.'•0.00'O.~Ol 00.••••......•"'65 ,...'",•••".n.0.'•,"., •.• Fig.5,Input data for a sample trial simuhtion as it appears on the data cards. 21 IREG number of different environmental types along ~given line of grid points IBEG(I)=the horizontal coordinate of the first grid pOlnt of a particular environmental type along a 9iven horizontal line tEND(I)The horizontal coordinate of ttY.:last grid point of a particular environmental type along a given horizontal line TYPE(I)=a numerical label attached to each environmental type to distinguish if from others Card F Input parameters:ITEM.IDISOX Format:215 JTHI 0 if spatial temperature data is given by an equation in the pro:.ram 1 of spatial temperature data is read in point by point IOISOX =0 if spatial dissolved oxygen is given by an equation in the program 1 if spatial dissolved oxygen data is read in point by point Card Set G (included only if ITEM =I) Input parameters:(TEMPA(I.J).I=I,NHOR).J=I.NVER Format:7EIO.0 TEMPA(I.J)=temperature at grid point (I.J) Card Set H (included only if IDISOX =I) Input parameters:(DISOX(I.J).I=I.NHOR).J·I.NVER Format:7£10.0 DISOX(I.J)=dissolved ox,gen le,el at grid point (i,J) Card I Input parameters:TEMPRF,TEMFCR Format:2EI0.0 TEMPFR ::preferred temperature of f"ish TEMF~::force of attraction of preferred temperature of fish 22 Card J Input parameters:OOXMIN,DOXFOR Format:2EIO.O DOXHIN =minimum tolerable dissolved oxygen level for fish OOXFOR =attr~ctive force of higher dissolved oxygen levels on fish Card K Input parameter:NFOOD Format:15 NFooD =nllmber of centers of high food avallability Card L Input parameter:FOAler Format:ElO.O FOAler =force of attraction of food availability on fish movements Card Set M Input parameters: Format:5EIO.O FONi.I'I(I) FOALP{l) FOBET(I)= FO IQ(I) FOJQ(I) FONi.I'I(I),FDALP(I),FOBET(I),FOIQ(I),FOJQ(I) parameters describing spatial distributions of food about each of the centers of food availability (see EQ.24 and Table I) Card N Input parameter:NHAB Format:IS NHAD ~umber of centers of high habitat favorability Card 0 Input parameter:HBATCT Format:EIO.O HBATCT =force of attraction of habitat favorability on fish movements Card Set P Input parameters: Format:5EIO.0 HBNIJoI(I) HBALP(l) HBBET(l) HBIQ(l) HBJQ(i) 23 HBNIJoI(I),HBALP(l),HBBET(I).HBIQ(I),HBJQ(I) parameters describing the spatial distribution of habitat favorability about the high habitat favorability centers (analogous to Eq.(24);also see Table 1 for definitions) Card Set Q Input parameters:RES(l),I=I,NREG Format:7EIO.0 RES(I)=boundary crossing factors (causing fish to remain in the body of water) Card R Input parameters:ERTIA(I),1=1,5 Format:5ElO.0 ERTIA(I)=Inertia of forward motion.e j (see Eq.18) Card S Input parameter:IX Fonnat:15 IX =pseudo-random number generator initilization or "seed".It must be an odd integer.A different value of IX should be used each time the program is run . Card T Input parameters:NFISH,NSTEP Format:215 NFISH =number of fish considered in the body of water NSTEP =number of steps in space each fish is allowed to take _.--_.~--- f 24 Card U Input parameters:JPLOT,ISOTH Format:2[5 IPlOT =-1 if the fish paths are to be plotted,0 otherwise [SOTil :1 if the isotherms are to be plotted,0 otherwise Card V Input parameters:TEML,·TEMH.TEMINT Format:3EI0.0 TEMl =-minimum isotherm to be plotted TEHH =-maximum isotherm to be plotted TEMINT :width of intervals between isotherms Part B.Output The printed output consists of two parts.First.the input data is printed out (Fig.6).Second,a schemata of the body of water is plotted.into which fish paths or spatial population distribution are plotted (Figs.7 and B).The plotting is done using the DISSPLA graphics package (Integrated Software Systems Corporation 1970)which is available at many computer installations.Programming changes would be necessary to adapt the program to other graphics packages. Part C.Computer program details The complete computer program listing is printed in the Appendix. The comment cards interspersed through the program should enable the user to unders tand its genera 1 des i g"",However I some add i tiona 1 comments may be useful. 1.The arrays are dimensioned to permit a maximum of 90x60 grid points at present.This can be changed if desired. 2.A typical run dispersing 500 fish takes about 3 minutes of CPU time in the IBM 360/91 computer.although this changes to some extent as some of the model parameters are varied.The GO step uses less than 230K of computer core. I ! I f 0.00.0O.10 O.001 0.10 0.001 0.10 P.AlfDOII )1101181:1 IUTUTOR.II'•98165 FORCE or "frUeTlDI or GR!ATER fOOD UAIL'BILITf.pOATer.0.0 )l1OOO:E 0 T!rIPERATUR!IS DESCRIBED Sf A P1I,TlllIUTICAL 'UleTIC" VALUES or PORIlAIlO JNER1U.EP1U • POUMOA!lf CROSS]"G '..CTCFS.REStl)• "UIIBER OF rISK Ilf BOD!or VATU.MFISH SAO 25 NHAB • 0 FOIlCE Of'ATTRACTION Or H"BITA'I PPEnU:If:ES.RBATeT • fOlcr or ATTRACTIO'or KIGHER DIssoLUO (lUGE'LUtLS 0.0 DISSOLVEO OHeEll nOONTS DESCPIBED SY A P1ATUIlATIClL 'U)lCTlOJ PIl~P!RRED TEIlPEILATORl.TEIlPR'• IIDllen or unRoUE.TAL REctO'S,liRE:>•2 PISH !I0lllllMT rill A BODY cr IIATEP rORCE or lTTRAeTlal or fREFUFfO TIrlPEP:lTORI.II:"rOIl •1.0000 !lfNI"O"ISCTHIIUI PLOTTED.TE"L'"'16.0000 DISTAIIC!IIlTV!!1 ISOTRlIUIS.TIRIHT '"'11.0000 ""11"0"ISCTHFIIII PLO'!TU:.TEft./III.DOOO 11111111011 TOLERABLE DISSOLVED onGEIf LEVP.L.DOUX_•2.0000 NUften or HOBII0llTAL GRID POIlTS.IIHOI 90 HUflB!R or ¥!ITICU GRID POU1!,Iflil.60 1I0llBEIl OF STEPS EACH 'I~a IS ALLovID Tn TAKE.lfSTEPS 200 Fig.6.Input data for a sample trial simulation as it is printed out by the computer program. "."' ORNl·DWG 78-2b43 fISH DISTRIBUTION o ~ o S o Ii! o $ :I:..... t.J 00 il o lil ------- A -----.14° zo' ,,' _36° _];10 ~ o 2 --------"'--- 10'0,., o6~• , •i ,ii,,• 20'0 30'0 40'0 SO'O 60'0 70'0 80'0 90'0 100'0 LENGTH Fig.7.Plot of simulated motions of two fish initially placed at points A and B.The assumed preferred temperature ;s TEMP p =29.0°C and the force of temperature attraction.PT'is 1.0 for case A and 50.0 for case B. 'I.-...-- r -\1 r ------ -- -- -----, ORNL-DWG 78-2Mb fISH DISTRIBUTION N ~ r--j ,I , 60·0 10-0 80'0 90'0 100-0 J6' iO'O",., n' 20'0 .·;:t • .:·":.":'f~··.. "\:)~..:':.:~;....'..' .....,.:....:,.:......:.:.. .....:....•...;~,.:/..:,......::~";~:-;;_:"':-;... .'.";", ,,' 10'0 16'-- ~ ~ 0 lil 0 51 0 0 ~ :l:.... ll. W "'0 51 0 ~ 0 ~ 0 '"0'0 50'0 LENGTH Fig.8.The distribution of 500 fish influenced only by temperature in the reservoir after 200 steps.The assumed preferred temperature is 29.0 0 C.Other parameters of the model are given in Table 2. 28 Table 1 is a compilation of the principal FORTRAN variables in the computer program.The equivalent mathematical symbols.of any.and definitions are given as well. TRIAl SlfoULATlONS The fundamental question that must be asked of this model is how accurately it can simulate the movements of individual fish and the spatial distribution patterns of populations of fish.There is not enough data on either of these phenom(~a in natural environments to allow parameters for a model to be thoroughly tested.However, laboratory experiments provide some data on fish distributions in environments in which only thermal effects are important.We shall focus on the thermal influences on the 'i~h in our model and only briefly note how the other factors influence fish distributions in space. Fish Movements Consider the reservoir pictured in Fig.7.with only t~ temperature gradient assumed to have an effect on the fish.The temperature isoclines are given by Eq.(23)and the remaining para- meters of the model are given in Table 2.A simulated fish is placed in the reservoir at the position A;it moves.with a fair amount of meandering.toward the preferred temperature.TEMP p =29.0°C.The amount of meandering can be decreased by increasing the force of the temperature gradient on the fish movement;that is.by increasing PT'When PT is increased from PT =1.0 to PT =SO .•and a fish is released at point 8.it moves more directly toward the preferred temperature. Fish Distribution Patterns Allow SOO fish to be releasL~at randomly selected initial positions in the body of water.and to move in response to temperature gradients only.After 200 steps.they have all had a chance to respond Table I.Principal rogram variables Fortran Dimension Mathematical variable (if array)symbol Definition """ ARA'(50)Storage array for horizontal coordinates of isotherm c~rves for later plo:ting ARAY (50)Storage array for vertical coordinates of isotherm curves for later plotting ARRA'fX (50)Storage array for horizontal coordinates of outline of body of water ARRA'f'f (50)Storage array for vertical coordinates of outline of body of water D Random number chosen from uniform distribution on the interval (0,1) DOIFF Difference between the dissolved oxygen level N at the current position of the fish and its ~ minimum tolerable dissolved oxygen leyel DDIFFA Difference between dissolyed oxygen level of any of the next eight possible positions of the fish and its minimum tolerable dissolved oxygen 1eve 1 DDR (l,l)I(k.m)Measure of the strength of the inertia of forward moyement of the fish DIA (l,l)DQ{k,ml Attraction of point (k.m)on fish because of the difference In the dissolYed oxygen leyel from that of the current location of the fish DISOX nOD}DISOX(k,m)Storage array for dissolved oxygen Il:els along some given horizontal line,k 00'OISOX(i,j)leyel of dissolyed osygen at the current position of the fish t --, Table I.(continued) Fortran Oimens ion Mathematical variable (if array)symbol Definition name OOXFOR '00 Attractive force of higher dissolved oKygen level on fis~movements OOXMIN OISOX min Minimum tolerable dissolved oxygen level for fi sh ERTlA (5)';Strength of forward inertia of fish FOAlP (20)'"Parameter describing the spatial distribution of food about each of the centers of food availability (see EC!.24) FOAlel SF ,'I Force of attraction of food availability on fish movemen ts FOSEl (20)'"Parameter describing the spatial distribution of food about each of the centers of food w availability (see Eq.24)0 FDIQ ('0)'"Parameter (horizontal coordinate)describing the spatial dhtribution of food about tdCh of the centers of food availability (see [q.24) 'OJO (20)J"Same as above definition (vertical coordinate) FOHUM '2O)'0 Parameter describing the spatial distribution of favorable habitat about each of the centers of food availability (see ['I.24) FOR (3,3)FQ(k,m)Attraction of point (k,m)on fish because of the difference in food availability from the current location (I,j) '000 Measure of the amount of food available to the fish at Its currenl location FOOOA Measure of the amount of food available to fish in its possible next location , r , • Table 1.(contln~~d) Fortr.n Din;ens ion Ma theD'.a tical v.rlable (If array)symbol Definition.."" GRID 190.501 Array that stores lnfomatlon QI'l the tiP!of region each grid point h In.as well as 'I ts temperature and dissolved oxy~en level HAS Measure of the ravorabllity of habitat at the current location of the fish HA8A Measure of the favorabl1lty of habitat at the possible next location of the (Ish HA8AlP ('0)'H,Parameter describing the spatial distribution of favorable habitat about each of the centers of favorable habitat (In equation analogous to EQ.24) HBATCT 5H,q Force of attraction of habit (aYOr/lbillty on flsh movements w-HBBET ('O)BH,Q Parameters describing the spathl distribution of f ....or.ble habitat about each of the centers of favorable habitat (In equation analogous to [q.24) HBIQ 1'0)I Center of a region of favorable habitatH"(horizontal coordinate) H8JQ 1'01 JH,q Center of a region of favorable habitat (vertical coordinate) HBNUM ('0)HO Parameters describing the spatial distribution of favorable habitat about each of the centers of favorable habitat (in equation analogous to [q.24) IOISOX Logical variable specifying whether dissolved oxygen levels are described by a mathe~tical function (IOISOX.O)or point by point (IOISOX·1) '=='="=:;=::::::'!;:>...--....-------~-----~_====""'=""'.",;,.._.....iiiii.. Table I.(continued) ", Fortran variaDle """" IPlOT IPRES ISOTH ISTRT ITEM IX JPRES JSTRT HOiST NFISH IlFOOO NHAB HHOR NREG NSY Dimension (if array) Ha thema t i ell 1 symbol oef;01 tion Logical variable specifying whether or not fish paths are to be plotted Current position of the fish (horizontal coordinate) logical variable specifying whether or not the isotherms are to be plotted Horizontal coordinate of the starting position of 11 given fish Logical variable specifying whether temperature is described by a mathematical function (ITEHmO) or by point-by-point data (ITEM-l) Pseudo-random number generator initiator Current position of the fish {vertical coordinate) Starting position of tne flSh (vertical coordinat~) Integer variable that increases by 1 for each step a particular fish takes.When NDIST=NSTEPS. no further steps are taken liumber of fish simulated in the body of water Number of centers of food availability Number of centers of high habitat favorability lIumber of horizontal grid lines NUr:lber of env i ronmen ta 1 reg ions [u sua 11y there will be only two;(1)the body of water,and (2)the surrounding air and land] Integer variable that increases by 1 for each fish that is "inserted"into the body of water. When NSV ~NFISH,no further fish are inserted. W N Table 1.(continued) Fortran varlable ".. IlSTEPS NVER RES SAYl SAVJ TDIFF TDIFFA TOR TEMIl TEHINT TEHl TEMFOR TEMP TEMPA T£HPRF V Dimension (if array) (SOl (SOOI (SOO) 13.31 (l00) {3.31 Ma~hematical symbol B(k,m) dT(i ,J 1 dT(k,m) Tq(k,m) ST TEMP(i ,j) TEMP P Pij,km Definition Number of steps in space that each fish Is allowed to take Number of vertical grid lines Boundary crossing factors (causing fish to remain In the body of water) Array that stores horizontal coordinates of fish movement for later plotting Array that stores vertical coordinates of fish movement for later plotting Difference between temperature of current position of fish and its preferred temperature Difference between temperature of possible next position of the fish and its preferred temperature Attraction of point (k,m)on the fish because of the difference on tenlperature from it~ current position Temperature or maxilll:l::l isotherm to be plotted Width of intervals between Isotherms Temperature of minimum isotherm to be plotted Force of attraction of preferred temperature of fish Temperature at current location of fish Storage array for temperature data along a given horizontal line,t Preferred temperature of the fish Transition probability from grid point (i,Jj to grid point (k,m) ww 34 Table 2.Parameter values for the example in Fig.5 NHOR '"90 MYER '"60 NREG a 2 NREGP '"17 ARRAY'(I)(1'1,17)•2.0.5.0,10.0,15.0,20.0.25.0.30.0,35.0,'3.0,55.0, 10.0.77.0.82.0. 88.0.2.0.2.0 ARRAVY(I)(l s 1.17)=3.0.3.0.4.0.5.0.6.0.7.0.9.0.10.0.16.0.22.0,30.0. 36.0.38.0.39.0,55.0.55.0.3.0 IREG l'E~(l)!Er1O(l)TYPE (1)l'EG(2)IENO(2)TYPE(2)l'EG(3)IENO(3)TYPE(3) 1 01 90 1.0 1 01 90 1.0 3 01 02 1.0 03 05 3.0 06 90 1.0 3 01 02 1.0 03 07 3.0 08 90 1.0 3 01 02 1.0 03 12 3.0 13 90 1.0 3 01 02 1.0 03 1.3.0 15 90 1.0 3 01 02 1.0 03 "3.0 23 90 1.0 3 01 02 1.0 03 26 3.0 27 90 1.0 3 01 02 1.0 03 29 3.0 30 90 1.0 3 01 02 1.0 03 31 3.0 32 90 1.0 3 01 02 1.0 03 3.3.0 35 90 1.0 3 01 02 1.0 03 36 3.0 37 90 1.0 3 01 02 1.0 03 38 3.0 39 90 1.0 3 01 02 1.0 03 39 3.0 .0 90 1.0 3 01 02 1.0 03 40 3.0 .1 90 1.0 3 01 02 1.0 03 42 3.0 43 90 1.0 3 01 02 1.0 03 44 3.0 45 90 1.0 3 01 02 1.0 03 45 3.0 46 90 1.0 3 01 02 1.0 03 47 3.0 48 90 1.0 3 01 02 1.0 03 49 3.0 50 90 1.0 3 01 02 1.0 03 51 3.0 52 90 1.0 3 01 02 1.0 03 53 3.0 54 90 1.0 3 01 02 1.0 03 55 3.0 56 90 1.0 3 01 02 1.0 03 57 3.0 58 90 1.0 'I 35 .\ ! Table 2.(continued) IREG I8£G(1)IEIlO(I)TYPE{I)IBEG{Z)IENO(Z)TYPE(Z)IBEG(3)l(fm{3)TYPE(3) 3 01 OZ 1.0 03 59 3.0 60 90 1.0 3 01 OZ 1.0 03 61 3.0 6Z 90 1.0 3 01 OZ 1.0 03 03 3.0 6'90 1.0 3 01 OZ 1.0 03 65 3.0 66 90 1.0 '3 01 OZ 1.0 03 66 3.0 67 90 1.0 3 01 OZ 1.0 03 68 3.0 69 90 1.0 3 01 OZ 1.0 03 69 3.0 70 90 1.0 3 01 OZ 1.0 03 71 3.0 72 90 1.0 3 01 OZ 1.0 03 72 3.0 73 90 1.0 3 01 OZ 1.0 03 73 3.0 74 90 1.0 3 01 OZ 1.0 03 74 3.0 75 90 1.0 3 01 OZ 1.0 03 75 3.0 76 90 1.0 ;1 I 3 01 OZ 1.0 03 76 3.0 77 90 1.0 3 01 OZ 1.0 03 80 3.0 81 90 1.0 (II 3 01 OZ 1.0 03 87 3.0 88 90 1.0 3 01 OZ 1.0 03 87 3.0 88 90 1.0 3 01 OZ 1.0 03 87 3.0 88 90 1.0 3 01 OZ 1.0 03 87 3.0 88 90 1.0 3 01 OZ 1.0 03 87 3.0 88 90 1.0 3 01 OZ 1.0 03 87 3.0 88 90 1.0 , I 3 01 OZ 1.0 03 87 3.0 88 90 1.0 II 3 01 OZ 1.0 03 87 3.0 88 90 1.0 3 01 OZ 1.0 03 87 3.0 88 90 1.0 II, 3 01 OZ 1.0 OZ 87 3.0 88 90 1.0 'I301OZ1.0 03 87 3.0 88 90 1.0 3 01 OZ 1.0 03 87 3.0 88 90 1.0 I 3 01 OZ 1.0 03 81 3.0 88 90 1.0 3 01 OZ 1.0 03 87 3.0 88 90 1.0 3 01 OZ 1.0 03 87 3.0 88 90 1.0 3 01 OZ 1.0 03 87 3.0 88 90 1.0 3 01 OZ 1.0 03 87 3.0 88 90 1.0 I 01 90 1.0 I 01 90 1.0 I 01 90 1.0 I 01 '0 1.0 I 01 90 1.0 " HHINT '"4.0 NST[P "200 ISOTH "1 TEHH "44.0 36 Table Z.(continued) ITEM"0 J~ISOX ~0 T£HPA(I,J)not entered DISOX(I.J)not entered T£HPRF =29.0 TEHFOR ..1.0 OOXHIH =2.0 OOXFOR ..0.0 HrQOD ..0 FOATer "0.0 FOHUH(I).FOAlP(I).FOSH(I),FOIQ(I).FOJQ(I) NHAB " 0 HBATCT ::-0.0 HBNUM(!).HBAlP(I),HSBH(I),HBIQ(!).HBJIHI) RES(!)(1'1,3)-0.001,0.001.10.0 ERTlA(I)(1-1.5)•0.1, 0.1,0.1.0.0.0.0 IX =9876'5 NFJSH " 2 IPlOT " 1 TEMl "16.0 not entered not entered 37 to the preferred temperature.The distribution of fish after 200 steps is stoW"in Fig.8,for parameter values given in Table 2.except that now NFISH =500 and IPlOT =O.It is interesting to look at the histo· gram describing the percent distribution of fish about the preferred temperature of 29.0OC ~Fig.9).since this can be compared with laboratory data.such as that shown in Fig.10 for largemouth bass {Reynolds and Casterlin 1975}.The agreement is not bad (although the model results are more peaked and lack.the skewing seen in the experiment),which is some indication that we have chosen a reasonable set of parameters for our model;however,other choices of parameter va hies may give better results. Next we add in the effects of dissolved oxygen (Fig.I),food availability (Fig.4),and habitat preferendJ,with the appropriate changes in parameter values frem Table 2 shown in Table 3.The ulti- mate average distribution of fish is nCM greatly altered (Fig.11). DISCUSSION AND SUMMARY The model described in this report is designed to simulate the movements of individual fish in a body of water and to predict the spatial patterns of a population of fish under the influence of temperature,dissolved oxygen levels,fl'lOd availability and habitat preferences.The body of water is represented by a two-dimensional grid of points,with water depth and longitudinal axis being the coordinates.The simulated fish t3kes one spatial step at a time,the direction of travel being chosen by·a pseudo-random number generator, but biased by the initial direction of motion of the fish,as well as its response to temperature gradients and the other factors mentioned above.Model output is plotted in graphs. This mOOel is designed for use in planning and evaluating the results of experimental laboratory and field studies of fish movement ~nd spatial distribution.The application of the model to experimental data is sti 11 in a prel iminary stage,and the development of the model into an effective predictive tool will take continued work.The model I I 38 ORNL-OWG 78-427715,--,--,--,--,--,__,--,.-_,--,_,--_., ;e ~ >-u 10z UJ :::> 0 UJa: "- UJ>5I- <[ ...J UJa: 0 24 25 26 27 28 29 30.31 32 33 34 35 TEMPERATURE (Oe) Fig.9.Histogram of percent distribution of fish in Fig.8 aboutthepreferredtemperatureof29.0°C. ·--&...0 39 ORNl-OWC 78-3270 TEMPERATURE SELECTION 0 :l ~~ 0x 0..~ ""0u.z'"~ow.oo-... 0 I-w·>"~-.. 0;0 ...J';w-oo 0 Co ~ 0..I- 0•I- 0 ~f--;, 11- . 0 h n,; .0 .po ~O ~o 4 0 00/'0 .po ~ TEMPERATURE I .. Fig.10.Histogram of relative frequency of largemouth bass in ambient water temperatures during daytime (from Reynolds and Casterlin 1977)• r , ORNL-OWG 78-2647 o ~ FISH DISTRIBUTION o S Ao .'. JO' '.'. ..);)/~~./:.;~ lI' :.~.:::'::'~'~'~?;/~:(::. !l..'".~~.~;;:-"••..;:~.~"•...:::.~ 2J' ZJ" o R o :il o iI ;'; ~ Co ~ 10- 6~I _____ 0"10'0 20·.",..to·Q 50·. LENGTH ....70'0 ",..",..100'0 Fig.11.The distribution of 500 fish influenced by temperature,dissolved oxygen.food availability and habitat favorability in the res~rvoir after 200 steps.Parameter values aregiveninTable3. ~\=.::...============-------~=--.-'1 IY 41 Table 3.Changes in paremeter values from Table 2.relevant to the case shown in Fig_11 NFOOO •1 FONUM(l)•10.0 FOALP(l)•0.02 FOBET(l)•0.2 FOIQ(l)•60.0 FOJQ(l)•45.0 FONUM(2)•10.0 FOALP(2)•0.10 FOBET(2)•0.20 FOIQ(2)•70.0 FOJQ(2)•50.0 NHAB • 1 HBNUM(l)•10.0 HBALP(l)•0.05 HBET(l)•0.20 HBIQ(l)•45.0 HBJQ(l)•53.0 HBNUM(7)•10.0 HBALP(2)•0.05 HBBET(2)•0.2 HBIQ(2)•45.0 HBJQ(2)•53.0 NfISH ..500 !PLOT •0 42 is flexible enough to take into I1ccount most of the important factors influencing fish movement,but considerable effort needs to be expended in quantifying these factors. I i 43 REFERENCES Coutant.C. C.1975.Responses of bass to natural and artificitll temperature regimes.pp.272-285.IN:Stroud.R.H.t and H. Clepper (eds.).Black Bass Biology and Managem~t.Sports Fishing Institute.Washington,DC.534 pp. Coutant.C.C.,and D.K.Cox.1976.Growth rates of subadult large- mouth bass at 24 to 35.5 C.pp.188-120.IN:Esch,G.W.,and R.W.McFarlane (eds.).Thermal Ecology II.ERDA Symposium Series CONF-750425.National Technical Information System.Springfield, VA. Fraenkel.G.S.,and D.L.Gunn.1961.The Orientation of Animals (revised edition).Dover P.lb.,Inc.,Ne.r.r York.376 pp. Gibbons.J.W.,J.T.Hook,and D.l.Forney.1972.Winter responses of largemouth bass to heated effluent from a nuclear reactor. Prog.Fish Cult.34(2):88-90. Kitchell.J.F.,J.F.Koonce.R.V.O'Neill,H. H.Shugart.Jr., J. J.Magnuson,and R.S.Booth.1974.Model of fish biomass energetics.Trans.Am.Fish.Soc.103(4):786-798. McCauley.R.,and N.Huggins.1976.Behavioral thermoregulation by rainbOl'i trout in a temperature gradient.pp.171-175.IN:[sch, G.W.,and R.W.McFarlane (eds.),Thermal Ecology II.ERDA Sympo3ium Series CONF-750425.National Technical Information System,Springfield,VA. McGarth,E.J .•and D.C.Irving.1975.Techniques for efficient Monte Carlo simulation.Vol.II.Random number generation for selected probability distributions.ORNL/RSIC-38 (Vol.2).Oak Ridge National laboratory,Oak Ridge.TN. Moss,D.D.,and D.C.Scott.1961.Dissolved oxygen requirements of three species of fish.Trans.Am.Fish.Soc.90(4):377-393. Neill,W.H.1976.Mechanisms of behavioral the"ll1oregulation in Fishes.pp.156-169.IN:Sigma Research Inc.(ed),Report of a Workshcp on the Impact of Thermal Power Plant Cool ing Systems on Aquatic Environments.Electric Power Research Institute,Palo Alto,CA. 44 Peterson,S.E.,and R.M.Schutsky.1976.Some relationships of upper thermal tolerances to preference and avoidance responses of the bluegill.pp.148-153.IN:Esch,G.W.,and R.W.McFarlane (eds.),Thermal Ecology II.ERDA Symposium Series CONF-750425. National Technical Information System.Springfie1d.VA. Reynolds,W.W.,and M.E.Caster lin.1976.Thermal preferenda and behavioral thermoregulation in three centrarchid fishes.IN: Esch,G.W.,and R.W.McFarlane (eds.),Thermal Ecology II.ERDA Symposium Series CONF-750425.National Technical Information Syst(~ml Springfield,VA. Smith,S.F.1972.Effects of a thermal effluent on aquatic life in an East Tennessee reservoir.Prot.25th Annu.Conf.S.E.Game and Fish Coon.,374-384. StlJ'ltz.W.Eo,and J.J.Magnuson.1976.Daily ration,temperature selection.and activity of bluegi 11.pp.180-184.IN:Esch. G.W.,and R.W.McFarlane (eds.),Thermal Ecology II.ERDA SympJsium Series CONF-750425.National Technical Information System,Springfield,VA. Warden.R.L.•Jr .•and W.J.Lorio.1975.Movements of largemouth bass (Micropterus salmoides)in ifT1)ounded waters as determined by underwater telemetry.Trans.Am._Fish.Soc.104(4):696-702. 1 45 APPENDIX:THE COMPUTER PROGRAM 000 I Olt02 OC'l J 00011OC,,, 001)6 0001' DOt'8 COOl) on,o DOlt (1012 0013 00" 0015 DOl' 0011 DOH! 0011) c c c c c c c c c c c c c c 47 ........................•............•....••......................... TillS '"OCUli tOllfUT!S U!>H 015111180TIOl5 III A eDDY or lint•• "'IT'!'!:'8T O.1..DUllealS.1917 ............................•........•.......•.................•...... 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JPAST ...15111 SUI un,..1S'f1lT SA ".I 1t:!:Y)..J!TIlT o ..O'''I)IDU~'f) rtlAC ...125 DO 80 t-'.]no 80J_1.J Ull .ro....UG.J .:0:0.2)GO TO 80 I'(0 .U.""CI GO TO liS ruc ..rllAc ...125 80 CClnUOE 85 COIIT1I01: 1011 ..I .1011 ..J tPIES ..ISTIT - 1 ..tD~ JPIlES ..JSTllT - 2 •,lOll IrIClIItUS"l'ItT.JSTIlTl .U.1.0)GO TO 65 c c c •..••8'0IlllIlG or TIll!IT£llA'!'IOI C 100 COITUDt e C•••••D!TtIIlltl'COIIREIT 1!::'!!'tU'!'llH ...0 OISSOLf!O Ducr. e 1PIGnO(TPIlE~.JPRr:S1 .CT.).01 GO TO 105 Tltll'..IGIIIDI1l'PES.JPIlESI -2.0)·1('00. LYEll ..TEll' STtll ..LTEIl DOl ..IT!'IIP-ST!I'l1 -100. GO TO 107 105 CDnlJlI::' nil'..(GIl1D IIPlUS.JPIlP:SI -J.OI-'OOO. LTP:II -TP:II' ST!II -LTP:Il COl -ueIlP-SUIII-'OO. 107 COlfTIIIO! Ttllp -O.'-'!tllp TOIFP -AIlS(TrIIl'-TFJlP!l'1 oon,-001 -0011ln !oJl'l ST JPl SI SIPlST IPlST 5151'111'151'11 SJSTIT "STU SII'RtS Il'Rt! SJPRtS JI'RU c C•••••DtTl'IlIllt CURPP:1lT POClD UlYUBYL.ITT e IP(IIPOCO .eo.01 CO Tn '1' POOO -0.0 00"0 I-',.Pooo OISTI -18S(SIPfltS-POIOIII1 OISTJ -AIlS(SJl'US -POlO (11)• llPlRG _UP I-POlLP(I)-OISTI -ponT III -OISTJI pooo -roOD _'011011(1)-UPl.C I I I_____l 0211 0218 0219 0220 0111 02'1 022l 02211 0225 0226 0227 53 110 CO.TIIO! 11\CO'TlInc C •••••0!ttllllIlt COIl.!'T HUllnT P.,O.UILIT! C IP'I"'U .tg.01 :>0 TO 116 NUl •0.0 DO 115 ]*'.'"AI olSTI •US ISIP.!S -!!III a II II D]ST..I •US(S..I'US -ll&..Jall)) n'AIIG •tlP(-NULP(l1 aOISTI IIll1ltT(Tl a tlur..l1 IIAI·IIAI •IlfIlJIl(I)-!IP".G 115 CO.!Utl! 116 CCIT!Jot c C C •.•••CALCOUTIO.OP Tilt tPPP:TS OP IU:lITU OP POUA,t 1I0TIO••TM!EPP!CT:; C OP T!IlftllATtlllf AllD DISSJUto o,tGtII ",lOItITS.AID Til!I,'LOEK!OP C SPlTUL POOl'OISTPHlll'ilOI "'0 IUlnl!,IlEPUUcts C 0228 0229ono 0211 0212 02JJ DO 200 ]·'.l 00 200 J*1.l 1'1 •IPIl!S I ..IPI •..IfIlES J S]PI •1'1 S..I'I *..1'1c C •••••rl!IlTIII EPfECTS C ,, 02H 0215 0216 0237 0218 0239 02110 02111 02112 021l 0204 02115 02116 02111"..02119 0250 ""0252 ""02~1 0255 0 .....6 0257 025.",. 51 • 1 SJ •J 51011 •101 SJOII •JOt C·Ul5CSI-SII:Il)•USISJ·~..ID"I tr (C .GT.0.0):>0 TO 12lnn• , GO TO 129 123 lP'IC .GT.1.0):>0 TO 12' 1111'• 2 GO TO 129 1211 rr IC •lOT.2.0)GO TO 125 IEIIT •1 GO TO 129 125 IPCC .Gt.l.OI :>0 ",12' lIlT.II GO TO 129 126 lP'(C .Gt.11.01 .0 TO 127 IEin'• 5 GO TO 129 121 un •5 129 COIlTUOE 0111l.JI •EIITtIl(Iflltl c C •••••ilOOIUn UPIC1'5 C lP'II'].ca••11011 .01 •..IPI".Gt.nt',GO TO 60 IF lIP!.Lt.0 .or •..IPI •Lt.0)GO TO 60 IGIl1DP'•GIlID 11't •..I'!) 0260 "0 , 02b2 02f,3 02611 "'"0266 0267 """"0270 0271 0272 0273 02711 0275 0276 0277 0278 0279 0280 ""0282 "03 02ell ""0286 ""02fl8 ':.2fl9 0290 ""0292"., 02911 0~5 0296 ""0298 0299.". 0301 "'"0303 03011 0305 0306 0307 54 BOTlI,JI ·IlUIIGIlIOrl,, C•••••urECTs OP POOO ATnACTtOI, tr(~rOOo .EO.01 GO TO n1 fOOD"-0.0 00 1110 1Ii"',IIPooo 01STI •"8SISIl'l -POI011li1) 01STJ -US ISJPJ -raJOI iii)) npoIoRG _EIPI-PULPllt,-OISTI P'J8tTlllil"aISrJI rOOD""rooo"-rOlltllllltl·EKPUG 1'0 CO.TUDE Iflrooo".LT.rOOOI GO"'O Ul fDlllI,JI "PCATeT GO TO 1112 1'1 COIITIIIDE rtlll(I.J)·0.0 1112 CONTIMO!, C•••••EPrECTs or '!AlIT"T PPEFUEICE, tr IIlHA!•EO.01 GO T'"151 H"8"-0.0 DO 150 1t·1,llHAB DIST!"185(SIPl -HilI 0(11:1 ) 01STJ "USISJPl -KIIJOIIl'II np"RG "EIP I-HflALPIItI ·OlS1'1 -KBBET(KI "DIST"I flAB""H"U_HBIIDII(It,·EXPUG 150 COlITllIOr trlK"U .LT.HAB)GO TO 151 KDllll,JI "HUTeT GO TO 152 151 CONtIllat KDR(!,J)·0.0 152 COllTlllOl, C •••••TEIIPEJlATDRt uo 01SSCLf!0 OnGE.E"ECTS c TORlI,oJl •0.0 JrIGRIOllPl,JPl).GT.3.01 GO TO 180 TElll'-IGRtOjlPl.JPII -2.01·'000. LTEft •'nllP STEil"LTEII 001 "ITEIlP-STEIlI -100. GO TO 185 180 COlITtlO! TEIlP -(GRlOIIPl."PII -L01-1000. LTEII "TElIl' STEil"LT!1l 001 _l'IEIlP-S'tEIl)-100 • 185 COll1'lIlU! TEIlP -O.l-TEIlP TOl""_"8S ITlKP-TEIlPRrl DIllr'A "DOt -OOIIlU IrITOIr"".G1.TOIFrl GO TO 190· TOR(I,oJ)"TtllPOR GO TO 191 • '. 0308"0'OJ10 0)11 0312 0313 03111 0315 OJ16 OJ17 0318 0319 0320 0321 OJ12 0323 OJJ' 0)25 0326 0327 032 8 0329 0])0 OJll 0331 0333 OlH O]~5 OJ]6 OlJ1 OlJ8 OB9 03110 0311 1 01112 0313 OJU 03\15 OJII6 031i'7 0.1118 03119 0350 0351 0352 0353 OlS. 0355 55 190 CO'TIIlDI: TDllfI,JI •0.0 191 cOlITuor UIGOIr,.CT.0.01 GO TO 199 001(1,.11 •0.0 IF(DOnn .LT.0.0)r.0 TO 195 00111 •.11 •0011"01I GO TO 199 195 CGllTlIlOr DDR (I.J)O.C 199 COIlTIIIut 200 co,Tun c c C •••••USIIIG TilE "eot'!CUCllLATlnllS TO 08TAlII THE PROBlBtLITII!S ,op TN! c OIRZctIOII 0'Till!:'[IT STEP If UCII or TN!IIGKT POSSIBLE DureTI0.S. c 'SOil.0.0 DO 210 t-',3 00 210 Jat,3 'f1I.JI -C1.0 •10D II •.I1 •OIP.(I.JI •oOIlU,l1 •'01111,.11 1 •IIDR 11.,))'80f(I,JI Irlt .EO.2 •.1010.J .10.21 co TO 210 'SOil''5011 •'(I,oll 210 COIlTUOE T •ORUO(DUIl'f) PEl'0.0 DO 250 t.'.] DO 250 .1_1,3 I?II .t\1.2 .UO.J .to.21 GO TO 2115 PtR -C'II.J)""SUftl •p", Irt'.GT.nl)GO TO 2 ..5 GO TO 251 2..5 COIlTIIlO! 250 COIITIIlDI: 251 COIlTIIlOt: IP _IPRtS JP •JSlltS IPIlt:S IPlIlS 2. JPRtS JPRI:S 2. IPlST IP JPAST JP lOR I JOR -Jc c c .••..COftPDTIIlG Tftl:DlSTPlBunOIl or FHA c 1I0IST •110151'• 1 lr(IfDI5T .GT.N5TEPSI G:)TO 280 I?(lPRt5 .LI:.0 .OR.JPRtS .LI!.01 GO '1"0 280 I?IIPRt5 .GT.1Ill0R .011.JPR!S .GT.II1'UI GO TO 280 IS'_IS'• 1 SAtICIH)IPIIlS SUJ IIs'l -JU!S GO TO 100 280 CONTIIlO! F1 -DUIIDCODIIJ) I.. I,; Ii<'.0356 O~7 O]S, .'.,015' 0360.","., OJ63 OJ" 0365.,,'0367 '''80369 0310 0]7 1 0372 0373 O)H 037S 0316 0317 0378 037' 03110 OJ'"0382 Ola] OJU..., 0386 03111 0388 0389.m 03".m 0393 0394 03'5 0396 0397 0398 OJ"o~oo 0'0' O~O2 Oll03 0110. 0"105 01106 01101 01108 0"0' 0"0 56 ,.2 ...OU.1I0(DOll11 SIr.1'111:5 SJP a J.IlZS 5PII1:51 (11 SIP -0.5 •" SPUS,J 11)S.:I.-0.5 •,.2 CALL IIlIltUlll CALL SCtrIC(.1251 CALL COIU:eSPIZSt.5PI!SJ.1,-1) 1S1'~,• 1 Ttll 0.0 DO 285 1··',80 T!Il,1.O ...TZII •O.S IF(T!II ••LT.nil .OR.nllP .CT.T""PLOI co TO 2" TEllS ...(I)...TlftS."In •1.0 2811 COIITIIUIi TE"...'tEll •0.5 285 conlin Ir(IPl01 .zo.01 GO '!'O 290 CALL CURfZ(SUl,SUJ.ISf,O, 290 connot l'IIIS'.zg_,,;OISHI GO '!'O JOO GO TO 60 300 (01111101, c •.•..PlOTTIIlG 0'I~OTHEILIIS, TEll ...1EIIL II[(TEIlII -TVllllT'"mT 18 t 00.00 K-',lIl SJ •0.0 JlA • 0 DO 350 J·1."U 5,)•,) ltGT •1'00000.-16 -(SJ-SS.I --2-10000.I -:rt:t),ItEn -0.81 lrlUGT •U.0.01 co TO )20 s:r •85.-SOlTe lIlCTI Ir(SI .LT.1.0.011.SI .:;T.'0.01 GO T0)20 I •51 1r(GIlID(I.J).LT.2.01 ~o TO 320 "A •II:A • 1 AIUI (ICAI •51 UA!(II:AI •SJ GO TO 1'5 120 CO'TIIDr Ir fICA •EO.01 00 TO litO CALL ceRn:IAUI•.IdI"f.';A.OI u.-0 ICI -Itt • 1"0 COITIIIIE 1.5 COIITII10! SJ-SJ.1.0 150 CO IlTI Ie E TEll.1EII •"IEIIII1T 1100 COIITIIOI '01 connol CALL UDPL(11 C"LL DCUPL I • 0.11 0.12 011130." 0.1~ O.Hi 57 c C •••••PLOTTIIl.or T!IlPUATUP!HISTOCPAII C DO SOO 1-1.80 SOO CO.TIlIOI CUL KIST (TIIISA'1 CALL OOUPL "or". 0001 58 rOIlCTIC.OlluqrIlAIj,, C •••••t.J.ItCGAlITK lID D.C.IPnIG.197':>.TtClilIQOtS rOil trnCIE.T "ont CULO C SIIIOUTIOll.YOL.2.RAMOO~IOlIlItR GelERATIO.rOR Sr:ltCTEo PIIOBUILITT C OISTIIIIIOTIO.5.ORlL-IlSIC-l8,, 0002 OOOl 00011 ""0006 0001 0008 0009 0010 001' 0012 0013 00111 0015 OOU, 0011 0018 00'9 0020 0021 0022 0023 002/1 0025 0026 0021 0028 0029 OOJO 0031 0032 30 2D 1D CO""OI/"I RIIG/RA.(10)•G!II (101 •'IIRo.IlA St,"00,Pill St.rllOO DIll tiS 1011 50"(10) III TIGtR IlA.,Gt ••III S1'..C AR III ,SO II.PROO,liP 1100 0030 15-'.111110 5011(151_0. 001 IG-l.lIlflit '2-'.10-IG+l DO 1 11_1,'2 IS-U+IG-l PIIOO _u.(Iftl +Gt.(IGI KPROD-FROD/BAS! LPIlOD-PIlOD-II PROO+BlSt SU"IISI-SU II (1 SI +:'PIIOD IF (IS.LT ••IIPDI SOIl{JS.'I-SUII (15+1,+IIPIIOO CO'Tun .2-.1111[-1 DO S 1!-,••2 CA lin-SOl!(lSI/lIAS t 5011 {lSI-SOli (I 51-CAIlIIT-""st SO 11115.1)-50"115+'l+cAP:n COllTtlOt 5011 ('11101 -SOIlI'IIIlDl-"OO·(S 0"In 1I01/"ODI DO 20 IS-1.,II,D IlAIlIISI-SOIl1l51 PIlA._50"111 DO 10 15-2.1111'0 PIl ..-PI1II/P8l St.SO"(1 51 PR AII-P RAN/PIIO[ OIlA.O-fIlA. AtTUIl.n, 000' 59 SOBllOOTUE 1l""SET llUIDlT.llstllTIc C c •••••!.J.IlClOU'nl ..,D O.C.ll1n'G.'97">.TECUIQOtS 1'01 ErFIeI"T 1I0.T£CAILO C SIIIUUTIO••'OL.2.11"'0011 .UftIEIl CtlllltATIOIL 1'0'SELECTEO PROB"81L1~T C OISTUlIllTIO.5.OllfL-RSIC-38 C C « 0002 000' 000' 000' 000. 0007 0008 000. 0010 0011 0012 DOll oon 001 S 0016 0017 0018 00'. 0(120 OC:t 1 0022 0023 00" 0025 0026 Don 0028 0029 00)0 DOH DOll 0033 OOJfI 00)5 DOl'oon 00)8 OOH .. 100 '01 '"'00 )00 COllIlOIl/IIIRIGI ""1'0I,c;r:I(101.'''IIO,IIo\5£.1I00,'1I15£,'"00 I1Ttc;l:l Ill ••G1I,lllSI:.ClIllT ,II!!. 1I1U-Ill1IIT/fI 18-0 lolS!-' II'(!lA!!.G1.III,UI GO "n 100 I.St-llSt-. 18-18" GO TO " elst-2"11 rUSE-eASI: nlItO·"/II" 1!1I_'7_1'+('''"0_1) 1100-2--IIEII FIlOo-IICD DO 101 '-',10 IIUIIl)-O lOt.(').0 GUp,-s DO 200.*'." CAUTaO DO 190 '-','11110 GEIlI')-CtM (')-s.c lllIT CAIl.T·O IF (GU(Il).LT.lIl51:'roo n '90 CAIlIlY"Gt_IIlI/BlSt G!II (II)"Grllllli -!AS !-CA II liT COIT1IlO! COIlTIIlOr IST.UT"'STIIT 11"(IIS'l'A".L!.O)IlSTAI'T-200' IlSrARr-2-(IISUIIT/21-' DO )00 ,"'.....,D IIT!IIP-IISTART/US! RAlllll).IlSTlJt't-JT!IIrIU S! IISTAIlT""!"" PtTORI no • 0001 000' 000) 000' 000' 000' 0007 000' 000' 0010 DOl' 0012 001] 00111 001S 0016 0017 0018 00" 0020 0021 0022 60 SO IIOOTUI PLeTT C0880,/'1.8L.,.,I ••••'G' eOllllo./oIlU/A nn I (50.50)•.lIl1l AT'(50,501 COIl80./1111."/IA.18.I'1T' OIIIUSIO.II 15001 •YT (500) cau cucar CALL lea'L (-11 CALL ,&Gll'•••l1.1 CALL tItLE I''1511 DISTill lOTIO'",100.'1.1.Gll1'.6.'tlIPTII'.~.10 ••6., caLL CU'(O.,'SC&1.1!'.l00 ••0.,'SClLE',65.1 UU 100. UIl 0.0 !Illlt •60. Till'•0.0 I • 1 DO 50 ,J_l ••IIr.GP IX (JI •UUTI (t.ol) ncol)•URlTl(t.Jl SO COIlTUOI r.ALL COIl'!{II.1'f.lln:;p.OI UtO u ,"0 I, \ J • • 000' 000' 0003 000' 000' 0006 000' 0008 0009 0010 0011 0011 (01) 00" 00lS 0016 0011 0018 0019 0020 0021 00;2 002l 002' 002S 0026 61 501111001111:IlI!TITlIlSlY} OIlU:IIS1CII TEIlSUltOOI DIIlEISIO.CLA!SI10D).r1lEQ11001 COIlIlOII/IIPIlLOK/llrISIl SIIPISH •"PISII IICLASS •"0 lIolT • 1 PIlOR!•1." tStEP •2.(l DO '01-','0 51 • I CUSSlJl •20 ••0.S-51 ,nOlI)•TEIISUll a llOI/s,rlSll 10 COnIllll! CALL llGI'L(-11 CALL 'ACEClI ••l'.1 call TI'll.E('TEIlPEIlATUI!E SEU:CTI0IlS'.100. "TEIlPEJATUllES'.lQO,'llllll11EI'or PUMS',100.7.,'.) CALL U:UllC(1I5.) CALL G 1'1.1,1'(20 ••1ST!P ,II 0 ••0 •••seA u:I •rllOIlI) CALL tIlTIlOIIlOlT.9.50,Q.61 BIIlOTH •7./I"CLASS-ll CALL 811518110'111' call COIlY!(CLISS,PIlI:O,IlCLlSS.Ol CALL UOPL 101 Ii.ETun no l • ORNL/TM-6310 INTERNAL OISTRIBUTION •1. 2-11. 12. 13. 14. 15. 16. 17-26. 27. 2B-3B. 39. 40. 41. 42. 43. 44. 45. 46. 47. S.M.Ada .. S.I.Auerbach l.W.Barnthouse R.W.Brocksen R.l.Burgess O.S.Carro 11 S.W.Christensen C. C.Coutant D.K.Cox O.L.DeAngelis J.W.n""od W.R.Emanuel R.H.Gardner W.F.Harris K.D.Kum!r' J.B.Mankin J.S.Matt ice R.B.McLean R.V.O'Neill 4B. 49. SO. 51. 52. 53. 54. 55. 56. 57. 58. 59. 60. 61. 62-63. 64-65. 66. 67. 6B. H.Postma O.E.Reichle C.R.Richmond B.Schaich H. H.Shugart R.H.Strand E.G.Struxness J.S.Suffern R.I.Van Hook,Jr. W.Van Winkle.Jr. O.S.Vaughan H.Waddle J.A.Watts Biology library Central Research library laboratory Records Dept. laboratory Records.ORNl-RC ORNl Y-12 Technical libr"ary ORNl Patent Offi ce • • • EXTERNAL DISTRIBUTION 69.Richard O.Anderson,Cooper~tive Fishery Research Unit, University of Missouri,Columbia,MO 65201 70.C.A.Barans.South Carolina Marine Resources Research Insti- tute.P.O.Box 12559,Charleston.SC 29412 71.Roger A.Barnhart,Cooperative Fishery Research Unit.Humboldt State University,Arcata,CA 95521 72.T.L.Beitinger,Dept.of Fisheries and Wildlife.Texas A &M University.College Station,TX 77840 73.O.H.Bennett,Virginia Polytechnic Institute and State Univer- sity,Blacksburg,VA 24060 74.Theodore C.Bjornn,Cooperative Fishery Research Unit. University of Idaho,Moscow.10 B3B43 75.Charles F.Bryan,Cooperat~e Fishery Research Unit.Louisiana State University,Baton Rouge.LA 70B03 76.Robert l.Butler,Cooperative Fishery Research Unit, Pennsylvania State University.University Park.PA 16B02 77.O.S.Cherry,Center for Environmental Studies.Virginia Poly- technic Institute and State University,Blacksburg,VA 24060 7B.J.P.Clugston,Southeast Reservoir Investigations.Clemson University,Clemson.SC 29631 79.Daniel W.Coble,Cooperative Fishery Research Unit,University of Wisconsin.Stevens Point,WI 54481 BO.A.E.Dizon.National Marine Fisheries Service,Honolulu,HI 96Boo , • • '1 '1 I' "I. , I•, I,, ~ • • 81.l.Farges.IAEA,Karnter Ring 11.P.O.Box 590 A-lOll.Vienna, Austria 82.R.Don Estes,Cooperative Fishery Research Unit.Tennessee Technological University.Cookeville,TN 38501 83.F.E.J.Fry,University of Toronto.Toronto,Ontario,Canada 84.J.R.GafTlllon.Biology Department,DePauw University, Greencastle,IN 46135 85.J.W.Gibbons.Savannah River Ecological laboratory,Aiken,SC 29801 86.J.Gift.Ichthyological Associates,Inc.,New Jersey Marine Ecological Study,3201 Bayshore Ave.,Brigantine,NJ 08203 87.C.P.Goodyear,Power Plant Te~m.U.S.Department of the Interior.Ann Arbor,HI 48105 88.Richard W.Gregory,Cooperative Fishery Research Unit,Montana State University,Bozeman,HT 59715 89.Bernard l.Griswold,Cooperative Fishery Research Unit.Ohio State University,Columbus,OH 43210 90.Donald C.Hales,Cooperative Fishery Research Unit,South Dakota State University,Brookings.SO 57006 91.Richard W.Hatch,Cooperative Fishery Research Unit.University of Maine at Orono,Orono.ME 04473 92.Melvin T.Huish,Cooperative Fishery Research Unit.North Carolina State University,Raleigh.NC 27606 93.P.R.Kamath,Bhabha Atomic Research Center.Trombay, Bombay.India 94.J.R.M.Kelso,Canada Centre for Inland Waters,Burlington. Ontario,l7R 4A6,Canada 95.W.C.leggett,Biology Department.McGill University,Montreal. Canada 96.John A.Maciolek,Cooperative Fishery Research Unit. University of Hawaii.Honolulu,HI 96822 97.J.J.Magnuson,laboratory of limnology,Univ.of Wisconsin, Madison,WI 53703 98.O.Eugene Maughan,Cooperative Fishery Research U~it. Oklahoma State University.Stillwater.OK 74074 99.James A.McCann,Chief,Division of Fishery Research.U.S. Department of the Interior.Fish and Wildlife Service, Washington.DC 20240 100.R.W.McCauley.Biology Oepartme'ht.Wi lfred laurier University.Waterloo.Ontario.N2l 3C5.Canada 101.William J.McConnell.Cooperative Fishery Research Unit, Colorado State University,Fort Collins.CO 80521 102.J.H.McCormick,USEPA.Environmental Research laboratory. Duluth,MN 55800 103.J.McMaho.Atomic Energy of Canada.ltd.,Chalk River,Canada 104.J.W.Meldrin,Ichthyological Associates.100 S.Cass St .• Middletown,DE 19709 105.D.Miller.USEPA.Environmental Research laboratory. Narragansett.RI 02882 106.Robert J.Muncy.Cooperative Fishery Research Unit,I('·.i State University.Ames.IA 50010 1••I , I 107. •lOS. •109. 110. Ill. 112. 113. 114. 115. 116. 117. liS. 119. 120. •121. 122. 123. 124. 125. 126. 127-153. • • W.Neil 1.Dept.of Fisheries and Wildlife,Texas A &M University,College Station.TX 77840 John G.Nickum.Cooperative Fishery Research Unit,Cornell University,Ithaca,NY 14850 Garland 8.Pardue,Cooperative Fishery Research Unit, Virginia Polytechnic Institute and State University, Slacksbur9,VA 24061 John S.Ramsey,Cooperative Fishery Research Unit,Auburn University,Auburn,Al 36830 Roger J.Reed.Cooperative Fishery Research Unit.University of Massachusetts,Amherst.MA Olooe Robert E.Reinert.Cooperative Fishery Research Unit, University of Georgia,Athens,GA 30601 J.M.Reutter,F.T.Stone Laboratory,Put-In-Bay,OH 43456 W.Reynolds,Biology Dept .•Pennsylvania State University, Wilkesbarre,PA 1870e F.P.Richards,Ecological Analysts,Melville,NY 11746 W.Schikarski,Nuclear Research Center,Karlsruhe,Federal Republic of Gennany M.Schneider,Ecosystems Dept.,Battelle Northwest,Richland, WA 99352 Carl B.Schreck,Cooperative Fishery Research Unit,Oregon State University,Corvallis,OR 97331 S.A.Spigarelli,Argonne National Laboratory,Argonne,IL 60439 J.R.Stauffer,Gunter Hall,Frostbury State College, Frostbur9,HD 21532 Jerry C.Tash,Cooperative Fishery Research Unit,University of Arizona,Tucson,AZ 85721 M.Van deu Avyle,Cooperative Fisheries Unit,Tennessee Tech. University,Cookville,TN 38501 t.Wilson,Dept.of Forestry,Wildlife,and Fisheries, University of Tennessee,Knoxville,TN 37916 Richard R.Whitney,Cooperative Fishery Research Unit, University of Washington,Seattle,WA sa105 Richard S.Wydoski,Cooperative Fishery Research Unit,Utah State University,Logan,UT 84321 Research and Technical Support Division,DOE-ORO. Technical Infonnation Center,Oak Ridge,TN 37830