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# Fisheries Management BIOL 432

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This 12 page Class Notes was uploaded by Urban Bauch on Tuesday October 13, 2015. The Class Notes belongs to BIOL 432 at Lake Superior State University taught by Geoffrey Steinhart in Fall. Since its upload, it has received 30 views. For similar materials see /class/222328/biol-432-lake-superior-state-university in Biology at Lake Superior State University.

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Date Created: 10/13/15

128 CHAPTER 6 Processes that regulate population size can be categorized as density dependent or density independent Densitydependent factors such as food availability preda tion cannibalism diseases parasites and availability of spawning sites vary with population size These factors usually operate in a compensatory manner so that extremes in population size are moderated by their action For example with increas ing sh population density food availability per sh declines leading to slower growth and poorer condition of the surviving fishi These responses may in turn lead to increased vulnerability to predation or cause delayed sexual maturation which would cause a decline in population size because of reduced rates of survival and reproduc tion A low population density could lead to rapid growth and maturation relatively high survival and reproduction and increased population size Density independent processes are not affected by population density Fac tors such as water temperature river flows lake levels drought and other fea tures of the environment may affect a population in ways that are not in uenced by the number of fish present The relative importance of density dependent and densityindependent fac tors in regulating population size can vary among ecosystems and life stages of a species In systems where the environment is relatively stable or undergoes recur ring longterm cycles density dependent processes tend to produce an equilib rium level about which the population varies in response to density independent environmental factors Because oceans and large lakes provide relatively con stant environments they often support fish populations that are regulated in this manner An exception to this relative constancy is the wellknown El Nino effect which can substantially alter the thermal environment Ecosystems with relatively unstable and unpredictable physical characteristics have fish populations that are regulated to a greater extent by densityindependent factors Examples of these systems are streams rivers and some reservoirs which are subject to in uence by storms drawdowns and temperature changes as well as other weather factors For many freshwater fishes the period of reproduction including spawning and egg incubation occurs during a relatively short period in spring when weather conditions water levels turbidity and other factors can be unstable Hence egg hatching success and the resultant number of young produced may be a function of densityindependent factors Survival of juveniles and adults is generally thought to be regulated primarily by densitydependent processes although in many fresh water situations the most pronounced in uence of increased population size is reduced growth Subsequently reduced growth can lead to increased mortality from predation because smaller fish are more vulnerable Older fish are better capable of surviving or avoiding extremes of physical environmental factors than are eggs and larvae Most freshwater fish populations are characterized by considerable variation in the number of young produced annually Such variation is most pronounced for species with brief spawning periods or those that spawn in variable unpredict able environments The extent to which variation in reproduction in uences the adult population depends on the rate of survival of the group of fish spawned in a given year termed a cohort or year class and the age structure of the population POPULATION DYNAMICS 1 29 The overall population abundance of a longlived species will show relatively less annual variation than will a short lived species subjected to the same annual variation of reproduction A key requirement for management of a fishery is knowledge of the pro cesses and factors that control survival of young fish to the age at which they are mature or reach a desired size The relative abundance of a yearclass termed year Class strength at any early developmental stage may show no obvious relationship to either the abundance of the spawning population that produced it or the number of fish that eventually is added to the adult population therefore knowledge of the processes that regulate the dynamics of yearclasses during their development is required to prescribe effective management programs The idea that year class strength is established during some specific relatively distinct phase of a species life cycle has been applied to fish populations The term critical period is defined as the time when natural regulatory factors determine the eventual abundance of a cohort The concept that a critical period exists during the early life of fishes is consistent with the belief that natural processes of population regulation have their greatest in uence on the youngest life stages The critical period has usually been postulated to occur during early larval development at a time when the fish become reliant on exogenous food Cashing and Harris 1973 Initially larvae use energy contained in the yolk sac to develop functional mouth parts and become capable of swimming and foraging for food At the point of transition to external food larval energy reserves are low and the fish are vulnerable to weather extremes food shortages and predation Henco biologists have often concluded that the number of fish surviving to juvenile and adult stages is functionally determined during the larval stage It is possible that a critical period may occur at later developmental stages In temperate inland waters seasonal changes in food availability can lead to a criti cal period during the first winter of life This has been demonstrated for juvenile largemouth bass in reservoirs and ponds Shelton et al 1979 Miranda and Hubbard 1994a 1994b Ludsin and DeVries 1997 Young largemouth bass initially feed on zooplankton and other small aquatic invertebrates but switch to larger inverte brates and small fish as they grow Individuals in a cohort that initially grow faster can realize an even greater growth and survival advantage because of their in creased size and greater flexibility in prey use During fall and winter prey abun dance can decline to an extent that food becomes limiting especially to the small est individuals that have the least flexibility in prey selection Consequently these individuals can have reduced condition and suffer greater losses to predators disease and other stresses in these examples population regulation is a function of density dependent processes but the intensity of their in uence is expected to vary with severity of fall and winter weather conditions In a study of smallmouth bass Watt 1959 showed convincingly that ageO fish that had not attained a critical size by October would not survive the winter Knowledge of the existence and timing of a critical period during a species life cycle can provide guidance for making management decisions Using large mouth bass as an example one can see that in systems regulated like those de 1 3 0 CHAPTER 6 scribed above management efforts should not be directed at increasing the num ber of young during the fall because survival is regulated by food availability during winter A more effective approach might be to use procedures that would enhance growth in summer and fall thereby increasing overwinter survival It is also clear from this example that estimates of cohort abundance shonld be made after not before the critical period if one intends to use the data to forecast year class strength in a fishery 622 Effects of Fishing on Population Dynamics Uncxploited stocks are typified by a high proportion of old fish slow indi vidual growth rates and low rates of total annual mortality Clady et a1 1975 Goedde and Coble 1981 The preSence of old fish in poor body condition is often reflective of little or no exploitation When unexploited populations are opened to fishing length and agefrequency distributions typically shift toward smaller and younger fish mean age declines and total mortality increases For stocks that are naturally regulated by densitydependent processes it is also ex pected that individual growth rates of surviving fish would increase after exploi tation because of reduced intraspecific competition Backiel and Le Cren 1967 At initial stages of exploitau39on a population usually is relatively stable because the abundance of adult fish is not reduced to an extent that reproduction is af fected In fact it is possible that the reduction in numbers of larger older fish could lead to increased survival of young because of reduced cannibalism Ricker 1954 Management objectives in these cases usually are directed at maximizing the recreational or economic benefit that can be obtained from each fish newly added to the population by reproduction However if harvest is further increased the reproductive potential of the population may be reduced to an extent that the adult population declines substantially At such times management goals are ad justed to help assure adequate reproduction in the population Angler catch rates number or weight of fish caught per unit of effort often are high for newly exploited stocks but decline rapidly thereafter Redmond 1974 estimated that during the first 3 d that five Missouri lakes 9 83 ha were opened to angling 39 66 of the largemouth bass populations was removed by anglers Similarly Goedde and Coble 1981 showed that 1 month s angling in a recently opened Wisconsin lake 5 ha reduced the number of harvestablesize pumpkin seed yellow perch largemouth bass and northern pike by 74 86 53 and 46 respectively High initial exploitation rates are partly a function of intense angling pressure but unexploited stocks may contain a large proportion of naive fish that are highly vulnerable to exploitation The effects of exploitation on the abundance of mature fish in a population is determined by the extent to which rates of mortality and replacement by repro duction are altered For a population that is not fished all growth and reproduc tion are balanced by natural mortality Ricker 1975 and the population size is expected to remain close to some equilibrium level With the addition of harvest mortality increases and the number of mature fish is reduced The longterm effects of harvest on the population are a function of the new rates of mortality POPULATION DYNAMICS l 3 1 growth and reproduction An excessive rate of harvest may tip the balance and fishing may steadily reduce a population to a level at which harvest is no longer economical or possible More commonly however a new equilibrium population level is leached because the decreased abundance of mature fish from harvest allows the remaining fish to respond with l a greater rate of growth 2 a re duced rate of natural mortality or 3 greater rates of reproduction and survival of young Ricker 1975 Fisheries managers use estimates of these rates and popula tion size to determine appropriate levels of harvest for fish stocks Ricker 1954 developed generalized models of the relationships between abundance of adult fish stock size and the number of new fish surviving to reach an exploitable size or age termed recruitment for stocks that are regulated by density dependent factors Because populations vary in age structure fecun dity and relative importance of densitydependent and densityindependent mor tality factors there are many ways that populations can respond to a reduction in the number of adults The possibilities range from direct proportionality between the number of adults and recruitment to total independence of these two mea sures Stock recruitment models have proven useful primarily in marine fisher ies for predicting population responses to changes in exploitation and for esti mating optimum levels of harvest Application of stock recruitment models to freshwater fisheries has been less common 623 Quantification of Dynamics A stock is the biological unit of interest in studies of fish population dynam ics Stocks are expected to respond differently to exploitation because of differ ences in growth or mortality rates They can often be defined as geographically isolated and biologists generally attempt to gather information for distinct stocks and manage each separately The term stock is almost synonymous with biologi cal usage of the term population which is defined as a collection of interbreeding organisms having its own birth rate death rate sex composition and age struc ture The major distinction is that stock refers to the biological unit that is ex ploited it may be a subset of a larger population or a collection of species that is exploited as a single unit Delineation of stocks and descriptions of their reproduction behavior and genetic characteristics are major areas of study in fisheries management such studies are necessary to define the extent to which management actions may in fluence a particular fishery Stocks of many inland fish species are easily de ned spatiallypopulations that occur in isolated lakes or are geographically distant obviously represent different stocks Marine fisheries managers often face a diffi cult task of stock identification because of species life histories that include ex tensive migrations that lead to mixing of stocks It is also difficult in some fresh water situations to know if a particular species within a body of water comprises one or more stocks This problem is most common in large river systems where the potential for evolution of distinct stocks is greater than it is in most lakes Migratory behavior of adults may lead to aggregations of individuals from sev eral stocks in one location In this situation management actions in uencing the 13 2 CHAPTER 6 species abundance and mortality at this location would affect several stocks si y us 1 actions directed toward improving sur vival at one stock s spawning grounds might not have the expected in uence on the overall abundance of adults because recruitment from other stocks is unaf fected Traditionally the most important biological statistics of fish populations have been population size total mortality rates at successive ages the fractions of total mortality attributable to natural mortality and fishing mortality individual growth rates recruitment rates and the rate of surplus production Ricker 1975 These parameters are needed to determine the greatest amount of biomass that can be harvested from a stock on a sustained basis For recreational fisheries typical of inland waters management objectives usually are far more complicated than simply maximizing harvest which sug gests that managers need to collect information beyond the statistics listed above Fisheries that illustrate this need emphasize catch and release fishing for fun or trophy angling where success is measured in terms of recreational enjoyment rather than biomass harvested Management objectives of inland fisheries fre quently address the need for maintaining balance in systems regulated by den sitydependent processes Here the size distribution of fish available to anglers can be more important than total harvest or yield In such cases aesthetic and economic values of a given fishery may not be related simply to stock biomass meaning that other measurements will be needed to monitor management suc cess These measurements might include estimates of the number of trips or hours fished by anglers economic benefits derived from a fishery number of hours required to catch a trophy fish number of fish caught and released number of fishing licenses sold and various indices of condition of the fish population itself Methods for conducting angler surveys to determine fishing effort catch rates and harvest have been reported by Malvestuto 1996 and procedures for deter mining social and economic values are described in Smith 1983 Weithman 1986 and Chapter 8 63 METHODS OF ESTIMATING POPULATION PARAMETERS 631 Estimation of Population Size Estimates of population size often provide the information needed for malt ing fisheries management decisions Research or survey programs that track fluc tuations in numbers of sh in a stock are used to identify in uences of environ mental factors and human exploitation and ultimately identify effective management strategies As such population monitoring activities often make up a significant proportion of a fisheries biologisfs workload This section intro duces three commonly used methods of population estimation counts on sample plots mark and recapture and decline in catch per unit effort Otis et al 1978 Seber 1982 White et al 1982 Brownie et al 1985 contain information on more advanced models POPULATION DYNAMICS l 3 3 6311 Counts on Sample Plots An estimate of population size can be obtained by determining the average density of animals per unit area in sample plots and multiplying this value by the total area covered by the population Seber 1982 outlined three main steps in developing a sampling scheme of this type H The size and shape of the sample area or plot should be determined This choice will be a function of the behavior of the animals to be evaluated physi cal features of the habitat and practical constraints associated with the sam pling gear Plots can cover a standardized area and be shaped as squares circles or rectangles termed quadrats or plots could consist of nonoverlapping strips running through the population area termed transects N The number of plots to be sampled should be established in advance Sampling of more than one plot is necessary to estimate sampling variance and the de sired level of precision of the population estimate can be used to determine the number of plots required t i The sample plots should be located randomly so that valid statistical estimates of sampling error can be calculated This method of estimation is used primarily when all members of the target population within each sample plot can be counted with reasonable certainty For example plots could be established by using nets to block off sections of a small stream and fish could be counted following removal with toxicants or electro shing Another example is the use of a seine to block a standardized quadrat along the shoreline of a lake or reservoir followed by application of toxicants such as rotenone to facilitate removal and counting of the fish Counts of fish made per unit of time or volume can also be used to estimate population size provided that the steps outlined above are followed For example counts of larval fish or plankton samples can be expanded to estimate population size provided that samples are collected randomly and have a standard sample volume An estimate of the population size N in an area can be calculated from the individual plot counts as follows E 61 where A is the size of the study area a is the size of the plot same unit of measure as A and 17A is the average number of animals counted per sample plot The variance VN of the population estimate is calculated as follows l 34 CHAPTER 6 where Vn is El n 2 s l n is the number of animals counted in the ith plot and s is the number of plots used Cochran 1977 An approximate 95 confidence interval for the true population size can be calculated as Ni r m V17 in designing a study it is important to predetermine a desired level of preci sion to be achieved for estimates of important parameters A convenient way of expressing the precision is to calculate a coefficient of variation CV which is defined as the square root of the variance of an estimate divided by the estimate itself Thus CV is a unitless measure of the relative amount of variation abont an estimate When using counts from sample plots to estimate population size we define the coefficient of variation to be CV Vail A coefficient of variation of 020 or less is usually judged to be adequate The number of plots sampled is a principal determinant of the precision of population estimates from simple random sampling designs Prior to conducting fieldwork a researcher should determine the number of plots that need to be sampled to achieve the target level of precision Cochran 1977 The above sampling procedures are termed simple random sampling when all potential sampling plots transects or intervals within their respective population areas or times have an equal chance of being included in the sample Thus every animal in the population has an equal chance of being included in the sample provided that the members of the population are randomly or uniformly distributed throughout the area Fish populations however are rarely distributed randomly and more typically are aggregated in certain areas or times In such cases estimates from equation 61 are not biased but have poor precision because of extreme variability in counts among plots If sh distribution patterns are known prior to conducting a population study precision may be improved by subdividing the study area into zones or strata ex pected to have different fish densities and selecting sample plots at random within each stratum This is termed stratified random sampling 6312 Mark and Recapture The simplest markrecapture technique of population estimation requires one sample period in which fish are collected marked and released and another pe riod in which fish are collected and examined for marks This method is the Petersen index alternatively known as the Lincoln index which is based on the assump tion that the proportion of marked fish in the second sample estimates the propor tion of marked fish in the total population The estimator of population size is a 63 where M is the number of fish initially marked and released C is the number of fish collected and examined for marks in the second period and R is the number of recaptures ie previously marked fish found in C This estimate applies to the population present during the first sample period not the recapture period POPULATION DYNAMICS l 3 5 The Petersen index can give biased estimates of population size when the number of sh sampled is low but several modifications of equation 63 have been proposed to help correct this bias Bailey s 1951 modification is MCl N Rl 6394 with variance A MZC 1 C R VN 6 5 Rl2R2 39 Bailey s modification is used in cases in which sampling during the recapture period is conducted with replacement meaning that each fish is returned re placed to the population after it is examined for marks and thus is eligible to be included in the sample again Chapman 1951 recommended using A MlCl N l Rl 6396 with variance M lC lM RC R WV R 12 R 2 67 This model is used when sampling during the recapture period is done without re placement as in cases in which anglers examine their catch for marks or when all fish collected in the recapture period are marked in a way different from the first mark and then released Differences among population estimates obtained from equations 63 64 and 66 would probably be of little significance in making fishery manage ment decisions if the number of fish recaptured R exceeds 7 Several important conditions or assumptions must be met to obtain valid esti mates using the Petersen index or its modifications 1 marked fish do not lose their marks prior to the recapture period 2 marked fish are not overlooked in the recapture sample 3 marked and unmarked fish are equally vulnerable to cap ture in the recapture period 4 marked and unmarked fish have equal mortality rates during the interval between the marking and recapture sample periods 5 following release marked animals become randomly mixed with the unmarked ones or recapture effort is distributed in proportion to the number of animals in different parts of the population area and 6 there are no additions to the popula tion during the study interval Assuring that these conditions are satisfied is one of the most difficult aspects of estimating population size with the Petersen method Any factor causing underrepresentation of marked fish in the second sample will lead to overestima 136 CHAPTER 6 tion of the population size This could result from poor mark retention failure to recognize all recaptures in the second sample impaired survival of marked fish and immigration of new thus unmarked animals before the recapture sampling Conversely any factor leading to overrepresentation of marked fish in the second sample caused perhaps by increased susceptibility of marked animals to capture will result in underestimation of the true population number Several methods may be used to establish confidence intervals for Petersen type population estimates These have been thoroughly developed for the most common sampling design one in which sampling is done without replacement during the recapture period For this design the random Variable is the ratio RC which estimates MN for the population and the distribution of RC is hypergeo metric Unfortunately neither tables nor explicit formulas are available for deter mining exact confidence intervals for the hypergeometric distribution Conse quently various approximations based on the binomial Poisson or normal distributions have been used depending on the magnitude of RC and the values of M C and R for a particular study Scber 1982 Precision and accuracy of Petersen estimates are affected by the numbers of fish marked and subsequently checked for marks Charts prepared by Robson and Regier 1964 can be used to determine values of M and C required to pro duce Petersen population estimates expected to differ from the true population number by no more than 50 25 or 10 at the 95 level of confidence They recommend the 50 level for preliminary surveys 25 for management studies and 10 for research evaluations Use of the charts requires an initial guess of population size A particular combination of M and C can be chosen as a function of the relative costs associated with marking fish and sampling for recaptures Mark recapture methods of population estimation that use two or more sample periods for marking animals are termed multiplecensus procedures The simplest of these was originally described by Schnabel 1938 Fish are collected from the population marked and released for a series of samples the numbers of recap tures and unmarked fish collected in each sample are recorded Assumptions of the method are identical to those of the Petersen index except that no mortality is allowed during the study Because of this requirement the multiple census is most appropriate when sampling periods are closely spaced and restricted to a rela tively short overall period so that the occurrence of mortality would not have a great influence on the validity of the population estimate Table 61 illustrates typical data and computational procedures for this method The Schnabel population estimation formula is C tl C39M 2quot R t 68 11 I where the subscript 1 refers to the individual sample period and n is the number of periods POPULATION DYNAMICS 1 3 7 Table 61 Data records and calculations for Schnabel 1938 multipleccnsus population estimate Total number of Number of fish captured marked Sh 31335551 prior to sample period M Sample period 7 Marked R Unmarked Total C X M l 0 150 150 0 0 2 22 203 225 150 33750 3 26 86 112 353 39536 4 53 150 203 439 89117 5 38 80 118 589 691502 6 2S 5 3 81 669 541189 7 87 150 237 722 171114 Total 2511 457208 For our example Table 611 AL LICth 457208 7 R 254 11 1 800 Confidence limits are determined by first computing the variance of lN be cause the inverse of N is more normally distributed than is N itself 2111 vnzv n 7 EMCMJ 69 We next determine a 95 con dence interval for UN as llNi1196th1N and compute the inverses of the limits to find the confidence interval of N itself For our example lN 11800 0000556 and A 4 V1N l539 71215x10 9 457208 From these the 95 confidence interval for UN is 0000488 0000624 and by calculating the inverses of these limits we obtain a confidence interval for N of 1602 2049 For cases in which the total number of recaptures in the study is small say less than 25 We do not expect UN to be normally distributed We then must calculate confidence limits by alternative methods This can be done by using tables of the Poisson distribution sec Ricker 1975 to determine 95 limits for the total number of recaptures and then substituting these values into the denomi nator of equation 68 to determine limits for N l 3 8 CHAPTER 6 6313 Removal Methods Population size can be estimated from data on fishing effort and catch rates Several estimators have been developed all of which are based on the theory that the number of fish caught per unit of effort will progressively decline as members of the population are removed The most common methods assume that 1 all members of the target population are equally vulnerable to capture 2 vulner ability to capture is constant over time and 3 there are no additions to the popu lation or losses other than those due to fishing during the study interval Addition ally one must be able either to quantify fishing or sampling effort or to create a sampling situation in which equal effort is expended in consecutive sampling periods Examples of ways that effort could be quantified include hours spent electrofishing angler trips vessel days seine hauls or gill nets fished The Leslie and DeLury methods are used in cases in which sampling effort may vary among periods These models which are part of a general class of methods described by Schnute 0985 have been used mainly for large popula tions for which there is low probability that an individual fish will be caught during a single unit of effort Typical applications have included commercial sh eries for which data on sampling effort and catch are obtained by monitoring the fishers but Leslie models have recently been applied to reservoir stock assess ments Maceina et a1 1993 1995 The Leslie method of estimation assumes that the number of fish caught per unit effort during some time interval 2 is proportional to the number of fish present at the beginning of the interval CZ 7qN 610 where C is the catch during period r is the amount of fishing effort during period t N is the number of fish present at beginning of period t and q is the catchability coefficient Because the method assumes that the population is closed to additions or losses other than shing we can express M as a function of the original population size NO minus the total number of sh caught and removed Kr prior to time I as NN0 K 611 We can substitute this expression for M into equation 610 and obtain C qNo 4Kp 612 f which is a linear relationship of the form Y a bX where Y CIf and X K A plot of catch per effort C versus cumulative catch X will approximate a straight line with slope actually the absolute value of the slope equal to q and intercept of 1N We can use linear leastnsquares regression methods to estimate the slope and intercept and then estimate the original population size as POPULATION DYNAMICS 139 A intercept qNO N 5 M i 613 slopej 1 When the fraction q of a population that is taken by a given unit of fishing effort is small say less than 002 lt2 of the population DeLury s modification of the Leslie model is preferred The DeLury method also is based on the premise that catch per effort is proportional to population size equation 610 and as sumes a closed population other than losses due to removal but uses a different expression of population decline N Noe qEr 614 where E is the cumulative total effort expended prior to period t and other vari ables are defined as before This implies that the population declines in propor tion to total effort whereas the Leslie method assumes that the decline is a func tion of the total catch Substituting the expression of NZ from equation 614 into equation 610 We get Ctf qN0e qE39 By taking the natural log of both sides we obtain 10ngfgtlogltqNogt qE ism which is also of the form Y a 12X with Y loge CYfr and X E39 So in this method we can plot the natural log of catch per effort Versus cumulative effort and again use linear leastsquares regression to estimate the slope and intercept The estimate of population size is inierce l A e F No SIOpei 616 Confidence limits for population estimates obtained from the Leslie and Delury methods are calculated from intermediate statistics obtained when performing the leastsquares regression and they may be determined using Ricker 1975 Because regression techniques are used these methods of estimation require a minimum of three sample periods Precision can be improved by increasing the number of sample periods but the in uences of immigration or natural mortality on accuracy of the estimates could become significant if the duration of the study is extended Removal methods of population estimation are also used in situations in which the catchability of fish is high and equal effort is expended in each sample period The most common example of this is sampling small streams where sections are blocked off with netsand fish are collected by making consecutive passes with electrofishing gear eg Thompson and Rahel 1996 Each pass represents one sample period Fish captured during each period can be released outside the sample reach or marked and then released back into the sampling area Marking in this case can be used to remove fish from consideration in subsequent samples A model for population estimation was described by Zippin 1956 1958 as

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