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This paper describes my research on fish population dynamics, which has aimed to improve the information available for management and conservation. Through numerous collaborations, my research program addressed three main objectives. (1) Increase the understanding of spatial and temporal variation in productivity of fish populations. (2) Quantify uncertainties and risks in fishery systems and their implications for management and conservation. (3) Develop methods to reduce those uncertainties and risks. To help young scientists, I present 11 general lessons, as well as some specific advice, that emerged from that research. The general lessons include pursuing a path of continuous learning, going beyond your comfort zone to broaden your skills and knowledge, and collaborating with others. More specific advice for fisheries scientists includes evaluating the bias and precision of parameter estimation methods via Monte Carlo simulations, and considering multiple models of whole fishery systems. This paper also illustrates, with examples, how the understanding of some aspects of fish population dynamics has evolved, at least from the limited perspective of my own group's research.

We expand on previous analyses of environmental factors related to productivity of Chinook salmon (Oncorhynchus tshawytscha) populations by analysing data on adult recruits per spawner from 24 wild (not hatchery) Chinook salmon stocks from Oregon through western Alaska. To determine the degree to which changes in productivity are shared and to help identify environmental variables that might be related to those changes, we estimated the magnitude and spatial characteristics of positive correlations in productivity trends among stocks separated by various distances. We used dynamic factor analysis to characterize shared time trends in productivity and found that these trends were most closely associated with the North Pacific Gyre Oscillation and, to a lesser extent, with the location of the bifurcation in the North Pacific Current as it reaches North America’s west coast. Chinook productivity patterns of separate populations have also become more synchronous in recent years, similar to results reported for other species of Pacific salmon. Such recent changes may reduce the resilience of the species to effects of climate change and habitat modification.

Pathways linking climate to population dynamics of higher-trophic-level fish species such as Pacific salmon often involve a hierarchy in which regional-scale physical and biological processes mediate the effects of large-scale climate variability. We used probabilistic networks to investigate 17 potential ecological pathways linking climate to Oregon coho salmon (Oncorhynchus kisutch) recruitment. We found that pathways originating with the Pacific Decadal Oscillation were the most influential on recruitment, with the net effect being two to four times greater than for pathways originating with the North Pacific Gyre Oscillation or the Oceanic Niño Index. Among all environmental variables, sea surface temperature and an index of juvenile salmon prey biomass had the greatest effects on recruitment, with a 76% chance of recruitment being equal to or below average given that ocean temperatures were above average and a 34% chance of recruitment being below average given that prey biomass was above average. Our results provide evidence that shifts in climate patterns could strongly influence recruitment simultaneously through multiple ecological pathways and highlight the importance of quantifying cumulative effects of these pathways on higher-trophic-level species.

We investigated spatial and temporal components of phytoplankton dynamics in the Northeast Pacific Ocean to better understand the mechanisms linking biological oceanographic conditions to productivity of 27 pink salmon (Oncorhynchus gorbuscha) stocks. Specifically, we used spatial covariance functions in combination with multistock spawner–recruit analyses to model relationships among satellite-derived chlorophyll a concentrations, initiation date of the spring phytoplankton bloom, and salmon productivity. For all variables, positive spatial covariation was strongest at the regional scale (0–800 km) with no covariation beyond 1500 km. Spring bloom timing was significantly correlated with salmon productivity for both northern (Alaska) and southern (British Columbia) populations, although the correlations were opposite in sign. An early spring bloom was associated with higher productivity for northern populations and lower productivity for southern populations. Furthermore, the spring bloom initiation date was always a better predictor of salmon productivity than mean chlorophyll a concentration. Our results suggest that changes in spring bloom timing resulting from natural climate variability or anthropogenic climate change could potentially cause latitudinal shifts in salmon productivity.

Assessments of extinction risk based on population declines are widely used, yet scientists have little quantitative understanding of their reliability. Incorrectly classifying whether a population is declining or not can lead to inappropriate conservation actions or management measures, with potentially profound societal costs. Here we evaluate key causes of misclassification of decline status and assess the reliability of 20 decline metrics using a stochastic model to simulate time series of population abundance of sockeye salmon (Oncorhynchus nerka). We show that between-year variability in population productivity (process variation) and, to a lesser extent, variability in abundance estimates (observation error) are important causes of unreliable identification of population status. We found that using all available data, rather than just the most recent three generations, consistently improved the reliability of risk assessments. The approach outlined here can improve understanding of the reliability of risk assessments, thereby reducing concerns that may impede their use for exploited taxa such as marine fishes.

Although there are many indicators of endangerment (i.e., whether populations or species meet criteria that justify conservation action), their reliability has rarely been tested. Such indicators may fail to identify that a population or species meets criteria for conservation action (false negative) or may incorrectly show that such criteria have been met (false positive). To quantify the rate of both types of error for 20 com- monly used indicators of declining abundance (threat indicators), we used receiver operating characteristic curves derived from historical (1938-2007) data for 18 sockeye salmon (Oncorhynchus nerka) populations in the Fraser River, British Columbia, Canada. We retrospectively determined each population's yearly status (reflected by change in abundance over time) on the basis of each indicator. We then compared that popu- lation's status in a given year with the status in subsequent years (determined by the magnitude of decline in abundance across those years). For each sockeye population, we calculated how often each indicator of past status matched subsequent status. No single threat indicator provided error-free estimates of status, but indicators that reflected the extent (i.e., magnitude) of past decline in abundance (through comparison of current abundance with some historical baseline abundance) tended to better reflect status in subsequent years than the rate of decline over the previous 3 generations (a widely used indicator). We recommend that when possible, the reliability of various threat indicators be evaluated with empirical analyses before such indicators are used to determine the need for conservation action. These indicators should include estimates from the entire data set to take into account a historical baseline.

Uncertainties prevalent in fisheries systems result in deviations between management targets and observed outcomes. As an example of attempting to deal with such uncertainty, fishery managers of sockeye salmon Oncorhynchus nerka from the Fraser River, British Columbia, use environmentally based management adjustment (MA) models to forecast indices of in-river loss of adults as they migrate upstream to spawn. Losses forecasted by MA models are directly incorporated into estimates of total allowable catch, resulting in harvest reductions that aim to increase the probability of achieving spawning escapement targets. However, the relative forecasting success of different MA models has not been rigorously assessed. Therefore, we used a suite of forecasting and hindcasting metrics to rank the performance of numerous MA models. We found that the rank of each model varied across sockeye salmon stock aggregates (i.e., run timing groups) and depended on the performance measures chosen for evaluation. Altho...

Complex dynamics of animal populations often involve deterministic and stochastic components. A fascinating example is the variation in magnitude of 2-year cycles in abundances of pink salmon ( Oncorhynchus gorbuscha ) stocks along the North Pacific rim. Pink salmon have a 2-year anadromous and semelparous life cycle, resulting in odd- and even-year lineages that occupy the same habitats but are reproductively isolated in time. One lineage is often much more abundant than the other in a given river, and there are phase switches in dominance between odd- and even-year lines. In some regions, the weak line is absent and in others both lines are abundant. Our analysis of 33 stocks indicates that these patterns probably result from stochastic perturbations of damped oscillations owing to density-dependent mortality caused by interactions between lineages. Possible mechanisms are cannibalism, disease transmission, food depletion and habitat degradation by which one lineage affects the other, although no mechanism has been well-studied. Our results provide comprehensive empirical estimates of lagged density-dependent mortality in salmon populations and suggest that a combination of stochasticity and density dependence drives cyclical dynamics of pink salmon stocks.

An important management challenge is to maintain productive populations of Pacific salmon ( Oncorhynchus spp.), despite highly variable environments and our weak understanding of future climatic conditions and mechanisms that link them to salmon. This understanding could be improved by including environmental covariates in salmon population models and applying advanced “meta-analyses” to large data sets to better estimate underlying functional relationships. However, the performance of such models needs to be determined in the context of an overall system. We therefore simulated a 15-population salmon fishery system and compared the performance (in terms of catch and an index of conservation concern) of 10 forecasting and stock assessment models, ranging from simple to complex, by stochastically simulating components of a salmon fishery using a “closed-loop simulation” (or “management strategy evaluation”) under a variety of plausible future climatic scenarios. We found that complex models perform better in some situations. However, their incremental benefits are small and are swamped by the large variability in outcomes of management actions caused by “outcome uncertainty”, which reflects noncompliance of fishing vessels with regulations as well as variation in catchability. Reduction of this outcome uncertainty should therefore be a top priority, as should evaluations of more complex stock assessment models before adopting them.

Using comprehensive data sets for chum salmon Oncorhynchus keta (40 stocks) and sockeye salmon O. nerka (37 stocks) throughout their North American ranges, we compared the retrospective performance of 11 models in preseason forecasting of adult abundance. Chum and sockeye salmon have more complicated age structures than pink salmon O. gorbuscha, which we investigated previously (Haeseker et al. 2005), and this complexity presents new challenges as well as opportunities for forecasting. We extended our previous work to include two new forecasting models that make use of leading indicators: either the survival rate of earlier-maturing pink salmon from the same brood year (Ricker pink salmon index model) or the abundance of earlier-maturing siblings (hybrid sibling model, a new version of the standard sibling model). No single forecasting model was consistently the best for either chum or sockeye salmon, but the hybrid sibling model frequently performed best based on mean absolute error, mean percen...

Estimates of the total stock biomass of marine invertebrates that aggregate, such as red sea urchins Strongylocentrotus franciscanus, are often highly uncertain, partly because it is difficult to estimate their density. To improve estimates, we used 200 simulated red sea urchin populations with spatial and numerical properties based on field data to evaluate various simulated survey designs for a given number of transects in terms of the precision, bias, and efficiency (relative variance) of their estimates. We considered a random transect sampling method that is currently used in British Columbia for red sea urchins, which samples every other quadrat within each transect, as well as a complete version of that transect method, which samples every quadrat. We also evaluated more complex random transect sampling designs, including restricted adaptive cluster sampling and a design stratified by type of substrate within each transect. The complete transect method produced essentially unbiased estimat...

The endangered population of sockeye salmon (Oncorhynchus nerka) in Cultus Lake, British Columbia, Canada, migrates through commercial fishing areas along with other, much more abundant sockeye salmon populations, but it is not feasible to selectively harvest only the latter, abundant populations. This situation creates controversial trade-offs between recovery actions and economic revenue. We conducted a Bayesian decision analysis to evaluate options for recovery of Cultus Lake sockeye salmon. We used a stochastic population model that included 2 sources of uncertainty that are often omitted from such analyses: structural uncertainty in the magnitude of a potential Allee effect and implementation uncertainty (the deviation between targets and actual outcomes of management actions). Numerous state-dependent, time-independent management actions meet recovery objectives. These actions prescribe limitations on commercial harvest rates as a function of abundance of Cultus Lake sockeye salmon. We also quantified how much reduction in economic value of commercial harvests of the more abundant sockeye salmon populations would be expected for a given increase in the probability of recovery of the Cultus population. Such results illustrate how Bayesian decision analysis can rank options for dealing with conservation risks and can help inform trade-off discussions among decision makers and among groups that have competing objectives.

We used decision analysis to assist the Great Lakes Fishery Commission (GLFC) with sea lamprey (Petromyzon marinus) control in the St. Marys River, which connects Lake Superior to Lake Huron and until recently has been a major source of sea lamprey infestation of Lake Huron. The process involved decision-makers, managers, and experts in an analysis of management options, objectives, and critical uncertainties affecting the expected perfor- mance of alternative choices. We developed quantitative assessments of uncertainty about sea lamprey demographics and about the implementation effectiveness of three pest control options: trapping adult lampreys, sterile male releases, and lampricide treatment. We used a stochastic simulation model to forecast future parasitic sea lamprey abundance in Lake Huron for 10 management options. Management options that included enhanced levels of trapping and sterile male releases exhibited the best performance for all measures. Our analysis substantially influenced the GLFC strategy for the St. Marys River, providing an example of how explicit consideration of uncertainty using decision analysis can influence fishery management decisions. Resume : Nous utilisons l'analyse decisionnelle pour aider la Commission des pecheries des Grands Lacs (GLFC) a controler la grande lamproie marine (Petromyzon marinus) dans la riviere St. Marys qui relie le lac Superieur au lac Huron et qui, jusqu'a recemment, etait une source majeure d'infestation des grandes lamproies marines au lac Huron. Le processus reunit les decideurs, les gestionnaires et les experts pour une analyse des options de gestion, des objectifs et des incertitudes critiques qui affectent la performance attendue des divers choix. Nous avons mis au point des eva- luations quantitatives de l'incertitude relative a la demographie de la grande lamproie marine, ainsi qu'a l'efficacite de la mise en oeuvre de trois choix de lutte contre ces ravageurs, soit le trappage des lamproies adultes, la liberation de mâles steriles et le traitement au lampricide. Nous utilisons un modele de simulation stochastique pour predire l'abondance future des grandes lamproies marines parasites au lac Huron en fonction de 10 options de gestion. De toutes les options de gestion, celles qui incluent une augmentation du trappage des adultes et de la liberation des mâles steriles connaissent les meilleures performances. Notre analyse a influence de facon importante la strategie de la GLFC dans la riviere St. Marys; c'est la un exemple qui montre comment la prise en consideration explicite de l'incertitude a l'aide d'une analyse decisionnelle peut influencer les choix de gestion des peches.

To regulate human-induced changes to fish habitat, resource managers commonly set standards based on maximum allowable changes. For example, new legislation in British Columbia (BC), Canada, calls for restrictions on harvesting of trees and related activities near temperature-sensitive streams. However, methods for designating such streams are still evolving. Our objective was to help develop such methods by (1) improving understanding of the temperature-dependent responses of fish and (2) devising improved methods for estimating the effects of forestry-related activities on stream temperature as well as the chance of exceeding upper temperature limits. Using previously published models, we found that for rainbow trout Oncorhynchus mykiss particular increases in stream temperature led to different effects on juvenile growth rate, egg survival rate, and resistance to mortality from diseases. In a separate analysis, to evaluate the chance that cumulative forestry activities will increase stream tem...

The sibling model is often one of the best methods for calculating preseason forecasts of adult return abundance (recruits) for populations of Pacific salmon Oncorhynchus spp. This model forecasts abundance of a given age-class for a given year based on the abundance of the previous age-class in the previous year. When sibling relations fit historical data well, the sibling model generally performs better than other forecasting methods, such as stock–recruitment models. However, when sibling relations are weak, better forecasts are obtained by other models, such as naive models that simply use an historical average. We evaluated the performance of a hybrid model that used quantitative criteria for switching between a sibling model and a naive model when generating forecasts for 21 stocks of chum salmon O. keta and 37 stocks of sockeye salmon O. nerka in the northeastern Pacific Ocean. Compared with the standard sibling model, the hybrid model reduced the root mean square error (RMSE) of forecasts...

For certain populations of sockeye salmon Oncorhynchus nerka, spawner and recruit data are either absent or too limited to estimate escapement goals (target abundance of spawners). In some cases, scientists instead use data on productivity of nursery lakes; however, many such analyses have not accounted for uncertainties. We therefore extended a previously developed lake productivity method for estimating escapement goals (the photosynthetic rate (PR) model) by using a Bayesian statistical approach that takes several sources of uncertainty into account. Utilizing data for Fraser River, British Columbia, sockeye salmon stocks, we compared this Bayesian PR method with stock–recruitment analysis. In six of seven cases, probability distributions of spawner abundance goals from the Bayesian PR method were 27% narrower on average than those from the stock–recruitment method. In four of seven cases, the Bayesian PR method produced higher median estimates of target spawner abundance than did stock–recrui...

Chilko Lake in British Columbia, Canada, was fertilized with nitrogen and phosphorus in the late 1980s and early 1990s to increase abundance and harvests of adult sockeye salmon Oncorhynchus nerka. Because of the short, 5-year duration of this program and the large inherent natural variation in adult recruits produced per spawner both before and during lake fertilization, there is considerable uncertainty about the efficacy of that fertilization. Recent analyses suggest a high probability that more adult sockeye salmon were produced per spawner from fertilization than would have been produced without fertilization, but the confidence interval on that increase is large. Furthermore, no economic analysis has been done to determine the effect of the large biological uncertainties on the benefit–cost (BC) ratio of the project. We filled this need by using Bayesian statistical analysis to estimate uncertainty in the parameters of four models that reflected different hypotheses about the biological eff...

Models for making preseason forecasts of adult abundance are an important component of the management of many stocks of Pacific salmon Oncorhynchus spp. Reliable forecasts could increase both the profits from fisheries and the probability of achieving conservation and other management targets. However, the predictive performance of salmon forecasting models is generally poor, in part because of the high variability in salmon survival rates. To improve the accuracy of forecasts, we retrospectively evaluated the performance of eight preseason forecasting models for 43 stocks of pink salmon O. gorbuscha over a total of 783 stock-years. The results indicate that no single forecasting model was consistently the most accurate. Nevertheless, across the 43 stocks we found that two naive time series models (i.e., those without explicitly modeled mechanisms) most frequently performed best based on mean raw error, mean absolute error, mean percent error, and root mean square error for forecasts of total adu...

We estimated the spatial scales of covariation in indices of spawner-to-recruit survival rates among 116 wild stocks of pink salmon Oncorhynchus gorbuscha, chum salmon O. keta, and sockeye salmon O. nerka. These data spanned roughly four decades and represented stocks from 15 geographical regions in Washington, British Columbia, and Alaska. For comparisons between pink and chum salmon, we found positive covariation in survival rates within regions and between certain adjacent regions (e.g., correlations between 0.3 and 0.7) but little covariation between stocks of distant regions (separated by 1,000 km or more). Our results indicate that, on average, shared environmental effects accounted for at least 36% of the variation in survival rates of nearby pink and chum salmon stocks but only 18% for stocks separated by about 500 km. By comparing these between-species patterns with within-species patterns, we conclude that differences in the geographical overlap of fish during the freshwater and early m...

To improve the understanding of effects of environmental factors on spawner-to-recruit survival rates of pink salmon (Oncorhynchus gorbuscha), we developed several spatial hierarchical Bayesian models (HBMs). We applied these models to 43 pink salmon stocks in the Northeast Pacific. By using a distance-based, spatially correlated prior distribution for stock-specific parameters, these multistock models explicitly allowed for positive correlation among nearby salmon stocks in their productivities and coefficients of early summer coastal sea surface temperature (SST). To our knowledge, this is the first time that such distance-based, spatial prior probability distributions for parameters have been applied to fisheries problems. We found that the spatial HBMs produce more consistent and precise estimates of effects of SST on productivity than a single-stock approach that estimated parameters for each stock separately. Similar to earlier results using mixed-effects models for the same stocks, we found significant positive effects of SST on survival rates of northern pink salmon stocks, but weaker negative effects of SST on survival rates of southern pink salmon stocks. However, we show a smoother transition in magnitude of effects between these regions.

Using indices of survival rate (residuals from stock-recruitment relationships) across four decades, we examined the spatial patterns of covariation among 40 wild and 27 hatchery stocks of chum salmon Oncorhynchus keta from 15 geographical regions in Washington, British Columbia, and Alaska. We found strong evidence of positive covariation among spawner-to-recruit survival rates of wild stocks within regions and between certain adjacent regions (e.g., correlations from 0.3 to 0.7) but little evidence of covariation between stocks of distant regions (e.g., separated by 1,000 km or more). Similarly, for hatchery stocks from Washington, British Columbia, and southeast Alaska, positive covariation in the indices of fry-to-recruit survival rate occurred only within regions and between certain adjacent regions. These patterns suggest that important environmental processes affecting interannual variation in spawner-to-recruit survival rates of chum salmon operate at local or regional spatial scales rath...

Fisheries management agencies are involved in many activities to enhance Pacific salmon Oncorhynchus spp. Monitoring the performance of pilot projects before deciding whether or not to apply a particular method of enhancement on a wide scale will result in better investment decisions. However, the costs of such monitoring can be substantial. We developed a quantitative framework based on decision analysis to determine whether the expected value of the information obtained through monitoring exceeds the costs of obtaining it. We applied this framework to a hypothetical problem in which managers have a fixed budget for constructing groundwater-fed side channels for chum salmon O. keta and must choose how much, if any, of that budget to allocate to monitoring. We used this example to identify the conditions under which monitoring can generate positive net economic returns and the characteristics of experimental designs for monitoring that yield the greatest net value. The choice between monitoring a...

Historically, forecast error for returns of sockeye salmon Oncorhynchus nerka to Bristol Bay, Alaska, has been large. Using cross-validation forecast error as our criterion, we selected forecast models for each of the nine principal Bristol Bay drainages. Competing forecast models included stock–recruitment relationships, environmental variables, prior returns of siblings, or combinations of these predictors. For most stocks, we found prior returns of siblings to be the best single predictor of returns; however, forecast accuracy was low even when multiple predictors were considered. For a typical drainage, an 80% confidence interval ranged from one half to double the point forecast. These confidence intervals appeared to be appropriately wide.

Pacific salmon (Oncorhynchus spp.) populations can experience persistent changes in productivity, possibly due to climatic shifts. Management agencies need to rapidly and reliably detect such changes to avoid costly suboptimal harvests or depletion of stocks. However, given the inherent variability of salmon populations, it is difficult to detect changes quickly, let alone forecast them. We therefore compared three methods of annually updating estimates of stock-recruitment parameters: standard linear regression, Walters' bias-corrected regression, and a Kalman filter. We used Monte Carlo simulations that hypothesized a wide range of future climate-induced changes in the Ricker a parameter of a salmon stock. We then used each parameter estimation method on the simulated stock and recruitment data and set escapement targets and harvest goals accordingly. In these situations with a time-varying true Ricker a parameter, Kalman filter estimation resulted in greater mean cumulative catch than was produced by the standard linear regression approach, Walters' bias correction method, or a fixed harvest rate policy. This benefit of the Kalman filter resulted from its better ability to track changing parameter values, thereby producing escapements closer to the optimal escapement each year. However, errors in implementing desired management actions can significantly reduce benefits from all parameter estimation techniques.

Despite the accumulating theoretical interest in experimental management, there are few practical applications of it. Because most fisheries management plans lack rigorous experimental design, managers often face controversy when results appear consistent with several alternative mechanisms or when results yield little information about causes of fish population dynamics. We provide a synthesis of the problems of experimental design in fisheries science and management, and we show how these problems can be solved to generate better information and better decisions, especially when combined with proper statistical practices and formal decision analysis. Reasons why experimental management is currently rare are (1) lack of unfamiliarity of management agencies with designing management actions to yield information, (2) logistical constraints placed on replication by fish migratory patterns, (3) resistance by fishermen who fear experimentation will lower incomes, or (4) risk of stock collapse, Howeve...

The author uses papers which reported little evidence of the effect of acid deposition on forest ecosystems to point out the problems of statistical reporting practices in ecology. He suggests that often we are not given the information necessary to judge the strength of the evidence in these reports; i.e., their data analyses or experiments may have had power too low to warrant being used as evidence. Low power could result from sample sizes too small or data sets too variable to have a high chance of finding a statistically significant effect of acid deposition. Risk assessments relevant to natural resource management should be based on concepts of probability of type II error, power and detectable effect size.

Data on sampling variability in smolt abundance for Babine Lake sockeye salmon (Oncorhynchus nerka) are combined with a previous analysis to calculate a more accurate estimate of the degree of nonlinearity in the relation between smolts and adults. Results indicate significant within-stock nonlinear mortality, large variability in mortality which tends to obscure any smolt-to-adult relation, or both. Analysis of age structure data identifies the first 15 mo of marine life as the period when most of this nonlinear or relation-masking mortality occurs. I also calculate the amount of smolt measurement error below which other salmon stocks are classed as having nonlinear marine survival. A distinct separation between even and odd brood year marine survival of Babine Lake sockeye suggests interactions with pink salmon. Juvenile pink salmon (O. gorbuscha) abundances correlate positively with residuals in Babine Lake sockeye survival for the same seaward migration year. This suggests a depensatory mortality effect which occurs later in the marine life stage than the possible within-population compensatory effect. Depensation is plausible because the size of pink fry equals that of sockeye smolts by August in coastal waters, permitting mutual swamping of predators. The paper concludes with implications for further enhancement.Key words: density dependence, marine survival, measurement error, enhancement, depensation, nonlinear, variability

We tested Hjort's and Lasker's hypotheses that the abundance of recruits in fishes is determined at an early life stage. Using 13 yr of data on components of population dynamics of the well-studied northern anchovy (Engraulis mordax), we reconstructed the abundance of anchovy in each year at three stages: eggs, 4.5-d-old yolk-sac larvae, and 19-d-old larvae. No abundance measure was significantly correlated with age 1 recruits, resulting in rejection of Hjort's and Lasker's hypotheses. We give reasons why the low correlations are not an artifact of estimation error. The lack of correlation exists because of the large variability (CV = 171%) in survival rate between age 19 d and age 1 yr. Therefore, attempts to understand interannual variability in recruitment in this, and perhaps other, marine fish species may have to rely not only on data on eggs and larvae, but especially on data on abundances estimated after 20 d, closer to the age at recruitment.

Depensatory predation mortality on salmon when added to a Ricker production model can create a system with at least two stable equilibria and two domains of attraction. The behavior of such a fish system is different from a single equilibrium situation and a simple mechanism is described through which commercial exploitation changes the ability of such multiple-equilibrium fish populations to respond to perturbations in survival rates. Furthermore, it is shown that this change in size of stability regions is proportional to the exploitation rate and that classically defined maximum sustainable yield (MSY) exploitation rates are inevitably close to the rates that would cause a drastic decrease in the population. The uncertainties inherent in environmental effects on survival and in achievement of desired exploitation rates precipitate the need to back away from the usual MSY exploitation rates and set up (through enhancement) a system of stocks whereby feedback information is provided to the manager. This approach of adaptive management seeks reasonable yields while gaining information about the state (or changes in state) of the system. Some applications of catastrophe theory are discussed, especially with reference to harvesting multiple-stock salmon systems. Key words: stability, resilience, exploitation, salmon, depensation, multiple equilibria, adaptive management, enhancement, catastrophe theory

The interaction between a modelling team, the technical staff of a government agency, and public advisory groups is described for the analysis of a major recreational and commercial fishery. A computer simulation model was used as the major policy analysis tool over a period of 4 years, and the problems and potential of this approach are discussed. Of particular interest was the high degree of turnover among technical staff within the government agency and the major role the model played in providing continuity.

A computer simulation model was used to examine growth and survival of all major British Columbia salmon stocks during their first 6 mo of ocean life. Factors included in the calculations were the space–time distribution of zooplankton production, timing of salmon ocean arrival and migration especially as regards overlaps between stocks, feeding and growth in relation to food availability, and mortality rates in relation to body size. It is concluded that ocean limitation of production is unlikely unless only a small fraction of total zooplankton production is available to the salmon. The model emphasizes several critical uncertainties about the marine biology of salmon: rates of replenishment of near surface zooplankton stocks (where most salmon feeding occurs) from deeper water have not been adequately measured, and the functional response of salmon to prey density is not understood. There is inadequate data on the relationship between body size and mortality rate, and migration patterns of juvenile fish have not been documented precisely enough. Hopefully some of these uncertainties will be resolved through the salmon enhancement programs. Key words: salmon, population limitation, juvenile marine production, simulation model

Many researchers have reported biases in estimates offish abundance reconstructed by virtual population analysis (VPA). We document that VPA can produce changing levels of bias through time, thereby creating spurious time trends in recruitment and stock biomass estimates. We generated catch data from empirically based simulations of nine fish populations, estimated abundances using VPA with a deliberately mis-specified natural mortality rate, M, and compared the estimates to the models' "true" abundances. A period of increasing fishing mortality rate, F, combined with an overestimate of M produced spurious decreasing time trends in estimated abundance and recruitment, even when the true time series of F was known. Analogously, an underestimate of M led to a spurious increasing time trend. Bias was increased by a higher true M, and (for a given total change in F) by a slower increase in F. Because field estimates of M are uncertain and trends in F are common, some apparent trends (or lack of them) in abundances reconstructed by VPA may be artifacts. Therefore, inferences about the results of past management actions and about physical or biological effects on variability in recruitment must be made cautiously when VPA estimates are used.

Estimates of the production of adult salmon can be biased by assuming an incorrect form of random noise term in the descriptive model. Many authors of theoretical studies of stock–recruitment relations assume multiplicative, log-normal distributions of random noise, while other workers assume additive, normally distributed terms. Marine survival data for three species of salmon are used to determine which type of random variation term is most appropriate for salmon population models. Results indicate that a multiplicative, log-normal distribution is most consistent with the data. The random processes described by this type of noise term cause higher absolute variation in total adult returns as abundance of seaward migrants increases. This phenomenon creates difficulties in evaluating the success of artificial enhancement programs and it should be taken into account during planning of such programs and during subsequent evaluations of their success.Key words: marine survival, salmon, enhancement, log-normal, random, variability, parameter estimation, stock–recruitment, normal distributions

Basic components of predation processes are briefly reviewed and data on these components are presented for several native Indian food fisheries. Depensatory mortality emerges as a common effect of these fisheries, which supports findings of earlier workers on Skeena River sockeye salmon (Oncorhynchus nerka). Native food fisheries therefore operate like natural "Type II" predators, and descriptive equations are provided for use by salmon managers and modelers.Key words: fishermen as predators, native, Indian, food, fisheries, salmon, depensation

Marine survival data for several different salmonid stocks were reviewed to determine whether there was significant density-dependent survival occurring in the ocean. Four classes of interaction were examined: (1) within-cohorts, (2) between-cohorts, (3) between stocks on the same or nearby rivers, and (4) between stocks of distant rivers. Results of statistical tests indicate that some stocks do not produce an increase in adult returns with increased smolt abundance, and that marine survival rate of other stocks is affected by abundance of other cohorts or stocks. Only a few stocks exhibit these density-dependent relations, but given present data, it is impossible to predict the frequency of occurrence of such limiting processes in future enhanced stocks. Salmonid enhancement planning is discussed in the context of this uncertainty and experimental enhancement projects are suggested that aim to obtain information about marine survival processes as well as additional catches. Key words: density dependent, marine survival, salmonids, experimental enhancement, stock interaction, adaptive

Significant decreases in adult body size and marine growth rate occur in seven British Columbia and Bristol Bay, Alaska, sockeye salmon (Oncorhynchus nerka) stocks when large numbers of sockeye are present in the Gulf of Alaska. These density-dependent effects arise mainly during early ocean life and are probably due to competition for food. The total sockeye abundance in the Gulf of Alaska is at least as important as within-stock abundance in determining final adult body size. British Columbia sockeye show a 10–22% decrease in adult body weight at high abundance of conspecifics. Thus, future evaluations of management strategies cannot simply focus on individual stocks, but must take a broader perspective which includes other sockeye populations.

Previous research has shown that, in some stocks, there can be a large (up to 22%) decrease in body weight of sockeye salmon Oncorhynchus nerka when large numbers of conspecifics are present in the Gulf of Alaska. This observation led to a hypothesis that may allow fisheries managers of British Columbia sockeye salmon to maximize the net economic benefits from enhancement efforts. Specifically, sockeye salmon enhancement efforts could be restricted to year classes that smolt in years when total smolt abundance in the ocean is low, resulting in faster growth and larger-than-average adult body sizes and biomass of catches. Lake enrichment is an appropriate enhancement method to manipulate smolt abundance. A “pulsed enhancement strategy” (deliberate variation in the number of sockeye salmon juveniles produced each year) was compared with an “annual enhancement strategy” (constant annual juvenile production) for four British Columbia stocks of sockeye salmon (Babine Lake, Chilko Lake, Owikeno Lake, a...

Interannual variations in mean age of maturity tend to be positively correlated among 10 stocks of sockeye salmon (Oncorhynchus nerka) which spawn in rivers emptying into Bristol Bay, Alaska. Taking a comparative approach, I utilized data from British Columbia and Alaska sockeye stocks with different life histories to test alternative hypotheses about sources of these variations in mean age at maturity. The hypotheses included freshwater environment, marine environment, and parental influences. Freshwater hypotheses were rejected and while some parental effects do exist, they are small compared with the effect of events in early marine life. Early marine growth rate data do not exist for these stocks but evidence from five other sockeye stocks shows that fast growth during this period tends to lead to earlier age at maturity.

We tested whether English sole (Parophrys vetulus) in Oregon and Washington waters show density-dependent growth. We found that there is a significant negative effect of cohort abundance on annual growth rate of age 1 fish, but not on growth of ages 2–7. Unlike most similar studies of density dependence, this result was not confounded by time trends in abundance and growth. The multiple regression of age 1 growth on cohort abundance and temperature accounted for 91% of the interannual variation in growth, which was a significant increase in r2 over that of the previously published relation with temperature alone. However, stock assessments which take into account only the previously published temperature effect on growth for this stock will probably not seriously overestimate the impact of management regulations which increase cohort abundance.

Pacific salmon sport-fishing data without time trends in the catchability coefficient q or in fish abundance N show that q is larger at lower N. This phenomenon causes serious management problems because it creates critical thresholds in population size and fishing effort that can lead to stock extinction. The inverse relation between q and N directly parallels the analogous relation shown by some predators in natural ecosystems.

The widespread occurrence of countershading in coral reef fish seems to be evidence that the colours and patterns of these animals, however conspicuous they may appear to the human observer, are at least partially concerned with camouflage from predators. The alternative presented here, particularly relative to a butterfly fish Chaetodon lunula , is that countershading can be an adaptation to concealing a conspicuous signal. The conclusion is supported by the observation that this species eliminates its countershading by rapid colour change during intense intraspecific encounters. This colour change exposes highly conspicuous yellow areas. Colour change can thus make the signal dynamic. These signals may function to establish dominance relationships, especially between evenly matched individuals.

Outbreaks of the Douglas-fir tussock moth, Orgyia pseudotsugata (McDunnough), have recurred periodically, at 7- to 10-year intervals, since the first recorded observation in 1916 in Chase, British Columbia, Canada. Anderson and May (1981) hypothesized that microparasites are responsible for the periodic population fluctuations of some defoliating insects. We chose the association between the Douglas-fir tussock moth and a viral disease, caused by a nuclear polyhedrosis virus (NPV), to test whether their model, and variants thereof, can predict the observed population cycles. Density-dependent mortality, vertical transmission of the virus and an incubation period were added to the free-living stages model of Anderson and May (1981). Parameter values for the models were derived from published data and from an experiment.Sensitivity analyses conducted for each model showed that none of the models generated the behavior of the Douglas-fir tussock moth as observed in the field. Thus, the periodicity of the outbreaks in field populations of tussock moths cannot be explained solely by the dynamics of the viral disease as described by Anderson and May's class of models; the virus is too short-lived and the growth rate of the insect population too high. Dynamics of other system components such as predators, parasites or food of the tussock moth probably play a significant role in the insect's population dynamics.