Return(s) on investment: Restoration spending in the Columbia River Basin and increased abundance of salmon and steelhead.

The decline in salmon and steelhead populations in the Columbia River Basin has been well documented, as have the decades-long, $9 billion restoration spending efforts by federal and state agencies. These efforts are mainly tied to Endangered Species Act (ESA) mandates for recovery of wild, naturally-spawning threatened or endangered fish species. The impact of these efforts remains poorly understood; many observers, including the federal courts, have long been concerned by the lack of evidence of recovery. Most studies evaluating restoration efforts have examined individual projects for specific species, reaches, or life stages, which limits the ability to make broad inferences at the basin level. There is a need to ask: is there evidence of an overall increase in wild fish abundance associated with the totality of these recovery efforts? To that end, the current study estimates fixed-effects panel regression models of adult returns of four species. Results indicate that restoration spending combined with hatchery production are associated with substantial increases in returning adult fish. Evidence of benefits to wild fish alone, however, require indirect approaches given the commingling of restoration spending with spending on hatchery releases, the impacts of spending on hatchery fish survival, and the density dependence effects of hatchery releases. To accomplish this, the models' predicted adult returns (both hatchery and wild fish) attributed to both spending and hatchery releases are compared to independent estimates of returning hatchery fish based on hatchery survival estimates (smolt-to-adult ratios). The comparison finds the model-predicted levels of adult returns due to spending and hatchery releases do not exceed the survival-rate based estimates for hatcheries alone, so that we are unable to reject the hypothesis of no benefits to wild fish from the restoration spending.

Effects of population density and environmental conditions on life-history prevalence in a migratory fish.

Individual variation in life-history traits can have important implications for the ability of populations to respond to environmental variability and change. In migratory animals, flexibility in the timing of life-history events, such as juvenile emigration from natal areas, can influence the effects of population density and environmental conditions on habitat use and population dynamics. We evaluated the functional relationships between population density and environmental covariates and the abundance of juveniles expressing different life-history pathways in a migratory fish, Chinook salmon (Oncorhynchus tshawytscha), in the Wenatchee River basin in Washington State, USA. We found that the abundance of younger emigrants from natal streams was best described by an accelerating or near-linear function of spawners, whereas the abundance of older emigrants was best described by a decelerating function of spawners. This supports the hypothesis that emigration timing varies in response to density in natal areas, with younger-emigrating life-history pathways comprising a larger proportion of emigrants when densities of conspecifics are high. We also observed positive relationships between winter stream discharge and abundance of younger emigrants, supporting the hypothesis that habitat conditions can also influence the prevalence of different life-history pathways. Our results suggest that early emigration, and a resultant increase in the use of downstream rearing habitats, may increase at higher population densities and with greater winter precipitation. Winter precipitation is projected to increase in this system due to climate warming. Characterizing relationships between life-history prevalence and environmental conditions may improve our understanding of species habitat requirements and is a first step in understanding the dynamics of species with diverse life-history strategies. As environmental conditions change-due to climate change, management, or other factors-resultant life-history changes are likely to have important demographic implications that will be challenging to predict when life-history diversity is not accounted for in population models.

Regularizing priors for Bayesian VAR applications to large ecological datasets.

Using multi-species time series data has long been of interest for estimating inter-specific interactions with vector autoregressive models (VAR) and state space VAR models (VARSS); these methods are also described in the ecological literature as multivariate autoregressive models (MAR, MARSS). To date, most studies have used these approaches on relatively small food webs where the total number of interactions to be estimated is relatively small. However, as the number of species or functional groups increases, the length of the time series must also increase to provide enough degrees of freedom with which to estimate the pairwise interactions. To address this issue, we use Bayesian methods to explore the potential benefits of using regularized priors, such as Laplace and regularized horseshoe, on estimating interspecific interactions with VAR and VARSS models. We first perform a large-scale simulation study, examining the performance of alternative priors across various levels of observation error. Results from these simulations show that for sparse matrices, the regularized horseshoe prior minimizes the bias and variance across all inter-specific interactions. We then apply the Bayesian VAR model with regularized priors to a output from a large marine food web model (37 species) from the west coast of the USA. Results from this analysis indicate that regularization improves predictive performance of the VAR model, while still identifying important inter-specific interactions.

Limited evidence for sardine and anchovy asynchrony: re-examining an old story.

Asynchronous fluctuations in abundance between species with similar ecological roles can stabilize food webs and support coexistence. Sardine (Sardinops spp.) and anchovy (Engraulis spp.) have long been used as an example of this pattern because low-frequency variation in catches of these species appears to occur out of phase, suggesting that fisheries and generalist predators could be buffered against shifts in productivity of a single species. Using landings data and biomass and recruitment estimates from five regions, we find that species do not have equivalent peak abundances, suggesting that high abundance in one species does not compensate for low abundance in the other. We find that globally there is a stronger pattern of asynchrony in landings compared to biomass, such that landings data have exaggerated the patterns of asynchrony. Finally, we show that power to detect decadal asynchrony is poor, requiring a time series more than twice the length of the period of fluctuation. These results indicate that it is unlikely that the dynamics of these two species are compensatory enough to buffer fisheries and predators from changes in abundance, and that the measurements of asynchrony have largely been a statistical artefact of using short time series and landings data to infer ecology.

Spatial heterogeneity contributes more to portfolio effects than species variability in bottom-associated marine fishes.

Variance of community abundance will be reduced relative to its theoretical maximum whenever population densities fluctuate asynchronously. Fishing communities and mobile predators can switch among fish species and/or fishing locations with asynchronous dynamics, thereby buffering against variable resource densities (termed 'portfolio effects', PEs). However, whether variation among species or locations represent the dominant contributor to PE remains relatively unexplored. Here, we apply a spatio-temporal model to multidecadal time series (1982-2015) for 20 bottom-associated fishes in seven marine ecosystems. For each ecosystem, we compute the reduction in variance over time in total biomass relative to its theoretical maximum if species and locations were perfectly correlated (total PE). We also compute the reduction in variance due to asynchrony among species at each location (species PE) or the reduction due to asynchrony among locations for each species (spatial PE). We specifically compute total, species and spatial PE in 10-year moving windows to detect changes over time. Our analyses revealed that spatial PE are stronger than species PE in six of seven ecosystems, and that ecosystems where species PE is constant over time can exhibit shifts in locations that strongly contribute to PE. We therefore recommend that spatial and total PE be monitored as ecosystem indicators representing risk exposure for human and natural consumers.

Applying spatiotemporal models to monitoring data to quantify fish population responses to the Deepwater Horizon oil spill in the Gulf of Mexico.

Quantifying the impacts of disturbances such as oil spills on marine species can be challenging. Natural environmental variability, human responses to the disturbance (e.g., fisheries closures), the complex life histories of the species being monitored, and limited pre-spill data can make detection of effects of oil spills difficult. Using long-term monitoring data from the state of Louisiana (USA), we applied novel spatiotemporal approaches to identify anomalies in species occurrence and catch rates. We included covariates (salinity, temperature, turbidity) to help isolate unusual events. While some species showed evidence of unlikely temporal anomalies in occurrence or catch rates, we found that the majority of the observed anomalies were also before the Deepwater Horizon event. Several species-gear combinations suggested upticks in the spatial variability immediately following the spill, but most species indicated no trend. Across species-gear combinations, there was no clear evidence for synchronous or asynchronous responses in occurrence or catch rates across sites following the spill. Our results are in general agreement to other analyses of monitoring data that detected small impacts, but in contrast to recent results from ecological modeling that showed much larger effects of the oil spill on fish and shellfish.

Estimating Common Growth Patterns in Juvenile Chinook Salmon (Oncorhynchus tshawytscha) from Diverse Genetic Stocks and a Large Spatial Extent.

Life history variation in Pacific salmon (Oncorhynchus spp.) supports species resilience to natural disturbances and fishery exploitation. Within salmon species, life-history variation often manifests during freshwater and estuarine rearing, as variation in growth. To date, however, characterizing variability in growth patterns within and among individuals has been difficult via conventional sampling methods because of the inability to obtain repeated size measurements. In this study we related otolith microstructures to growth rates of individual juvenile Chinook salmon (O. tshawytscha) from the Columbia River estuary over a two-year period (2010-2012). We used dynamic factor analysis to determine whether there were common patterns in growth rates within juveniles based on their natal region, capture location habitat type, and whether they were wild or of hatchery origin. We identified up to five large-scale trends in juvenile growth rates depending on month and year of capture. We also found that hatchery fish had a narrower range of trend loadings for some capture groups, suggesting that hatchery fish do not express the same breadth of growth variability as wild fish. However, we were unable to resolve a relationship between specific growth patterns and habitat transitions. Our study exemplifies how a relatively new statistical analysis can be applied to dating or aging techniques to summarize individual variation, and characterize aspects of life history diversity.

Assessing spatial covariance among time series of abundance.

For species of conservation concern, an essential part of the recovery planning process is identifying discrete population units and their location with respect to one another. A common feature among geographically proximate populations is that the number of organisms tends to covary through time as a consequence of similar responses to exogenous influences. In turn, high covariation among populations can threaten the persistence of the larger metapopulation. Historically, explorations of the covariance in population size of species with many (>10) time series have been computationally difficult. Here, we illustrate how dynamic factor analysis (DFA) can be used to characterize diversity among time series of population abundances and the degree to which all populations can be represented by a few common signals. Our application focuses on anadromous Chinook salmon (Oncorhynchus tshawytscha), a species listed under the US Endangered Species Act, that is impacted by a variety of natural and anthropogenic factors. Specifically, we fit DFA models to 24 time series of population abundance and used model selection to identify the minimum number of latent variables that explained the most temporal variation after accounting for the effects of environmental covariates. We found support for grouping the time series according to 5 common latent variables. The top model included two covariates: the Pacific Decadal Oscillation in spring and summer. The assignment of populations to the latent variables matched the currently established population structure at a broad spatial scale. At a finer scale, there was more population grouping complexity. Some relatively distant populations were grouped together, and some relatively close populations - considered to be more aligned with each other - were more associated with populations further away. These coarse- and fine-grained examinations of spatial structure are important because they reveal different structural patterns not evident in other analyses.

An explicit solution for calculating optimum spawning stock size from Ricker's stock recruitment model.

Stock-recruitment models have been used for decades in fisheries management as a means of formalizing the expected number of offspring that recruit to a fishery based on the number of parents. In particular, Ricker's stock recruitment model is widely used due to its flexibility and ease with which the parameters can be estimated. After model fitting, the spawning stock size that produces the maximum sustainable yield (S MSY) to a fishery, and the harvest corresponding to it (U MSY), are two of the most common biological reference points of interest to fisheries managers. However, to date there has been no explicit solution for either reference point because of the transcendental nature of the equation needed to solve for them. Therefore, numerical or statistical approximations have been used for more than 30 years. Here I provide explicit formulae for calculating both S MSY and U MSY in terms of the productivity and density-dependent parameters of Ricker's model.

Analyzing large-scale conservation interventions with Bayesian hierarchical models: a case study of supplementing threatened Pacific salmon.

Myriad human activities increasingly threaten the existence of many species. A variety of conservation interventions such as habitat restoration, protected areas, and captive breeding have been used to prevent extinctions. Evaluating the effectiveness of these interventions requires appropriate statistical methods, given the quantity and quality of available data. Historically, analysis of variance has been used with some form of predetermined before-after control-impact design to estimate the effects of large-scale experiments or conservation interventions. However, ad hoc retrospective study designs or the presence of random effects at multiple scales may preclude the use of these tools. We evaluated the effects of a large-scale supplementation program on the density of adult Chinook salmon Oncorhynchus tshawytscha from the Snake River basin in the northwestern United States currently listed under the U.S. Endangered Species Act. We analyzed 43 years of data from 22 populations, accounting for random effects across time and space using a form of Bayesian hierarchical time-series model common in analyses of financial markets. We found that varying degrees of supplementation over a period of 25 years increased the density of natural-origin adults, on average, by 0-8% relative to nonsupplementation years. Thirty-nine of the 43 year effects were at least two times larger in magnitude than the mean supplementation effect, suggesting common environmental variables play a more important role in driving interannual variability in adult density. Additional residual variation in density varied considerably across the region, but there was no systematic difference between supplemented and reference populations. Our results demonstrate the power of hierarchical Bayesian models to detect the diffuse effects of management interventions and to quantitatively describe the variability of intervention success. Nevertheless, our study could not address whether ecological factors (e.g., competition) were more important than genetic considerations (e.g., inbreeding depression) in determining the response to supplementation.

Shifting regimes and changing interactions in the Lake Washington, U.S.A., plankton community from 1962-1994.

Understanding how changing climate, nutrient regimes, and invasive species shift food web structure is critically important in ecology. Most analytical approaches, however, assume static species interactions and environmental effects across time. Therefore, we applied multivariate autoregressive (MAR) models in a moving window context to test for shifting plankton community interactions and effects of environmental variables on plankton abundance in Lake Washington, U.S.A. from 1962-1994, following reduced nutrient loading in the 1960s and the rise of Daphnia in the 1970s. The moving-window MAR (mwMAR) approach showed shifts in the strengths of interactions between Daphnia, a dominant grazer, and other plankton taxa between a high nutrient, Oscillatoria-dominated regime and a low nutrient, Daphnia-dominated regime. The approach also highlighted the inhibiting influence of the cyanobacterium Oscillatoria on other plankton taxa in the community. Overall community stability was lowest during the period of elevated nutrient loading and Oscillatoria dominance. Despite recent warming of the lake, we found no evidence that anomalous temperatures impacted plankton abundance. Our results suggest mwMAR modeling is a useful approach that can be applied across diverse ecosystems, when questions involve shifting relationships within food webs, and among species and abiotic drivers.

Spatial variation buffers temporal fluctuations in early juvenile survival for an endangered Pacific salmon.

Spatial, phenotypic and genetic diversity at relatively small scales can buffer species against large-scale processes such as climate change that tend to synchronize populations and increase temporal variability in overall abundance or production. This portfolio effect generally results in improved biological and economic outcomes for managed species. Previous evidence for the portfolio effect in salmonids has arisen from examinations of time series of adult abundance, but we lack evidence of spatial buffering of temporal variability in demographic rates such as survival of juveniles during their first year of life. We therefore use density-dependent population models with multiple random effects to represent synchronous (similar among populations) and asynchronous (different among populations) temporal variability as well as spatial variability in survival. These are fitted to 25 years of survey data for breeding adults and surviving juveniles from 15 demographically distinct populations of Chinook salmon (Oncorhynchus tshawytscha) within a single metapopulation in the Snake River in Idaho, USA. Model selection identifies the most support for the model that included both synchronous and asynchronous temporal variability, in addition to spatial variability. Asynchronous variability (log-SD = 0·55) is approximately equal in magnitude to synchronous temporal variability (log-SD = 0·67), but much lower than spatial variability (log-SD = 1·11). We also show that the pairwise correlation coefficient, a common measure of population synchrony, is approximated by the estimated ratio of shared and total variance, where both approaches yield a synchrony estimate of 0·59. We therefore find evidence for spatial buffering of temporal variability in early juvenile survival, although between-population variability that persists over time is also large. We conclude that spatial variation decreases interannual changes in overall juvenile production, which suggests that conservation and restoration of spatial diversity will improve population persistence for this metapopulation. However, the exact magnitude of spatial buffering depends upon demographic parameters such as adult survival that may vary among populations and is proposed as an area of future research using hierarchical life cycle models. We recommend that future sampling of this metapopulation employ a repeated-measure sampling design to improve estimation of early juvenile carrying capacity.

Performance of salmon fishery portfolios across western North America.

Quantifying the variability in the delivery of ecosystem services across the landscape can be used to set appropriate management targets, evaluate resilience and target conservation efforts. Ecosystem functions and services may exhibit portfolio-type dynamics, whereby diversity within lower levels promotes stability at more aggregated levels. Portfolio theory provides a framework to characterize the relative performance among ecosystems and the processes that drive differences in performance. We assessed Pacific salmon Oncorhynchus spp. portfolio performance across their native latitudinal range focusing on the reliability of salmon returns as a metric with which to assess the function of salmon ecosystems and their services to humans. We used the Sharpe ratio (e.g. the size of the total salmon return to the portfolio relative to its variability (risk)) to evaluate the performance of Chinook and sockeye salmon portfolios across the west coast of North America. We evaluated the effects on portfolio performance from the variance of and covariance among salmon returns within each portfolio, and the association between portfolio performance and watershed attributes. We found a positive latitudinal trend in the risk-adjusted performance of Chinook and sockeye salmon portfolios that also correlated negatively with anthropogenic impact on watersheds (e.g. dams and land-use change). High-latitude Chinook salmon portfolios were on average 2·5 times more reliable, and their portfolio risk was mainly due to low variance in the individual assets. Sockeye salmon portfolios were also more reliable at higher latitudes, but sources of risk varied among the highest performing portfolios. Synthesis and applications. Portfolio theory provides a straightforward method for characterizing the resilience of salmon ecosystems and their services. Natural variability in portfolio performance among undeveloped watersheds provides a benchmark for restoration efforts. Locally and regionally, assessing the sources of portfolio risk can guide actions to maintain existing resilience (protect habitat and disturbance regimes that maintain response diversity; employ harvest strategies sensitive to different portfolio components) or improve restoration activities. Improving our understanding of portfolio reliability may allow for management of natural resources that is robust to ongoing environmental change. Portfolio theory provides a straightforward method for characterizing the resilience of salmon ecosystems and their services. Natural variability in portfolio performance among undeveloped watersheds provides a benchmark for restoration efforts. Locally and regionally, assessing the sources of portfolio risk can guide actions to maintain existing resilience (protect habitat and disturbance regimes that maintain response diversity; employ harvest strategies sensitive to different portfolio components) or improve restoration activities. Improving our understanding of portfolio reliability may allow for management of natural resources that is robust to ongoing environmental change.

Quantifying effects of abiotic and biotic drivers on community dynamics with multivariate autoregressive (MAR) models.

Long-term ecological data sets present opportunities for identifying drivers of community dynamics and quantifying their effects through time series analysis. Multivariate autoregressive (MAR) models are well known in many other disciplines, such as econometrics, but widespread adoption of MAR methods in ecology and natural resource management has been much slower despite some widely cited ecological examples. Here we review previous ecological applications of MAR models and highlight their ability to identify abiotic and biotic drivers of population dynamics, as well as community-level stability metrics, from long-term empirical observations. Thus far, MAR models have been used mainly with data from freshwater plankton communities; we examine the obstacles that may be hindering adoption in other systems and suggest practical modifications that will improve MAR models for broader application. Many of these modifications are already well known in other fields in which MAR models are common, although they are frequently described under different names. In an effort to make MAR models more accessible to ecologists, we include a worked example using recently developed R packages (MAR1 and MARSS), freely available and open-access software.

Interacting effects of translocation, artificial propagation, and environmental conditions on the marine survival of Chinook salmon from the Columbia River, Washington, U.S.A.

Captive rearing and translocation are often used concurrently for species conservation, yet the effects of these practices can interact and lead to unintended outcomes that may undermine species' recovery efforts. Controls in translocation or artificial-propagation programs are uncommon; thus, there have been few studies on the interacting effects of these actions and environmental conditions on survival. The Columbia River basin, which drains 668,000 km(2) of the western United States and Canada, has an extensive network of hydroelectric and other dams, which impede and slow migration of anadromous Pacific salmon (Oncorhynchus spp.) and can increase mortality rates. To mitigate for hydrosystem-induced mortality during juvenile downriver migration, tens of millions of hatchery fish are released each year and a subset of wild- and hatchery-origin juveniles are translocated downstream beyond the hydropower system. We considered how the results of these practices interact with marine environmental conditions to affect the marine survival of Chinook salmon (O. tshawytscha). We analyzed data from more than 1 million individually tagged fish from 1998 through 2006 to evaluate the probability of an individual fish returning as an adult relative to its rearing (hatchery vs. wild) and translocation histories (translocated vs. in-river migrating fish that traveled downriver through the hydropower system) and a suite of environmental variables. Except during select periods of very low river flow, marine survival of wild translocated fish was approximately two-thirds less than survival of wild in-river migrating fish. For hatchery fish, however, survival was roughly two times higher for translocated fish than for in-river migrants. Competition and predator aggregation negatively affected marine survival, and the magnitude of survival depended on rearing and translocation histories and biological and physical conditions encountered during their first few weeks of residence in the ocean. Our results highlight the importance of considering the interacting effects of translocation, artificial propagation, and environmental variables on the long-term viability of species.

Using time series analysis to characterize evolutionary and plastic responses to environmental change: a case study of a shift toward earlier migration date in sockeye salmon.

Environmental change can shift the phenotype of an organism through either evolutionary or nongenetic processes. Despite abundant evidence of phenotypic change in response to recent climate change, we typically lack sufficient genetic data to identify the role of evolution. We present a method of using phenotypic data to characterize the hypothesized role of natural selection and environmentally driven phenotypic shifts (plasticity). We modeled historical selection and environmental predictors of interannual variation in mean population phenotype using a multivariate state-space model framework. Through model comparisons, we assessed the extent to which an estimated selection differential explained observed variation better than environmental factors alone. We applied the method to a 60-year trend toward earlier migration in Columbia River sockeye salmon Oncorhynchus nerka, producing estimates of annual selection differentials, average realized heritability, and relative cumulative effects of selection and plasticity. We found that an evolutionary response to thermal selection was capable of explaining up to two-thirds of the phenotypic trend. Adaptive plastic responses to June river flow explain most of the remainder. This method is applicable to other populations with time series data if selection differentials are available or can be reconstructed. This method thus augments our toolbox for predicting responses to environmental change.

Habitat structure determines resource use by zooplankton in temperate lakes.

While the importance of terrestrial linkages to aquatic ecosystems is well appreciated, the degree of terrestrial support of aquatic consumers remains debated. Estimates of terrestrial contributions to lake zooplankton have omitted a key food source, phytoplankton produced below the mixed layer. We used carbon and nitrogen stable isotope data from 25 Pacific Northwest lakes to assess the relative importance of particulate organic matter (POM) from the mixed layer, below the mixed layer and terrestrial detritus to zooplankton. Zooplankton and deep POM were depleted in ¹³C relative to mixed layer POM in lakes that can support deep primary production. A Bayesian stable isotope mixing model estimated that terrestrial detritus contributed <5% to zooplankton production, and confirms the role of lake optical and thermal properties; deep POM accounted for up to 80% of zooplankton production in the clearest lakes. These results suggest terrestrial support of lake zooplankton production is trivial.

Evolutionary responses by native species to major anthropogenic changes to their ecosystems: Pacific salmon in the Columbia River hydropower system.

The human footprint is now large in all the Earth's ecosystems, and construction of large dams in major river basins is among the anthropogenic changes that have had the most profound ecological consequences, particularly for migratory fishes. In the Columbia River basin of the western USA, considerable effort has been directed toward evaluating demographic effects of dams, yet little attention has been paid to evolutionary responses of migratory salmon to altered selective regimes. Here we make a first attempt to address this information gap. Transformation of the free-flowing Columbia River into a series of slack-water reservoirs has relaxed selection for adults capable of migrating long distances upstream against strong flows; conditions now favour fish capable of migrating through lakes and finding and navigating fish ladders. Juveniles must now be capable of surviving passage through multiple dams or collection and transportation around the dams. River flow patterns deliver some groups of juvenile salmon to the estuary later than is optimal for ocean survival, but countervailing selective pressures might constrain an evolutionary response toward earlier migration timing. Dams have increased the cost of migration, which reduces energy available for sexual selection and favours a nonmigratory life history. Reservoirs are a benign environment for many non-native species that are competitors with or predators on salmon, and evolutionary responses are likely (but undocumented). More research is needed to tease apart the relative importance of evolutionary vs. plastic responses of salmon to these environmental changes; this research is logistically challenging for species with life histories like Pacific salmon, but results should substantially improve our understanding of key processes. If the Columbia River is ever returned to a quasinatural, free-flowing state, remaining populations might face a Darwinian debt (and temporarily reduced fitness) as they struggle to re-evolve historical adaptations.

Big dams and salmon evolution: changes in thermal regimes and their potential evolutionary consequences.

Dams designed for hydropower and other purposes alter the environments of many economically important fishes, including Chinook salmon (Oncorhynchus tshawytscha). We estimated that dams on the Rogue River, the Willamette River, the Cowlitz River, and Fall Creek decreased water temperatures during summer and increased water temperatures during fall and winter. These thermal changes undoubtedly impact the behavior, physiology, and life histories of Chinook salmon. For example, relatively high temperatures during the fall and winter should speed growth and development, leading to early emergence of fry. Evolutionary theory provides tools to predict selective pressures and genetic responses caused by this environmental warming. Here, we illustrate this point by conducting a sensitivity analysis of the fitness consequences of thermal changes caused by dams, mediated by the thermal sensitivity of embryonic development. Based on our model, we predict Chinook salmon likely suffered a decrease in mean fitness after the construction of a dam in the Rogue River. Nevertheless, these demographic impacts might have resulted in strong selection for compensatory strategies, such as delayed spawning by adults or slowed development by embryos. Because the thermal effects of dams vary throughout the year, we predict dams impacted late spawners more than early spawners. Similar analyses could shed light on the evolutionary consequences of other environmental perturbations and their interactions.

The interplay between climate variability and density dependence in the population viability of Chinook salmon.

The viability of populations is influenced by driving forces such as density dependence and climate variability, but most population viability analyses (PVAs) ignore these factors because of data limitations. Additionally, simplified PVAs produce limited measures of population viability such as annual population growth rate (lamda) or extinction risk. Here we developed a "mechanistic" PVA of threatened Chinook salmon (Oncorhynchus tshawytscha) in which, based on 40 years of detailed data, we related freshwater recruitment of juveniles to density of spawners, and third-year survival in the ocean to monthly indices of broad-scale ocean and climate conditions. Including climate variability in the model produced important effects: estimated population viability was very sensitive to assumptions of future climate conditions and the autocorrelation contained in the climate signal increased mean population abundance while increasing probability of quasi extinction. Because of the presence of density dependence in the model, however we could not distinguish among alternative climate scenarios through mean lamda values, emphasizing the importance of considering multiple measures to elucidate population viability. Our sensitivity analyses demonstrated that the importance of particular parameters varied across models and depended on which viability measure was the response variable. The density-dependent parameter associated with freshwater recruitment was consistently the most important, regardless of viability measure, suggesting that increasing juvenile carrying capacity is important for recovery.