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Climate-driven changes in the timing of spawning or migration can affect the availability of fish to surveys designed to monitor their abundance, complicating efforts to assess stock status and sustainably manage fisheries. From 2017 to 2019, trends in biomass estimates from four surveys used to monitor Gulf of Alaska pollock diverged. These conflicting trends increased uncertainty in the stock assessment and occurred during a time of rapid environmental change. We hypothesized that changes in spawn timing affected availability of pollock to a winter survey that targets pre-spawning aggregations. To test this, we reconstructed relative spawn timing using two independent data sources: spring larval surveys and observations of spawning state in mature female pollock. We found that changes in spawn timing relative to survey timing explained a significant portion of recent and historical discrepancies between survey and model estimates of biomass. We then incorporated measures of spawn timing/survey timing mismatch as catchability covariates in an enhanced state-space stock assessment model. Including spawn timing-based catchability covariates significantly improved the model fit to survey data and provided a mechanistic explanation for recent survey discrepancies. [ABSTRACT FROM AUTHOR]

The British Columbia longline fishery for Pacific halibut (Hippoglossus stenolepis) has experienced important recent management changes, including the introduction of comprehensive electronic catch monitoring on all vessels; an integrated transferable quota system; a reduction in Pacific halibut quotas; and, beginning in 2016, sharp decreases in quota for yelloweye rockfish (Sebastes ruberrimus, an incidentally caught species). We describe this fishery before integration, after integration, and after the yelloweye rockfish quota reduction using spatial clustering methods to define discrete fishing opportunities. We calculate the relative utilization of these fishing opportunities and their overlap with areas with high encounter rates of yelloweye rockfish during each of the three periods. The spatial footprint (area fished) increased before integration, then decreased after integration. Each period showed shifts in utilization among four large fishing areas. Immediately after the reductions in yelloweye rockfish quota, fishing opportunities with high encounter rates of yelloweye rockfish had significantly lower utilization than areas with low encounter rates, implying rapid avoidance behaviour. La gestion de la peche au fletan du Pacifique (Hippoglossus stenolepis) a la palangre en Colombie-Britannique a recemment connu d'importants changements, dont l'introduction de la surveillance electronique exhaustive des prises sur tous les navires, un systeme de quotas transferables integre, une reduction des quotas de fletans du Pacifique et, depuis 2016, des baisses marquees des quotas de sebastes aux yeux jaunes (Sebastes ruberrimus, une espece pechee accessoirement). Nous decrivons cette peche avant l'integration, apres l'integration et apres la reduction des quotas de sebastes aux yeux jaunes en utilisant des methodes de regroupement spatial pour definir differentes possibilites de peche. Nous calculons l'utilisation relative de ces possibilites de peche et leur chevauchement de zones caracterisees par des taux eleves de rencontres de sebastes aux yeux jaunes durant chacune des trois periodes. L'empreinte spatiale (la superficie visee par la peche) a augmente avant l'integration, puis diminue apres l'integration. Chaque periode a connu des modifications de l'utilisation entre quatre grandes zones de peche. Immediatement apres les reductions des quotas de sebastes a yeux jaunes, les possibilites de peche caracterisees par des taux eleves de rencontres de sebastes a yeux jaunes etaient beaucoup moins utilisees que les zones caracterisees par de faibles taux de rencontres, ce qui indiquerait un comportement d'evitement. [Traduit par la Redaction], Introduction Managing multispecies fisheries with individual transferable quotas (ITQs), coupled with comprehensive monitoring and enforcement, can have positive conservation outcomes for both targeted and incidentally caught species (Costello et al. [...]

State-space assessment models (SSMs) have garnered attention recently because of their ability to estimate time variation in biological and fisheries processes such as recruitment, natural mortality, catchability, and selectivity. However, current SSMs cannot model time-varying growth internally nor accept length data, limiting their use. Here, we expand the Woods Hole Assessment Model to incorporate new approaches to modelling changes in growth using a combination of parametric and nonparametric approaches while fitting to length and weight data. We present these new features and apply them to data for three important Alaskan stocks with distinct data and model needs. We conduct a "self-test" simulation experiment to ensure the unbiasedness and statistical efficiency of model estimates and predictions. This research presents the first SSM that can be applied when length data are a key source of information, variation in growth is an essential part of the dynamics of the assessed stock, or when linking climate variables to growth in hindcasts or forecasts is relevant. Consequently, the state-space approach and growth estimation can be applied to more fish stocks worldwide, facilitating real-world applications and implementation of simulation experiments for performance evaluation of SSMs for the many stocks whose assessments rely on length data. [ABSTRACT FROM AUTHOR]

Deviations from equal sex ratios in mammals can reveal insights into sex‐specific growth, survival, movements, and behavior. We assessed blue whale (Balaenoptera musculus) sex ratios based on 21,542 fetal and 311,901 whaling records, finding that males were slightly but significantly more common than females (51.3% fetal, 52.1% postnatal). Antarctic catches shifted from 52.4% male before 1951 to 48.0% male thereafter, even though larger females were preferentially targeted by whalers and should have declined. The southernmost land stations caught more males than those in southern Africa, and at land stations, sex ratios shifted subtly over the course of a year. Pelagic catches demonstrated spatial structure in sex ratios, including more males being caught in the Ross Sea. In utero, the smallest females were often misidentified as males, and there was some evidence for higher prenatal male mortality. Once born, medium‐sized blue whales within each region were more often male, while the longest were nearly all female; explained entirely by females growing faster and reaching longer sizes. Overall, though, sex ratios are remarkably close to equality across time, space, and length; with any deviations best explained by faster female growth and size‐selective whaling. [ABSTRACT FROM AUTHOR]

Statistical inference is a widely-used, powerful tool for learning about natural processes in diverse fields. The statistical software platforms AD Model Builder (ADMB) and Template Model Builder (TMB) are particularly popular in the ecological literature, where they are typically used to perform frequentist inference of complex models. However, both lack capabilities for flexible and efficient Markov chain Monte Carlo (MCMC) integration. Recently, the no-U-turn sampler (NUTS) MCMC algorithm has gained popularity for Bayesian inference through the software Stan because it is efficient for high dimensional, complex hierarchical models. Here, we introduce the R packages and , which provide NUTS sampling in parallel and interactive diagnostics with ShinyStan. The ADMB source code was modified to provide NUTS, while TMB models are linked directly into Stan. We describe the packages, provide case studies demonstrating their use, and contrast performance against Stan. For TMB models, we show how to test the accuracy of the Laplace approximation using NUTS. For complex models, the performance of ADMB and TMB was typically within +/- 50% the speed of Stan. In one TMB case study we found inaccuracies in the Laplace approximation, potentially leading to biased inference. provides a new method for estimating hierarchical ADMB models which previously were infeasible. TMB users can fit the same model in both frequentist and Bayesian paradigms, including using NUTS to test the validity of the Laplace approximation of the marginal likelihood for arbitrary subsets of parameters. These software developments extend the available statistical methods of the ADMB and TMB user base with no additional effort by the user. [ABSTRACT FROM AUTHOR]

Bayesian inference is a powerful tool to better understand ecological processes across varied subfields in ecology, and is often implemented in generic and flexible software packages such as the widely used BUGS family (BUGS, WinBUGS, OpenBUGS and JAGS). However, some models have prohibitively long run times when implemented in BUGS. A relatively new software platform called Stan uses Hamiltonian Monte Carlo (HMC), a family of Markov chain Monte Carlo (MCMC) algorithms which promise improved efficiency and faster inference relative to those used by BUGS. Stan is gaining traction in many fields as an alternative to BUGS, but adoption has been slow in ecology, likely due in part to the complex nature of HMC., Here, we provide an intuitive illustration of the principles of HMC on a set of simple models. We then compared the relative efficiency of BUGS and Stan using population ecology models that vary in size and complexity. For hierarchical models, we also investigated the effect of an alternative parameterization of random effects, known as non-centering., For small, simple models there is little practical difference between the two platforms, but Stan outperforms BUGS as model size and complexity grows. Stan also performs well for hierarchical models, but is more sensitive to model parameterization than BUGS. Stan may also be more robust to biased inference caused by pathologies, because it produces diagnostic warnings where BUGS provides none. Disadvantages of Stan include an inability to use discrete parameters, more complex diagnostics and a greater requirement for hands-on tuning., Given these results, Stan is a valuable tool for many ecologists utilizing Bayesian inference, particularly for problems where BUGS is prohibitively slow. As such, Stan can extend the boundaries of feasible models for applied problems, leading to better understanding of ecological processes. Fields that would likely benefit include estimation of individual and population growth rates, meta-analyses and cross-system comparisons and spatiotemporal models. [ABSTRACT FROM AUTHOR]

A typical assumption used in most fishery stock assessments is that natural mortality (M) is constant across time and age. However, M is rarely constant in reality as a result of the combined impacts of exploitation history, predation, environmental factors, and physiological trade-offs. Misspecification or poor estimation of M can lead to bias in quantities estimated using stock assessment methods, potentially resulting in biased estimates of fishery reference points and catch limits, with the magnitude of bias being influenced by life history and trends in fishing mortality. Monte Carlo simulations were used to evaluate the ability of statistical age-structured population models to estimate spawning-stock biomass, fishing mortality, and total allowable catch when the true M was age-invariant, but time-varying. Configurations of the stock assessment method, implemented in Stock Synthesis, included a single age- and time-invariant M parameter, specified at one of the three levels (high, medium, and low) or an estimated M. The min–max (i.e. most robust) approach to specifying M when it is thought to vary across time was to estimate M. The least robust approach for most scenarios examined was to fix M at a high value, suggesting that the consequences of misspecifying M are asymmetric. [ABSTRACT FROM PUBLISHER]

Blue whales were targeted in the North Pacific from 1905-1971 and are listed as endangered by the IUCN. Despite decades without whaling, abundance estimates for eastern North Pacific ( ENP) blue whales ( Balaenoptera musculus) suggest little evidence for a recent increase. One possible reason is fatal strikes by large ships, which have affected populations of other cetaceans and resulted in mitigation. We used a population dynamics model to assess the trends and status of ENP blue whales, and the effects of ship strikes. We estimate the population likely never dropped below 460 individuals, and is at 97% of carrying capacity (95% interval 62%-99%). These results suggest density dependence, not ship strikes, is the key reason for the observed lack of increase. We also estimate future strikes will likely have a minimal impact; for example, an 11-fold increase in vessels would lead to a 50% chance the long-term population would be considered depleted. Although we estimate ship strike mitigation would have minimal impacts on population trends and status, current levels of ship strikes are likely above legal limits set by the U.S. The recovery of ENP blue whales from whaling demonstrates the ability of blue whale populations to rebuild under careful management. [ABSTRACT FROM AUTHOR]

Management of marine resources depends on the assessment of stock status in relation to established reference points. However, many factors contribute to uncertainty in stock assessment outcomes, including data type and availability, life history, and exploitation history. A simulation–estimation framework was used to examine the level of bias and accuracy in assessment model estimates related to the quality and quantity of length and age composition data across three life-history types (cod-, flatfish-, and sardine-like species) and three fishing scenarios. All models were implemented in Stock Synthesis, a statistical age-structured stock assessment framework. In general, the value of age composition data in informing estimates of virgin recruitment (R0), relative spawning-stock biomass (SSB100/SSB0), and terminal year fishing mortality rate (F100), decreased as the coefficient of variation of the relationship between length and age became greater. For this reason, length data were more informative than age data for the cod and sardine life histories in this study, whereas both sources of information were important for the flatfish life history. Historical composition data were more important for short-lived, fast-growing species such as sardine. Infrequent survey sampling covering a longer period was more informative than frequent surveys covering a shorter period. [ABSTRACT FROM PUBLISHER]