We sought to determine the potential effect of invasive green crab (Carcinus maenas) on commercially and ecologically important species in the Pacific Northwest through choice and no-choice assays conducted with green crab of different sizes. We looked at the feeding behavior of green crab in relation to various prey choices, including adult Manila clam (Ruditapes philippinarum), adult Pacific oyster (Crassostrea gigas), young Pacific oyster as spat on shell, and native eelgrass (Zostera marina). No-choice assays were modeled with a negative binomial regression, and choice assays were modeled with a logistic regression. Results from the no-choice model reveal that the interaction of claw size and prey type was significant, and green crab of all sizes fed on spat of Pacific oyster on shells. Results from the choice model indicate that sex was not significant in predicting whether green crab consumed any prey type. In our study, green crab that fed exclusively on 1 prey type chose spat on shell or eelgrass over adult prey items. On the basis of the data, we suggest that growers focus on protecting spat of Pacific oyster from all sizes of green crab over protecting adult Pacific oyster if resources are limited.

Environmental and anthropogenic processes have led to widespread changes in productivities and spatial distributions of marine fishery resources. As geographic distributions of fish stocks and subsequently fishing fleets shift, improved spatiotemporal data and spatial modeling will become necessary to estimate abundance and productivity. The goal of this paper is to propose a strategy for engineering a modeling platform for spatially explicit, next-generation stock assessment models. We recount our approach for developing a system prototype, the Metapopulation Assessment System (MAS), that is easy to use, modular, and extensible. The MAS prototype was designed to support complex metapopulation modeling, which includes handling multiple populations, areas, fleets, and surveys and sex differentiation. We describe the components of the software life cycle, engineering, and infrastructure design to support a spatially explicit, next-generation stock assessment system. Software infrastructure was designed and implemented with 3 components: GitHub for collaboration, version control, and code organization; the C++ language for coding fishery system dynamics and estimation modeling; and the R language for coding the input-output interface and systematic testing. Systematic testing was a key component of the MAS development life cycle and was applied to guarantee that system requirements, such as accurate estimation of quantities of interest, are successfully implemented. We conclude with a discussion of some lessons learned and future challenges for ongoing efforts to implement a next-generation stock assessment platform.

Deepwater fisheries have become increasingly important over the past couple of decades, yet challenges in adequately characterizing relative abundance and population demographics of deepwater stocks have persisted for fishery-independent surveys. Consequently, in stock assessments of the complex of deepwater snapper and grouper species along the Atlantic coast of the southeastern United States, fishery-dependent data have been relied on to track population trends, which may be biased by management actions and fishing behavior. In this study, we investigated the effects of increasing the sampling intensity and spatial scale of a historical deepwater fishery-independent survey on estimates of abundance and population demographics and aimed to identify important habitat associations for snowy grouper (Hyporthodus niveatus) and blueline tilefish (Caulolatilus microps). Increased sampling intensity and spatial expansion of the survey did not significantly affect estimates of abundance for either of these species, but model uncertainty was reduced for snowy grouper. Length compositions differed significantly for snowy grouper. Inclusion of significant covariates related to habitat association into indices of abundance did not affect estimates of abundance or uncertainty for snowy grouper but increased the magnitude of abundance and improved model fit for blueline tilefish. Identifying and incorporating habitat association information into stock assessments are critical for improving the management of data-limited deepwater species in the region.

Black sea bass (Centropristis striata) feed on epibenthic prey, particularly decapods, and become more piscivorous as they grow larger, a trend that has energetic consequences for growth. In the coming decades, construction of wind energy systems will expose black sea bass to a large-scale manipulation of continental shelf habitats in the northeastern United States. In this study, we tested the effects of habitat type (natural versus artificial reef habitats) on size, age, growth, diet, and trophic dynamics of black sea bass, using 407 specimens collected with rod-and-reel gear near Ocean City, Maryland, in 2016 and 2018. No significant differences in fish length, age, size at age, or diet are attributable to habitat. The stable isotope composition (δ13C and δ15N) in samples of 3 tissue types (liver, muscle, and mucus) vary significantly by habitat except for δ15N values in mucus samples. Across tissue type, δ13C values are higher for fish at artificial habitats, indicating more littoral than pelagic feeding. We conclude that, although both types of reef habitats are ecologically equivalent as a source of growth and diet for black sea bass, the differences in stable isotope signatures indicate functional differences in system energy flow that should be investigated further in this and other marine species that will be affected by offshore wind energy development.

Accurate estimates of age, somatic growth, maturity, and natural mortality are essential for effective conservation of endangered species. This study resulted in updated growth data and the first direct assessments of length at maturity and age at maturity for the endangered smalltooth sawfish (Pristis pectinata). A Bayesian approach using the von Bertalanffy growth function was used to combine vertebral band counts, mark-recapture data, and results from increment analysis to estimate somatic growth and to derive age at maturity and natural mortality rates. Smalltooth sawfish grow rapidly in their first 3 years, reaching 235 cm stretch total length (STL), 3.2 times their mean length at birth (73.7 cm STL), before growth slows. Asymptotic length was 446 cm STL for males and 484 cm STL for females, with a Brody growth coefficient of 0.178 year−1 for males and 0.170 year−1 for females. We directly estimated median age at maturity as 6.9 years for males and 7.9 years for females, similar to previous indirect assessments. Constant natural mortality was estimated to be between 0.151 and 0.278 on the basis of life history surrogates. The oldest individual examined in this study was a 30.1-year-old female, confirming that the species exceeds 30 years in the wild. These results are vital for refining population recovery models, and they underscore the need for ongoing monitoring and data collection to support long-term recovery efforts.

The aim of stock assessment modeling is to evaluate current and future stock statuses under various management scenarios. For these assessments, particularly short-term projections, researchers rely heavily on recruitment estimates. However, accurately estimating recruitment levels, especially for the most recent years, is challenging because reliable information is limited. Indices of relative recruitment can provide valuable insights for stock assessment models in such cases. Herein, a method for assessing the reliability of a recruitment index with diagnostic and randomization tests in an age-structured production model (ASPM) is presented. The proposed method can be used to evaluate whether the process variability implied by a recruitment index for the spawner–recruit relationship enhances the connection between observed catches, indices of adult abundance, and the assessment model’s production function. We applied this approach to Pacific bluefin tuna (Thunnus orientalis) as an illustrative example. Results indicate that the ASPM, with recruitment fluctuations matching the recruitment index for the Sea of Japan (ASPM-R-FIX), improved the fits to recent adult abundance indices over those of the standard ASPM models. The results from statistical analysis further provide strong evidence that extreme recruitment fluctuations in the ASPM-R-FIX enhanced predictions for recent indices for adults. This analysis revealed a strong link between recruitment variability and adult abundance, highlighting the importance of adding a consistent recruitment index to an assessment model to improve management decisions.