Marine and fisheries research

This study shows that increasing spatial resolution in ecological models can reduce prediction quality for some species, highlighting the need for careful spatial complexity selection.

This study shows that fish morphology can predict life history strategies, offering a scalable method for assessing demographic vulnerability in data-poor fish populations.

SwimmingIndividuals is an agent-based model framework that simulates marine ecosystems with high biological realism and computational scalability, reproducing complex ecological phenomena and testing management strategies.

This study examines temperature-related changes in nearshore fish communities in Casco Bay, Maine, using 11 years of beach seine survey data, showing shifts in species abundance and growth rates.

The paper examines the exploitation ratios of demersal fish species in the Celtic Seas and finds no evidence that rarer species have lower exploitation ratios than common ones, suggesting current management methods are insufficient for conserving the assemblage as a whole.

The paper examines how temperature variation and life history traits influence nonlinearity in marine fish population fluctuations, finding temperature amplifies nonlinearity while life history dampens it in slow-lived species.

The paper analyzes dynamic stability and sensitivity patterns in three Atlantic cod subpopulations to inform fisheries management.

This paper combines eDNA and acoustic-trawl data using a Bayesian joint model to estimate fish biomass, showing eDNA suggests broader distribution and potentially higher abundance of European anchovy.

The paper introduces the 'Green Band' concept to assess fishing pressure's impact on ecosystem structure using catch and production data across four case studies.

The paper evaluates the sustainability of a brown shrimp fishery using catch and effort data to estimate biological reference points and assess exploitation levels.

The paper identifies global hotspots of climate-driven fish biomass decline risks by integrating biomass projections, fishing effort, and socioeconomic vulnerability.

This study identifies declining prey densities as the main driver of size declines in lesser sandeel in the North Sea, while temperature effects are smaller and context-dependent.

The paper introduces surveyjoin, a database and R package that standardizes and integrates bottom trawl survey data from the Northeast Pacific Ocean to improve fisheries management and ecosystem assessments.

This study examines changes in fish and mollusc species in the Mediterranean Sea from 130,000 years ago to the Industrial Revolution, showing environmental and human impacts on their abundance and size.

This study examines fishing strategies in multispecies fisheries, showing predators are more affected by fishing than prey, and high yields come with ecological trade-offs and risks.

This study validates the use of dorsal scute microchemistry to reconstruct migratory life-history of Atlantic Sturgeon using telemetry data.

The paper models ecosystem changes in Newfoundland & Labrador after the cod collapse, showing shifts in biomass and species dominance, with capelin remaining low and Arctic cod becoming more prevalent.

The paper introduces IRIIS, a framework that integrates population genomics, fish biology, and fisheries policies to assess overexploitation risk in interjurisdictional fisheries.

This study examines group composition and its ontogenetic changes in two marine fish species, finding that group structure shifts from age/growth-similar individuals in juveniles to more random composition in sub-adults.

This paper introduces a discrete time model of stock-recruit relationships using life-history stanzas, showing it can generate diverse SR patterns and improve understanding of population dynamics.

This paper reviews 389 articles to assess the effectiveness of bycatch mitigation measures in fishing, finding pingers, TEDs, and BSLs most effective for marine mammals, sea turtles, and seabirds, respectively, while elasmobranchs remain challenging.

The paper uses machine learning to analyze tuna school association with dFADs using echo-sounder buoy data, finding symmetric aggregation and disaggregation times across oceans.

The paper develops predictive models to estimate proportions of Chinook Salmon ESUs in bycatch for Pacific Hake fisheries using genetic mixture analysis and regression methods.

This paper develops a Machine Learning model to estimate tuna biomass using oceanographic and echosounder FAD data.