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Scientific bottom-trawl surveys are ecological observation programs conducted along continental shelves and slopes of seas and oceans that sample marine communities associated with the seafloor. These surveys report taxa occurrence, abundance and/or weight in space and time, and contribute to fisheries management as well as population and biodiversity research. Bottom-trawl surveys are conducted all over the world and represent a unique opportunity to understand ocean biogeography, macroecology, and global change. However, combining these data together for cross-ecosystem analyses remains challenging. Here, we present an integrated dataset of 29 publicly available bottom-trawl surveys conducted in national waters of 18 countries that are standardized and pre-processed, covering a total of 2,170 sampled fish taxa and 216,548 hauls collected from 1963 to 2021. We describe the processing steps to create the dataset, flags, and standardization methods that we developed to assist users in conducting spatio-temporal analyses with stable regional survey footprints. The aim of this dataset is to support research, marine conservation, and management in the context of global change.

Key traits of functional biodiversity are examined for 31,134 species of fishes. These traits are maximum body weight, productivity, and trophic level. A new, simple framework is presented that shows the combined usage of these traits, in ordinal categories, for close to 90% of extant species of fishes. Most species are clustered tightly along an evolutionary axis in size-productivity-trophic space (SPT-space) from few large, evolutionary old species with very low productivity to many medium-sized newly evolved species with high productivity, superseding Cope’s rule of a within-lineages trend towards larger size and lower productivity. The across-lineages evolutionary axis is also found in the subsets of marine, freshwater, and Arctic species. Another notable prediction is the five-fold increase in top predators in Arctic waters in 2100, which could cause the extinction of endemic species. The main purpose of this study is to demonstrate the usefulness of the SPT-framework for comparing functional biodiversity patterns in ecosystems by salinity, geography or time. Also, the SPT-framework was used to explore correlations with other traits such as body shape, and to display the position of individual species, represented by pictograms of body shape and habitat, within SPT-space.

This contribution presents the detailed responses to the peer-review of Froese et al. (2019) “Estimating stock status from relative abundance and resilience” (ICES J. Mar. Sci. 2019) which outlined a method called “AMSY” for inferring biomass trends for stocks for which only catch-per-unit-effort and limited ancillary (‘priors’) data are available. The responses emphasize that the required priors are legitimate and straightforward to obtain, thus, making AMSY a method of choice in data-sparse situations. This is also a good example of the role of peer-review in validating and improving science.

The Law of the Sea as well as regional and national laws and agreements require exploited populations or stocks to be managed so that they can produce maximum sustainable yields. However, exploitation level and stock status are unknown for most stocks because the data required for full stock assessments are missing. This study presents a new method (AMSY) that estimates relative population size when no catch data are available using time-series of catch-per-unit-effort or other relative abundance indices as the main input. AMSY predictions for relative stock size were not significantly different from the “true” values when compared with simulated data. Also, they were not significantly different from relative stock size estimated by data-rich models in 88% of the comparisons within 140 real stocks. Application of AMSY to 38 data-poor stocks showed the suitability of the method and led to the first assessments for 23 species. Given the lack of catch data as input, AMSY estimates of exploitation come with wide margins of uncertainty which may not be suitable for management. However, AMSY seems to be well suited for estimating productivity as well as relative stock size and may, therefore, aid in the management of data-poor stocks.

To facilitate the wider implementation of ecosystem modeling platforms and, thereby, to help advance ecosystem-based fisheries management (EBFM) worldwide, tools delivering a large quantity of inputs to ecosystem models are needed. We developed a web application providing OSMOSE ecosystem models with values for trophic, growth and reproduction parameters derived from data from two global information systems (FishBase and SeaLifeBase). Our web application guides the user through simple queries to extract information from FishBase and SeaLifeBase data archives, and it delivers all the configuration files necessary for running an OSMOSE model. Here, we present our web application and demonstrate it for the West Florida Shelf ecosystem. Our software architecture can serve as a basis for designing other advanced web applications using FishBase and SeaLifeBase data in support of EBFM.

The development of fisheries in the oceans, and other human drivers such as climate warming, have led to changes in species abundance, assemblages, trophic interactions, and ultimately in the functioning of marine food webs. Here, using a trophodynamic approach and global databases of catches and life history traits of marine species, we tested the hypothesis that anthropogenic ecological impacts may have led to changes in the global parameters defining the transfers of biomass within the food web. First, we developed two indicators to assess such changes: the Time Cumulated Indicator (TCI) measuring the residence time of biomass within the food web, and the Efficiency Cumulated Indicator (ECI) quantifying the fraction of secondary production reaching the top of the trophic chain. Then, we assessed, at the large marine ecosystem scale, the worldwide change of these two indicators over the 1950-2010 time-periods. Global trends were identified and cluster analyses were used to characterize the variability of trends between ecosystems. Results showed that the most common pattern over the study period is a global decrease in TCI, while the ECI indicator tends to increase. Thus, changes in species assemblages would induce faster and apparently more efficient biomass transfers in marine food webs. Results also suggested that the main driver of change over that period had been the large increase in fishing pressure. The largest changes occurred in ecosystems where 'fishing down the marine food web' are most intensive.