Murray S. A. Thompson, Izaskun Preciado, Federico Maioli, Valerio Bartolino, Andrea Belgrano, Michele Casini, Pierre Cresson, Elena Eriksen, Gema Hernandez-Milian, Ingibjörg G. Jónsdóttir, Stefan Neuenfeldt, John F. Pinnegar, Stefán Ragnarsson, Sabine Schueckel, Ulrike Schueckel, Brian E. Smith, María Á. Torres, Thomas J. Webb, Christopher P. Lynam
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引用次数: 0
Abstract
Abstract. International efforts to assess the status of marine ecosystems have been hampered by insufficient observations of food web interactions across many species, their various life stages, and geographic ranges. Hence, we collated data from multiple databases of fish stomach contents from samples taken across the North Atlantic and Arctic Oceans containing 944,129 stomach samples from larvae to adults, with 14,196 unique interactions between 227 predator species and 2158 prey taxa. We use these data to develop a data-driven, reproducible approach to classifying broad functional feeding guilds and then apply these to fish survey data from the Northeast Atlantic shelf seas to reveal spatial and temporal changes in ecosystem structure and functioning. In doing so, we construct predator-prey body size scaling models to predict the biomass of prey functional groups, e.g., zooplankton, benthos, and fish, for different predator species. These predictions provide empirical estimates of species- and size-specific feeding traits of fish, such as predator-prey mass ratios, individual prey mass, and the biomass contribution of different prey to predator diets. The functional groupings and feeding traits provided here help to further resolve our understanding of interactions within marine food webs and support the use of trait-based indicators in biodiversity assessments. The data used and predictions generated in this study are published on the Cefas Data Hub at: https://doi.org/10.14466/CefasDataHub.149 (Thompson et al., 2024).
Earth System Science DataGEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
18.00
自引率
5.30%
发文量
231
审稿时长
35 weeks
期刊介绍:
Earth System Science Data (ESSD) is an international, interdisciplinary journal that publishes articles on original research data in order to promote the reuse of high-quality data in the field of Earth system sciences. The journal welcomes submissions of original data or data collections that meet the required quality standards and have the potential to contribute to the goals of the journal. It includes sections dedicated to regular-length articles, brief communications (such as updates to existing data sets), commentaries, review articles, and special issues. ESSD is abstracted and indexed in several databases, including Science Citation Index Expanded, Current Contents/PCE, Scopus, ADS, CLOCKSS, CNKI, DOAJ, EBSCO, Gale/Cengage, GoOA (CAS), and Google Scholar, among others.