Moving Toward a Strategy for Addressing Climate Displacement of Marine Resources: A Proof-of-Concept

M. Cristina Mangano, Nova Mieszkowska, Brian Helmuth, Tiago Domingos, Tania Sousa, Giuseppe Baiamonte, Giuseppe Bazan, Angela Cuttitta, Fabio Fiorentino, Antonio Giacoletti, Magnus Johnson, Giuseppe D. Lucido (+7 others)
2020 Frontiers in Marine Science  
Realistic predictions of climate change effects on natural resources are central to adaptation policies that try to reduce these impacts. However, most current forecasting approaches do not incorporate species-specific, process-based biological information, which limits their ability to inform actionable strategies. Mechanistic approaches, incorporating quantitative information on functional traits, can potentially predict species-and population-specific responses that result from the
more » ... from the cumulative impacts of small-scale processes acting at the organismal level, and can be used to infer population-level dynamics and inform natural resources management. Here we present a proof-of-concept study using the European anchovy as a model species that shows how a trait-based, mechanistic species distribution model can be used to explore the vulnerability of marine species to environmental changes, producing quantitative outputs useful for informing fisheries management. We crossed scenarios of temperature and food to generate quantitative maps of selected mechanistic model outcomes (e.g., Maximum Length and Total Reproductive Output). These results highlight changing patterns of source and sink spawning areas as well as the incidence of reproductive failure. This study demonstrates that model predictions based on functional traits can reduce the degree of uncertainty when forecasting future trends of fish stocks. Frontiers in Marine Science | July 2020 | Volume 7 | Article 408 Mangano et al. Climate-Informed Management at Sea GRAPHICAL ABSTRACT | Climate-informed management at sea. However, to be effective they must be based on high spatial-and temporal resolution environmental data. Such a sensitive and spatially explicit predictive approach may be used to inform more effective adaptive management strategies of resources in novel climatic conditions.
doi:10.3389/fmars.2020.00408 fatcat:ydcymjygrfh47in7oaw5gfstvy