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

Gianluca Sara', Antonio Giacoletti, Giuseppe Bazan, M. Cristina Mangano, Riccardo Martellucci, Nova Mieszkowska, Tania Sousa, Giuseppe Baiamonte, Marco Marcelli, Tiago Domingos, Bernardo Patti, Fabio Pranovi, Angela Cuttitta, Brian Helmuth, Fabio Fiorentino, Simone Mirto, Gray A. Williams, Magnus Johnson, Giuseppe Dejan Lucido

Risultato della ricerca: Articlepeer review

3 Citazioni (Scopus)

Abstract

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 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. 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.
Lingua originaleEnglish
pagine (da-a)1-16
Numero di pagine16
RivistaFrontiers in Marine Science
Volume7
Stato di pubblicazionePublished - 2020

All Science Journal Classification (ASJC) codes

  • Oceanography
  • Global and Planetary Change
  • Aquatic Science
  • Water Science and Technology
  • Environmental Science (miscellaneous)
  • Ocean Engineering

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