Moving Toward a Strategy for Addressing Climate Displacement of Marine Resources: A Proof-of-Concept
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 actio...
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Frontiers Media S.A.
2020-07-01
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Series: | Frontiers in Marine Science |
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Online Access: | https://www.frontiersin.org/article/10.3389/fmars.2020.00408/full |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
M. Cristina Mangano Nova Mieszkowska Nova Mieszkowska Brian Helmuth Tiago Domingos Tania Sousa Giuseppe Baiamonte Giuseppe Bazan Angela Cuttitta Fabio Fiorentino Antonio Giacoletti Magnus Johnson Giuseppe D. Lucido Marco Marcelli Marco Marcelli Riccardo Martellucci Riccardo Martellucci Simone Mirto Bernardo Patti Fabio Pranovi Gray A. Williams Gianluca Sarà |
spellingShingle |
M. Cristina Mangano Nova Mieszkowska Nova Mieszkowska Brian Helmuth Tiago Domingos Tania Sousa Giuseppe Baiamonte Giuseppe Bazan Angela Cuttitta Fabio Fiorentino Antonio Giacoletti Magnus Johnson Giuseppe D. Lucido Marco Marcelli Marco Marcelli Riccardo Martellucci Riccardo Martellucci Simone Mirto Bernardo Patti Fabio Pranovi Gray A. Williams Gianluca Sarà Moving Toward a Strategy for Addressing Climate Displacement of Marine Resources: A Proof-of-Concept Frontiers in Marine Science climate-informed management Dynamic Energy Budget model Engraulis encrasicolus life-history traits scenarios temperature increase |
author_facet |
M. Cristina Mangano Nova Mieszkowska Nova Mieszkowska Brian Helmuth Tiago Domingos Tania Sousa Giuseppe Baiamonte Giuseppe Bazan Angela Cuttitta Fabio Fiorentino Antonio Giacoletti Magnus Johnson Giuseppe D. Lucido Marco Marcelli Marco Marcelli Riccardo Martellucci Riccardo Martellucci Simone Mirto Bernardo Patti Fabio Pranovi Gray A. Williams Gianluca Sarà |
author_sort |
M. Cristina Mangano |
title |
Moving Toward a Strategy for Addressing Climate Displacement of Marine Resources: A Proof-of-Concept |
title_short |
Moving Toward a Strategy for Addressing Climate Displacement of Marine Resources: A Proof-of-Concept |
title_full |
Moving Toward a Strategy for Addressing Climate Displacement of Marine Resources: A Proof-of-Concept |
title_fullStr |
Moving Toward a Strategy for Addressing Climate Displacement of Marine Resources: A Proof-of-Concept |
title_full_unstemmed |
Moving Toward a Strategy for Addressing Climate Displacement of Marine Resources: A Proof-of-Concept |
title_sort |
moving toward a strategy for addressing climate displacement of marine resources: a proof-of-concept |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Marine Science |
issn |
2296-7745 |
publishDate |
2020-07-01 |
description |
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. |
topic |
climate-informed management Dynamic Energy Budget model Engraulis encrasicolus life-history traits scenarios temperature increase |
url |
https://www.frontiersin.org/article/10.3389/fmars.2020.00408/full |
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doaj-c15b2084b1094b6abc33ce3dddc9ee2a2020-11-25T03:18:41ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452020-07-01710.3389/fmars.2020.00408539583Moving Toward a Strategy for Addressing Climate Displacement of Marine Resources: A Proof-of-ConceptM. Cristina Mangano0Nova Mieszkowska1Nova Mieszkowska2Brian Helmuth3Tiago Domingos4Tania Sousa5Giuseppe Baiamonte6Giuseppe Bazan7Angela Cuttitta8Fabio Fiorentino9Antonio Giacoletti10Magnus Johnson11Giuseppe D. Lucido12Marco Marcelli13Marco Marcelli14Riccardo Martellucci15Riccardo Martellucci16Simone Mirto17Bernardo Patti18Fabio Pranovi19Gray A. Williams20Gianluca Sarà21Stazione Zoologica Anton Dohrn, Dipartimento di Ecologia Marina Integrata (EMI), Palermo, ItalyThe Marine Biological Association of the UK, Plymouth, United KingdomSchool of Environmental Sciences, University of Liverpool, Liverpool, United KingdomMarine Science Center, Northeastern University, Nahant, MA, United StatesMARETEC – Marine Environment and Technology Centre, Instituto Superior Técnico (IST), University of Lisbon, Lisbon, PortugalMARETEC – Marine Environment and Technology Centre, Instituto Superior Técnico (IST), University of Lisbon, Lisbon, PortugalDipartimento di Scienze e Tecnologie, Università degli Studi del Sannio, Benevento, ItalyDipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche (STEBICEF), Università degli Studi di Palermo, Palermo, ItalyIstituto per lo Studio degli Impatti Antropici e Sostenibilità in Ambiente Marino (IAS) Consiglio Nazionale delle Ricerche (CNR), Torretta Granitola, ItalyIstituto per le Risorse Biologiche e per le Biotechnologie Marine (IRBIM) Consiglio Nazionale delle Ricerche (CNR), Mazara del Vallo, Italy0Dipartimento di Scienze della Terra e del Mare (DiSTeM), Università degli Studi di Palermo, Palermo, Italy1School of Environmental Sciences, University of Hull, Hull, United Kingdom0Dipartimento di Scienze della Terra e del Mare (DiSTeM), Università degli Studi di Palermo, Palermo, Italy2Laboratory of Experimental Oceanology and Marine Ecology, DEB, Tuscia University, Molo Vespucci snc Porto di Civitavecchia, Civitavecchia, Italy3Centro Euro-Mediterraneo sui Cambiamenti CLimatici (CMCC), Via Augusto Imperatore, Lecce, Italy2Laboratory of Experimental Oceanology and Marine Ecology, DEB, Tuscia University, Molo Vespucci snc Porto di Civitavecchia, Civitavecchia, Italy4National Institute of Oceanography and Applied Geophysics (OGS), Borgo Grotta Gigante, ItalyIstituto per lo Studio degli Impatti Antropici e Sostenibilità in Ambiente Marino (IAS) Consiglio Nazionale delle Ricerche (CNR), Torretta Granitola, ItalyIstituto per lo Studio degli Impatti Antropici e Sostenibilità in Ambiente Marino (IAS) Consiglio Nazionale delle Ricerche (CNR), Torretta Granitola, Italy5Department of Environmental Sciences, Informatics and Statistics, University Ca’ Foscari, Venice, Italy6The Swire Institute of Marine Science and School of Biological Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong0Dipartimento di Scienze della Terra e del Mare (DiSTeM), Università degli Studi di Palermo, Palermo, ItalyRealistic 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.https://www.frontiersin.org/article/10.3389/fmars.2020.00408/fullclimate-informed managementDynamic Energy Budget modelEngraulis encrasicoluslife-history traitsscenariostemperature increase |