6533b7d2fe1ef96bd125e0f9
RESEARCH PRODUCT
Moving Toward a Strategy for Addressing Climate Displacement of Marine Resources: A Proof-of-Concept
Giuseppe BaiamonteMagnus L. JohnsonBrian HelmuthGray A. WilliamsTania SousaAngela CuttittaM. Cristina ManganoFabio FiorentinoAntonio GiacolettiTiago DomingosNova MieszkowskaNova MieszkowskaGiuseppe BazanGiuseppe LucidoFabio PranoviGianluca SaràMarco MarcelliMarco MarcelliBernardo PattiSimone MirtoRiccardo MartellucciRiccardo Martelluccisubject
0106 biological sciencesMarine conservationSettore BIO/07 - Ecologia010504 meteorology & atmospheric scienceslcsh:QH1-199.5Engraulis encrasicolusProcess (engineering)Computer scienceClimate changeOcean EngineeringAquatic Sciencelcsh:General. Including nature conservation geographical distributionclimate-informed management; Dynamic Energy Budget model; Engraulis encrasicolus; life-history traits; scenarios; temperature increaseOceanography01 natural sciencesEnvironmental dataDynamic Energy Budget model14. Life underwaterNatural resource managementlcsh:Scienceclimate-informed management0105 earth and related environmental sciencesWater Science and TechnologyGlobal and Planetary Changebusiness.industry010604 marine biology & hydrobiologyEnvironmental resource managementscenariosNatural resourcelife-history traitsAdaptive management13. Climate actionSettore BIO/03 - Botanica Ambientale E Applicatatemperature increaselcsh:QFisheries managementbusinessdescription
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.
year | journal | country | edition | language |
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2020-01-01 |