FN Archimer Export Format
PT J
TI Impacts of climate change on the Bay of Seine ecosystem: Forcing a spatio‐temporal trophic model with predictions from an ecological niche model
BT 
AF Bourdaud, Pierre
   Ben Rais Lasram, Frida
   Araignous, Emma
   Champagnat, Juliette
   Grusd, Samantha
   Halouani, Ghassen
   Hattab, Tarek
   Leroy, Boris
   Noguès, Quentin
   Raoux, Aurore
   Safi, Georges
   Niquil, Nathalie
AS 1:1;2:1;3:1,2;4:1;5:3,4;6:5;7:6;8:7;9:8;10:8,9;11:2,8;12:8;
FF 1:;2:;3:;4:;5:;6:PDG-RBE-HMMN-LRHBL;7:PDG-RBE-MARBEC-LHM;8:;9:;10:;11:;12:;
C1 CNRS, UMR 8187, LOG, Laboratoire d’Océanologie et de Géosciences, Univ. Littoral Côte d’Opale, Univ. Lille, Wimereux, France
   France Energies Marines ITE-EMR, Plouzané, France
   Marine Research (MA-RE) Institute, University of Cape Town, Rondebosch, South Africa
   Department of Biological Sciences, University of Cape Town, Rondebosch, South Africa
   Ressources Halieutiques, Ifremer Manche Mer du Nord, Boulogne-sur- Mer, France
   MARBEC, Univ Montpellier, CNRS, Ifremer, IRD Sète, Sète, France
   MNHN, UMR BOREA (MNHN, UPMC, UCN, CNRS-7208, IRD-207), Paris, France
   Laboratoire BOREA (MNHN, UPMC, UCN, CNRS, IRD), Normandie Université UNICAEN, Caen, France
   Laboratoire Morphodynamique Continentale et Côtière, UNICAEN, UNIROUEN, Normandie Univ., Caen, France
C2 CNRS, FRANCE
   FRANCE ENERGIES MARINES, FRANCE
   UNIV CAPE TOWN, SOUTH AFRICA
   UNIV CAPE TOWN, SOUTH AFRICA
   IFREMER, FRANCE
   IFREMER, FRANCE
   MNHN, FRANCE
   UNIV CAEN, FRANCE
   UNIV NORMANDIE, FRANCE
SI BOULOGNE
   SETE
SE PDG-RBE-HMMN-LRHBL
   PDG-RBE-MARBEC-LHM
UM MARBEC
IN WOS Ifremer UPR
   WOS Ifremer UMR
   copubli-france
   copubli-univ-france
   copubli-int-hors-europe
   copubli-sud
IF 2.67
TC 7
UR https://archimer.ifremer.fr/doc/00682/79413/82046.pdf
LA English
DT Article
DE ;climate change;ecological niche modelling;Ecospace;fisheries;trophic interactions
AB Climate change is already known to cause irreversible impacts on ecosystems that are difficult to accurately predict due to the multiple scales at which it will interact. Predictions at the community level are mainly focused on the future distribution of marine species biomass using ecological niche modelling, which requires extensive efforts concerning the effects that trophic interactions could have on the realized species dynamics. In this study, a set of species distribution models predictions were used to force the spatially‐explicit trophic model Ecospace in order to evaluate the potentials impacts that two 2,100 climate scenarios, RCP2.6 and RCP8.5, could have on a highly exploited ecosystem, the Bay of Seine (France). Simulations demonstrated that both scenarios would influence the community of the Bay of Seine ecosystem: as expected, more intense changes were predicted with the extreme scenario RCP8.5 than with the RCP2.6 scenario. Under both scenarios, a majority of species underwent a decrease of biomass, although some increased. However, in both cases the stability of the majority of species dynamics was lowered, the sustainability of the fishery. Differences between niche modelling predictions and those obtained through the forcing in Ecospace highlighted the paramount importance of considering trophic interactions in climate change simulations. These results illustrate the requirement of multiplying novel approaches for efficiently forecasting potential impacts of climate change. 
PY 2021
PD SEP
SO Fisheries Oceanography
SN 1054-6006
PU Wiley
VL 30
IS 5
UT 000623888200001
BP 471
EP 489
DI 10.1111/fog.12531
ID 79413
ER

EF