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Auteur Benedetti, F.; Guilhaumon, F.; Adloff, F.; Ayata, S.-D.
Titre (up) Investigating uncertainties in zooplankton composition shifts under climate change scenarios in the Mediterranean Sea Type Article scientifique
Année 2018 Publication Revue Abrégée Ecography
Volume 41 Numéro 2 Pages 345-360
Mots-Clés marine biodiversity; species distribution models; north-atlantic; beta diversity; calanoid copepods; ecological-niche; envelope models; habitat-suitability; mass mortality; pseudo-absence data
Résumé Ensemble niche modelling has become a common framework to predict changes in assemblages composition under climate change scenarios. The amount of uncertainty generated by the different components of this framework has rarely been assessed. In the marine realm forecasts have usually focused on taxa representing the top of the marine food-web, thus overlooking their basal component: the plankton. Calibrating environmental niche models at the global scale, we modelled the habitat suitability of 106 copepod species and estimated the dissimilarity between present and future zooplanktonic assemblages in the surface Mediterranean Sea. We identified the patterns (species replacement versus nestedness) driving the predicted dissimilarity, and quantified the relative contributions of different uncertainty sources: environmental niche models, greenhouse gas emission scenarios, circulation model configurations and species prevalence. Our results confirm that the choice of the niche modelling method is the greatest source of uncertainty in habitat suitability projections. Presence-only and presence-absence methods provided different visions of the niches, which subsequently lead to different future scenarios of biodiversity changes. Nestedness with decline in species richness is the pattern driving dissimilarity between present and future copepod assemblages. Our projections contrast with those reported for higher trophic levels, suggesting that different components of the pelagic food-web may respond discordantly to future climatic changes.
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ISSN 0906-7590 ISBN Médium
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Numéro d'Appel MARBEC @ alain.herve @ collection 2282
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Auteur Schickele, A.; Leroy, B.; Beaugrand, G.; Goberville, E.; Hattab, T.; Francour, P.; Raybaud, V.
Titre (up) Modelling European small pelagic fish distribution: Methodological insights Type Article scientifique
Année 2020 Publication Revue Abrégée Ecological Modelling
Volume 416 Numéro Pages 108902
Mots-Clés Convex hull; Pseudo-absence; Sampling bias; Small pelagic fish; Species distribution models; Uncertainty
Résumé The distribution of marine organisms is strongly influenced by climatic gradients worldwide. The ecological niche (sensu Hutchinson) of a species, i.e. the combination of environmental tolerances and resources required by an organism, interacts with the environment to determine its geographical range. This duality between niche and distribution allows climate change biologists to model potential species’ distributions from past to future conditions. While species distribution models (SDMs) have been intensively used over the last years, no consensual framework to parametrise, calibrate and evaluate models has emerged. Here, to model the contemporary (1990–2017) spatial distribution of seven highly harvested European small pelagic fish species, we implemented a comprehensive and replicable numerical procedure based on 8 SDMs (7 from the Biomod2 framework plus the NPPEN model). This procedure considers critical issues in species distribution modelling such as sampling bias, pseudo-absence selection, model evaluation and uncertainty quantification respectively through (i) an environmental filtration of observation data, (ii) a convex hull based pseudo-absence selection, (iii) a multi-criteria evaluation of model outputs and (iv) an ensemble modelling approach. By mitigating environmental sampling bias in observation data and by identifying the most ecologically relevant predictors, our framework helps to improve the modelling of fish species’ environmental suitability. Not only average temperature, but also temperature variability appears as major factors driving small pelagic fish distribution, and areas of highest environmental suitability were found along the north-western Mediterranean coasts, the Bay of Biscay and the North Sea. We demonstrate in this study that the use of appropriate data pre-processing techniques, an often-overlooked step in modelling, increase model predictive performance, strengthening our confidence in the reliability of predictions.
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Volume de collection Numéro de collection Edition
ISSN 0304-3800 ISBN Médium
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Notes WOS:000514022500015 Approuvé pas de
Numéro d'Appel MARBEC @ isabelle.vidal-ayouba @ collection 2675
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Auteur Stephenson, F.; Goetz, K.; Sharp, B.R.; Mouton, T.L.; Beets, F.L.; Roberts, J.; MacDiarmid, A.B.; Constantine, R.; Lundquist, C.J.
Titre (up) Modelling the spatial distribution of cetaceans in New Zealand waters Type Article scientifique
Année 2020 Publication Revue Abrégée Diversity and Distributions
Volume 26 Numéro 4 Pages 495-516
Mots-Clés boosted regression tree models; cetacean distribution; New Zealand; relative environmental suitability models; spatial management; species distribution models
Résumé Aim Cetaceans are inherently difficult to study due to their elusive, pelagic and often highly migratory nature. New Zealand waters are home to 50% of the world's cetacean species, but their spatial distributions are poorly known. Here, we model distributions of 30 cetacean taxa using an extensive at-sea sightings dataset (n > 14,000) and high-resolution (1 km2) environmental data layers. Location New Zealand's Exclusive Economic Zone (EEZ). Methods Two models were used to predict probability of species occurrence based on available sightings records. For taxa with <50 sightings (n = 15), Relative Environmental Suitability (RES), and for taxa with ≥50 sightings (n = 15), Boosted Regression Tree (BRT) models were used. Independently collected presence/absence data were used for further model evaluation for a subset of taxa. Results RES models for rarely sighted species showed reasonable fits to available sightings and stranding data based on literature and expert knowledge on the species' autecology. BRT models showed high predictive power for commonly sighted species (AUC: 0.79–0.99). Important variables for predicting the occurrence of cetacean taxa were temperature residuals, bathymetry, distance to the 500 m isobath, mixed layer depth and water turbidity. Cetacean distribution patterns varied from highly localised, nearshore (e.g., Hector's dolphin), to more ubiquitous (e.g., common dolphin) to primarily offshore species (e.g., blue whale). Cetacean richness based on stacked species occurrence layers illustrated patterns of fewer inshore taxa with localised richness hotspots, and higher offshore richness especially in locales of the Macquarie Ridge, Bounty Trough and Chatham Rise. Main conclusions Predicted spatial distributions fill a major knowledge gap towards informing future assessments and conservation planning for cetaceans in New Zealand's extensive EEZ. While sightings datasets were not spatially comprehensive for any taxa, these two best available approaches allow for predictive modelling of both more common, and of rarely sighted, cetacean species with limited available information.
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Éditeur de collection Titre de collection Titre de collection Abrégé
Volume de collection Numéro de collection Edition
ISSN 1472-4642 ISBN Médium
Région Expédition Conférence
Notes WOS:000510589200001 Approuvé pas de
Numéro d'Appel MARBEC @ isabelle.vidal-ayouba @ collection 2692
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Auteur Cazelles, K.; Mouquet, N.; Mouillot, D.; Gravel, D.
Titre (up) On the integration of biotic interaction and environmental constraints at the biogeographical scale Type Article scientifique
Année 2016 Publication Revue Abrégée Ecography
Volume 39 Numéro 10 Pages 921-931
Mots-Clés biodiversity; climate-change; cooccurrence; distributions; ecological communities; evolutionary; food webs; networks; niche; species distribution models
Résumé Biogeography is primarily concerned with the spatial distribution of biodiversity, including performing scenarios in a changing environment. The efforts deployed to develop species distribution models have resulted in predictive tools, but have mostly remained correlative and have largely ignored biotic interactions. Here we build upon the theory of island biogeography as a first approximation to the assembly dynamics of local communities embedded within a metacommunity context. We include all types of interactions and introduce environmental constraints on colonization and extinction dynamics. We develop a probabilistic framework based on Markov chains and derive probabilities for the realization of species assemblages, rather than single species occurrences. We consider the expected distribution of species richness under different types of ecological interactions. We also illustrate the potential of our framework by studying the interplay between different ecological requirements, interactions and the distribution of biodiversity along an environmental gradient. Our framework supports the idea that the future research in biogeography requires a coherent integration of several ecological concepts into a single theory in order to perform conceptual and methodological innovations, such as the switch from single-species distribution to community distribution.
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Langue English Langue du Résumé Titre Original
Éditeur de collection Titre de collection Titre de collection Abrégé
Volume de collection Numéro de collection Edition
ISSN 0906-7590 ISBN Médium
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Notes Approuvé pas de
Numéro d'Appel MARBEC @ alain.herve @ collection 1683
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Auteur Yates, K.L.; Bouchet, P.J.; Caley, M.J.; Mengersen, K.; Randin, C.F.; Parnell, S.; Fielding, A.H.; Bamford, A.J.; Ban, S.; Marcia Barbosa, A.; Dormann, C.F.; Elith, J.; Embling, C.B.; Ervin, G.N.; Fisher, R.; Gould, S.; Graf, R.F.; Gregr, E.J.; Halpin, P.N.; Heikkinen, R.K.; Heinanen, S.; Jones, A.R.; Krishnakumar, P.K.; Lauria, V.; Lozano-Montes, H.; Mannocci, L.; Mellin, C.; Mesgaran, M.B.; Moreno-Amat, E.; Mormede, S.; Novaczek, E.; Oppel, S.; Crespo, G.O.; Peterson, A.T.; Rapacciuolo, G.; Roberts, J.J.; Ross, R.E.; Scales, K.L.; Schoeman, D.; Snelgrove, P.; Sundblad, G.; Thuiller, W.; Torres, L.G.; Verbruggen, H.; Wang, L.; Wenger, S.; Whittingham, M.J.; Zharikov, Y.; Zurell, D.; Sequeira, A.M.M.
Titre (up) Outstanding Challenges in the Transferability of Ecological Models Type Article scientifique
Année 2018 Publication Revue Abrégée Trends Ecol. Evol.
Volume 33 Numéro 10 Pages 790-802
Mots-Clés abundance; biotic interactions; climate-change; decision-making; distributions; habitat selection; niche; predictive models; species distribution models; temporal transferability
Résumé Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world. However, limited understanding of the accuracy and precision of models transferred to novel conditions (their 'transferability') undermines confidence in their predictions. Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers. These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best practices for transferring models. Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions.
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Editeur Lieu de Publication Éditeur
Langue English Langue du Résumé Titre Original
Éditeur de collection Titre de collection Titre de collection Abrégé
Volume de collection Numéro de collection Edition
ISSN 0169-5347 ISBN Médium
Région Expédition Conférence
Notes Approuvé pas de
Numéro d'Appel MARBEC @ alain.herve @ collection 2447
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