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Auteur Boavida, J.; Assis, J.; Silva, I.; Serrao, E.A.
Titre Overlooked habitat of a vulnerable gorgonian revealed in the Mediterranean and Eastern Atlantic by ecological niche modelling Type Article scientifique
Année 2016 Publication Revue Abrégée Sci Rep
Volume 6 Numéro Pages 36460
Mots-Clés climate-change; marine ecosystems; octocorals; paramuricea-clavata; prediction; sea; species distribution models; suitability; temperature; validation
Résumé (up) Factors shaping the distribution of mesophotic octocorals (30-200 m depth) remain poorly understood, potentially leaving overlooked coral areas, particularly near their bathymetric and geographic distributional limits. Yet, detailed knowledge about habitat requirements is crucial for conservation of sensitive gorgonians. Here we use Ecological Niche Modelling (ENM) relating thirteen environmental predictors and a highly comprehensive presence dataset, enhanced by SCUBA diving surveys, to investigate the suitable habitat of an important structuring species, Paramuricea clavata, throughout its distribution (Mediterranean and adjacent Atlantic). Models showed that temperature (11.5-25.5 degrees C) and slope are the most important predictors carving the niche of P. clavata. Prediction throughout the full distribution (TSS 0.9) included known locations of P. clavata alongside with previously unknown or unreported sites along the coast of Portugal and Africa, including seamounts. These predictions increase the understanding of the potential distribution for the northern Mediterranean and indicate suitable hard bottom areas down to > 150 m depth. Poorly sampled habitats with predicted presence along Algeria, Alboran Sea and adjacent Atlantic coasts encourage further investigation. We propose that surveys of target areas from the predicted distribution map, together with local expert knowledge, may lead to discoveries of new P. clavata sites and identify priority conservation areas.
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Langue English Langue du Résumé Titre Original
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Volume de collection Numéro de collection Edition
ISSN 2045-2322 ISBN Médium
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Numéro d'Appel MARBEC @ alain.herve @ collection 1680
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Auteur Authier, M.; Saraux, C.; Péron, C.
Titre Variable selection and accurate predictions in habitat modelling: a shrinkage approach Type Article scientifique
Année 2017 Publication Revue Abrégée Ecography
Volume 40 Numéro 4 Pages 549-560
Mots-Clés account; distributional data; Ecology; indian-ocean; inference; Mediterranean Sea; regression methods; small pelagic fish; spatial autocorrelation; species distribution models
Résumé (up) Habitat modelling is increasingly relevant in biodiversity and conservation studies. A typical application is to predict potential zones of specific conservation interest. With many environmental covariates, a large number of models can he investigated but multi-model inference may become impractical. Shrinkage regression overcomes this issue by dealing with the identification and accurate estimation of effect size for prediction. In a Bayesian framework we investigated the use of a shrinkage prior, the Horseshoe, for variable selection in spatial generalized linear models (GLM). As study cases, we considered 5 datasets on small pelagic fish abundance in the Gulf of Lion (Mediterranean Sea, France) and 9 environmental inputs. We compared the predictive performances of a simple kriging model, a full spatial GLM model with independent normal priors for regression coefficients, a full spatial GLM model with a Horseshoe prior for regression coefficients and 2 zero-inflated models (spatial and non-spatial) with a Horseshoe prior. Predictive performances were evaluated by cross validation on a hold-out subset of the data: models with a Horseshoe prior performed best, and the full model with independent normal priors worst. With an increasing number of inputs, extrapolation quickly became pervasive as we tried to predict from novel combinations of covariate values. By shrinking regression coefficients with a Horseshoe prior, only one model needed to be fitted to the data in order to obtain reasonable and accurate predictions, including extrapolations.
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Langue English Langue du Résumé Titre Original
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Volume de collection Numéro de collection Edition
ISSN 0906-7590 ISBN Médium
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Numéro d'Appel MARBEC @ alain.herve @ collection 2130
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Auteur Mannocci, L.; Roberts, J.J.; Halpin, P.N.; Authier, M.; Boisseau, O.; Bradai, M.N.; Canadas, A.; Chicote, C.; David, L.; Di-Meglio, N.; Fortuna, C.M.; Frantzis, A.; Gazo, M.; Genov, T.; Hammond, P.S.; Holcer, D.; Kaschner, K.; Kerem, D.; Lauriano, G.; Lewis, T.; di Sciara, G.N.; Panigada, S.; Antonio Raga, J.; Scheinin, A.; Ridoux, V.; Vella, A.; Vella, J.
Titre Assessing cetacean surveys throughout the Mediterranean Sea: a gap analysis in environmental space Type Article scientifique
Année 2018 Publication Revue Abrégée Sci Rep
Volume 8 Numéro Pages 3126
Mots-Clés species distribution models; tursiops-truncatus; population-structure; sperm-whales; bottle-nosed dolphins; fin whales; habitat preference; pelagos sanctuary; seasonal distribution; whales balaenoptera-physalus
Résumé (up) Heterogeneous data collection in the marine environment has led to large gaps in our knowledge of marine species distributions. To fill these gaps, models calibrated on existing data may be used to predict species distributions in unsampled areas, given that available data are sufficiently representative. Our objective was to evaluate the feasibility of mapping cetacean densities across the entire Mediterranean Sea using models calibrated on available survey data and various environmental covariates. We aggregated 302,481 km of line transect survey effort conducted in the Mediterranean Sea within the past 20 years by many organisations. Survey coverage was highly heterogeneous geographically and seasonally: large data gaps were present in the eastern and southern Mediterranean and in non-summer months. We mapped the extent of interpolation versus extrapolation and the proportion of data nearby in environmental space when models calibrated on existing survey data were used for prediction across the entire Mediterranean Sea. Using model predictions to map cetacean densities in the eastern and southern Mediterranean, characterised by warmer, less productive waters, and more intense eddy activity, would lead to potentially unreliable extrapolations. We stress the need for systematic surveys of cetaceans in these environmentally unique Mediterranean waters, particularly in non-summer months.
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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 2045-2322 ISBN Médium
Région Expédition Conférence
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Numéro d'Appel MARBEC @ alain.herve @ collection 2312
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Auteur Meynard, C.N.; Kaplan, D.M.; Leroy, B.
Titre Detecting outliers in species distribution data: Some caveats and clarifications on a virtual species study Type Article scientifique
Année 2019 Publication Revue Abrégée J. Biogeogr.
Volume 46 Numéro 9 Pages 2141-2144
Mots-Clés enm; observation errors; outliers; prevalence; probabilistic approach; sample bias; simulations; species distribution models; thresholds; virtual ecology; virtual species
Résumé (up) Liu et al. (2018) used a virtual species approach to test the effects of outliers on species distribution models. In their simulations, they applied a threshold value over the simulated suitabilities to generate the species distributions, suggesting that using a probabilistic simulation approach would have been more complex and yield the same results. Here, we argue that using a probabilistic approach is not necessarily more complex and may significantly change results. Although the threshold approach may be justified under limited circumstances, the probabilistic approach has multiple advantages. First, it is in line with ecological theory, which largely assumes non-threshold responses. Second, it is more general, as it includes the threshold as a limiting case. Third, it allows a better separation of the relevant intervening factors that influence model performance. Therefore, we argue that the probabilistic simulation approach should be used as a general standard in virtual species studies.
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Langue English Langue du Résumé Titre Original
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Volume de collection Numéro de collection Edition
ISSN 0305-0270 ISBN Médium
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Notes WOS:000483602900019 Approuvé pas de
Numéro d'Appel MARBEC @ isabelle.vidal-ayouba @ collection 2640
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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 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 (up) 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
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Numéro d'Appel MARBEC @ alain.herve @ collection 2447
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