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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 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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ISSN 0906-7590 ISBN Médium
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Numéro d'Appel MARBEC @ alain.herve @ collection 2130
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Auteur Bailleul, D.; Stoeckel, S.; Arnaud-Haond, S.
Titre RClone: a package to identify MultiLocus Clonal Lineages and handle clonal data sets in r Type Article scientifique
Année 2016 Publication Revue Abrégée Methods Ecol. Evol.
Volume 7 Numéro 8 Pages 966-970
Mots-Clés clonal diversity; clonality; clonal population; diversity; genotype; markers; multilocus genotypes; multilocus lineages; organisms; population-genetics; program; software; spatial autocorrelation
Résumé Partially, clonal species are common in the Tree of Life. And yet, population genetic models still mostly focus on the extremes: strictly sexual versus purely asexual reproduction. Here, we present an R package built upon genclone software including new functions and several improvements. The RClone package includes functions to handle clonal data sets, allowing (i) checking for data set reliability to discriminate multilocus genotypes (MLGs), (ii) ascertainment of MLG and semi-automatic determination of clonal lineages (MLL), (iii) genotypic richness and evenness indices calculation based on MLGs or MLLs and (iv) describing several spatial components of clonality. RClone allows the one-shot analysis of multipopulation data sets without size limitation, suitable for data sets now increasingly produced through next-generation sequencing. A major improvement compared to existing software is the ability to determine the threshold to cluster similar MLGs into MLLs, based on implemented simulations of sexual events. Several functions allow data importation, conversion and exportation with adegenet, Genetix or Arlequin. RClone is provided with two vignettes to handle analysis on one (RClonequickmanual) or several populations (RCloneqmsevpops).
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ISSN 2041-210x ISBN Médium
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Numéro d'Appel MARBEC @ alain.herve @ collection 1637
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Auteur Parravicini, V.; Kulbicki, M.; Bellwood, D.R.; Friedlander, A.M.; Arias-Gonzalez, J.E.; Chabanet, P.; Floeter, S.R.; Myers, R.; Vigliola, L.; D'Agata, S.; Mouillot, D.
Titre Global patterns and predictors of tropical reef fish species richness Type Article scientifique
Année 2013 Publication Revue Abrégée Ecography
Volume 36 Numéro 12 Pages 1254-1262
Mots-Clés Biogeography; constraints; coral-reefs; dispersal; diversity; eastern; gradients; marine biodiversity; ocean; pacific; spatial autocorrelation
Résumé In the marine realm, the tropics host an extraordinary diversity of taxa but the drivers underlying the global distribution of marine organisms are still under scrutiny and we still lack an accurate global predictive model. Using a spatial database for 6336 tropical reef fishes, we attempted to predict species richness according to geometric, biogeographical and environmental explanatory variables. In particular, we aimed to evaluate and disentangle the predictive performances of temperature, habitat area, connectivity, mid-domain effect and biogeographical region on reef fish species richness. We used boosted regression trees, a flexible machine-learning technique, to build our predictive model and structural equation modeling to test for potential mediation effects' among predictors. Our model proved to be accurate, explaining 80% of the total deviance in fish richness using a cross-validated procedure. Coral reef area and biogeographical region were the primary predictors of reef fish species richness, followed by coast length, connectivity, mid-domain effect and sea surface temperature, with interactions between the region and other predictors. Important indirect effects of water temperature on reef fish richness, mediated by coral reef area, were also identified. The relationship between environmental predictors and species richness varied markedly among biogeographical regions. Our analysis revealed that a few easily accessible variables can accurately predict reef fish species richness. They also highlight concerns regarding ongoing environmental declines, with region-specific responses to variation in environmental conditions predicting a variable response to anthropogenic impacts.
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Numéro d'Appel MARBEC @ isabelle.vidal-ayouba @ collection 623
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