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How does spatial scale affect species richness modelling? A test using remote sensing data and geostatistics / M. Marcantonio in Annali di Botanica, vol 7 (2017)  

Public [article]  inAnnali di Botanica > vol 7 (2017) Titre : How does spatial scale affect species richness modelling? A test using remote sensing data and geostatistics Type de document : Article/Communication Auteurs : M. Marcantonio, Auteur ; S. Martellos, Auteur ; A. Altobelli, Auteur ; et al., Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] autocorrélation spatiale [Termes IGN] krigeage [Termes IGN] modèle linéaire [Termes IGN] modélisation de la forêt [Termes IGN] richesse floristique [Termes IGN] Sienne [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Spatially-explicit dataset of plant species occurrences collected in the Province of Siena (Central Italy) is analysed, with the aim of investigating a) the relative role of environmental factors in shaping spatial patterns of plant species richness, and b) how the spatial scale at which predictors have been sampled determines the explicative power of species richness models. The optimal spatial resolution of analysis was evaluated with respect to the total deviance explained by models, using a set of environmental and remotely sensed derived predictors calculated at different spatial scales. Results confirm the hypothesis that the predictive power of landscape structure is influenced by the spatial scale at which predictor variables have been sampled. Furthermore, the relevance of identifying a proper geographical scale of investigation, hence minimizing the redundancy in the predictor variables and maximising the explanatory power of the single groups of predictor variables, is highlighted as well. Numéro de notice : A2017-649 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.4462/annbotrm-138 En ligne : http://dx.doi.org/10.4462/annbotrm-13804 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87017 [article]