HOW DOES SPATIAL SCALE AFFECT SPECIES RICHNESS MODELLING? A TEST USING REMOTE SENSING DATA AND GEOSTATISTICS

M. Marcantonio, S. Martellos, A. Altobelli, F. Attorre, E. Tordoni, S. Ongaro, D. Rocchini, D. Da Re, A. Chiarucci, G. Bacaro

Abstract


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.


Keywords


community structure, kriging, generalised linear models, spatial autocorrelation

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DOI: http://dx.doi.org/10.4462/annbotrm-13804

Annali di Botanica is published by the Department of Environmental Biology - University La Sapienza of Rome, Italy. The journal is printed by Sapienza Università di Roma - Centro Stampa Università.

ISSN: 2239-3129