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

Authors

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

DOI:

https://doi.org/10.4462/annbotrm-13804

Keywords:

community structure, kriging, generalised linear models, spatial autocorrelation

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.

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Published

2017-04-28

How to Cite

Marcantonio, M., Martellos, S., Altobelli, A., Attorre, F., Tordoni, E., Ongaro, S., Rocchini, D., Da Re, D., Chiarucci, A., & Bacaro, G. (2017). HOW DOES SPATIAL SCALE AFFECT SPECIES RICHNESS MODELLING? A TEST USING REMOTE SENSING DATA AND GEOSTATISTICS. Annali Di Botanica, 7, 11–24. https://doi.org/10.4462/annbotrm-13804

Issue

Section

Research Articles