Species distribution models are often used to study the biodiversity of ecosystems. The modelling processuses a number of parameters to predict others, such as the occurrence of determinate species, populationsize, habitat suitability or biodiversity. It is well known that the heterogeneity of landscapes can lead tochanges in species’ abundance and biodiversity. However, landscape metrics depend on maps and spatialscales when it comes to undertaking a GIS analysis.We explored the goodness of fit of several models using the metrics of landscape heterogeneity andaltitude as predictors of bird diversity in different landscapes and spatial scales. Two variables were usedto describe biodiversity: bird richness and trophic level diversity, both of which were obtained from abreeding bird survey by means of point counts. The relationships between biodiversity and landscapemetrics were compared using multiple linear regressions. All of the analyses were repeated for 14 differ-ent spatial scales and for cultivated, forest and grassland environments to determine the optimal spatialscale for each landscape typology.Our results revealed that the relationships between species’ richness and landscape heterogeneity using1:10,000 land cover maps were strongest when working on a spatial scale up to a radius of 125–250 maround the sampled point (circa 4.9–19.6 ha). Furthermore, the correlation between measures of land-scape heterogeneity and bird diversity was greater in grasslands than in cultivated or forested areas.The multi-spatial scale approach is useful for (a) assessing the accuracy of surrogates of bird diversity indifferent landscapes and (b) optimizing spatial model procedures for biodiversity mapping, mainly overextensive area

Landscape heterogeneity metrics as indicators of bird diversity: determining the optimal spatial scales in different landscapes.

MORELLI, FEDERICO DANIEL;SANTOLINI, RICCARDO;SISTI, DAVIDE
2013-01-01

Abstract

Species distribution models are often used to study the biodiversity of ecosystems. The modelling processuses a number of parameters to predict others, such as the occurrence of determinate species, populationsize, habitat suitability or biodiversity. It is well known that the heterogeneity of landscapes can lead tochanges in species’ abundance and biodiversity. However, landscape metrics depend on maps and spatialscales when it comes to undertaking a GIS analysis.We explored the goodness of fit of several models using the metrics of landscape heterogeneity andaltitude as predictors of bird diversity in different landscapes and spatial scales. Two variables were usedto describe biodiversity: bird richness and trophic level diversity, both of which were obtained from abreeding bird survey by means of point counts. The relationships between biodiversity and landscapemetrics were compared using multiple linear regressions. All of the analyses were repeated for 14 differ-ent spatial scales and for cultivated, forest and grassland environments to determine the optimal spatialscale for each landscape typology.Our results revealed that the relationships between species’ richness and landscape heterogeneity using1:10,000 land cover maps were strongest when working on a spatial scale up to a radius of 125–250 maround the sampled point (circa 4.9–19.6 ha). Furthermore, the correlation between measures of land-scape heterogeneity and bird diversity was greater in grasslands than in cultivated or forested areas.The multi-spatial scale approach is useful for (a) assessing the accuracy of surrogates of bird diversity indifferent landscapes and (b) optimizing spatial model procedures for biodiversity mapping, mainly overextensive area
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11576/2558774
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