Linking variability in species composition and MODIS NDVI based on beta diversity measurements

摘要: Finding an effective method to quantify species compositional changes in time and space has been important task for ecologists biogeographers. Recently, exploring regional floristic patterns using data derived from satellite imagery, such as the normalized difference vegetation index (NDVI) drawn considerable research interests among ecologists. Studies have shown that NDVI could be a fairly good surrogate primary productivities. In this study, we used plant distribution North South Carolina states investigate correlations between composition within defined ecoregions Mantel test multi-response permutation procedure (MRPP). Our analytical approach involved generating dissimilarity matrices by computing pairwise beta diversities of 145 counties two Euclidian distances series data. We argue diversity measurements take dissimilarities into consideration explicitly provide more spatial correlation information compared with uni- or multi-dimensional regressions. results showed significant positive distance matrices. also found first strength increased at lower taxonomic rank. Same trends were discovered when incorporating variability phenological NDVI. findings suggest remotely sensed can viable monitoring scales.