Finding an effective method to quantify species distribution in time and space has been an important task for ecologists and biogeographers. Recently, exploring the relationship between species richness and productivity using satellite image data, such as the Normalized Difference Vegetation Index (NDVI) has extracted considerable research interests among ecologists. In most studies, multivariate statistical techniques are used to correlate environmental variables and species richness (alpha diversity). In this study, we argue that beta diversity measurements take the pair-wise dissimilarities into consideration explicitly and could provide more correlation information compared with uni- or multi-dimensional regressions.
We used plant distribution data in the North and South Carolina states and the MODIS NDVI data at the same area to test the correlations between species richness and NDVI. Dissimilarity matrices were generated by computing pair-wise beta diversities for a total of 145 counties in the two states using both species richness data and NDVI time series data. The results of Mantel permutation test indicate that correlations between NDVI dissimilarity and species richness dissimilarity matrices are all significant at three taxonomical levels (p<0.001); the r values decreased from 0.3278 at the species rank to 0.2665 at the family rank. We also subgrouped the NDVI dissimilarity and species dissimilarity matrices by associating county data with defined ecoregions, and we conducted Multi Response Permutation Procedure (MRPP) test to determine whether the NDVI values and species richness values among the same ecoregions are more similar to each other. The MRPP test results show that counties within a same ecoregion have less within-group dissimilarity and greater between-group dissimilarity for the NDVI dissimilarity matrix and the species dissimilarity matrix at the three taxon ranks, all with significance of delta <0.001.