Vina, A; Tuanmu, MN; Xu, WH; Li, Y; Qi, JG; Ouyang, ZY; Liu, JG (2012). Relationship between floristic similarity and vegetated land surface phenology: Implications for the synoptic monitoring of species diversity at broad geographic regions. REMOTE SENSING OF ENVIRONMENT, 121, 488-496.
Assessing species composition and its changes through time across broad geographic regions is time consuming and a difficult endeavor. The synoptic view provided by imaging remote sensors offers an alternative. But while many studies have developed procedures for assessing biodiversity using multi- and hyper-spectral imagery, they may only provide snapshots at particular months/seasons due to the seasonal variability of spectral characteristics induced by vegetated land surface phenologies. Thus, procedures for remotely assessing biodiversity patterns may not fully represent the biodiversity on the ground if vegetated land surface phenologies are not considered. Using Mantel tests, ordinarily least square regression models and spatial autoregressive models, we assessed the relationship between floristic diversity and vegetated land surface phenologies, as captured by time series of vegetation indices derived from data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS). The relationship was calibrated with data from temperate montane forests of the Qinling Mountains region, Shaanxi Province, China. Our results show that floristically similar areas also exhibit a comparable similarity in phenological characteristics. However, phenological similarity obtained using the Visible Atmospherically Resistant Index (VARI), a spectral vegetation index found to be not only sensitive to changes in chlorophyll content but also linearly related with the relative content of foliar anthocyanins, exhibited the strongest relationship with floristic similarity. Therefore, analysis of the temporal dynamics of pigments through the use of satellite-derived metrics, such as VARI, may be used for evaluating the spatial patterns and temporal dynamics of species composition across broad geographic regions. (c) 2012 Elsevier Inc. All rights reserved.