Alpha and beta diversity mapping in Indian tropical deciduous forests using high-fidelity imaging spectroscopy

Abstract

The present study evaluates the potential of airborne hyperspectral and space-borne multispectral satellite datasets to determine alpha (α) and beta (β) diversity combining in-situ floristic composition in tropical deciduous forests (TDFs) of Mudumalai Tiger Reserve (MTR), India. 43 forest plots (each of 0.04 ha) were sampled to record the species diversity in MTR. The very high-resolution AVIRIS-NG hyperspectral images and temporal Sentinel-2 multispectral images were used to extract spectral variables by associating each field plot with corresponding pixels of the satellite images. A high positive correlation of field-based α-diversity (Shannon-Wiener diversity index (H′)) with AVIRIS-NG based α-diversity (R2: 0.83 (2016); R2: 0.82 (2018)) was observed compared to Sentinel-2 based α-diversity (R2: 0.50 to 0.63) with high correlation during post-monsoon (R2: 0.63). Principal coordinate analysis of AVIRIS-NG based β-diversity signifies a low diversity (H′: <1.00) in the eastern parts (0.13% of MTR) in contrast to moderate (H′: 1.00 to 2.00; 13.39% of MTR) to high diversity (H′ >2.00; 86.49% of MTR) in the remaining parts of MTR. The study highlights the application of high spectral-spatial AVIRIS-NG images for precise tree diversity mapping and the high temporal-spatial Sentinel-2 satellite images for assessing the phenological variations of the forest species. The integration of high spatial-hyperspectral and temporal multispectral satellite datasets with field-based observations for fine-scale tree species diversity mapping at geographical and temporal scales is the novelty of the study that may effectively contribute in devising effective forest management plans for biodiversity conservation.