Satellite hyperspectral imagery reveals scale dependence of functional diversity patterns in a Qinghai-Tibetan alpine meadow

Abstract

Knowing how functional diversity varies across environmental gradients is crucial in investigating biodiversity formation and community assembly processes. The majority of studies concerning functional diversity are based on one fixed plot size, resulting in weakened sensitivity of the spatial patterns to sampling resolution. This weakness may obscure the true mechanisms behind community assemblage. In this study, we utilized hyperspectral imagery collected by Orbita hyperspectral satellites (OHS) to explore the spatial distribution patterns of functional traits and diversity in alpine meadows at four sampling radii (25 m, 50 m, 100 m, 200 m). We examined how functional traits and their diversity responded to variations in climatic and soil conditions at different sampling resolutions. Our findings revealed a significant influence of solar radiation and soil depth on the patterns of functional traits in alpine meadows. Scale dependency was evident in the functional richness (FRic), functional evenness (FEve), and functional dispersion (FDis) of different traits, indicated by a notable difference from the null model. In the presence of stronger soil nutrient and water limitation, chlorophyll a content (CAC), specific leaf area (SLA), leaf thickness (LT), and plant height (Height) exhibited increased clustering and convergence at larger sampling resolutions, illustrating environmental filtering in habitat patch assembly in the alpine meadow. For the first time, this study explores scale dependency in functional diversity patterns in alpine meadows using satellite-based hyperspectral imagery. It unveils the environmental filtering effect of soil nutrient limitation on shaping vegetation patch structures at a landscape level from a remote sensing perspective. The study underscores the significance of accounting for sampling resolution in future related research.