Global vegetation biomass change (1988-2008) and attribution to environmental and human drivers

Abstract

Aim Vegetation optical depth (VOD) is an indicator of the water content of both woody and leaf components in terrestrial aboveground vegetation biomass that can be derived from passive microwave remote sensing. VOD is distinct from optical vegetation remote sensing data such as the normalized difference vegetation index in that it is: (a) less prone to saturation in dense canopies; (b) sensitive to both photosynthetic and non-photosynthetic biomass; and (c) less affected by atmospheric conditions. Our primary objective was to analyse a recently developed long-term VOD record and investigate how the vegetation water content of various land-cover types responded to environmental changes and human influences from 1988 to 2008. Location Global. Methods We first conducted Mann–Kendall trend tests on annual average VOD to identify regions with significant changes over the period 1988–2008. To diagnose the underlying cause of the observed changes, patterns for these identified regions were further compared with independent datasets of precipitation, crop production, deforestation and fire occurrence. Results (1) Over grassland and shrubland, VOD patterns corresponded strongly to temporal precipitation patterns. (2) Over croplands, annual average VOD showed a general increase that corresponded to reported crop production patterns and was attributed to a combination of precipitation patterns and agricultural improvements. (3) Over humid tropical forest, the spatial pattern of VOD decline agrees well with deforestation patterns; the 2005 Amazon drought corresponded with a temporary VOD decrease. (4) Over boreal forests, regional VOD declines are attributed to a combination of fires and clear cutting. Main conclusions Passive microwave remote sensing of VOD can be used to monitor global changes in total aboveground vegetation water content and biomass over various land-cover types. This new observational record can help in hydrological, agricultural, ecological and climate change studies, and provides new insights into large-scale vegetation change and its drivers.