Spatiotemporal Variations of Dryland Vegetation Phenology Revealed by Satellite-Observed Fluorescence and Greenness across the North Australian Tropical Transect

Abstract

Accurate characterization of spatial patterns and temporal variations in dryland vegetation is of great importance for improving our understanding of terrestrial ecosystem functioning under changing climates. Here, we explored the spatiotemporal variability of dryland vegetation phenology using satellite-observed Solar-Induced chlorophyll Fluorescence (SIF) and the Enhanced Vegetation Index (EVI) along the North Australian Tropical Transect (NATT). Substantial impacts of extreme drought and intense wetness on the phenology and productivity of dryland vegetation are observed by both SIF and EVI, especially in the arid/semiarid interior of Australia without detectable seasonality in the dry year of 2018–2019. The greenness-based vegetation index (EVI) can more accurately capture the seasonal and interannual variation in vegetation production than SIF (EVI r2: 0.47~0.86, SIF r2: 0.47~0.78). However, during the brown-down periods, the rate of decline in EVI is evidently slower than that in SIF and in situ measurement of gross primary productivity (GPP), due partially to the advanced seasonality of absorbed photosynthetically active radiation. Over 70% of the variability of EVI (except for Hummock grasslands) and 40% of the variability of SIF (except for shrublands) can be explained by the water-related drivers (rainfall and soil moisture). By contrast, air temperature contributed to 25~40% of the variability of the effective fluorescence yield (SIFyield) across all biomes. In spite of high retrieval noises and variable accuracy in phenological metrics (MAE: 8~60 days), spaceborne SIF observations, offsetting the drawbacks of greenness-based phenology products with a potentially lagged end of the season, have the promising capability of mapping and characterizing the spatiotemporal dynamics of dryland vegetation phenology.

Improved Vegetation Photosynthetic Phenology Monitoring in the Northern Ecosystems Using Total Canopy Solar‐Induced Chlorophyll Fluorescence Derived From TROPOMI

“…Forests and grasslands exhibit a relatively consistent response to precipitation within the respective ecosystem, resulting in less variability. In contrast, VI‐based growing season length did not show a similarly increased variability from forests to shrublands, indicating a decoupling mechanism between greenness and photosynthetic activity (Leng et al., 2022). This decoupling might be due to the slower chlorophyll degradation and leaf falling compared to stomatal closure (Ma et al., 2013).…”

An improved global vegetation health index dataset in detecting vegetation drought

“…Currently, satellite data are widely used for drought assessment, because of its ability to identify drought conditions on different underlying surfaces 26 . Remotely sensed drought monitoring has advantages such as being suitable for large-scale drought monitoring 27 , having a powerful real-time update function 28 , 29 , and high accuracy, as well as unmatched cost-effectiveness when compared to other methods 30 , 31 . Therefore, the combination of satellite remote sensing technology and traditional drought index is a very promising drought assessment method.…”

Impacts of land cover changes on dust emissions in northern China (2000–2020)

“…Land cover changes, as both a driver and outcome of global environmental change, have significantly altered the earth's energy balance and biogeochemical cycle. It influences climate change (Leng et al, 2022;Wan et al, 2023;Wang, Zeng, et al, 2021) and impacts surface characteristics and the provision of ecosystem services (Chen, Meng, et al, 2022;Song et al, 2018). However, the quantitative effects of land use type transformation on dust emissions have not been fully assessed due to the complex interplay of various factors (Jebali & Zare Chahouki, 2022;Wu et al, 2022).…”