Biological Processes Underpin the Persistence of Dryland Productivity Following Extreme Wet Years

Abstract

Global warming has induced more years of above‐average rainfall, significantly affecting the interannual variability of the terrestrial global carbon cycle. An extreme wet year can cause changes to vegetation structure and function that persist beyond itself, referred to as “legacy effects”. The physical and biological mechanisms underlying these effects are poorly understood, introducing uncertainty into climate–carbon models to accurately represent post–wet year vegetation dynamics. Here we used multi‐source satellite‐derived vegetation productivity metrics, as well as eddy covariance (EC) measurements, to investigate the legacy effects of extreme wet years on the productivity of Australia's drylands. We found that the impact of the 2010–2011 extreme wet year extended beyond generating a record‐breaking carbon uptake, which exceeded the 40‐year mean by more than 1.5 standard deviations. It also resulted in a widespread positive legacy effect in the following year. Specifically, up to 56% of the vegetated areas that experienced anomalous wetness showed significant legacy effects after 1 year, with impact size contributing up to 40% of total productivity in those regions. Biological memory in wet years, representing a potential process for carbon storage and subsequent remobilization, was shown to dominate the legacy effect. Random forest analysis identified key ecogeographic controls on biological memory, such as resource‐conservative strategies associated with drier climates and relatively fertile soils. Comparisons with Dynamic Global Vegetation Models (DGVMs) further revealed that current models may underestimate this biological memory by up to 70%, in part due to limited representation of carbon storage dynamics. Our results contribute to more accurate modelling of the dryland carbon cycle and provide a framework to better account for post‐wet‐year legacy effects by incorporating the influence of wet‐year productivity.