Forest-savanna transitions: Understanding adaptation and resilience of the tropical forest ecosystems using remote sensing

Abstract: Climate and deforestation-induced changes in precipitation drive tropical forest-savanna transitions. However, precipitation alone provides a superficial understanding of the underlying mechanism behind these transitions. This is because our knowledge of how vegetation responds to changes in hydroclimate is fragmented. Under a rapidly changing climate, it is increasingly important to understand forest adaptation to predict future forest-savanna transition risks. However, there are two major bottlenecks to achieving this: (i) there is no universal metric that represents forest adaptation, and (ii) at continental scale, empirical evidence to ecosystem response under changing climate is still lacking. This thesis uses remote sensing-derived root zone storage capacity – a novel metric representing the vegetation's capacity to utilise subsoil moisture storage - and above-ground tree cover structure to provide empirical evidence to ecosystems’ response under changing hydroclimate and the influence of hydroclimatic adaptation on the resilience of tropical forests. The results reveal a non-linear relationship between ecosystem’s above-ground structure and subsoil moisture storage capacity. Furthermore, the ecosystem’s capacity to utilise subsoil moisture is much more dynamic and reflective of their transient conditions under changing precipitation than above-ground structure; thereby highlighting its application as an early warning signal. Ignoring this adaptive capacity can undermine forest resilience. The result from this thesis also emphasises the applicability of remote sensing in inferring and assessing ecosystem adaptation under rapid hydroclimatic change and can assist in strengthening management and conservation efforts across the continents.