Tropical forests sustain a disproportionate share of global biodiversity and of nature’s contributions to people, yet they are increasingly destabilized by interacting pressures from climate change, land-use change and intensifying disturbance regimes. Understanding and monitoring forest resilience — the capacity to resist, absorb, recover from and adapt to disturbance — requires scalable approaches that integrate biodiversity, ecosystem structure and function across space and time. In this Review, we discuss how the essential biodiversity variables (EBV) framework, enabled by satellite remote sensing, has improved understanding of forest resilience under global environmental change. Remotely sensed EBV proxies derived from multispectral, thermal, hyperspectral, radar, light detection and ranging (LiDAR) and solar-induced fluorescence observations capture multiple facets of biodiversity and ecosystem dynamics. However, scale dependence, observational biases and the limited capacity of current EBVs to resolve fine-grained biological and mechanistic processes underpinning resilience (particularly species turnover and functional reassembly) are critical limitations. Emerging opportunities, including data fusion, next-generation satellite missions and integration with in situ observations, will advance the operationalization of EBV-based resilience monitoring, particularly in the context of the Kunming–Montreal Global Biodiversity Framework. Advances in remote sensing now enable the detection of multiple properties of tropical forest biodiversity. This Review discusses how remotely sensed biodiversity facets and essential biodiversity variables can be used to draw inference about tropical forest resilience to global change.
Aguirre‐Gutiérrez et al. (Tue,) studied this question.
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