Higher tree diversity reduces critical slowing down in the Amazon forest

Abstract. The Amazon forest is influenced by strong feedback loops between its biotic and abiotic components. Local forest loss increases CO₂ emissions, which, in turn, drives climate change, raising temperatures and reducing rainfall, causing further forest loss. Additionally, forest loss disrupts important forest-rainfall cycles, threatening the overall forest stability. These feedbacks make the system vulnerable to tipping points, where parts of the forest could transition to a degraded state. Critical slowing down is an early warning indicator for approaching tipping points, as it indicates slower recovery to short-term disturbances. However, the role of tree species diversity in this process is yet to be clarified. Furthermore, it is highly uncertain how the relation between tree species diversity and critical slowing down varies with spatial scales. To examine how tree species diversity impacts critical slowing down across multiple spatial scales, we used modelled tree species diversity data at the alpha (local), beta (asynchrony across local communities), and gamma (regional) scales. We quantified critical slowing down on the same scales using temporal autocorrelation trends in monthly satellite-derived vegetation productivity time series over 2001–2019. Our findings reveal more pronounced slowing down at the alpha level (25 km²) compared to the gamma level (209,903 km²), indicating that Amazonian tipping points are more likely to occur locally than regionally or basin-wide. We also observe significant but weak positive linear relationships between tree species diversity and stability at both alpha and beta scales. This emphasizes both the importance of biodiversity conservation at multiple spatial scales and the complexity of understanding the stability of the Amazon forest.