Coupled dynamics of tree-ring growth and canopy greenness (NDVI) along a disturbance gradient in South Asian moist tropical forests

Stem radial growth is driven by the interaction between environmental conditions and tree physiological processes. As a result, tree rings serve as valuable natural archives, recording environmental information over time. In tropical forests, data on past climate variability and historical canopy greenness—an important indicator of forest health—are often limited in duration. Studying tree rings can thus provide essential insights into historical climate dynamics and canopy condition, helping us better predict the responses of tropical forests to global environmental changes. Here we present the first ring-width index chronologies (RWI) and canopy greenness (NDVI) time series of Zanthoxylum rhetsa (Roxb.) DC. from three moist forest sites in Bangladesh aligned along a gradient of increasing human disturbance. We compared historical annual radial growth rates with monthly, seasonal and annual climate data and NDVI values derived from high resolution Landsat images. Our analyses showed that the growth of Z. rhetsa is primarily influenced by pre-monsoon temperatures and monsoon precipitation, with pre-monsoon climate signals becoming stronger in recent decades. The signal strength of the RWI chronologies, however, varied across study sites along the disturbance gradient, with stronger signals in the sites with low disturbance intensity. At the ecosystem level, canopy greenness (NDVI) was highly correlated with tree growth rates over the past two decades. NDVI showed high sensitivity to drought, particularly at drier sites. Global warming and drought are detrimental to forest health and thus limiting the carbon sequestration potential of moist tropical forests. By taking Zanthoxylum rhetsa as a model tree species in three Bangladeshi moist tropical forests we demonstrate how tree-ring analysis can be combined with remote sensing to reconstruct canopy dynamics for periods preceding the availability of satellite imagery for NDVI calculations that could be replicable to other tropical forests.