Climate Dynamics
Description and Project Aims
Kibale National Park is a globally important 795 km² forest, but its common description as a “moist evergreen forest” masks critical ecological complexity. The park spans a significant altitudinal range (1100-1600m) and, more importantly, a steep north-to-south aridity gradient. While the northern sector is characterized by a wet, humid climate, the park’s southern region becomes progressively drier, eventually transitioning into the savanna-grassland ecosystem of Queen Elizabeth National Park. This environmental continuum is a key driver of biodiversity and ecosystem function, yet it remains poorly mapped.
Effective, spatially-aware conservation and ecological research depend on an accurate understanding of this environmental heterogeneity. Treating the park as a uniform habitat block can lead to flawed models of species distribution, poor predictions of climate change impacts, and inefficient allocation of conservation resources.
The central aim of this long-term project is to create the first high-resolution, data-driven map of Kibale’s diverse climatic zones. Our lab is tackling this by fusing two powerful data sources:
Ground-Based Network: We have deployed a network of in-situ weather stations along the park’s primary gradients to capture fine-scale, real-time data on temperature, rainfall, and humidity.
Remote Sensing: We are augmenting this ground data with satellite-derived products, such as Land Surface Temperature (LST) and vegetation indices, which provide comprehensive spatial coverage across the entire park.
By using the ground station data to calibrate and validate the satellite imagery, we can build a robust model of the park’s microclimates. This foundational dataset will be a powerful tool, enabling our lab and our partners to more accurately model habitat suitability for key species, predict how different zones will respond to climate change, and ultimately guide more effective, site-specific conservation strategies.
Contact Information
Dipto Sarkar
