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Data for simulating near-term climate change impacts on Kenyan tree cover using LRange

Warrier, Rekha1; Keys, Patrick2; Sen, Devosmita3; Boone, Randall1; Galvin, Kathleen1; Kehbila, Anderson4; Oeba, Vincent5

Published Mar 17, 2026 on Dryad. https://doi.org/10.5061/dryad.sj3tx96j0

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Mar 17, 2026 version files 177.41 KB

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Abstract

Data associated with our paper “Near-term climate change impacts on Kenyan tree cover” are archived here. In this work, using L-Range – an ecosystem model – and the most recent downscaled climate projections we explored the durability and wider impacts of ongoing afforestation efforts across Kenya. These data represent input layers for the ecosystem model L-Range which is a localized version of the global rangelands model GRange. LRange retains GRange’s model architecture. However, within L-Range inference is constrained to the spatial extent of Kenya by creating requisite input spatial layers that most accurately represent land use, land cover, soil, and vegetation conditions extant across the nation. Using this model we explored how existing and planned tree cover across Kenya would respond under multiple future climate scenarios. Our simulations indicate that, under all scenarios, tree cover across Kenya will remain stable or show increasing trends in the near term. This will be accompanied by increases in overall woody vegetation, driven by shrub cover expansion and the contraction of herb cover areas. These impacts will be particularly pronounced in areas dominated by savannas and deciduous tree cover. Alongside these changes in vegetative cover, simulations indicate declines in net primary productivity and aboveground live biomass. The repository also includes a link to an interactive web-based decision-support application hosting results from this worl is also included.