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Modeling multifunctional landscape change in southern Kenya: Spatial trade-offs and drivers in an arid and semi-arid landscape

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dc.contributor.author Susan M. Kotikot a, * , Erica A.H. Smithwick a,b , Sarah E. Gergel c , Jedidah Nankaya d , Romulus Abila
dc.date.accessioned 2026-08-10T14:11:15Z
dc.date.available 2026-08-10T14:11:15Z
dc.date.issued 2026
dc.identifier.uri http://hdl.handle.net/123456789/19835
dc.description.abstract Arid and Semi-Arid Landscapes (ASALs) support a substantial portion of the world's population and multiple ecological and social functions. However, landcover outcomes in ASALs are determined by competing land uses, which are governed by fine gradients in biophysical conditions, legacy land use policies, and complex socio- economic drivers. Simulating these land use and land cover (LULC) interactions can promote policy that en- hances human and ecosystem well-being but capturing dynamics at scales relevant to local livelihoods remains challenging. To explore these interactions, we used the Land Change Modeler (LCM) to simulate spatial patterns of LULC change from 2010 to 2018 in a multifunctional landscape in southern Kenya. Results showed that spatial patterns of LULC transition were associated with biophysical and socio-political factors such as proximity to existing land use types, rainfall and temperature, and land tenure arrangements. Our calibrated model achieved 83% overall correctness, with remaining errors (17%) linked to spatial misallocation. These errors were spatially clustered, suggesting the possible influence of localized socioeconomic factors not included in our parameteri- zation. Notably, transitions in humid–arid ecotones were consistently underestimated, reflecting the challenges of capturing fine-scale heterogeneity in ecologically sensitive landscapes. Our findings demonstrate where conservation objectives, agricultural expansion, and pastoral livelihoods spatially converge, highlighting land- scape zones where policy interventions and development investments are most likely to generate trade-offs rather than synergies under increasing climate stress. These results underscore the value of spatially explicit modeling as a diagnostic tool for identifying priority areas where competing land-use demands and socio- ecological vulnerabilities are most tightly coupled. en_US
dc.language.iso en en_US
dc.title Modeling multifunctional landscape change in southern Kenya: Spatial trade-offs and drivers in an arid and semi-arid landscape en_US
dc.type Article en_US


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