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Spatial distribution and perceived drivers of provisioning service values across an East African montane forest landscape

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  • Ethan F. Miller
  • Amity A. Doolittle
  • Paolo Omar Cerutti
  • Jared Naimark
  • Mariana C. Rufino
  • Mark S. Ashton
  • Esther Mwangi
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Article number103995
<mark>Journal publication date</mark>1/03/2021
<mark>Journal</mark>Landscape and Urban Planning
Volume207
Number of pages14
Publication StatusPublished
Early online date11/12/20
<mark>Original language</mark>English

Abstract

Increasingly, resource managers and planners seek to manage forested landscapes for the value of the services they provide. This is especially true in the Mau Forest of Kenya, a montane area that harbors some of Kenya's most important headwaters but has lost a quarter of its forest cover since 1999. While managing for the Mau Forest's landscape services is a priority, it is critical to understand why and how people value these services differently. Otherwise, land management policies risk exacerbating rather than alleviating conservation and environmental justice problems. This is particularly true of provisioning services, a category of landscape services on which communities directly depend. This research combines participatory mapping and semi-structured interviews to understand how socio-cultural values of provisioning services are distributed across two sites within the Western Mau Forest and analyze linkages between mapped values, their locations, and influencing factors. In total, 55 informants were interviewed. Frequently listed provisioning services were water, firewood, cultivation, grazing, timber, and medicine. Results indicate that four main factors influence the location from where these services were derived: historical and legal arrangements, social relations, economic conditions, and biophysical conditions. How these factors influence where people value provisioning services differ based on the service and community in question. This study demonstrates that communities can use and value provisioning services differently and that the distributions of these services are influenced by the factors mentioned above. Understanding this heterogeneity can enable managers and policy makers to create local land use plans that account for spatially-explicit values.