Modelling habitat conversion in miombo woodlands: insights from Tanzania

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dc.contributor.author Lobora, Alex L.
dc.contributor.author Nahonyo, Cuthbert L.
dc.contributor.author Munishi, Linus K.
dc.contributor.author Caro, Tim
dc.contributor.author Foley, Charles
dc.contributor.author Beale, Colin M.
dc.date.accessioned 2019-05-21T10:29:06Z
dc.date.available 2019-05-21T10:29:06Z
dc.date.issued 2017-05-29
dc.identifier.issn 1747-4248
dc.identifier.uri DOI: 10.1080/1747423X.2017.1331271
dc.identifier.uri http://dspace.nm-aist.ac.tz/handle/123456789/115
dc.description Research Article published by Taylor & Francis Group en_US
dc.description.abstract Understanding the drivers of natural habitat conversion is a major challenge, yet predicting where future losses may occur is crucial to preventing them. Here, we used Bayesian analysis to model spatio-temporal patterns of land-use/cover change in two protected areas designations and unclassified land in Tanzania using time-series satellite images. We further investigated the costs and benefits of preserving fragmenting habitat joining the two ecosystems over the next two decades. We reveal that habitat conversion is driven by human population, existing land-use systems and the road network. We also reveal the probability of habitat conversion to be higher in the least protected area category. Preservation of habitat linking the two ecosystems saving 1640 ha of land from conversion could store between 21,320 and 49,200 t of carbon in the next 20 years, with the potential for generating between US$ 85,280 and 131,200 assuming a REDD+ project is implemented. en_US
dc.language.iso en_US en_US
dc.publisher Taylor & Francis Group en_US
dc.subject Spatio-temporal en_US
dc.subject land use en_US
dc.title Modelling habitat conversion in miombo woodlands: insights from Tanzania en_US
dc.type Article en_US

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