期刊
APPLIED GEOGRAPHY
卷 40, 期 -, 页码 40-50出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.apgeog.2013.01.007
关键词
Coffee agroforests; Deforestation; Land transitions; Land-use/cover change; Drivers of change
类别
This study examines the land-use/cover change (LUCC) dynamics and drivers for two prominent land-use/cover systems in Guatemala: natural forests (FOR) and coffee agroforests (CAF). To-date, very little research has examined the LUCC dynamics of CAF, in large part due to the high degree of spectral similarity that exists between agroforests and other forest-cover types. Given the ecosystem and livelihood services provided by shade-grown coffee production, it is increasingly necessary to map and identify the dynamics and drivers of CAF changes over space and time. This research uses remote sensing analysis, land transition matrices, and multinomial regression models to examine LUCC dynamics over two ten-year intervals (1990-2000; 2000-2010) in Guatemala. Spatially explicit biophysical (e.g. slope, elevation) and accessibility (e.g. distance to roads) factors are used to model and compare drivers of change for CAF and FOR. Results demonstrate LUCC dynamics and drivers for the two land-use/cover systems to be complex over space and time. For example, FOR losses are evident for both time intervals, largely associated with conversion to CAF and croplands (CPL) in low slope, low altitude areas, and in areas close to existing croplands, respectively. CAF losses are also evident in the 1990s, but are outpaced by expansion in the 2000s. Losses are associated with conversion to CPL, particularly near roads and existing croplands, while expansion and/or persistence of CAF occurs near cities. These results suggest that conservation programs aimed at tree cover preservation and expansion should consider natural forests and managed agroforests separately. Further, such programs should be tailored to specific locations and institutional settings given the influence of topography and accessibility factors in determining localized patterns of landscape transformations over space and time. (c) 2013 Elsevier Ltd. All rights reserved.
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