Multilevel Analysis of the Impact of Land Use on Interannual Land-Cover Change in East Africa

The aim of this study was to characterize the short-term land-cover change processes that were detected in Eastern Africa, based on a set of change metrics that allow for the quantification of interannual changes in vegetation productivity, changes in vegetation phenology and a combination of both....

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Bibliographic Details
Published in:Ecosystems (New York) 2007-04, Vol.10 (3), p.402-418
Main Authors: Serneels, S, Linderman, M, Lambin, E. F
Format: Article
Language:English
Subjects:
Animal and plant ecology
Animal, plant and microbial ecology
Biological and medical sciences
Biomes
Climate change
Climate variability
Fundamental and applied biological sciences. Psychology
General aspects
Grazing
human impact
Land cover
Land use
Landforms
Livestock
MODIS
multilevel model
Multilevel models
Phenology
Productivity
Rain
Rangelands
Remote sensing
Synecology
Time series
Vegetation
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Summary:The aim of this study was to characterize the short-term land-cover change processes that were detected in Eastern Africa, based on a set of change metrics that allow for the quantification of interannual changes in vegetation productivity, changes in vegetation phenology and a combination of both. We tested to what extent land use, fire activity and livestock grazing modified the vegetation response to short-term rainfall variability in East Africa and how this is reflected in change metrics derived from MODerate Imaging Spectrometer (MODIS) time series of remote sensing data. We used a hierarchical approach to disentangle the contribution of human activities and climate variability to the patterns of short-term vegetation change in East Africa at different levels of organization. Our results clearly show that land use significantly influences the vegetation response to rainfall variability as measured by time series of MODIS data. Areas with different types of land use react in a different way to interannual climate variability, leading to different values of the change indices depending on the land use type. The impact of land use is more reflected in interannual variability of vegetation productivity and overall change in the vegetation, whereas changes in phenology are mainly driven by climate variability and affect most vegetation types in similar ways. Our multilevel approach led to improved models and clearly demonstrated that climate influence plays at a different scale than land use, fire and herbivore grazing. It helped us to understand dynamics within and between biomes in the study area and investigate the relative importance of different factors influencing short-term variability in change indices at different scales.
ISSN:1432-9840
1435-0629
DOI:10.1007/s10021-007-9026-y