The vegetation dynamics of semi-arid and arid landscapes are temporally and spatially heterogeneous and subject to various disturbance regimes that act on decadal scales. Traditional field-based monitoring methods have failed to sample adequately in time and space in order to capture this heterogeneity and thus lack the spatial extent and the long-term continuous time series of data necessary to detect anomalous dynamics in landscape behavior.
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Library ResourceArtículos de revistas y librosDiciembre, 2004
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Library ResourceArtículos de revistas y librosDiciembre, 2009Tailandia
This study profiled soils over a land degradation gradient to obtain formulae as integrative measures for describing the gradient as a result of deforestation in Thailand. We applied antibiotic resistance most-probable-number profiling to the soil bacterial communities, and then described the gradient. Soil samples were collected on the gradient represented by dry evergreen forest (the original vegetation), dry deciduous forest (moderately disturbed) and bare ground (the most degraded) in February (dry season), March (shortly after temporal precipitation) and June (rainy season) 2001.
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Library ResourceArtículos de revistas y librosDiciembre, 2009Etiopía
We suggest a classificatory approach for land cover analysis that integrates fuzzy set theory with permutation techniques. It represents a non parametric alternative and/or a complement of traditional multivariate statistics when data are scarce, missing, burdened with high degree of uncertainty and originated from different sources and/or times. According to this approach, the Operational Geographic Units (OGUs) in which landscape is subdivided and sampled are classified with hierarchical clustering methods.
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