Abstract
Areas affected by land degradation in Sub-Saharan West Africa between 1982 and 2012 are identified using time-series analysis of vegetation index data derived from satellites. The residual trend (RESTREND) of a Normalized Difference Vegetation Index (NDVI) time-series is defined as the fraction of the difference between the observed NDVI and the NDVI predicted from climate data. It has been widely used to study desertification and other forms of land degradation in drylands. The method works on the assumption that a negative trend of vegetation photosynthetic capacity is an indication of land degradation if it is independent from climate variability. In the past, many scientists depended on rainfall data as the major climatic factor controlling vegetation productivity in drylands when applying the RESTREND method. However, the water that is directly available to vegetation is stored as soil moisture, which is a function of cumulative rainfall, surface runoff, infiltration and evapotranspiration. In this study, the new NDVI third generation (NDVI3g), which was generated by the National Aeronautics and Space Administration-Goddard Space Flight Center Global Inventory Modeling and Mapping Studies (NASA-GSFC GIMMS) group, was used as a satellite-derived proxy of vegetation productivity, together with the soil moisture index product from the Climate Prediction Center (CPC) and rainfall data from the Climate Research Unit (CRU). The results show that the soil moisture/NDVI pixel-wise residual trend indicates land degraded areas more clearly than rainfall/NDVI. The spatial and temporal trends of the RESTREND in the region follow the patterns of drought episodes, reaffirming the difficulties in separating the impacts of drought and land degradation on vegetation photosynthetic capacity. Therefore, future studies of land degradation and desertification in drylands should go beyond using rainfall as a sole predictor of vegetation condition, and include soil moisture index datasets in the analysis.
Highlights
Livelihoods and wildlife in the Sub-Saharan West African environment depend largely on the moisture regime, which is the main limiting factor to ecosystem productivity [1]
From 15° N latitude northwards this pattern prevails, except in very small portions where the moisture from the nearby water sources such as Lake Chad in northern Nigeria, supplied and compensate for low rainfall due to natural through flow. In both figures, high value of Normalized Difference Vegetation Index (NDVI) is concentrated along the coastal areas in the southern and western parts of the study area; this is due to the availability of water in the soil throughout the year around these areas
This study has shown that RESTREND analysis of NDVI and soil moisture data can provide indicators of land degradation and vegetation recovery in Sub-Saharan West Africa more reliably than if only rainfall data are used
Summary
Livelihoods and wildlife in the Sub-Saharan West African environment depend largely on the moisture regime, which is the main limiting factor to ecosystem productivity [1]. Wetter climate prevailed in the Sub-Saharan region between 1930 and 1965, which was followed by extreme widespread droughts from 1968 to 1973, 1982–1985 and in the 1990s leading to large-scale food shortage and famine [1,2]. Speculations about major causes of these droughts are still unresolved [3]. It has been argued that rainfall variability in the region is influenced by large-scale sea surface temperature (SST). Some studies have claimed that rainfall variability in the area can be traced to the overall changes in land cover and land-atmosphere interactions in the region [1,6,7]. The overall impacts of the droughts led to widespread land degradation in the Sub-Saharan West
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