S. Serneels

Proximate causes of land-use change in Narok District, Kenya: a spatial statistical model.

This study attempts to identify how much understanding of the driving forces of land-use changes can be gained through a spatial, statistical analysis. Hereto, spatial, statistical models of the proximate causes of different processes of land-use change in the Mara Ecosystem (Kenya) were developed, taking into account the spatial variability of the land-use change processes. The descriptive spatial models developed here suggest some important factors driving the land-use changes that can be related to some well-established theoretical frameworks. The explanatory variables of the spatial model of mechanised agriculture suggest a von Thunen-like model, where conversion to agriculture is controlled by the distance to the market, as a proxy for transportation costs, and agro-climatic potential. Expansion of smallholder agriculture and settlements is also controlled by land rent, defined, in this case, by proximity to permanent water, land suitability, location near a tourism market, and vicinity to villages to gain access to social services (e.g. health clinics, schools, local markets). This difference in perception of land rent reflects the widely different social and economic activities and objectives of smallholders versus the large entrepreneurs involved in mechanised farming. Spatial heterogeneity as well as the variability in time of land-use change processes affect our ability to use regression models for wide ranging extrapolations. The models allow evaluating the impact of changes in driving forces that are well represented by proximate causes of land-use change.

Long-term changes in Serengeti-Mara wildebeest and land cover: pastoralism, population, or policies?

Declines in habitat and wildlife in semiarid African savannas are widely reported and commonly attributed to agropastoral population growth, livestock impacts, and subsistence cultivation. However, extreme annual and shorter-term variability of rainfall, primary production, vegetation, and populations of grazers make directional trends and causal chains hard to establish in these ecosystems. Here two decades of changes in land cover and wildebeest in the Serengeti-Mara region of East Africa are analyzed in terms of potential drivers (rainfall, human and livestock population growth, socio-economic trends, land tenure, agricultural policies, and markets). The natural experiment research design controls for confounding variables, and our conceptual model and statistical approach integrate natural and social sciences data. The Kenyan part of the ecosystem shows rapid land-cover change and drastic decline for a wide range of wildlife species, but these changes are absent on the Tanzanian side. Temporal climate trends, human population density and growth rates, uptake of small-holder agriculture, and livestock population trends do not differ between the Kenyan and Tanzanian parts of the ecosystem and cannot account for observed changes. Differences in private versus state/communal land tenure, agricultural policy, and market conditions suggest, and spatial correlations confirm, that the major changes in land cover and dominant grazer species numbers are driven primarily by private landowners responding to market opportunities for mechanized agriculture, less by agropastoral population growth, cattle numbers, or small-holder land use.

Land cover changes around a major east African wildlife reserve: the Mara Ecosystem (Kenya)

The dynamics of savannah vegetation are still poorly understood. This study aims at analysing land cover changes over the past 20 years in the rangelands area of Narok District, Kenya. To analyse the impact of inter-annual climate variability and human activities on land cover modifications in the area, change detection techniques based on remote sensing data at different spatial and temporal resolutions were used. Coarse spatial, high temporal resolution NOAA (National Oceanic and Atmospheric Administration) data were analysed to investigate the role of inter-annual climate variations on the ecosystem. A combination of time contextual and spatial contextual change detection approaches was used on a set of three high spatial resolution Landsat images to map land cover modifications over the past 20 years. Both datasets are highly complementary in the detection of land cover dynamics. On the one hand, the coarse spatial resolution data detected areas that are sensitive to inter-annual climate fluctuations, but are not subjected to land cover conversion. On the other hand, the high spatial resolution data allowed the detection of land cover conversions or modifications between two consecutive dates that have a more permanent character and are independent of climate-induced fluctuations in surface attributes.

Land‐cover change and vegetation dynamics across Africa

Using improved metrics and recently available MODerate resolution Imaging Spectrometer (MODIS) data, we examined the magnitude, extent, and nature of changes in photosynthetic activity and its timing across Sub-Saharan Africa. Changes in overall vegetation activity and shifts in its timing have considerable implications for a variety of processes including surface-atmosphere energy exchanges, terrestrial sources and sinks of carbon, the contribution of local evapotranspiration to the water cycle, disturbance regimes such as fires and pests, and the food security of societies using these ecosystems. While previous studies have examined broad-scale trends in phenology or provided more detailed estimates of land-cover conversion in the tropics, less is known of the year-to-year dynamics of vegetation. Here we quantified the overall changes in vegetation activity for each year between 2000 and 2004 and examined the proportion linked to differences in phenology and overall photosynthetic activity. In addition, we examined the nature of these changes in terms of frequency and duration, the proportion per ecosystem, identified areas of intensive change, and discuss the potential consequences of these changes. We found that most interannual change was not from shifts in timing or phenology, but rather largely due to differences in the amount of annual photosynthetic activity. In fact, there was as much as a 5% annual difference in vegetation activity across the continent. The changes were likely climate driven with particular vegetation types most susceptible to interannual change with high spatial and temporal variability found across the continent.

A multilevel analysis of the impact of land use on interannual land-cover change in East Africa

A bstractThe 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.

LAND USE STRATEGIES IN THE MARA ECOSYSTEM: A SPATIAL ANALYSIS LINKING SOCIO-ECONOMIC DATA WITH LANDSCAPE VARIABLES

This paper presents an analysis of the determinants of shifts in production among a Maasai pastoral population adjacent to the Masai Mara National Reserve in Kenya. The Maasai have traditionally followed a pastoral livestock land use system, which has been largely compatible with wildlife. More recently Maasai land use systems have diversified, with large scale mechanized cultivation and tourism now providing considerable incomes. Large-scale cultivation has in particular been seen to compete with both traditional pastoral livestock keeping and with wildlife-based tourism. We used a set of landscape-, accessibility-, and socio-economic-based variables to test assumptions regarding the forces seen to be driving production system and land use change. We first analyzed which land use strategies are followed by the pastoralists in the study area, and then used generalized logit models to assess the determinants of these strategies. We then tested whether groups of households diversifying from a traditional cattle-keeping economy can be related to patterns of land cover change around their homesteads. This is highly relevant to unfolding policy in the field of environment and development in East Africa where there is widespread concern in policy circles over the expansion of mechanized cultivation and its impacts for wildlife and biodiversity conservation.

Maasai Mara – Land Privatization and Wildlife Decline: Can Conservation Pay Its Way?

The rangelands around the Maasai Mara National Reserve (MMNR) provide an important example of the ways in which land use and land ownership are changing rapidly in Kenya Maasailand, particularly in areas of higher agricultural and economic potential. Privatization of once-communal rangelands and subsequent subdivision into individually owned plots are far advanced. Land privatization has potentially major impacts on wildlife conservation, as fencing and land-use intensification reduce availability of land for the formerly free-ranging wildlife-livestock mix. At the same time, there has been a proliferation of game viewing enterprises and tourist camps on sites throughout the Mara rangelands, particularly in areas close to the MMNR. Data from surveys undertaken in 1998–2000 and in 2004 are used here to describe the livelihood strategies characterizing the Mara, and to document the pattern, scale and extent of diversification. The two sets of surveys allow us to look at how livelihoods changed over a 6-year period during which land in parts of the study area was privatized. The data allows us to discern trends in the spread of (or decline in) cultivation, in who captures the benefits flowing from wildlife conservation and in overall wealth differentiation, and to explore the implications of these trends on land-use change. Our analysis shows the enduring importance of livestock, the widespread benefits flowing from wildlife enterprises to the study households and the fluctuating importance of off-farm employment and cultivation. A more nuanced picture of landuse change due to commercial cultivation emerges. Whilst opportunities for leasing out land for commercial cultivation are still lucrative, rather than widespread conversion of land, cultivation pressure is decreasing in some areas, partially as a result of local conservation initiatives, amidst an overall trend during the two study periods towards a reduction in cultivation. In terms of wildlife returns, whilst the majority is captured by the most wealthy, wildlife revenue provides an important contribution to household income across the Mara study areas. Overall, while income streams from