In this study, the relationship of above-ground net primary productivity (ANPP) with precipitation using the enhanced vegetation index (EVI) from satellite data as surrogate for ANPP was assessed. To use EVI as a proxy for ANPP we extracted the satellite data from areas with uniform vegetation in a 2x2 km area for the multi-site approach.In the multi-site analysis in the United States our results showed a strong exponential relationship between iEVI and annual precipitation across the sites and climate regimes studied. We found convergence of all sites toward common and maximum rain use efficiency under the water-limited conditions represented by the driest year at each site. Measures of inter-annual variability in iEVI with rainfall variation across biomes were similar to that reported by Knapp and Smith (2001) in which the more herbaceous dominant sites were found to be most sensitive to interannual variations in precipitation with no relationships found in woodland sites.The relationship was also evaluated in the southern hemisphere using a multi-site analysis with information from satellite TRMM for precipitation and MOD13Q1 from MODIS for EVI values at calendar and hydrologic year periods. The tested sites were located across the 6 major land cover types inAustralia, obtained from MODIS MCD12Q1 product and used to compare the relationship across different biomes. The results showed significant agreement between the annual iEVI and annual precipitation across the biomes involved in this study showing non-significant differences between the calendar and hydrologic years for the 24 sites across different climatic conditions.At the regional scale we also assessed the ANPP-precipitation relationship across all of Australia. Precipitation data from TRMM was obtained at 0.25x0.25 degrees spatial resolution and monthly temporal resolution and EVI values were obtained from the CGM (Climate Grid Modeling) MOD13C1-16-days and 5.6km temporal and spatial resolutions, respectively. Our results were in fair agreement with those from our first two studies and previous research and provided specific insights regarding the use iEVI as a proxy for productivity over extended regions as well as its combination with data sets from TRMM sensor for precipitation data.

Student Number : 9511039F - MSc Dissertation - School of Animal, Plant and Environmental Sciences - Faculty of Science / An estimated 91 % of South Africa’s total land area is considered dryland and susceptible to desertification. In response, South Africa has prepared a National Action Programme to combat land degradation, and this requires assessment and monitoring to be conducted in a systematic, cost effective, objective, timely and geographically-accurate way. Despite a perception-based assessment of land degradation conducted in 1999, and a land-cover mapping exercise conducted for 2000/2001, there are few national scientifically rigorous degradation monitoring activities being undertaken, due largely to a lack of objective, quantitative methods for use in large-scale assessments. This study therefore tests a satellitederived index of degradation for the Limpopo Province in South Africa, which is perceived to be one of the most degraded provinces in the country. The long-term average maximum normalized difference vegetation index (NDVI), calculated from a time series (1985-2004) of NOAA AVHRR satellite images, as a proxy for vegetation productivity, was related to water balance datasets of mean annual precipitation (MAP) and growth days index (GDI), using both linear and non-linear functions. Although the linear regressions were highly significant (p<0.005), a non-linear four parameter Gompertz curve was shown to fit the data more accurately. The curve explained only a little of the variance in the data in the relationship between NDVI and GDI, and so GDI was excluded from further analysis. All pixels that fell below a range of threshold standard deviations less than the fitted curve were deemed to represent degraded areas, where productivity was less than the predicted value. The results were compared qualitatively to existing spatial datasets. A large proportion of the degraded areas that were mapped using the approach outlined above occurred on areas of untransformed savanna and dryland cultivation. However the optical properties of dark igneous derived soils with high proportions of smectitic minerals and therefore low reflectance, were shown to lower NDVI values substantially. Overall, there was an acceptable agreement between the mapped degradation and the validation datasets. While further refinement of the methodology is necessary, including a rigorous field-based resource condition assessment for validation purposes, and research into the biophysical effects on the NDVI values, the methodology shows promise for regional assessment in South Africa.

In order to understand the dynamics of desertification after the 1980s droughts, the trends and changes of photosynthetically active fraction of the vegetation cover of the semi-arid region of West Africa have been analyzed across three ecoclimatic entities. This study focuses on six countries (Senegal, Mauritania, Mali, Burkina-Faso, Niger and Benin) that reflect quite well the human and environmental context of semi-arid regions. The main objective of this thesis is to check in the before-mentioned biophysical and human context, if the state of the vegetation improves because of more favourable rainfall conditions, or if, conversely, the long environmental deterioration during recent decades has a healthy dose of irreversibility for several years. The process of investigation proceeds in three stages defined by geographical scales and a geoclimatic gradient. At the regional level, we compared vegetation productivity data from 1982-1999 time series of NOAA-AVHRR NDVI data to rainfall data. We analyzed data from 315 rain gauges distributed across five countries (Senegal, Mauritania, Mali, Burkina-Faso and Niger) with annual average isohyets ranging from 100 to 900 mm. For trends analysis, we used the ratio of the integrated vegetation index (iNDVI) during the crop-growth period (June to October) to the May to October sum of rainfall (RR). This ratio (iNDVI/RR), a proxy of the Rain Use Efficiency, is widely used by ecologists as an indicator for detecting desertification processes. Overall, our results show a significant increase of the net primary production as a response of post-drought rainfall increase. However, the trends of iNDVI/RR ratio suggest that most of the studied stations (54%) in sahelian and sahelo-sudanese belts were stable and 31.4% showed strong to very strong negative change in iNDVI/RR ratio, while 13.3% of the stations showed a moderate decrease and only 1.3% showed a positive trend. At the country level, similar trends were recorded throughout 128 stations in Burkina Faso located between the 500 mm and 1100 mm isohyets. In fact, more than half the studied stations showed a stability of iNDVI/RR ratio. However, 39.8% of them show a negative trend from low to high, while only 2.4% of them show a slight positive trend. In addition, a comparison with more detailed local case studies confirmed these observed trends. However, the obtained results for wetter stations in the southern part of the country should be taken with precaution, as the relationship between NDVI and rainfall tends to weaken when annual rainfall is higher than 1000 mm. Overall, the negative trends highlight a gradual decline in plant productivity. These results recorded in 44.7% of the analyzed stations may reflect ongoing desertification processes in the sahelian and sahelo-sudanian zones over the past two decades. At the local level, a structural characterization of woody units in three bioclimatic regions of the sudanian zone (900 mm 1200 mm) in the north of Benin was conducted to assess their degradation status. We recorded the structural characteristics of stands (basal area, density), species diversity as well as disturbances type and intensity. Multivariate analysis revealed a gradient of productivity between the three regions: there was a high diversity of woody stands in the south-sudanian sector, while the north-sudanian and sudano-sahelian sectors were dominated by savannas and shrub, which had low productivity. The productivity gradient is influenced by a disturbance gradient suggesting that the decline in productivity is stronger from south-sudanian to the sudano-sahelian region. In addition, the spatial component of the observable changes in vegetation cover has been mapped by remote sensing in a restricted area of the sudanian zone in northern Benin with SPOT-XS data over the period 1986-2005. Over the past two decades, 19.6% of the woody stands have completely disappeared; 12.9% of this extinction of woody stands was due to deforestation, and 13.9 % due to degradation processes. In contrast to these trends, 21.8% of the study area were stable, while less than a third (31.7%) of the area were experiencing woody recovery (reforestation). The analysis also reveals significant disparities in the rates of change of the identified land use class units. These variations are more pronounced for the woody units and agricultural land than in villages. These results suggest that land cover degradation throughout the study area is primarily due to anthropogenic factors (livestock and agricultural expansion, logging, breeding). In fact, this area is a preferred destination for agricultural migrants fleeing the unpredictable climatic conditions of the drier semi-arid areas. Overall, our results highlight the rapid decline of vegetation resources, challenging assumptions that the impact of ongoing desertification processes is mixed, outside of the arid and semi-arid regions of West Africa. The developed framework is easily reproducible and allows the implementation of a reliable diagnosis on the state of the vegetation cover from accessible and inexpensive data. Its implementation should facilitate the development of managerial techniques for better assistance to the poor, especially vulnerable to the gradual degradation of their environment.