Changes in Vegetation and Rainfall over West Africa during the Last Three Decades (1981-2010)

The decadal variability of rainfall and vegetation over West Africa have been studied over the last three decades, 1981-1990, 1991-2000 and 2001-2010 denoted as 1980s, 1990s and 2000s, respectively. Climate Research Unit (CRU) monthly precipitation and Normalized Difference Vegetation Index (NDVI) from the National Oceanic and Atmosphere Administration (NOAA), all covering the period 1981-2010 have been used. This study aimed to assess the changes in the land surface condition and the spatio-temporal distribution of rainfall over West Africa region. The relationship between rainfall and vegetation indices over this region was determined using Pearson’s correlation. Also, the decadal comparison between rainfall and NDVI over the region was based on the significant t-test and the Pearson’s correlation. Results showed that significant return to wet conditions is observed between decade 1980s and decade 1990s over West Africa, and also during decade 2000s with the exception of central Benin and the western Nigeria. Meanwhile, a regreening of the central Sahel and Sudano-Sahel regions is noted. From 1990s to 2000s, this regreening belt is located in the South and the coastal areas: the Guinea Coast, Sudano-Guinea and western Sahel regions. A northward displacement of this re-greening belt is also detected. Thus, a linear relationship occurs between rainfall and NDVI in the Sudanian savannah region, but it is not the case in the rest of West Africa. This may suggest that the re-growth of vegetation in the Sudanian savannah region may be linked to rainfall supplies. Therefore, re-greening over Sahel region in1990s is related to rainfall recovery. However, this re-greening was not sustained in the decade 2000s due to a slight decrease in rainfall

The potential for remote sensing and hydrologic modelling to assess the spatio-temporal dynamics of ponds in the Ferlo Region (Senegal)

In the Ferlo Region in Senegal, livestock depend on temporary ponds for water but are exposed to the Rift Valley Fever (RVF), a disease transmitted to herds by mosquitoes which develop in these ponds. Mosquito abundance is related to the emptying and filling phases of the ponds, and in order to study the epidemiology of RVF, pond modelling is required. In the context of a data scarce region, a simple hydrologic model which makes use of remote sensing data was developed to simulate pond water dynamics from daily rainfall. Two sets of ponds were considered: those located in the main stream of the Ferlo Valley whose hydrological dynamics are essentially due to runoff, and the ponds located outside, which are smaller and whose filling mechanisms are mainly due to direct rainfall. Separate calibrations and validations were made for each set of ponds. Calibration was performed from daily field data (rainfall, water level) collected during the 2001 and 2002 rainy seasons and from three different sources of remote sensing data: 1) very high spatial resolution optical satellite images to access pond location and surface area at given dates, 2) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model (DEM) data to estimate pond catchment area and 3) Tropical Rainfall Measuring Mission (TRMM) data for rainfall estimates. The model was applied to all ponds of the study area, the results were validated and a sensitivity analysis was performed. Water height simulations using gauge rainfall as input were compared to water level measurements from four ponds and Nash coefficients >0.7 were obtained. Comparison with simulations using TRMM rainfall data gave mixed results, with poor water height simulations for the year 2001 and good estimations for the year 2002. A pond map derived from a Quickbird satellite image was used to assess model accuracy for simulating pond water areas for all the ponds of the study area. The validation showed that modelled water areas were mostly underestimated but significantly correlated, particularly for the larger ponds. The results of the sensitivity analysis showed that parameters relative to pond shape and catchment area estimation have less effects on model simulation than parameters relative to soil properties (rainfall threshold causing runoff in dry soils and the coefficient expressing soil moisture decrease with time) or the water loss coefficient. Overall, our results demonstrate the possibility of using a simple hydrologic model with remote sensing data to track pond water heights and water areas in a homogeneous arid area

Seasonal and diurnal variability of convection over the Amazonia: A comparison of different vegetation types and large scale forcing

A climatological description of the convection over Amazonia is based on the seasonal and diurnal cycle analysis. Long series of observations are used from four sites: two sites are representative of dense rainforest, either continental (Manaus) or coastal (Belém); one site is in southeast Amazonia, in a region of ecological tension where forest has been partly replaced by pasture (Vilhena); and finally, one is in the south of Amazonia, in a region typical of savanna (Brasília). Each site has a long series of radiosonde and surface observations. Other parameters are also used: rainfall averaged from the raingauges in the vicinity of each site; vegetation monitored using NDVI averaged over 128km×128km boxes centred on each site; and total and high cloud cover estimated using the 2.5°×2.5° ISCCP products derived from satellite data. It is shown that the main differences between rainforest and savanna or deforested sites occur in the dry season, whereas the magnitude and diurnal cycle of convection as well as amount of rainfall and NDVI are quite similar during the wet season. For the savanna site the seasonal variation is well defined for every parameter, whereas for rainforest sites the vegetation and atmospheric thermodynamics show very weak seasonal variations, yet driving significant diurnal variations of the convection and precipitation. The transition season from dry to wet and the beginning of the wet season is generally the period of strongest intensity of convection

The sensitivity of Sahelian runoff to climate change

A simple method is used to study the response of runoff in the Sahel to climate change. The statistical characteristics of rainfall are calculated over the western part of the Sahel for the period 1961-1990, using the BADOPLU network. Daily rainfall is simulated using a Markov process with Weibull distribution for rainfall depths. Runoff is modelled using a conceptual SCS model and the curve numbers are calculated for West Africa. Climate change is provided by simulations using the Arpege GCM (Scenario A1B), and a perturbation method is used on the parameters which describe the rainfall. Changes in rainfall are assumed to occur through increases in frequency, not intensity. Using Arpege, runoff is mainly found to increase, in depth and in number of events, by the end of the 21st century. Changes in evaporation and land use are not included in the analysis. The impact of this 21st century potential climate change (rainfall) on the runoff is found to be of the same magnitude as the impact of changes in land use

Can a 25-year trend in Soudano-Sahelian vegetation dynamics be interpreted in terms of land use change? A remote sensing approach

International audienceThis study is based on the premise that, in the Sahel/Sudanian belt of Africa, the main determinants of interannual variation in vegetation dynamics are rainfall and land cover type. We analyzed the spatiotemporal sensitivity of the NOAA–AVHRR 8 km-resolution vegetation index (NDVI) to (i) annual rainfall variability (0.58 _ 0.58 resolution) acquired over a 25-year period (1982–2006); and (ii) land use changes in the different eco-climatic regions of the Bani catchment in Mali (130 000 km2). During the period 1982–2006, there was no clear trend in rainfall over the catchment, whereas there was a strong positive trend in the NDVI, both when the NDVI values were corrected using annual rainfall variability and when they were not. We divided the catchment into three eco-climatic regions based on the relationship between the annual NDVI and rainfall. In each region, we analyzed the observed greening in relation to changes in land use after correcting for the effect of annual rainfall on the NDVI. Results show that there is a mixed level of agreement between the land cover changes at the grid cell scale and the spatial pattern of the NDVI trend. Increased cropping does not explain the increase in the annual NDVI, except in the Sahelian part of the catchment. We hypothesize that the natural vegetation dynamics related to the nonlinearrainfall patterns during the 25-year study period were responsible for these results

High spatial resolution land use and land cover mapping of the Brazilian Legal Amazon in 2008 using Landsat-5/TM and MODIS data.

Understanding spatial patterns of land use and land cover is essential for studies addressing biodiversity, climate change and environmental modeling as well as for the design and monitoring of land use policies. The aim of this study was to create a detailed map of land use land cover of the deforested areas of the Brazilian Legal Amazon up to 2008. Deforestation data from and uses were mapped with Landsat-5/TM images analysed with techniques, such as linear spectral mixture model, threshold slicing and visual interpretation, aided by temporal information extracted from NDVI MODIS time series. The result is a high spatial resolution of land use and land cover map of the entire Brazilian Legal Amazon for the year 2008 and corresponding calculation of area occupied by different land use classes. The results showed that the four classes of Pasture covered 62% of the deforested areas of the Brazilian Legal Amazon, followed by Secondary Vegetation with 21%. The area occupied by Annual Agriculture covered less than 5% of deforested areas; the remaining areas were distributed among six other land use classes. The maps generated from this project ? called TerraClass - are available at INPE?s web site (http://www.inpe.br/cra/projetos_pesquisas/terraclass2008.php)Made available in DSpace on 2016-06-29T07:53:44Z (GMT). No. of bitstreams: 1 APHighspatialActaAmazonicaAlmeidaetal.pdf: 8415999 bytes, checksum: 3ac83a65b97b12994541d66041e212cc (MD5) Previous issue date: 2016-06-28201

Twenty-five novel mutations including duplications in the ATP7A gene.

Menkes disease (MD) and occipital horn syndrome (OHS) are allelic X-linked recessive copper deficiency disorders resulting from ATP7A gene mutations. MD is a severe condition leading to progressive neurological degeneration and death in early childhood, whereas OHS has a milder phenotype with mainly connective tissue abnormalities. Until now, molecular analyses have revealed only deletions and point mutations in both diseases. This study reports new molecular data in a series of 40 patients referred for either MD or OHS. We describe 23 point mutations (9 missense mutations, 7 splice site variants, 4 nonsense mutations, and 3 small insertions or deletions) and 7 intragenic deletions. Of these, 18 point mutations and 3 deletions are novel. Furthermore, our finding of four whole exon duplications enlarges the mutation spectrum in the ATP7A gene. ATP7A alterations were found in 85% of cases. Of these alterations, two thirds were point mutations and the remaining one third consisted of large rearrangements. We found that 66.6% of point mutations resulted in impaired ATP7A transcript splicing, a phenomenon more frequent than expected. This finding enabled us to confirm the pathogenic role of ATP7A mutations, particularly in missense and splice site variant