Pierre Hiernaux

Determinants of woody cover in African savannas

Savannas are globally important ecosystems of great significance to human economies. In these biomes, which are characterized by the co-dominance of trees and grasses, woody cover is a chief determinant of ecosystem properties. The availability of resources (water, nutrients) and disturbance regimes (fire, herbivory) are thought to be important in regulating woody cover, but perceptions differ on which of these are the primary drivers of savanna structure. Here we show, using data from 854 sites across Africa, that maximum woody cover in savannas receiving a mean annual precipitation (MAP) of less than ∼650 mm is constrained by, and increases linearly with, MAP. These arid and semi-arid savannas may be considered ‘stable’ systems in which water constrains woody cover and permits grasses to coexist, while fire, herbivory and soil properties interact to reduce woody cover below the MAP-controlled upper bound. Above a MAP of ∼650 mm, savannas are ‘unstable’ systems in which MAP is sufficient for woody canopy closure, and disturbances (fire, herbivory) are required for the coexistence of trees and grass. These results provide insights into the nature of African savannas and suggest that future changes in precipitation may considerably affect their distribution and dynamics.

Savanna vegetation-fire-climate relationships differ among continents.

Surveying Savannas Savannas are structurally similar across the three major continents where they occur, leading to the assumption that the factors controlling vegetation structure and function are broadly similar, too. Lehmann et al. (p. 548) report the results of an extensive analysis of ground-based tree abundance in savannas, sampled at more than 2000 sites in Africa, Australia, and South America. All savannas, independent of region, shared a common functional property in the way that moisture and fire regulated tree abundance. However, despite qualitative similarity in the moisture–fire–tree-biomass relationships among continents, key quantitative differences exist among the three regions, presumably as a result of unique evolutionary histories and climatic domains. Evolution cannot be overlooked when aiming to predict the potential global impacts on savanna dynamics in a warming world. Ecologists have long sought to understand the factors controlling the structure of savanna vegetation. Using data from 2154 sites in savannas across Africa, Australia, and South America, we found that increasing moisture availability drives increases in fire and tree basal area, whereas fire reduces tree basal area. However, among continents, the magnitude of these effects varied substantially, so that a single model cannot adequately represent savanna woody biomass across these regions. Historical and environmental differences drive the regional variation in the functional relationships between woody vegetation, fire, and climate. These same differences will determine the regional responses of vegetation to future climates, with implications for global carbon stocks.

On the delineation of tropical vegetation types with an emphasis on forest/savanna transitions

Background: There is no generally agreed classification scheme for the many different vegetation formation types occurring in the tropics. This hinders cross-continental comparisons and causes confusion as words such as ‘forest’ and ‘savanna’ have different meanings to different people. Tropical vegetation formations are therefore usually imprecisely and/or ambiguously defined in modelling, remote sensing and ecological studies. Aims: To integrate observed variations in tropical vegetation structure and floristic composition into a single classification scheme. Methods: Using structural and floristic measurements made on three continents, discrete tropical vegetation groupings were defined on the basis of overstorey and understorey structure and species compositions by using clustering techniques. Results: Twelve structural groupings were identified based on height and canopy cover of the dominant upper stratum and the extent of lower-strata woody shrub cover and grass cover. Structural classifications did not, however, always agree with those based on floristic composition, especially for plots located in the forest–savanna transition zone. This duality is incorporated into a new tropical vegetation classification scheme. Conclusions: Both floristics and stand structure are important criteria for the meaningful delineation of tropical vegetation formations, especially in the forest/savanna transition zone. A new tropical vegetation classification scheme incorporating this information has been developed.

Radar Signatures of Sahelian Surfaces in Mali Using ENVISAT-ASAR Data

This paper presents an analysis of ENSIVAT advanced synthetic aperture radar data acquired over a Sahelian region located in Mali, West Africa. The considered period is 2004-2005 and includes two rainy seasons. Emphasis is put on two ScanSAR modes, namely, the global monitoring (GM) and the wide swath (WS) modes characterized by spatial resolutions of about 1 km and 150 m, respectively. Results show that the WS mode offers better performance in terms of radiometric resolution, radiometric stability, and speckle reduction than the GM mode. The latter is more appropriate for studies at large scale (> 10 times 10 km). In both modes, pronounced angular and temporal signatures are observed for most soil surfaces, and azimuthal effects are observed on markedly orientated rocky surfaces. In contrast, polarization differences (VV/HH) are small during the dry season except on flat loamy soil surfaces. Finally, a relationship is observed between the normalized WS backscattering signal at HH polarization and the surface soil moisture of sandy soils.

Differences between cropland and rangeland MODIS phenology (start-of-season) in Mali

Abstract Start-of-season data are more and more used to qualify the land surface phenology trends in relation with climate variability and, more rarely, with human land management. In this paper, we compared the phenology of rangeland vs cropped land in the Sahel belt of Africa, using the only currently available global phenology product (MODIS MCD12Q2 – Land Cover Dynamics Yearly), and an enhanced crop mask of Mali. The differences in terms of start-of-season (SOS) are spatially (north south gradient), and temporally (10 years, 2001–2009) analyzed in bioclimatic terms. Our results show that globally the MODIS MCD12Q2 SOS dates of croplands and rangelands differ, and that these differences depend on the bioclimatic zone. In Sahelian and Guinean regions, cropland vegetation begins to grow earlier than rangeland vegetation (8-day and 4-day advance, respectively). Between, in the Sudanian and Sudano-Sahelian parts of Mali, rangeland vegetation greens about one week earlier than croplands. These results are discussed in the context of the land surface heterogeneity at MODIS scale, and in the context of the natural vegetation ecology. These results could help interpreting phenological trends in climate change analysis.

Comparison of ERS wind-scatterometer and SSM/I data for Sahelian vegetation monitoring

ERS wind scatterometer (WSC) and SSM/I data are compared for monitoring the seasonal variation of herbaceous vegetation over a sahelian region. Temporal evolution of polarization difference brightness temperatures derived from SSM/I data and WSC backscattering coefficient acquired at 45/spl deg/ of incidence angle over four different sites during the period 1992-1993, exhibits a marked seasonality with opposite and symmetrical trends. Observed differences between both signals are mainly attributed to atmospheric effects affecting SSM/I data. The use of a semi-empirical model during the 1992 rainy season shows that /spl Delta/T temporal evolution is mainly due to the variation of integrated water vapor content of the atmosphere, surface, and air temperature, soil moisture content, and bare soil fraction area. In order to retrieve biomass from SSM/I data, an inversion procedure is performed and compared to previous results obtained with ERS WSC data. The absence of accurate atmospheric data over the Sahel, combined with the sensitivity of the passive model to soil moisture leads to poor results with regard to biomass retrieval from SSM/I data.

Do Agrometeorological Data Improve Optical Satellite-Based Estimations of the Herbaceous Yield in Sahelian Semi-Arid Ecosystems?

Quantitative estimates of forage availability at the end of the growing season in rangelands are helpful for pastoral livestock managers and for local, national and regional stakeholders in natural resource management. For this reason, remote sensing data such as the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) have been widely used to assess Sahelian plant productivity for about 40 years. This study combines traditional FAPAR-based assessments with agrometeorological variables computed by the geospatial water balance program, GeoWRSI, using rainfall and potential evapotranspiration satellite gridded data to estimate the annual herbaceous yield in the semi-arid areas of Senegal. It showed that a machine-learning model combining FAPAR seasonal metrics with various agrometeorological data provided better estimations of the in situ annual herbaceous yield (R2 = 0.69; RMSE = 483 kg·DM/ha) than models based exclusively on FAPAR metrics (R2 = 0.63; RMSE = 550 kg·DM/ha) or agrometeorological variables (R2 = 0.55; RMSE = 585 kg·DM/ha). All the models provided reasonable outputs and showed a decrease in the mean annual yield with increasing latitude, together with an increase in relative inter-annual variation. In particular, the additional use of agrometeorological information mitigated the saturation effects that characterize the plant indices of areas with high plant productivity. In addition, the date of the onset of the growing season derived from smoothed FAPAR seasonal dynamics showed no significant relationship (0.05 p-level) with the annual herbaceous yield across the whole studied area. The date of the onset of rainfall however, was significantly related to the herbaceous yield and its inclusion in fodder biomass models could constitute a significant improvement in forecasting risks of a mass herbaceous deficit at an early stage of the year.

Desertification, Adaptation and Resilience in the Sahel: Lessons from Long Term Monitoring of Agro-ecosystems

The desertification paradigm has a long history in the Sahel, from colonial to modern times. Despite scientific challenge, it continued to be influential after independence, revived by the dramatic droughts of the 1970s and 1980s, and was institutionalized at local, national and international levels. Collaborative efforts were made to improve scientific knowledge on the functioning, environmental impact and monitoring of selected agricultural systems over the long term, and to assess trends in the ecosystems, beyond their short term variability. Two case studies are developed here: the pastoral system of the arid to semi-arid Gourma in Mali, and the mixed farming system of the semi-arid Fakara in Niger. The pastoral landscapes are resilient to droughts, except on shallow soils, and to grazing, following a non-equilibrium model. The impact of cropping on the landscape is larger and longer lasting. It also induces locally high grazing pressure that pushes rangeland resilience to its limits. By spatial transfer of organic matter and mineral, farmers’ livestock create patches of higher fertility that locally enhance the system’s resilience. The agro-pastoral ecosystem remains non-equilibrial provided that inputs do not increase stocking rates disproportionately. Remote sensing confirms the overall re-greening of the Sahel after the drought of the 1980s, contrary to the paradigm of desertification. Ways forward are proposed to adapt the pastoral and mixed farming economies and their regional integration to the context of human and livestock population growth and expanding croplands.

Comparing drag partition schemes over a herbaceous Sahelian rangeland

Modeling of dust emissions from the surface remains complex, especially in semiarid regions where vegetation must be accounted for because of its potentially important protective effect. Protection is directly linked to the fraction of the soil surface covered by vegetation, but it is also driven by the interaction of vegetation elements with the wind field. The sensitivity of simulated dust emissions to various drag partition schemes—mainly those proposed by Raupach (1992), Marticorena and Bergametti (1995), and Okin (2008)—is evaluated for a typical Sahelian rangeland, covered by a seasonal grass layer, over a complete vegetation cycle. The application of these schemes requires a fine characterization of the vegetation cover; field measurements from an ecological survey are used to derive the geometric dimensions of the grass patches. Models are run with meteorological forcing from automatic weather stations. As a result, the impacts of soil moisture and grass cover are estimated over April to September. Soil moisture inhibits dust emissions by 27% in mass. The different drag partition schemes exhibit distinctive limitations, mostly due to the properties of the Sahelian grass cover, which is composed of large and low patches of short grass, with a strong seasonal dynamics. However, the drag partition schemes result in remarkably coherent estimations of dust emissions. When soil moisture is taken into account, vegetation reduces the total vertical mass fluxes by 6 to 26% of the emissions of a bare soil, depending on the drag partition scheme.

Observations and simulations of the ERS wind scatterometer response over a Sahelian region

ERS-1 wind-scatterometer data acquired over a saharo-sahelian region located in the Gourma (Mali) during the period 1992-1995, are analysed. Experimental observations show that /spl sigma//spl deg/(45/spl deg/) temporal data display a marked seasonality associated with the development and senescence of annual grasses during the rainy seasons. The interpretation of the temporal /spl sigma//spl deg/ plots is performed with the assistance of a semi-empirical backscattering model combined with an ecosystem grassland model. The use of this model allows the total biomass to be estimated with a 33% error.