Differing Responses to Rainfall Suggest More Than One Functional Type of Grassland in South Africa

Parametric Models to Characterize the Phenology of the Lowveld Savanna at Skukuza, South Africa

Mathematical models, such as the logistic curve, have been extensively used to model the temporal evolution of biological processes, though other similarly shaped functions could be (and sometimes have been) used for this purpose. Most previous studies focused on agricultural regions in the Northern Hemisphere and were based on the Normalized Difference Vegetation Index (NDVI). This paper compares the capacity of four parametric double S-shaped models (Gaussian, Hyperbolic Tangent, Logistic, and Sine) to represent the seasonal phenology of an unmanaged, protected savanna biome in South Africa’s Lowveld, using the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) generated by the Multi-angle Imaging SpectroRadiometer-High Resolution (MISR-HR) processing system on the basis of data originally collected by National Aeronautics and Space Administration (NASA)’s Multi-angle Imaging SpectroRadiometer (MISR) instrument since 24 February 2000. FAPAR time series are automatically split into successive vegetative seasons, and the models are inverted against those irregularly spaced data to provide a description of the seasonal fluctuations despite the presence of noise and missing values. The performance of these models is assessed by quantifying their ability to account for the variability of remote sensing data and to evaluate the Gross Primary Productivity (GPP) of vegetation, as well as by evaluating their numerical efficiency. Simulated results retrieved from remote sensing are compared to GPP estimates derived from field measurements acquired at Skukuza’s flux tower in the Kruger National Park, which has also been operational since 2000. Preliminary results indicate that (1) all four models considered can be adjusted to fit an FAPAR time series when the temporal distribution of the data is sufficiently dense in both the growing and the senescence phases of the vegetative season, (2) the Gaussian and especially the Sine models are more sensitive than the Hyperbolic Tangent and Logistic to the temporal distribution of FAPAR values during the vegetative season, and, in particular, to the presence of long temporal gaps in the observational data, and (3) the performance of these models to simulate the phenology of plants is generally quite sensitive to the presence of unexpectedly low FAPAR values during the peak period of activity and to the presence of long gaps in the observational data. Consequently, efforts to screen out outliers and to minimize those gaps, especially during the rainy season (vegetation’s growth phase), would go a long way to improve the capacity of the models to adequately account for the evolution of the canopy cover and to better assess the relation between FAPAR and GPP.

A global-scale dataset of direct natural groundwater recharge rates: A review of variables, processes and relationships

Groundwater recharge indicates the existence of renewable groundwater resources and is therefore an important component in sustainability studies. However, recharge is also one of the least understood, largely because it varies in space and time and is difficult to measure directly. For most studies, only a relatively small number of measurements is available, which hampers a comprehensive understanding of processes driving recharge and the validation of hydrogeological model formulations for small- and large-scale applications. We present a new global recharge dataset encompassing >5000 locations. In order to gain insights into recharge processes, we provide a systematic analysis between the dataset and other global-scale datasets, such as climatic or soil-related parameters. Precipitation rates and seasonality in temperature and precipitation were identified as the most important variables in predicting recharge. The high dependency of recharge on climate indicates its sensitivity to climate change. We also show that vegetation and soil structure have an explanatory power for recharge. Since these conditions can be highly variable, recharge estimates based only on climatic parameters may be misleading. The freely available dataset offers diverse possibilities to study recharge processes from a variety of perspectives. By noting the existing gaps in understanding, we hope to encourage the community to initiate new research into recharge processes and subsequently make recharge data available to improve recharge predictions.

The Future of Semi-Arid Regions: A Weak Fabric Unravels

The regions of the world where average precipitation is between one fifth and half of the potential plant water demand are termed ‘semi-arid’. They make up 15.2% of the global land surface, and the approximately 1.1 billion people who live there are among the world’s poorest. The inter-annual variability of rainfall in semi-arid regions is exceptionally high, due to intrinsic features of the global atmospheric circulation. The observed and projected climate trends for most semi-arid regions indicate warming at rates above the global mean rate over land, increasing evaporative demand, and reduced and more variable rainfall. Historically, the ecosystems and people coped with the challenges of semi-arid climates using a range of strategies that are now less viable. Semi-arid ecosystems are by definition water limited, generally only suitable for extensive pastoralism and opportunistic cropping, unless irrigation supplementation is available. The characteristics of dryland plant production in semi-arid ecosystems, as they interact with climate change and human systems, provide a conceptual framework for why land degradation is so conspicuous in semi-arid regions. The coupled social-ecological failures are contagious, both within the landscape and at regional and global scales. Thus, semi-arid lands are a likely flashpoint for Earth system changes in the 21st century.