Modeling the Future Tree Distribution in a South African Savanna Ecosystem: An Agent-Based Model Approach

Understanding the dynamics of tree species and their demography is necessary for predicting future developments in savanna ecosystems. In this contribution, elephant-tree and firewood collector-tree interactions are compared using a multiagent model. To investigate these dynamics, we compared three different tree species in two plots. The first plot is located in the protected space of Kruger National Park (KNP), South Africa, and the second plot in the rural areas of the Bushbuckridge Municipality, South Africa. The agent-based modeling approach enabled the modeling of individual trees with characteristics such as species, age class, size, damage class, and life history. A similar level of detail was applied to agents that represent elephants and firewood collectors. Particular attention was paid to modeling purposeful behavior of humans in contrast to more instinct-driven actions of elephants. The authors were able to predict future developments by simulating the time period between 2010 and 2050 with more than 500,000 individual trees. Modeling individual trees for a time span of 40 years might yield more detailed information than a simple woody mass aggregation. The results indicate a significant trend toward more and thinner trees together with a notable reduction in mature trees, while the total aboveground biomass appears to stay more or less constant. Furthermore, the KNP scenarios show an increase in young Combretum apiculatum, which may correspond to bush encroachment.

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.

Estimating and Analyzing Savannah Phenology with a Lagged Time Series Model

Savannah regions are predicted to undergo changes in precipitation patterns according to current climate change projections. This change will affect leaf phenology, which controls net primary productivity. It is of importance to study this since savannahs play an important role in the global carbon cycle due to their areal coverage and can have an effect on the food security in regions that depend on subsistence farming. In this study we investigate how soil moisture, mean annual precipitation, and day length control savannah phenology by developing a lagged time series model. The model uses climate data for 15 flux tower sites across four continents, and normalized difference vegetation index from satellite to optimize a statistical phenological model. We show that all three variables can be used to estimate savannah phenology on a global scale. However, it was not possible to create a simplified savannah model that works equally well for all sites on the global scale without inclusion of more site specific parameters. The simplified model showed no bias towards tree cover or between continents and resulted in a cross-validated r2 of 0.6 and root mean squared error of 0.1. We therefore expect similar average results when applying the model to other savannah areas and further expect that it could be used to estimate the productivity of savannah regions.

Gas exchange and photosynthetic performance of the tropical tree Acacia nigrescens when grown in different CO(2) concentrations

The photosynthetic responses of the tropical tree species Acacia nigrescens Oliv. grown at different atmospheric CO(2) concentrations-from sub-ambient to super-ambient-have been studied. Light-saturated rates of net photosynthesis (A (sat)) in A. nigrescens, measured after 120 days exposure, increased significantly from sub-ambient (196 microL L(-1)) to current ambient (386 microL L(-1)) CO(2) growth conditions but did not increase any further as [CO(2)] became super-ambient (597 microL L(-1)). Examination of photosynthetic CO(2) response curves, leaf nitrogen content, and leaf thickness showed that this acclimation was most likely caused by reduction in Rubisco activity and a shift towards ribulose-1,5-bisphosphate regeneration-limited photosynthesis, but not a consequence of changes in mesophyll conductance. Also, measurements of the maximum efficiency of PSII and the carotenoid to chlorophyll ratio of leaves indicated that it was unlikely that the pattern of A (sat) seen was a consequence of growth [CO(2)] induced stress. Many of the photosynthetic responses examined were not linear with respect to the concentration of CO(2) but could be explained by current models of photosynthesis.

Thresholds of potential concern as benchmarks in the management of African savannahs

In the Kruger National Park (KNP), South Africa, ecosystem managers use a series of monitoring endpoints, known as thresholds of potential concern (TPCs), to define the upper and the lower levels of accepted variation in ecosystems. For woody vegetation, the current TPC suggests that woody cover should not drop by more than 80% of its 'highest ever' value. In this paper, we explore the utility of palaeoecological data in informing TPCs. We use calibrated fossil pollen data to explore variability in vegetation at two sites over the past 5000 years, to provide a long-term record of changes in woody vegetation cover and a context for interpreting more recent vegetation change. The fossil pollen data are calibrated using studies of modern pollen and vegetation from KNP; arboreal pollen percentage was simulated using pollen-landscape modelling software for savannah landscapes of varying woody vegetation cover, and the relationship between vegetation and pollen data was quantified using nonlinear regression. This quadratic equation was then applied to fossil pollen data in order to estimate woody vegetation cover from arboreal pollen percentages. Our results suggest that the TPCs have not been exceeded during the period represented in the pollen record, because estimated woody vegetation cover has remained above 20% of its highest ever value. By comparing the fossil pollen data with TPCs, our study demonstrates how palaeoecological data can be presented in a form that is directly relevant to management objectives.