Roelof J. Oomen

Are There Consistent Grazing Indicators in Drylands? Testing Plant Functional Types of Various Complexity in South Africa’s Grassland and Savanna Biomes

Despite our growing knowledge on plants’ functional responses to grazing, there is no consensus if an optimum level of functional aggregation exists for detecting grazing effects in drylands. With a comparative approach we searched for plant functional types (PFTs) with a consistent response to grazing across two areas differing in climatic aridity, situated in South Africa’s grassland and savanna biomes. We aggregated herbaceous species into PFTs, using hierarchical combinations of traits (from single- to three-trait PFTs). Traits relate to life history, growth form and leaf width. We first confirmed that soil and grazing gradients were largely independent from each other, and then searched in each biome for PFTs with a sensitive response to grazing, avoiding confounding with soil conditions. We found no response consistency, but biome-specific optimum aggregation levels. Three-trait PFTs (e.g. broad-leaved perennial grasses) and two-trait PFTs (e.g. perennial grasses) performed best as indicators of grazing effects in the semi-arid grassland and in the arid savanna biome, respectively. Some PFTs increased with grazing pressure in the grassland, but decreased in the savanna. We applied biome-specific grazing indicators to evaluate if differences in grazing management related to land tenure (communal versus freehold) had effects on vegetation. Tenure effects were small, which we mainly attributed to large variability in grazing pressure across farms. We conclude that the striking lack of generalizable PFT responses to grazing is due to a convergence of aridity and grazing effects, and unlikely to be overcome by more refined classification approaches. Hence, PFTs with an opposite response to grazing in the two biomes rather have a unimodal response along a gradient of additive forces of aridity and grazing. The study advocates for hierarchical trait combinations to identify localized indicator sets for grazing effects. Its methodological approach may also be useful for identifying ecological indicators in other ecosystems.

Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa

Image time series of high temporal and spatial resolution capture land surface dynamics of heterogeneous landscapes. We applied the ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) algorithm to multi-spectral images covering two semi-arid heterogeneous rangeland study sites located in South Africa. MODIS 250 m resolution and RapidEye 5 m resolution images were fused to produce synthetic RapidEye images, from June 2011 to July 2012. We evaluated the performance of the algorithm by comparing predicted surface reflectance values to real RapidEye images. Our results show that ESTARFM predictions are accurate, with a coefficient of determination for the red band 0.80 < R2 < 0.92, and for the near-infrared band 0.83 < R2 < 0.93, a mean relative bias between 6% and 12% for the red band and 4% to 9% in the near-infrared band. Heterogeneous vegetation at sub-MODIS resolution is captured adequately: A comparison of NDVI time series derived from RapidEye and ESTARFM data shows that the characteristic phenological dynamics of different vegetation types are reproduced well. We conclude that the ESTARFM algorithm allows us to produce synthetic remote sensing images at high spatial combined with high temporal resolution and so provides valuable information on vegetation dynamics in semi-arid, heterogeneous rangeland landscapes.

Cooperation and collapse in a communal livestock production SES model - A case from South Africa

Institutional arrangements are considered necessary for successfully governing the commons. They are considered to be most effective if they are self-organized rather than imposed from outside. However, endogenous institutional arrangements, such as local norms, are specific to a particular socio-ecological system (SES). This paper presents a SES model of communal livestock producers in South Africa. Its bio-physical component accounts for the impact of biotic and abiotic factors on livestock population. The social agent-based component models individual and socially determined behaviour, the latter of which is a social norm specific to the case. Model results show that when cooperative agents obey and sanction the norm, there is less likelihood of SES collapse in terms of livestock population crashes. However, cooperation among agents only emerges in times of ecological crisis where social reorganization is fostered. The crisis creates an opportunity for initializing a self-enforcing process of mutual cooperation. Model specifications are based on survey data, and agents were parameterized according to individual household data. A sensitivity analysis shows that this empirical heterogeneity cannot be reduced without changing model outcomes. We model a communal cattle production SES in South Africa to investigate the impact of a social norm.The SES model is a full integration of an ABM with a dynamic rangeland model.The emergence of norm compliance prevents SES collapse.A SES crisis is the opportunity for cooperative behaviour to emerge.The model is sensitive towards the parameterization of agent attributes from field data.

Discrimination and characterization of management systems in semi-arid rangelands of South Africa using RapidEye time series

In South African grasslands, rangeland management is strongly related to land tenure. Communal farms are reported to exhibit less desirable vegetation conditions for livestock than commercial farms. Time series of high spatial and temporal resolution imagery may be useful for improved evaluation of these rangelands as they provide information at a spatial scale similar to the typical scale of field assessments and may thus overcome the limited spatio-temporal representativeness of field measurements. A time series of 13 RapidEye images over one growing season (2010–2011) was used to explore spectral differences between and within two management systems (commercial vs. communal). Isomap ordination was applied to map continuous spectral dissimilarities of sample plots. Using regression with simultaneous autoregressive models (SAR), dissimilarities were subsequently related to ecological variables of plant and soil, including indicators for grazing effects. The largest differences were found between sample plots of communal and commercial farms. Vegetation attributes were significantly related to dissimilarities in reflectance, both from the growing season and the dormant period. However, these relationships did not suggest vegetation degradation on communal farms. They further suggest that a management-related pattern of grazing disturbance in the summer months led to spectral differences between farms but could have impaired the detailed characterization of spectral dissimilarities related to differences in vegetation composition.

Uncertainty in future irrigation water demand and risk of crop failure for maize in Europe

While crop models are widely used to assess the change in crop productivity with climate change, their skill in assessing irrigation water demand or the risk of crop failure in large area impact assessments is relatively unknown. The objective of this study is to investigate which aspects of modeling crop water use (reference crop evapotranspiration (ET0), soil water extraction, soil evaporation, soil water balance and root growth) contributes most to the variability in estimates of maize crop water use and the risk of crop failure, and demonstrate the resulting uncertainty in a climate change impact study for Europe. The SIMPLACE crop modeling framework was used to couple the LINTUL5 crop model in factorial combinations of 2–3 different approaches for simulating the 5 aspects of crop water use, resulting in 51 modeling approaches. Using experiments in France and New Zeland, analysis of total sensitivity revealed that ET0 explained the most variability in both irrigated maize water use and rainfed grain yield levels, with soil evaporation also imporatant in the French experiment. In the European impact study, net irrigation requirement differed by 36% between the Penman and Hargreaves ET0 methods in the baseline period. Average EU grain yields were similar between models, but differences approached 1–2 tonnes in parts of France and Southern Europe. EU wide esimates of crop failure in the historical period ranged between 5.4 years for Priestley–Taylor to every 7.9 years for the Penman ET0 methods. While the uncertainty in absolute values between models was significant, estimates of relative changes were similar between models, confirming the utility of crop models in assessing climate change impacts. If ET0 estimates in crop models can be improved, through the use of appropriate methods, uncertainty in irrigation water demand as well as in yield estimates under drought can be reduced.

Effect of management on rangeland phytomass, cover and condition in two biomes in South Africa

In rangelands, grazing management is a main driver of rangeland condition. Due to masking effects of seasonal climate fluctuations, little is known about (dis)similarity of management effects on rangeland condition and forage provision across major dryland biomes. Taking a macro-ecological perspective, we analysed if management effects differed between South Africa’s central grassland and Kalahari savanna biomes. We recorded proxies of forage provision (phytomass, vegetation cover and their ratio) over five seasons, annual rainfall to account for seasonal climate fluctuations, and rangeland condition (through relative abundances of increaser and decreaser species). Regarding forage provision, we found effects of management for the savanna, where, irrespective of rainfall, rotational grazing management resulted in higher phytomass and phytomass–cover ratios than management with continuous grazing. In the grassland, however, this difference was only discernible for phytomass–cover ratio in two years with above-average antecedent rainfall. This suggests that management effects are biome-dependent and that modulating effects of annual rainfall are stronger in the grassland. In either biome, management effects on the dominance of increaser and decreaser species were negligible, i.e. rangeland condition did not differ across management types in either biome. We conclude that investigations on management effects should account for interactions with biome and rainfall.

Soil microbial communities in different rangeland management systems of a sandy savanna and clayey grassland ecosystem, South Africa

Soil nutrient supply in rangelands depends on the maintenance and performance of soil microbiological communities. In this study we investigated how different rangeland management systems affects the structure and function of soil microbial communities in the clayey grassland and sandy savanna ecosystems, South Africa. These ecosystems differ in climate, soil and vegetation, with the sandy savanna ecosystem being drier, and encroached by bush. Soils were sampled under continuous and rotational grazing systems along a gradient with increasing grazing pressure. Analyses comprised of enzyme activities and phospholipid fatty acids (PLFA). The results revealed that the clayey grassland ecosystem displayed elevated enzyme activities and PLFA contents compared with the drier, sandy savanna ecosystem, irrespective of the rangeland management practices, likely because soil texture played a significant role in maintaining microbial communities. However, when microbial activity was normalized to carbon, nitrogen and microbial biomass, specific enzyme activities were significantly higher in the sandy savanna ecosystem, indicating a more efficient functioning of microbes here. Furthermore, these microbial parameters were more sensitive to grazing pressure in the clayey grassland ecosystem than other chemical or physical soil properties, whereas in the sandy savanna ecosystem this was not the case. Decreasing the grazing pressure on rangeland, as, e.g., done by commercial farmers practicing rotational grazing, appeared to stimulate microbial performance and thus microbial mediated nutrient mineralization with positive consequences on plant growth.

Stimulating seedling growth in early stages of secondary forest succession: a modeling approach to guide tree liberation

Excessive growth of non-woody plants and shrubs on degraded lands can strongly hamper tree growth and thus secondary forest succession. A common method to accelerate succession, called liberation, involves opening up the vegetation canopy around young target trees. This can increase growth of target trees by reducing competition for light with neighboring plants. However, liberation has not always had the desired effect, likely due to differences in light requirement between tree species. Here we present a 3D-model, which calculates photosynthetic rate of individual trees in a vegetation stand. It enables us to examine how stature, crown structure, and physiological traits of target trees and characteristics of the surrounding vegetation together determine effects of light on tree growth. The model was applied to a liberation experiment conducted with three pioneer species in a young secondary forest in Vietnam. Species responded differently to the treatment depending on their height, crown structure and their shade-tolerance level. Model simulations revealed practical thresholds over which the tree growth response is heavily influenced by the height and density of surrounding vegetation and gap radius. There were strong correlations between calculated photosynthetic rates and observed growth: the model was well able to predict growth of trees in young forests and the effects of liberation there upon. Thus, our model serves as a useful tool to analyze light competition between young trees and surrounding vegetation and may help assess the potential effect of tree liberation.