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Shrub encroachment, i.e. the increase in woody plant cover, is a major concern for livestock farming in southern Kalahari savannas. We developed a grid-based computer model simulating the population dynamics of Grewia flava, a common, fleshy-fruited encroaching shrub. In the absence of large herbivores, seeds of Grewia are largely deposited in the sub-canopy of Acacia erioloba. Cattle negate this dispersal limitation by browsing on the foliage of Grewia and dispersing seeds into the grassland matrix. In this study we first show that model predictions of Grewia cover dynamics are realistic by comparing model output with shrub cover estimates obtained from a time series of aerial photographs. Subsequently, we apply a realistic range of intensity of cattle-induced seed dispersal combined with potential precipitation and fire scenarios. Based on the simulation results we suggest that cattle may facilitate shrub encroachment of Grewia. The results show that the severity of shrub encroachment is governed by the intensity of seed dispersal. For a high seed dispersal intensity without fire (equivalent to a high stocking rate) the model predicts 56% shrub cover and 85% cell cover after 100 yr. With fire both recruitment and shrub cover are reduced, which may, under moderate intensities, prevent shrub encroachment. Climate change scenarios with two-fold higher frequencies of drought and wet years intensified shrub encroachment rates, although long-term mean of precipitation remained constant. As a management recommendation we suggest that shrub encroachment on rangelands may be counteracted by frequent fires and controlling cattle movements to areas with a high proportion of fruiting Grewia shrubs
Environmental heterogeneity is a major determinant of plant population dynamics. In semi-arid Kalahari savannas, heterogeneity is created by savanna structure, i.e. by the spatial arrangement and temporal dynamics of woody plant and open grassland microsites. We formulate a conceptual model describing the effects of savanna dynamics on the population dynamics of the animal-dispersed shrub Grewia flava. From empirical results we derive model rules describing effects of savanna structure on several processes in Grewia's life cycle. By formulating the model, we summarise existing information on Grewia demography and identify gaps in this knowledge. Despite a number of such gaps, the model can be used to make certain quantitative predictions. As an example, we apply the model to investigate the role of seed dispersal in Grewia encroachment on rangelands. Model results show that cattle promote encroachment by depositing substantial numbers of seeds in open areas, where Grewia is otherwise dispersal-limited. Finally, we draw some general conclusions about Grewia's life history and population dynamics. Under natural conditions, concentrated seed deposition under woody plants appears to be a key process causing the observed association between Grewia and other woody plants. Furthermore, low rates of recruitment and high adult survival result in slow-motion dynamics of Grewia populations. As a consequence, Grewia populations interact with savanna dynamics on long temporal and short to intermediate spatial scales.
Ecologists increasingly use spatial statistics to study vegetation patterns. Mostly, however, these techniques are applied in a purely descriptive fashion without a priori statements on the pattern characteristics expected. We formulated such a priori predictions in a study of spatial pattern in a semi-arid Karoo shrubland, South Africa. Both seed dispersal and root competition have been discussed as processes shaping the spatial structure of this community. If either of the two processes dominates pattern formation, patterns within and between shrub functional groups are expected to show distinct deviations from null models. We predicted the type and scale of these deviations and compared predicted to observed pattern characteristics. As predicted by the seed dispersal hypothesis, small-scale co-occurrence within and between groups of colonisers and successors was increased as compared to complete spatially random arrangement of shrubs. The root competition predictions, however, were not met as shrubs of similar rooting depth co- occurred more frequently than expected under random shrub arrangement. Since the distribution of rooting groups to the given shrub locations also failed to match the root competition predictions, there was little evidence for dominance of root competition in pattern formation. Although other processes may contribute to small-scale plant co-occurrence, the sufficient and most parsimonious explanation for the observed pattern is that its formation was dominated by seed dispersal. To characterise point patterns we applied both cumulative (uni- and bivariate K-function) and local (pair- and mark-correlation function) techniques. Based on our results we recommend that future studies of vegetation patterns include local characteristics as they independently describe a pattern at different scales and can be easily related to processes changing with interplant distance in a predictable fashion.