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Precipitation and land use in terms of livestock grazing have been identified as two of the most important drivers structuring the vegetation composition of semi-arid and arid savannas. Savanna research on the impact of these drivers has widely applied the so-called plant functional type (PFT) approach, grouping the vegetation into two or three broad types (here called meta-PFTs): woody plants and grasses, which are sometimes divided into perennial and annual grasses. However, little is known about the response of functional traits within these coarse types towards water availability or livestock grazing. In this study, we extended an existing eco-hydrological savanna vegetation model to capture trait diversity within the three broad meta-PFTs to assess the effects of both grazing and mean annual precipitation (MAP) on trait composition along a gradient of both drivers. Our results show a complex pattern of trait responses to grazing and aridity. The response differs for the three meta-PFTs. From our findings, we derive that trait responses to grazing and aridity for perennial grasses are similar, as suggested by the convergence model for grazing and aridity. However, we also see that this only holds for simulations below a MAP of 500 mm. This combined with the finding that trait response differs between the three meta-PFTs leads to the conclusion that there is no single, universal trait or set of traits determining the response to grazing and aridity. We finally discuss how simulation models including trait variability within meta-PFTs are necessary to understand ecosystem responses to environmental drivers, both locally and globally and how this perspective will help to extend conceptual frameworks of other ecosystems to savanna research.
1. Savanna systems exhibit a high plant functional diversity. While aridity and livestock grazing intensity have been widely discussed as drivers of savanna vegetation composition, physical soil properties have received less attention. Since savannas can show local differences in soil properties, these might act as environmental filters and affect plant diversity and ecosystem functioning at the patch scale. However, research on the link between savanna vegetation diversity and ecosystem function is widely missing. 2. In this study, we aim at understanding the impact of local heterogeneity in soil conditions on plant diversity and on ecosystem functions. For this, we used the ecohydrological savanna model EcoHyD. The model simulates the fate of multiple plant functional types and their interactions with local biotic and abiotic conditions. We applied the model to a set of different landscapes under a wide range of livestock grazing and precipitation scenarios to assess the impact of local heterogeneity in soil conditions on the composition and diversity of plant functional types and on ecosystem functions. 3. Comparisons between homogeneous and heterogeneous landscapes revealed that landscape soil heterogeneity allowed for a higher functional diversity of vegetation under conditions of high competition, i.e. scenarios of low grazing stress. However, landscape heterogeneity did not have this effect under low grazing stress in combination with high mean annual precipitation. Further, landscape heterogeneity led to a higher community biomass, especially for lower rainfall conditions, but also dependent on grazing stress. Total transpiration of the plant community decreased in heterogeneous landscapes under arid conditions. 4. This study highlights that local soil conditions interact with precipitation and grazing in driving savanna vegetation. It clearly shows that vegetation diversity and resulting ecosystem functioning can be driven by landscape heterogeneity. We therefore suggest that future research on ecosystem functioning of savanna systems should focus on the links between local environmental conditions via plant functional diversity to ecosystem functioning.
The El Nino-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.
The El Nino-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.
The El Nino-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.
We analyzed relative sensitivities of small- and medium-sized carnivores to livestock husbandry (stocking rates and predator control) in Kalahari, South Africa, rangelands at a regional scale. We monitored small carnivores using track counts on 22 Kalahari farms across a land-use gradient ranging from low to high stocking rates and also interviewed each farm manager to identify farmers" perception of small carnivores as potential predators for livestock. We recorded 12 species of small- and medium-sized carnivores across 22 Kalahari farms. Stocking rate was the most important driving variable for local carnivore abundance. Abundance of all species was lowest on farms where stocking rate was high. Most farm managers perceived medium-sized carnivores, in particular, African wildcat (Felis silvestris lybica), black-backed jackal (Canis mesomelas), and caracal (Caracal caracal), as potential predators of livestock. Multiple regression analysis shows that black-backed jackal, African wildcat, and caracal were negatively affected by predator control measures, whereas bat-eared fox (Otocyon megalotis), cape fox (Vulpes chama), and small-spotted genet (Genetta genetta) were positively affected. Our results show a need for expanding research and conservation activities toward small- and medium-sized carnivores in southern African savannah rangelands. We, therefore, suggest developing a monitoring program combining passive tracking with indigenous knowledge of local Khoisan Bushmen to monitor carnivore populations, and we recommend additional predator removal experiments that manipulate predator densities.
The impact of inter-annual rainfall variability on African savannas changes with mean rainfall
(2018)
Savannas are mixed tree-grass ecosystems whose dynamics are predominantly regulated by resource competition and the temporal variability in climatic and environmental factors such as rainfall and fire. Hence, increasing inter-annual rainfall variability due to climate change could have a significant impact on savannas. To investigate this, we used an ecohydrological model of stochastic differential equations and simulated African savanna dynamics along a gradient of mean annual rainfall (520–780 mm/year) for a range of inter-annual rainfall variabilities. Our simulations produced alternative states of grassland and savanna across the mean rainfall gradient. Increasing inter-annual variability had a negative effect on the savanna state under dry conditions (520 mm/year), and a positive effect under moister conditions (580–780 mm/year). The former resulted from the net negative effect of dry and wet extremes on trees. In semi-arid conditions (520 mm/year), dry extremes caused a loss of tree cover, which could not be recovered during wet extremes because of strong resource competition and the increased frequency of fires. At high mean rainfall (780 mm/year), increased variability enhanced savanna resilience. Here, resources were no longer limiting and the slow tree dynamics buffered against variability by maintaining a stable population during ‘dry’ extremes, providing the basis for growth during wet extremes. Simultaneously, high rainfall years had a weak marginal benefit on grass cover due to density-regulation and grazing. Our results suggest that the effects of the slow tree and fast grass dynamics on tree-grass interactions will become a major determinant of the savanna vegetation composition with increasing rainfall variability.
Dry lands are exposed to a highly variable environment and face a high risk of degradation. The effects of climate change are likely to increase this risk; thus a profound knowledge of the system dynamics is crucial for evaluating management options. This applies particularly for the interactions between water and vegetation, which exhibit strong feedbacks. To evaluate these feedbacks and the effects of climate change on soil moisture dynamics, we developed a generic, process-based, spatially explicit soil moisture model of two soil layers, which can be coupled with vegetation models. A time scale relevant for ecological processes can be simulated without difficulty, and the model avoids complex parameterization with data that are unavailable for most regions of the world. We applied the model to four sites in Israel along a precipitation and soil type gradient and assessed the effects of climate change by comparing possible climatic changes with present climate conditions. The results show that in addition to temperature, the total amount of precipitation and its intra-annual variability are an important driver of soil moisture patterns. This indicates that particularly with regard to climate change, the approach of many ecological models that simulate water dynamics on an annual base is far too simple to make reliable predictions. Thus, the introduced model can serve as a valuable tool to improve present ecological models of dry lands because of its focus on the applicability and transferability.
1. The complex, nonlinear response of dryland systems to grazing and climatic variations is a challenge to management of these lands. Predicted climatic changes will impact the desertification of drylands under domestic livestock production. Consequently, there is an urgent need to understand the response of drylands to grazing under climate change. 2. We enhanced and parameterized an ecohydrological savanna model to assess the impacts of a range of climate change scenarios on the response of a semi-arid African savanna to grazing. We focused on the effects of temperature and CO2 level increase in combination with changes in inter- and intra-annual precipitation patterns on the long-term dynamics of three major plant functional types. 3. We found that the capacity of the savanna to sustain livestock grazing was strongly influenced by climate change. Increased mean annual precipitation and changes in intra-annual precipitation pattern have the potential to slightly increase carrying capacities of the system. In contrast, decreased precipitation, higher interannual variation and temperature increase are leading to a severe decline of carrying capacities owing to losses of the perennial grass biomass. 4. Semi-arid rangelands will be at lower risk of shrub encroachment and encroachment will be less intense under future climatic conditions. This finding holds in spite of elevated levels of atmospheric CO2 and irrespective of changes in precipitation pattern, because of the drought sensitivity of germination and establishment of encroaching species. 5. Synthesis and applications. Changes in livestock carrying capacities, both positive and negative, mainly depend on the highly uncertain future rainfall conditions. However, independent of the specific changes, shrub encroachment becomes less likely and in many cases less severe. Thus, managers of semi-arid rangelands should shift their focus from woody vegetation towards perennial grass species as indicators for rangeland degradation. Furthermore, the resulting reduced competition from woody vegetation has the potential to facilitate ecosystem restoration measures such as re-introduction of desirable plant species that are only little promising or infeasible under current climatic conditions. On a global scale, the reductions in standing biomass resulting from altered degradation dynamics of semi-arid rangelands can have negative impacts on carbon sequestration.
Ecohydrology analyses the interactions of biotic and abiotic aspects of our ecosystems and landscapes. It is a highly diverse discipline in terms of its thematic and methodical research foci. This article gives an overview of current German ecohydrological research approaches within plant-animal-soil-systems, meso-scale catchments and their river networks, lake systems, coastal areas and tidal rivers. It discusses their relevant spatial and temporal process scales and different types of interactions and feedback dynamics between hydrological and biotic processes and patterns. The following topics are considered key challenges: innovative analysis of the interdisciplinary scale continuum, development of dynamically coupled model systems, integrated monitoring of coupled processes at the interface and transition from basic to applied ecohydrological science to develop sustainable water and land resource management strategies under regional and global change.