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Shrub encroachment linked to heavy grazing has dramatically changed savanna landscapes, and is a major form of rangeland degradation. Our understanding of how shrub encroachment affects arthropod communities is poor, however. Here, we investigate the effects of shrub encroachment on abundance and diversity of ground-dwelling (wingless) arthropods at varying levels of shrub cover in the southern Kalahari. We also ascertain if invertebrate assemblage composition changes with habitat structure and identify which aspects of habitat structure (e.g., grass cover, herbaceous plant cover, shrub density) correlate most strongly with these changes. Ant, scorpion and dung beetle abundance increased with shrub cover, whereas grasshoppers and solifuges declined. Spider and beetle abundance exhibited hump-shaped relationships with shrub cover. RTU richness within orders either mirrored abundances, or exhibited no trend. Shrub density was the habitat component most correlated with similarities between invertebrate assemblages. Ground-dwelling arthropods showed clear shifts in species assemblage composition at a similarity level of 65% according to shrub density. Changes in indicator species showed that within the Tenebrionidae (darkling beetles), certain species respond positively to shrub thickening, replacing other species within the Family. Small-bodied, wingless Scarabaeidae (dung beetles) tended to increase with increased shrub density and three species emerged as significant indicators of more thickened habitats, although this might be a response to greater dung availability, rather than habitat structure itself. We conclude that because ground- dwelling invertebrates showed such clear responses in species assemblage composition, they present excellent candidates for use as indicator species in further studies into bush encroachment.
Improving our understanding of biodiversity and ecosystem functioning and our capacity to inform ecosystem management requires an integrated framework for functional biodiversity research (FBR). However, adequate integration among empirical approaches (monitoring and experimental) and modelling has rarely been achieved in FBR. We offer an appraisal of the issues involved and chart a course towards enhanced integration. A major element of this path is the joint orientation towards the continuous refinement of a theoretical framework for FBR that links theory testing and generalization with applied research oriented towards the conservation of biodiversity and ecosystem functioning. We further emphasize existing decision-making frameworks as suitable instruments to practically merge these different aims of FBR and bring them into application. This integrated framework requires joint research planning, and should improve communication and stimulate collaboration between modellers and empiricists, thereby overcoming existing reservations and prejudices. The implementation of this integrative research agenda for FBR requires an adaptation in most national and international funding schemes in order to accommodate such joint teams and their more complex structures and data needs.
While several empirical and theoretical studies have clearly shown the negative effects of climate or landscape changes on population and species survival only few of them addressed combined and correlated consequences of these key environmental drivers. This also includes positive landscape changes such as active habitat management and restoration to buffer the negative effects of deteriorating climatic conditions. In this study, we apply a conceptual spatial modelling approach based on functional types to explore the effects of both positive and negative correlations between changes in habitat and climate conditions on the survival of spatially structured populations. We test the effect of different climate and landscape change scenarios on four different functional types that represent a broad spectrum of species characterised by their landscape level carrying capacity, the local population turnover rates at the patch level (K-strategies vs. r-strategies) and dispersal characterstics. As expected, simulation results show that correlated landscape and climatic changes can accelerate (in case of habitat loss or degradation) or slow down (in case of habitat gain or improvement) regional species extinction. However, the strength of the combined changes depends on local turnover at the patch level, the overall landscape capacity of the species, and its specific dispersal characteristics. Under all scenarios of correlated changes in habitat and climate conditions we found the highest sensitivity for functional types representing species with a low landscape capacity but a high population growth rate and a strong density regulation causing a high turnover at the local patch level.
The relative importance of habitat loss or habitat degradation, in combination with climate deterioration, differed among the functional types. However, an increase in regional capacity revealed a similar response pattern: For all types, habitat improvement led to higher survival times than habitat gain, i.e. the establishment of new habitat patches. This suggests that improving local habitat quality at a regional scale is a more promising conservation strategy under climate change than implementing new habitat patches. This conceptual modelling study provides a general framework to better understand and support the management of populations prone to complex environmental changes.
To assess the ecological and economic implications of the redistributive land reform in semi-arid Namibia, we investigated to what extent land reform beneficiaries adjust herd size and herd composition according to environmental (rainfall, vegetation) and economic variables (herd size, financial assets, running costs). We performed model-based role-plays with Namibian land reform beneficiaries, simulating 10 years of rangeland management.
Our study revealed that the farmers surveyed mainly manage their herds according to their economic situation (herd size and account balance) but do not take environmental variability (rainfall and vegetation) into account. Further, our results indicate that, due to financial pressure, farmers are not able to apply their desired management strategies, and that owners of small farms face a higher risk of economic failure. However, farmers apply rather conservative and constant stocking rates and will thus, given the current economic limitations, likely not contribute to semi-arid savanna degradation.
We conclude that land reform beneficiaries need support to be able to apply straightforward and efficient management strategies. This could be achieved by facilitating cooperation between small farming businesses and by supporting initial investment in productive cattle herds at the time of redistribution of the land.
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.
Savanna rangelands worldwide are threatened by shrub encroachment, i.e. the increase of woody plant species at the cost of perennial grasses, causing a strong decline in the productivity of domestic livestock production. Although recent studies indicate that fire might be of great importance for semi-arid and arid savanna dynamics, it is largely not applied in the management of semi-arid rangelands especially with regard to woody plant control. We used the eco-hydrological savanna model EcoHyD to simulate the effects of different fire management strategies on semi-arid savanna vegetation and to assess their longterm suitability for semi-arid rangeland management. Simulation results show that prescribed fires, timed to kill tree seedlings prevented shrub encroachment for a broad range of livestock densities while the possible maximum long-term cattle densities on the simulated semi-arid rangeland in Namibia increased by more than 30%. However, when grazing intensity was too high, fire management failed in preventing shrub encroachment.
Our findings indicate that with regard to fire management a clear distinction between mesic and more arid savannas is necessary: While the frequency of fires is of relevance for mesic savannas, we recommend a fire management focussing on the timing of fire for semi-arid and arid savannas. (C) 2014 Elsevier Ltd. All rights reserved.
The abandonment of military areas leads to succession processes affecting valuable open-land habitats and is considered to be a major threat for European butterflies. We assessed the ability of hyper spectral remote sensing data to spatially predict the occurrence of one of the most endangered butterfly species (Hipparchia statilinus) in Brandenburg (Germany) on the basis of habitat characteristics at a former military training area. Presence-absence data were sampled on a total area of 36 km(2), and N = 65 adult individuals of Hipparchia statilinus could be detected. The floristic composition within the study area was modeled in a three-dimensional ordination space. Occurrence probabilities for the target species were predicted as niches between ordinated floristic gradients by using Regression Kriging of Indicators. Habitat variance could be explained by up to 81 % with spectral variables at a spatial resolution of 2 x 2 m by transferring PLSR models to imagery. Ordinated ecological niche of Hipparchia statilinus was tested against environmental predictor variables. N = 6 variables could be detected to be significantly correlated with habitat preferences of Hipparchia statilinus. They show that Hipparchia statilinus can serve as a valuable indicator for the evaluation of the conservation status of Natura 2000 habitat type 2330 (inland dunes with open Corynephorus and Agrostis grasslands) protected by the Habitat Directive (Council Directive 92/43/EEC). The authors of this approach, conducted in August 2013 at Doberitzer Heide Germany, aim to increase the value of remote sensing as an important tool for questions of biodiversity research and conservation.
Military areas are valuable habitats and refuges for rare and endangered plants and animals. We developed a new approach applying innovative methods of hyperspectral remote sensing to bridge the existing gap between remote sensing technology and the demands of the nature conservation community. Remote sensing has already proven to be a valuable monitoring instrument. However, the approaches lack the consideration of the demands of applied nature conservation which includes the legal demands of the EU Habitat Directive. Following the idea of the Vital Signs Monitoring in the USA, we identified a subset of the highest priority monitoring indicators for our study area. We analyzed continuous spectral response curves and tested the measurability of N=19 indicators on the basis of complexity levels aggregated from extensive vegetation assemblages. The spectral differentiability for the floristic as well as faunistic indicators revealed values up to 100% accuracy. We point out difficulties when it comes to distinguishing faunistic habitat requirements of several species adapted to dry open landscapes, which in this case results in OVERALL ACCURACY of 67, 87-95, and 35% in the error matrix. In summary, we provide an applicable and feasible method to facilitating monitoring military areas by hyperspectral remote sensing in the following. (C) 2014 Elsevier Ltd. All rights reserved.
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.