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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.
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.