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SUMMARYThis article discusses how decentralisation policies are enacted in the planning and implementation of natural resource management interventions in rural Ethiopia. A key element of decentralisation policy is the emphasis on greater participation by local communities. Drawing on qualitative research conducted with government staff and farmers, this paper illustrates how different actors perceive and implement national policy and how these actions affect the longer‐term sustainability of land management interventions. Copyright © 2014 John Wiley & Sons, Ltd.

The basins of the Indus and Ganges rivers cover 2.20 million km2 and are inhabited by more than a billion people. The region is under extreme pressures of population and poverty, unregulated utilization of the resources and low levels of productivity. The needs are: (1) development policies that are regionally differentiated to ensure resource sustainability and high productivity; (2) immediate development and implementation of policies for sound groundwater management and energy use; (3) improvement of the fragile food security and to broaden its base; and (4) policy changes to address land fragmentation and improved infrastructure. Meeting these needs will help to improve productivity, reduce rural poverty and improve overall human development.

Land-use change and intensification play a key role in the current biodiversity crisis. The resulting species loss can have severe effects on ecosystem functions and services, thereby increasing ecosystem vulnerability to climate change. We explored whether land-use intensification (i.e. fertilization intensity), plant diversity and other potentially confounding environmental factors may be significantly related to water use (i.e. drought stress) of grassland plants. Drought stress was assessed using δ13C abundances in aboveground plant biomass of 150 grassland plots across a gradient of land-use intensity. Under water shortage, plants are forced to increasingly take up the heavier 13C due to closing stomata leading to an enrichment of 13C in biomass. Plants were sampled at the community level and for single species, which belong to three different functional groups (one grass, one herb, two legumes). Results show that plant diversity was significantly related to the δ13C signal in community, grass and legume biomass indicating that drought stress was lower under higher diversity, although this relation was not significant for the herb species under study. Fertilization, in turn, mostly increased drought stress as indicated by more positive δ13C values. This effect was mostly indirect by decreasing plant diversity. In line with these results, we found similar patterns in the δ13C signal of the organic matter in the topsoil, indicating a long history of these processes. Our study provided strong indication for a positive biodiversity-ecosystem functioning relationship with reduced drought stress at higher plant diversity. However, it also underlined a negative reinforcing situation: as land-use intensification decreases plant diversity in grasslands, this might subsequently increases drought sensitivity. Vice-versa, enhancing plant diversity in species-poor agricultural grasslands may moderate negative effects of future climate change.

The delta(34)S values of biological material, especially food commodities, serve as indicators for origin assignments. However, in the metabolism of higher plants sulfur isotope fractionations must be expected. As a matter of fact, the delta(34)S values of the sulfate- and organic-S, respectively, of Brassicaceae and Allium species vegetables showed differences between 3 and 6 per thousand, and differences in glucosinolates were between 0 and 14 per thousand. delta(34)S-value differences of total-S between individual tissues of the same plant were approximately 3 per thousand. It is believed that these relatively small and variable fractionations are due to the partition of individual S-metabolism steps to different plant compartments, where they may occur independently and quantitatively. The delta(34)S values of herbivore muscle meat and milk relative to the diet and between an animal and its child had trophic shifts of approximately 1.5 per thousand. (34)S enrichments of up to 4 per thousand were observed for hair, hooves, and horn, an isotope fractionation of -5 per thousand between the diet sulfate and cartilage. Therefore, the reported agreements between delta(34)S value of biomass and primary S sources are true for only bulk material and not for individual compounds or tissues.

This article illustrates the impact of potential future climate scenarios on water quantity in time and space for an East African floodplain catchment surrounded by mountainous areas. In East Africa, agricultural intensification is shifting from upland cultivation into the wetlands due to year-round water availability and fertile soils. These advantageous agricultural conditions might be hampered through climate change impacts. Additionally, water-related risks, like droughts and flooding events, are likely to increase. Hence, this study investigates future climate patterns and their impact on water resources in one production cluster in Tanzania. To account for these changes, a regional climate model ensemble of the Coordinated Regional Downscaling Experiment (CORDEX) Africa project was analyzed to investigate changes in climatic patterns until 2060, according to the RCP4.5 (representative concentration pathways) and RCP8.5 scenarios. The semi-distributed Soil and Water Assessment Tool (SWAT) was utilized to analyze the impacts on water resources according to all scenarios. Modeling results indicate increasing temperatures, especially in the hot dry season, intensifying the distinctive features of the dry and rainy season. This consequently aggravates hydrological extremes, such as more-pronounced flooding and decreasing low flows. Overall, annual averages of water yield and surface runoff increase up to 61.6% and 67.8%, respectively, within the bias-corrected scenario simulations, compared to the historical simulations. However, changes in precipitation among the analyzed scenarios vary between −8.3% and +22.5% of the annual averages. Hydrological modeling results also show heterogeneous spatial patterns inside the catchment. These spatio-temporal patterns indicate the possibility of an aggravation for severe floods in wet seasons, as well as an increasing drought risk in dry seasons across the scenario simulations. Apart from that, the discharge peak, which is crucial for the flood recession agriculture in the floodplain, is likely to shift from April to May from the 2020s onwards.

Anaerobic digestion is a technology which is used to produce methane from organic solids and energy crops. Especially in recent years, the fermentation of energy crops has become more and more important because of increasing costs for energy and special benefits for renewable energy sources in Germany. Anaerobic bacteria require macro and micro nutrients to grow. Absence of these elements can inhibit the anaerobic process significantly. In particular mono-substrates like maize or certain industrial wastewater often cannot provide all required nutrients. For this reason this research investigates the influence of substrate and trace elements on anaerobic digestion in detail. Different agricultural anaerobic biomasses are analysed with special regard to their trace element content. Based on these results, the influence of three trace elements (iron, cobalt, and nickel) on anaerobic digestion was studied in anaerobic batch tests at different sludge loading rates and for different substrates (maize and acetate). Biogas production was found to be 35% for maize silage and up to 70% higher for acetate with trace element dosage than in the reference reactor.

Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve.

Climate change is continuously intensifying droughts. Extreme droughts are expected to reduce soil water content and thus, ecosystem functioning such as above-ground primary productivity. Nonetheless, results of experimental drought studies vary from no impact to a significant decrease in soil water content and/or productivity. We experimentally imposed extreme drought as 30 % and 50 % precipitation reductions using rainout shelters for four years in temperate grasslands and in the forest understory. We studied the concurrent impact of two intensities of extreme drought on the soil water content and above-ground primary productivity in the last experimental year (resistance). Furthermore, we observed resilience as the extent to which both variables differ from ambient conditions after the removal of the 50 % reduction. We show a systematic difference in response to extreme experimental drought between grasslands and the forest understory irrespective of the intensity of the extreme drought. Namely, extreme drought resulted in a significant decrease of the soil water content and productivity in grasslands but not in the forest understory. Interestingly, the negative impacts in the grasslands did not persist as evidenced by the fact that soil water content and productivity were similar to ambient conditions after the removal of the drought. Our results indicate that extreme drought on small spatial scales does not necessarily result in a concurrent soil water decrease in the forest understory, while this is the case for grasslands, with respective consequences for the resistance of productivity. Grasslands, however, can be resilient. Our study highlights that considering the response of the soil water content is key to understanding divergent productivity responses to extreme drought among different ecosystems.