• Energy Research
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Atmospheric concentrations of the greenhouse gas nitrous oxide (N(2)O) have increased significantly since pre-industrial times owing to anthropogenic perturbation of the global nitrogen cycle, with animal production being one of the main contributors. Grasslands cover about 20 per cent of the temperate land surface of the Earth and are widely used as pasture. It has been suggested that high animal stocking rates and the resulting elevated nitrogen input increase N(2)O emissions. Internationally agreed methods to upscale the effect of increased livestock numbers on N(2)O emissions are based directly on per capita nitrogen inputs. However, measurements of grassland N(2)O fluxes are often performed over short time periods, with low time resolution and mostly during the growing season. In consequence, our understanding of the daily and seasonal dynamics of grassland N(2)O fluxes remains limited. Here we report year-round N(2)O flux measurements with high and low temporal resolution at ten steppe grassland sites in Inner Mongolia, China. We show that short-lived pulses of N(2)O emission during spring thaw dominate the annual N(2)O budget at our study sites. The N(2)O emission pulses are highest in ungrazed steppe and decrease with increasing stocking rate, suggesting that grazing decreases rather than increases N(2)O emissions. Our results show that the stimulatory effect of higher stocking rates on nitrogen cycling and, hence, on N(2)O emission is more than offset by the effects of a parallel reduction in microbial biomass, inorganic nitrogen production and wintertime water retention. By neglecting these freeze-thaw interactions, existing approaches may have systematically overestimated N(2)O emissions over the last century for semi-arid, cool temperate grasslands by up to 72 per cent.

Weighting scheme definition represents an important step in assessment of adaptive capacity to climate change with indicator approach since it defines the trade-offs among indicators or components and can be source of uncertainty. This study aims to assess smallholder farmers' adaptive capacity to climate change by using a mixed weighting scheme that reflect farmers' perceived importance of adaptive capacity components to inform policy makers. To achieve that objective, the sustainable livelihood framework was adopted and indicator approach was used for the assessment. The mixed weighting scheme were defined by using both equal weights and experts judgement methods during the assessment process. The mixed weighting scheme index is compared to the case where equal weights are applied in the assessment process and an uncertainty analysis was performed on relative standard deviation through a Monte Carlo simulation. Primary Data were collected from 450 farmers in two communities in northern Benin with a structured questionnaire and through focus groups discussion. The results show that smallholder farmers in both communities do not have the same perceived importance of adaptive capacity components. The index scores show that farmers have in majority low adaptive capacity. When weighted product aggregation method is used, there is more uncertainty related to the index computed with the mixed weighting scheme, but it leads to the same characterisation when compared with the index computed with the equal weights. It is recommended that mixed weighting scheme should be preferred for the assessment of adaptive capacity and weighted product aggregation method should be used.

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.

Abstract Although wind power is a promising source of renewable energy, previous studies have focused on uncovering species and abundance decreases caused by wind farms. However, very few studies focus on collision risk of onshore wind farms in relation to birds’ movements which are the important indicators for balancing wind energy development and biodiversity conservation. Here, birds’ movement were recorded by combining 15 ducks’ satellite tracking and six field surveys to assess collision risks in Yangtze River Mouth, the wintering site for migratory waterbirds along the East Asian–Australasian Flyway. It is found that distances between ducks’ locations and nearest wind turbines in middle and later wintering periods were significantly higher than during early period. Besides, ducks inside wind farm tended to fly outside turbine rotor height range (45–135 m: between lowest and highest points the rotor tips) within 300 m from the dyke where the turbines were located, thus decreasing their collision risk. Ducks also tended to fly below the minimum rotor tip height (< 45 m) when the turbines were rotating. These results suggest that ducks adopt behavioural avoidance strategies in response to wind farms, and turning off turbines to reduce collision risks may be unnecessary.

This study deals with the flood-hazard assessment and mapping in the catchment of Megalo Rema (East Attica, Greece). Flood-hazard zones were identified utilizing Multi-Criteria Decision Analysis (MCDA) integrated with Geographic Information System (GIS). Five factors were considered as the most influential parameters for the water course when high storm-water runoff exceeds drainage system capacity and were taken into account. These factors include slope, elevation, distance from stream channels, geological formations in terms of their hydro-lithological behavior and land cover. To obtain the final weights for each factor, rules of the Analytic Hierarchy Process (AHP) were applied. The final flood-hazard assessment and mapping of the study area were produced through Weighted Linear Combination (WLC) procedures. The final map showed that approximately 26.3 km2, which corresponds to 22.7% of the total area of the catchment, belongs to the high flood risk zone, while approximately 25 km2, corresponding to ~15% of the catchment, is of very high flood risk. The highly and very highly prone to flooding areas are located mostly at the southern and western parts of the catchment. Furthermore, the areas on both sides of the channel along the lower reaches of the main stream are of high and very high risk. The highly and very highly prone to flooding areas are relatively low-lying, gently sloping and extensively urbanized, and host the densely populated settlements of Rafina-Pikermi, Penteli, Pallini, Peania, Spata, Glika Nera, Gerakas and Anthousa. The accuracy of the flood-hazard map was verified by correlating flood events of the last 30 years, the Hydrologic Engineering Center’s River Analysis System (HEC–RAS) simulation and quantitative geomorphological analysis with the flood-hazard level. The results of our approach provide decision makers with important information for land-use planning at a regional scale, determining safe and unsafe areas for urban development.

There are strong relationships between climate and ecosystems. With the prospect of anthropogenic forcing accelerating climate change, there is a need to understand how terrestrial vegetation responds to this change as it influences the carbon balance. Previous studies have primarily addressed this question using empirically based models relating the observed pattern of vegetation and climate, together with scenarios of potential future climate change, to predict how vegetation may redistribute. Unlike previous studies, here we use an advanced mechanistic, individually based, ecosystem model to predict the terrestrial vegetation response from future climate change. The use of such a model opens up opportunities to test with remote sensing data, and the possibility of simulating the transient response to climate change over large domains. The model was first run with a current climatology at half-degree resolution and compared to remote sensing data on dominant plant functional types for northern North America for validation. Future climate data were then used as inputs to predict the equilibrium response of vegetation in terms of dominant plant functional type and carbon redistribution. At the domain scale, total forest cover changed by ~2% and total carbon storage increased by ~8% in response to climate change. These domain level changes were the result of much larger gross changes within the domain. Evergreen forest cover decreased 48% and deciduous forest cover increased 77%. The dominant plant functional type changed on 58% of the sites, while total carbon in deciduous vegetation increased 107% and evergreen vegetation decreased 31%. The percent of terrestrial carbon from deciduous and evergreen plant functional types changed from 27%/73% under current climate conditions, to 54%/46% under future climate conditions. These large predicted changes in vegetation and carbon in response to future climate change are comparable to previous empirically based estimates, and motivate the need for future development with this mechanistic model to estimate the transient response to future climate changes.

This research looked at the state of soils faced with urbanization processes in the Arctic region of the Yamal-Nenets Autonomous District (YANAO). Soils recently used in agriculture, which are now included in the infrastructure of the cities of Salekhard, Labytnangi, Kharsaim, and Aksarka in the form of various parks and public gardens were studied. Morphological, physico-chemical, and agrochemical studies of selected soils were conducted. Significant differences in fertility parameters between urbanized abandoned agricultural soils and mature soils of the region were revealed. The quality of soil resources was also evaluated in terms of their ecotoxicology condition, namely, the concentrations of trace metals in soils were determined and their current condition was assessed using calculations of various individual and complex soil quality indices.

The conceptualization of the Shared Socioeconomic Pathways (SSPs) framework represented a major leap in scenario development in the context of global environmental change and sustainability, providing significant advances from the previous scenario frameworks-especially the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios. It is highly likely that the SSP concept, along with its scenario narratives and their respective results, including land-use change projections, will play a substantial role in the forthcoming Sixth Assessment Report by the IPCC. Here, we offer some insights that could make the SSPs' projected future changes in global land use more comprehensive and also help improve the interpretability of such projections. For example, instead of focusing on the quantity of each land-use class at various time points which results only in a net change when change is detected between time points, we recommend that the projected gross gains and gross losses in each land-use class across all scenarios should also be considered. Overall, the insights presented could also help pave the way for stronger collaboration between the SSP-climate science community and the land system science community; such collaboration is much needed in addressing the challenges of global environmental change towards a climate-resilient sustainable development pathway.