• Energy Research

AbstractDue to higher oil prices, abundance of labor and suitable land and its stable political climate, Tanzania attracted many investments in Jatropha. Although several studies on Jatropha's economic potential are available, its true economics are still uncertain. This paper aims to add to the growing body of knowledge on the socio‐economic performance of the Jatropha system by (i) studying the economic potential (net present value – NPV) of the current most prevailing Jatropha system for Tanzanian farmers and its regional differences, by (ii) making a greenhouse gas (GHG) balance and its economic value of the Jatropha activities on regional level, and by (iii) calculating break‐even thresholds for yield and seed price. Therefore, regional yield modeling, regional life‐cycle assessment, and NPV calculations based on Monte Carlo simulations, each with its set of assumptions, are combined. This study shows positive economic potential of Jatropha cultivation in most of the Tanzanian regions. However, the results also show that 13 of 20 Tanzanian regions will not attain a net positive GHG balance within 10 years. This indicates that the environmental impacts might be more restrictive for Jatropha's sustainability potential in Tanzania than the socio‐economic potential. These results are based on the combination of three models, which consists of strong interdisciplinary modeling work. However, this modeling also contains simplifications (e.g., no opportunity cost for ‘marginal’ land) and uncertainties (e.g., using globally modeled potential yield estimations), which have to be considered in the interpretation of the results.

Climate change is projected to impact on biodiversity conservation and the effectiveness of the existing protected area network in biologically rich Yunnan Province of southwestern China. A statistically derived bioclimatic stratification is used to analyze projected bioclimatic conditions across Yunnan by the year 2050. The multi-model approach is based on an ensemble of CIMP5 Earth System Models, down-scaled to a set of 1 km(2) resolution climate projections (n = 63), covering four representative concentration pathways (RCP). Nine bioclimatic zones, composed of 33 strata, are currently found within Yunnan. By 2050, the mean elevation of these zones is projected to shift upwards by an average of 269 m, with large increases in area of the warmer zones, and decreases in the colder, higher elevation zones. Temperate and alpine areas of high biodiversity value are at risk. Displacement in the geographic distribution of bioclimatic conditions is likely to have substantial impact across all bioclimatic zones, vegetation types, and habitats currently found in Yunnan. On average, across all RCPs, 45% of the total combined area of the protected area network will shift to a completely different zone, with 83% shifting to a different strata. The great majority of protected area will experience substantially changed, spatially shifted, and novel bioclimatic conditions by 2050. The spatial displacement and upwards shifting of bioclimatic conditions indicates a prolonged period of significant ecological perturbation, which will have a major impact upon the conservation effectiveness of the established protected area network, and other conservation efforts across Yunnan. (C) 2015 Elsevier Ltd. All rights reserved.

Division Forest, Nature and Landscape, Katholieke Universiteit Leuven, Celestijnenlaan 200E-2411, BE-3001 Leuven, Belgium Centre for International Forestry Research, P.O. Box 0113 BOCBD, Bogor 16000, Indonesia Division Agricultural and Food Economics, Katholieke Universiteit Leuven, Celestijnenlaan 200E-2411, BE-3001 Leuven, Belgium World Agroforestry Centre (ICRAF), Regional Office South Asia, Pusa Campus, New Delhi, India

The Mediterranean basin has been identified as a prominent hotspot of climate change, with expected negative impacts on crop productivity, among others. Given the primary role that agriculture has to sustain cultural values, economic opportunities, and food security, it is crucial to identify specific risks in agriculture due to climate change, which can address more effective adaptation strategies and policies to cope with climate change. This study aims to evaluate the high-resolution impacts of climate change on the length of the growing cycle and yield of durum wheat, common wheat, and maize in Italy by using the CERES-Wheat and CERES-Maize crop models implemented in the Decision Support System for Agrotechnology Transfer (DSSAT) software. A digital platform (GIS-DSSAT) was developed to couple crop simulation models with dynamically downscaled climate projections at high resolution for Italy, which can better represent the Italian landscape complexity and the spatial distribution of different pedological and crop management features, providing more detailed information on the expected impacts on crops respect to previous studies at a coarser resolution. The projections have been extended for two climate change scenarios and accounting for uncertainty, either considering or not the potential direct effects of increasing atmospheric CO2 concentrations ([CO2]). Results show that climate change may affect Italian cereal production in the medium to long term periods. Maize is the main affected crop, with yield reductions homogeneously distributed from North to South Italy. Wheat yield is expected to decrease mainly in southern Italy, while northern Italy may benefit from higher precipitation regimes. Higher levels of atmospheric CO2 concentrations may partially offset the negative impact posed by climate change and increase the benefits in the northern regions, especially for common and durum wheat.

[Context] Climate change is considered an important factor affecting the distribution and genetic diversity of species. While many studies have described the influence of climate change on population structure at various scales, little is known about the genetic consequences of a changing climate on endemic species. [Objectives] To assess possible changes in the distribution and genetic structure of the endangered Nilgiri tahr (Nilgiritragus hylocrius), which is endemic to the Western Ghats in India, under climate change and human disturbances. [Methods] We integrated tahr occurrence and nuclear DNA data with environmental geo-datasets to project the response of tahr populations to future climate change with respect to its distribution, genetic diversity and population structure. We screened the environmental variables using MaxEnt to identify a manageable set of predictors to be used in an ensemble approach, based on ten species distribution modelling techniques, to quantify the current tahr distribution. We then projected the distribution and genetic structure under two climate change scenarios. [Results] We found that suitable habitat for tahr (9,605 km2) is determined predominantly by a combination of climatic, human disturbance and topographic factors that result in a highly fragmented habitat throughout its distribution range in the Western Ghats. Under the severe high emissions RCP8.5 scenario tahr populations may lose more than half of their available habitat (55.5%) by 2070. Application of spatial Bayesian clustering suggests that their current genetic structure comprise four genetic clusters, with three of them reflecting a clear geographic structure. However, under climate change, two of these clusters may be lost, and in the future a homogenization of the genetic background of the remaining populations may arise due to prevalence of one gene pool cluster in the remaining populations. [Conclusions] Our interdisciplinary approach that combines niche modelling and genetic data identified the climate refugia (i.e., the remaining stable habitats that overlap with the current suitable areas), where the tahr populations would be restricted to small, isolated and fragmented areas. Essential factors to avert local extinctions of vulnerable tahr populations are a reduction of human disturbances, dispersal of tahr between fragmented populations, and the availability of corridors. This research was supported by the Department of Biotechnology, Ministry of Science and Technology, Government of India, and by a German Research Foundation (DFG) fellowship awarded to RK (project number 273837911). Peer reviewed

Climate change in Mediterranean countries is anticipated to have a strong impact on water availability by exacerbating drought conditions and water scarcity. In this context, efficient irrigation practices are becoming essential for sustaining crop production. This work assesses vulnerability of irrigated agriculture for six irrigation districts and their associated reservoirs in Mediterranean areas across Italy under climate change (1976–2005 versus 2036–2065; RCP 4.5 and 8.5), evaluating changes in irrigation requirements, evaporation from reservoirs, and the availability of freshwater supplies. Irrigation requirements are estimated through a crop water model (SIMETAW_R) integrated into a GIS platform, while inflows to reservoirs are hydrologically modelled as partitioning of precipitation contributing to runoff. Results are aggregated into indicators that show the general decreasing resilience and increasing vulnerability of irrigated agriculture under climate change conditions in each case study. The highest percentage of allowable water losses for irrigation is estimated in the Cuga-Alto Temo system, during the prolonged drought period, to be able to satisfy irrigation demand for less than a year. Climate change may only partially affect irrigation in resilient systems, in which storage capacity and the water level entering into the reservoir are considerably higher than the water distribution volumes.

Abstract How functional traits at community level relate with environmental conditions is of great relevance to assess potential effects of climate change on ecosystem functioning. Species’ specific leaf area (SLA) is well recognised to be closely correlated with species drought resistance and with other forest functions such as productivity. Here, we used tree species abundance data from 44 501 forest plots from the Third Spanish National Forest Inventory and species SLA values from literature to assess how community weighted mean SLA (CWM SLA ) and SLA diversity within communities (FDis SLA ) of Spanish forests correlate with aridity. Later, using 19 climate change projections and following an approach that limits the values of CWM SLA along an aridity gradient, we assessed the potential climatic effects on CWM SLA for 2050 under the representative concentration pathways (RCP) 4.5 and 8.5. Results showed that CWM SLA and FDis SLA decreased significantly with aridity (deviance explained was 22 and 9%, respectively) suggesting an effect of climatic filtering at community level constraining the diversity of co-occurring strategies at harsher conditions. Up to 25% of plots were predicted to suffer changes in CWM SLA with these impacts being more common and of a greater magnitude in communities characterised by a high CWM SLA and located at humid and mid-altitude zones. Instead, communities already striving in arid areas appeared to be more resilient. The study proves useful for orienting forest management practices in current permanent forest stands based on trait ecology (e.g. promoting communities species composition with specific trait values), to increase their mitigation potential and adaptive capacity to current and future changing climate conditions.