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Vulnerability assessment is increasingly recognised as a starting point to identify climate adaptation needs and improve adaptive capacity. However, vulnerability assessments are challenging because of the complexity of multifaceted biophysical, human and institutional factors, interacting at different scales and levels within socio-ecological systems. Using a participatory approach across levels and genders, this paper explores the vulnerability of livestock- and forest-based livelihoods to climate variability and change in Lake Faguibine, northern Mali, where drastic ecological, political and social changes have occurred. Our results show that the distribution of vulnerabilities within livelihoods and groups shifted when the ecosystem evolved from a lake to a forest. New vulnerability drivers have emerged, related to resources availability, access and power relations. In addition, political interests and psychological barriers hinder the local transition to an equitable and sustainable use of forest ecosystem services. Divergent perceptions, social identities, interests and power explained why different actors—governmental and non-governmental, men and women, local, sub-national and national—differed in their vulnerability assessments. This is exemplified in the way actors at different levels and of different gender analysed the effects of herders’ mobility and in the way women analysed men’s migration. This case study confirms the need for participatory and gender-sensitive vulnerability assessments across different scales and levels that consider the interaction between socio-ecological systems and the dynamics and distribution of vulnerability across different social sub-systems.

Mali is a Sahelian country with a large climatic contrast from North to South. The current climatic and production evolutionary study is focused on the six major agro-climatic cereal production zones ranging from Kayes (400 mm) to Sikasso (>1000 mm) of rainfalls. Climatic data are rainfall records, daily maximum and minimum temperatures from 60 years of the six major synoptic weather observation stations. Data were analyzed on comparing average decades of the two normal periods of 30 years (1951-1980) and (1981-2010). Annual agronomic production data for millet, sorghum, maize and rice are derived from Mali's agricultural statistics base from 1984 to 2013. Main climatic results analyses indicate that climate change resulted in a decrease of 100 mm isohyets between the 2 periods of 30 years. The structure of the rainy season was little changed between these two periods since the average start of the season was delayed by 6 days and the average end date of the season became earlier by 4 days. Maximum temperatures increased significantly from + 0.44°C to + 1.53°C and minimum temperatures significantly increased from + 1.05°C to + 1.93°C in varying way depending on the sites. Statistics of major agronomic food crop production in Mali from 1984 to 2013 indicate an average increase of 985 to 4492 thousand tones, or 22% increase per year. There is a positive upward in saw tooth trend in Malian production from 1984 to 2013. This positive trend is the result of a combination of agricultural extension, agronomic research application and the management of small farmer holder in the Sahel. This evolution needs better study for drawing necessary right conclusions.

AbstractRice is the most important food crop in the developing world. For rice production systems to address the challenges of increasing demand and climate change, potential and on‐farm yield increases must be increased. Breeding is one of the main strategies toward such aim. Here, we hypothesize that climatic and atmospheric changes for the upland rice growing period in central Brazil are likely to alter environment groupings and drought stress patterns by 2050, leading to changing breeding targets during the 21st century. As a result of changes in drought stress frequency and intensity, we found reductions in productivity in the range of 200–600 kg/ha (up to 20%) and reductions in yield stability throughout virtually the entire upland rice growing area (except for the southeast). In the face of these changes, our crop simulation analysis suggests that the current strategy of the breeding program, which aims at achieving wide adaptation, should be adjusted. Based on the results for current and future climates, a weighted selection strategy for the three environmental groups that characterize the region is suggested. For the highly favorable environment (HFE, 36%–41% growing area, depending on RCP), selection should be done under both stress‐free and terminal stress conditions; for the favorable environment (FE, 27%–40%), selection should aim at testing under reproductive and terminal stress, and for the least favorable environment (LFE, 23%–27%), selection should be conducted for response to reproductive stress only and for the joint occurrence of reproductive and terminal stress. Even though there are differences in timing, it is noteworthy that stress levels are similar across environments, with 40%–60% of crop water demand unsatisfied. Efficient crop improvement targeted toward adaptive traits for drought tolerance will enhance upland rice crop system resilience under climate change.

Agroforestry systems (AFS) are complex to model mainly due to the high spatial variability induced by the shade trees. Recently, the microclimate and lighf heterogeneity issue in AFS has been addressed using the 30 ecophysiological process-based model MAESPA (Charbonnier et al., 2013; Vezy et al., 2018). MAESPA surpassed the classical sun/shade dichotomy in AFS (Charbonnier et al., 2014) and provided continuous maps of e.g. available light, light-use~ fficiency and canopy temperature within Coffea Agroforestry Systems (GAS). A step further was to design a crop model for Coffea grown under agroforestry that would benefit from this continuum to estimate ecosystem services on the long term and under climate change scenarios. We designed DynA_Cof, a new process-based growth and yield model to compute plot-scale net and gross primary productivity, carbon allocation, growth, yield, energy, and water balance of GAS according to shade tree species and management, while accounting for fine-scale spatial effects using MAESPA metamodels (Figure 1). DynA_Cof satisfactorily simulated the daily plot-scale gross primary productivity (RMSE= 1.69 gc m-2 d-1 on 1562 days) and the energy and water balances (RMSE: AET = 0.63 mm d-1 , H= 1.27 MJ m-2 d-1, Rn= 1.98 MJ m-2 d-1) compared to measurements from an eddy-flux tower in Aquiares (Costa Rica) and also the NPP for above and below-ground organs, coffee bean yield and shade tree wood production compared to a comprehensive database from this site.

West Nile virus (WNV) is transmitted by mosquitoes in both urban as well as in rural environments and can be pathogenic in birds, horses and humans. Extrinsic factors such as temperature and land use are determinants of WNV outbreaks in Europe, along with intrinsic factors of the vector and virus.With a multivariate model for WNV transmission we computed the probability of WNV infection in 2014, with July 2014 temperature anomalies. We applied the July temperature anomalies under the balanced A1B climate change scenario (mix of all energy sources, fossil and non-fossil) for 2025 and 2050 to model and project the risk of WNV infection in the future. Since asymptomatic infections are common in humans (which can result in the contamination of the donated blood) we estimated the predictive prevalence of WNV infections in the blood donor population.External validation of the probability model with 2014 cases indicated good prediction, based on an Area Under Curve (AUC) of 0.871 (SD = 0.032), on the Receiver Operating Characteristic Curve (ROC). The climate change projections for 2025 reveal a higher probability of WNV infection particularly at the edges of the current transmission areas (for example in Eastern Croatia, Northeastern and Northwestern Turkey) and an even further expansion in 2050. The prevalence of infection in (blood donor) populations in the outbreak-affected districts is expected to expand in the future.Predictive modelling of environmental and climatic drivers of WNV can be a valuable tool for public health practice. It can help delineate districts at risk for future transmission. These areas can be subjected to integrated disease and vector surveillance, outreach to the public and health care providers, implementation of personal protective measures, screening of blood donors, and vector abatement activities.

Earthworm distribution in global soils Earthworms are key components of soil ecological communities, performing vital functions in decomposition and nutrient cycling through ecosystems. Using data from more than 7000 sites, Phillips et al. developed global maps of the distribution of earthworm diversity, abundance, and biomass (see the Perspective by Fierer). The patterns differ from those typically found in aboveground taxa; there are peaks of diversity and abundance in the mid-latitude regions and peaks of biomass in the tropics. Climate variables strongly influence these patterns, and changes are likely to have cascading effects on other soil organisms and wider ecosystem functions. Science , this issue p. 480 ; see also p. 425