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In mountains, grasslands managed for livestock production sustain local economies, culture and identity. However, their future fodder production is highly uncertain under climate change: While an extended growing season may be beneficial, more frequent and intense summer droughts could also reduce fodder quantity and quality. Land use and land cover (LULC) changes are another major driver of grassland biomass production, but combined effects of future land use transitions and climate change are rarely quantified. We modelled combined climate and LULC scenarios for grassland production of the Maurienne Valley (French Alps) by 2085. We built a Bayesian Belief Network (BBN) from long-term grassland production monitoring data complemented with expert knowledge. We assessed the potential of two candidate adaptations, intensification as an incremental solution and silvopastoralism as a transformative solution to compensate combined impacts of two climate scenarios and three land use change scenarios. Total biomass production was far more sensitive to LULC than to climate scenarios. Production losses were largest under the conservation LULC scenario (−28% on average between 2020 and 2085), followed by the tourism development scenario (−7%) and the business-as-usual scenario (+3%). Climate change under representative concentration pathways (RCP) 8.5 altered the seasonality of production by increasing potential production from May to July while decreasing summer regrowth. Synthesis and applications: Changes in LULC are more decisive for global biomass production than climate change. However, under the most extreme climate change scenario (RCP8.5), the seasonal shift in production and increased interannual variability threaten the current grass-based protected designation of origin (PDO) production system. Only the intensification adaptation solution showed significant gains in total biomass production. Still, the silvopastoralism would require less investment compared to the

Sustainable harvest of wildlife is a major food security and conservation issue. In Africa, where wildlife is harvested mainly for subsistence, this remains a challenge. In this study, using waterbirds as model for natural resources, we assessed the sustainability of harvest through fishing bycatch on Lake Fitri (Chad). We estimated the abundance of 24 target taxa through aerial distance sampling over four consecutive years (2018–2021) and in parallel estimated the number of birds harvested through interviews of a sample of 105 out of approximately 5500 fishermen. By modelling their potential excess growth, we found a high risk of overexploitation for four species, including the world-threatened Black Crowned Crane Balearica pavonina, likely due to an influx of fishermen to Lake Fitri fleeing the Boko Haram security crisis. Synthesis and applications: This work is likely the first quantitative approach of bird harvest sustainability in Africa. It should contribute to fill a methodological and an information gap in the strategic planification of several multilateral environmental agreements like the African-Eurasian Waterbird Agreement and the Ramsar Convention. In particular, this work could help implementing adaptive management of natural resources (including birds) in Ramsar site management plans. African wetlands such as Lake Fitri may not be able to provide enough natural resources in the medium term for movements of displaced civilians forced by armed conflict into such biodiversity strongholds.

Evaluators widely utilize theory of change or impact pathway approaches to design and evaluate interventions. In research settings, there is increasing demand for ex ante impact pathways that are place-based, coherent, and plausible, in order to foster more impactful interventions. Foresight approaches, which enable a collaborative, structured, and systematic way to anticipate, prepare, and affect the course of change, can help achieve this by exploring diverse future scenarios, the consequences of different assumptions, or how to overcome threats and leverage opportunities for change. Through three case examples, we show how foresight tools used prior to developing impact pathways can free participants from preconceived notions of the intervention's context, actors, and impacts, and thus support creative and systemic analyses of the future to rethink the present. They extend the analysis of how different actors can shape the future, identifying effects that might otherwise be overlooked or marginalized during the planning and evaluation of the intervention, while also helping to identify the conditions necessary for desired impacts. Nonetheless, their use entails evaluative judgments about the potential impacts to be prioritized in intervention design and evaluation. This is especially relevant in the case of research where scientific or technical aspects are usually prioritized. Finally, there is an entry cost to foresight tools for evaluators, in particular for the facilitation of strategic thinking about the future. However, we recommend them as a worthwhile addition to the evaluator's toolbox to broaden the scope of design and evaluation.

BACKGROUND: Potato varieties have diverse biophysical characteristics, so it is important for breeders to have the capacity to choose those that meet the preferences of end users, such as mealiness, firmness, and taste, among others. Combining user preferences with descriptive information regarding the sensory characteristics of boiled potatoes can contribute to the improvement of consumer-driven varieties. This study aimed to factor in the preferences of end users to improve the prospects for varietal acceptance, adoption, and discrimination among genotypes in potato breeding. RESULTS: The priority quality traits (traits that play the most significant roles in acceptance and adoption) of the boiled potatoes were determined by evaluating gender and livelihood using the G+ tool. The G+ tool is designed to assess gender impact on roots, tubers and bananas (RTB) traits by serving as a validation check to reflect on important gender-based issues in agricultural food systems in order to reduce harm and promote positive impact. Potato genotypes were differentiated by penetration (textural parameters as measured by standard texture probe) and the procedure was repeatable, as there was no significant difference between the cooking replicates at 40 min of cooking. Instrument-based texture parameters, such as penetration peak force (hardness/firmness) and area (area under the curve, which represents energy needed to penetrate) of boiled potato tubers were significantly associated with sensory attributes such as fracturability and hardness in the mouth. An attempt to differentiate genotypes using near-infrared spectroscopy (NIRS) revealed that the average results observed for the calibration for yellow color (r2 = 0.70), homogeneity of color (r2 = 0.48), moisture in mass (r2 = 0.40), and uniformity of texture (r2 = 0.56) suggested that these parameters could be used for initial breeding screening purposes. CONCLUSIONS: The preferred traits of the boiled potato can be integrate

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high‐resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED‐2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED‐2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems.

An important part of conservation practice is the empirical evaluation of program and policy impacts. Understanding why conservation programs succeed or fail is essential for designing cost-effective initiatives and for improving the livelihoods of natural resource users. The evidence we seek can be generated with modern impact evaluation designs. Such designs measure causal effects of specific interventions by comparing outcomes with the interventions to outcomes in credible counterfactual scenarios. Good designs also identify the conditions under which the causal effect arises. Despite a critical need for empirical evidence, conservation science has been slow to adopt these impact evaluation designs. We identify reasons for the slow rate of adoption, and provide suggestions for mainstreaming impact evaluation in nature conservation.

Rift Valley fever (RVF) is a severe mosquito-borne disease affecting humans and domestic ruminants. RVF virus has been reported in most African countries, as well as in the Arabic Peninsula. This paper reviews the different types of socio-economic impact induced by RVF disease and the attempts to evaluate them. Of the 52 papers selected for this review, 13 types of socio-economic impact were identified according to the sector impacted, the level and temporal scale of the impact. RVF has a dramatic impact on producers and livestock industries, affecting public and animal health, food security and the livelihood of the pastoralist communities. RVF also has an impact on international trade and other agro-industries. The risk of introducing RVF into disease-free countries via the importation of an infected animal or mosquito is real, and the consequent restriction of access to export markets may induce dramatic economic consequences for national and local economies. Despite the important threat of RVF, few studies have been conducted to assess the socio-economic impact of the disease. The 17 studies identified for quantitative analysis in this review relied only on partial cost analysis, with limited reference to mid- and long-term impact, public health or risk mitigation measures. However, the estimated impacts were high (ranging from $5 to $470 million USD losses). To reduce the impact of RVF, early detection and rapid response should be implemented. Comprehensive disease impact studies are required to provide decision-makers with science-based information on the best intervention measure to implement ensuring efficient resource allocation. Through the analysis of RVF socio-economic impact, this scoping study proposes insights into the mechanisms underpinning its often-underestimated importance. This study highlights the need for comparative socio-economic studies to help decision-makers with their choices related to RVF disease management.

Anthropogenic deforestation in tropical countries is responsible for a significant part of global carbon dioxide emissions in the atmosphere. To plan efficient climate change mitigation programs (such as REDD+, Reducing Emissions from Deforestation and forest Degradation), reliable forecasts of deforestation and carbon dioxide emissions are necessary. Although population density has been recognized as a key factor in tropical deforestation, current methods of prediction do not allow the population explosion that is occurring in many tropical developing countries to be taken into account. Here, we propose an innovative approach using novel computational and statistical tools, including R/GRASS scripts and the new phcfM R package, to model the intensity and location of deforestation including the effect of population density. We used the model to forecast anthropogenic deforestation and carbon dioxide emissions in five large study areas in the humid and spiny-dry forests of Madagascar. Using our approach, we were able to demonstrate that the current rapid population growth in Madagascar (+3.39% per year) will significantly increase the intensity of deforestation by 2030 (up to +1.17% per year in densely populated areas). We estimated the carbon dioxide emissions associated with the loss of aboveground biomass to be of 2.24 and 0.26 tons per hectare and per year in the humid and spiny-dry forest, respectively. Our models showed better predictive ability than previous deforestation models (the figure of merit ranged from 10 to 23). We recommend this approach to reduce the uncertainty associated with deforestation forecasts. We also underline the risk of an increase in the speed of deforestation in the short term in tropical developing countries undergoing rapid population expansion.

Wildlife is a maintenance host for several significant livestock diseases. Interspecific pathogen transmission may occur in complex socio-ecological systems at wild-domestic interfaces that have so far been seldom studied. We investigated the relationship between the dynamics of foot and mouth disease (FMD) in vaccinated and unvaccinated cattle populations with respect to frequency of contacts with African buffalo at different buffalo-cattle interfaces. A total of 36 GPS collars were deployed on African buffalo (Syncerus caffer) and cattle (Bos taurus, Bos indicus) to assess contact patterns at the periphery of 3 protected areas in Zimbabwe. Simultaneously, a longitudinal survey of 300 cattle with five repeated sampling sessions on known individuals during 16 months was undertaken. Immunological assays (ELISAs), that allowed tracking the production of antibodies following infection or vaccination, were used to assess serological transitions (i.e., incidence and reversion) in the surveyed cattle. Variation in rates of serological transitions across seasons, sites and as a function of the frequency of contact with buffalo was analyzed using generalized linear mixed models. The incidence in the cattle populations of FMD antibodies produced following infection varied among sites and as a function of contact rates with African buffalo. The incidence was higher for sites with higher contact rates between the two species. The serological incidence was also related to seasons, being higher during the dry or rainy seasons depending on sites. The reversion rate pattern was the opposite of this incidence rate pattern. Vaccination seemed partly efficient at the individual level, but it did not prevent the diffusion of FMD viruses from the wild reservoir host to the domestic cattle population. Furthermore, antibodies were detected in areas where cattle had not been vaccinated, suggesting that the virus may have spread without being detected in domestic populations. Access to res