• Energy Research
• 13. Climate action close
• EU close
• University of Cambridge close

AbstractChanges in land‐use and climate affect the distribution and diversity of plant and animal species at different spatiotemporal scales. The extent to which species‐specific phenotypic plasticity and biotic interactions mediate organismal adaptation to changing environments, however, remains poorly understood. Woody plant expansion is threatening the extent of alpine grasslands worldwide, and evaluating and predicting its effects on herbivores is of crucial importance. Here, we explore the impact of shrubification on the feeding efficiency of Pyrenean chamois (Rupicapra p. pyrenaica), as well as on the three most abundant coexisting domestic ungulate species: cattle, sheep and horses. We use observational diet composition from May to October and model different scenarios of vegetation availability where shrubland and woodland proliferate at the expense of grassland. We then predicted if the four ungulate species could efficiently utilize their food landscapes with their current dietary specificities measuring their niche breath in each scenario. We observed that the wild counterpart, due to a higher trophic plasticity, is less disturbed by shrubification compared to livestock, which rely primarily on herbaceous plants and will be affected 3.6 times more. Our results suggest that mixed feeders, such as chamois, could benefit from fallow landscapes, and that mountain farmers are at a growing economic risk worldwide due to changing land‐use practices and climate conditions.

Variation in weather patterns can influence reproductive effort and success not only within but also between breeding seasons. Where environmental conditions can be highly variable between years, the weather, and particularly extreme weather events such as heat waves and droughts, may exert a strong influence on reproductive effort (number of breeding attempts) and success (number of surviving young) from one breeding season to the next. We used a 15-year dataset for a cooperatively-breeding bird, the southern pied babbler Turdoides bicolor, to determine the impact of high temperatures and drought on reproductive effort and success. We tested the influence on reproductive effort and success of mean daily maximum air temperature and drought both within a breeding season, to determine the relative importance of current conditions, and during the previous breeding season, to determine the relative importance of compensatory effects in response to prior conditions. Reproductive effort and success were lower during breeding seasons characterised by drought, and higher in the breeding seasons that followed droughts, but were not predicted by mean daily maximum temperatures measured over the full length of the breeding season. We provide evidence of compensatory breeding following drought in a bird species endemic to a semi-arid ecosystem and suggest that compensatory mechanisms may be an important part of both long-term population persistence and post-drought population recovery.

Abstract Moderate or Intense Low-oxygen Dilution (MILD) combustion has drawn increasing attention as it allows to avoid the thermo-chemical conditions prone to the formation of pollutant species while ensuring high energy efficiency and fuel flexibility. MILD combustion is characterized by a strong competition between turbulent mixing and chemical kinetics so that turbulence-chemistry interactions are naturally strengthened and unsteady phenomena such as local extinction and re-ignition may occur. The underlying physical mechanisms are not fully understood yet and the validation of combustion models featuring enhanced predictive capabilities is required. Within this context, high-fidelity data from Direct Numerical Simulation (DNS) represent a great opportunity for the assessment and the validation of combustion closure formulations. In this study, the performance of the Partially Stirred Reactor (PaSR) combustion model in MILD conditions is a priori assessed on Direct Numerical Simulations (DNS) of turbulent combustion of MILD mixtures in a cubical domain. Modeled quantities of interest, such as heat release rate and reaction rates of major and minor species, are compared to the corresponding filtered quantities extracted from the DNS. Different submodels for the key model parameters, i.e., the chemical time scale τc and the mixing time scale τmix, are considered and their influence on the results is evaluated. The results show that the mixing time scale is the leading scale in the investigated cases. The best agreement with the DNS data regarding the prediction of heat release rate and chemical source terms is achieved by the PaSR model that employs a local dynamic approach for the estimation of the mixing time scale. An overestimation of the OH species source terms occurs in limited zones of the computational domain, characterized by low heat release rates.

Mitigating climate change will require innovation in energy technologies. Policy makers are faced with the question of how to promote this innovation, and whether to focus on a few technologies or to spread their bets. We present results on the extent to which public R&D might shape the future cost of energy technologies by 2030. We bring together three major expert elicitation efforts carried out by researchers at UMass Amherst, Harvard, and FEEM, covering nuclear, solar, Carbon Capture and Storage (CCS), bioelectricity, and biofuels. The results show experts believe that there will be cost reductions resulting from R&D and report median cost reductions around 20 % for most of the technologies at the R&D budgets considered. Although the improvements associated to solar and CCS R&D show some promise, the lack of consensus across studies, and the larger magnitude of the R&D investment involved in these technologies, calls for caution when defining what technologies would benefit the most from additional public R&D. In order to make R&D funding decisions to meet particular goals, such as mitigating climate change or improving energy security, or to estimate the social returns to R&D, policy makers need to combine the information provided in this study on cost reduction potentials with an analysis of the macroeconomic implications of these technological changes. We conclude with recommendations for future directions on energy expert elicitations.