• Energy Research

AbstractSpatially explicit simulations of gene flow within complex landscapes could help forecast the responses of populations to global and anthropological changes. Simulating how past climate change shaped intraspecific genetic variation can provide a validation of models in anticipation of their use to predict future changes. We review simulation models that provide inferences on population genetic structure. Existing simulation models generally integrate complex demographic and genetic processes but are less focused on the landscape dynamics. In contrast to previous approaches integrating detailed demographic and genetic processes and only secondarily landscape dynamics, we present a model based on parsimonious biological mechanisms combining habitat suitability and cellular processes, applicable to complex landscapes. The simulation model takes as input (a) the species dispersal capacities as the main biological parameter, (b) the species habitat suitability, and (c) the landscape structure, modulating dispersal. Our model emphasizes the role of landscape features and their temporal dynamics in generating genetic differentiation among populations within species. We illustrate our model on caribou/reindeer populations sampled across the entire species distribution range in the Northern Hemisphere. We show that simulations over the past 21 kyr predict a population genetic structure that matches empirical data. This approach looking at the impact of historical landscape dynamics on intraspecific structure can be used to forecast population structure under climate change scenarios and evaluate how species range shifts might induce erosion of genetic variation within species.

AbstractTerrestrial ecosystems affect climate by reflecting solar irradiation, evaporative cooling, and carbon sequestration. Yet very little is known about how plant traits affect climate regulation processes (CRPs) in different habitat types. Here, we used linear and random forest models to relate the community‐weighted mean and variance values of 19 plant traits (summarized into eight trait axes) to the climate‐adjusted proportion of reflected solar irradiation, evapotranspiration, and net primary productivity across 36,630 grid cells at the European extent, classified into 10 types of forest, shrubland, and grassland habitats. We found that these trait axes were more tightly linked to log evapotranspiration (with an average of 6.2% explained variation) and the proportion of reflected solar irradiation (6.1%) than to net primary productivity (4.9%). The highest variation in CRPs was explained in forest and temperate shrubland habitats. Yet, the strength and direction of these relationships were strongly habitat‐dependent. We conclude that any spatial upscaling of the effects of plant communities on CRPs must consider the relative contribution of different habitat types.

AbstractThe European Alps are highly rich in species, but their future may be threatened by ongoing changes in human land use and climate. Here, we reconstructed vegetation, temperature, human impact and livestock over the past ~12,000 years from Lake Sulsseewli, based on sedimentary ancient plant and mammal DNA, pollen, spores, chironomids, and microcharcoal. We assembled a highly-complete local DNA reference library (PhyloAlps, 3923 plant taxa), and used this to obtain an exceptionally rich sedaDNA record of 366 plant taxa. Vegetation mainly responded to climate during the early Holocene, while human activity had an additional influence on vegetation from 6 ka onwards. Land-use shifted from episodic grazing during the Neolithic and Bronze Age to agropastoralism in the Middle Ages. Associated human deforestation allowed the coexistence of plant species typically found at different elevational belts, leading to levels of plant richness that characterise the current high diversity of this region. Our findings indicate a positive association between low intensity agropastoral activities and precipitation with the maintenance of the unique subalpine and alpine plant diversity of the European Alps.

At macroecological scales, the provision of Nature's contributions to people (NCP) is mostly estimated with biophysical information, ignoring the ecological processes underlying them. This hinders our ability to properly quantify the impact of declining biodiversity and the provision of NCP. Here, we propose a framework that combines local-scale food web energy flux approaches and large-scale biodiversity models to evaluate ecosystem functions and flux-related NCP at extensive spatiotemporal scales. Importantly, this approach has the potential to upscale ecosystem functions, assess the vulnerability of flux-related NCP to the climate crisis, and support the development of multiscale mitigation policies.

AbstractIdentifying climate refugia is key to effective biodiversity conservation under a changing climate, especially for mountain‐specialist species adapted to cold conditions and highly threatened by climate warming. We combined species distribution models (SDMs) with climate forecasts to identify climate refugia for high‐elevation bird species (Lagopus muta, Anthus spinoletta, Prunella collaris, Montifringilla nivalis) in the European Alps, where the ecological effects of climate changes are particularly evident and predicted to intensify. We considered future (2041–2070) conditions (SSP585 scenario, four climate models) and identified three types of refugia: (1) in‐situ refugia potentially suitable under both current and future climate conditions, ex‐situ refugia suitable (2) only in the future according to all future conditions, or (3) under at least three out of four future conditions. SDMs were based on a very large, high‐resolution occurrence dataset (2901–12,601 independent records for each species) collected by citizen scientists. SDMs were fitted using different algorithms, balancing statistical accuracy, ecological realism and predictive/extrapolation ability. We selected the most reliable ones based on consistency between training and testing data and extrapolation over distant areas. Future predictions revealed that all species (with the partial exception of A. spinoletta) will undergo a range contraction towards higher elevations, losing 17%–59% of their current range (larger losses in L. muta). We identified ~15,000 km2 of the Alpine region as in‐situ refugia for at least three species, of which 44% are currently designated as protected areas (PAs; 18%–66% among countries). Our findings highlight the usefulness of spatially accurate data collected by citizen scientists, and the importance of model testing by extrapolating over independent areas. Climate refugia, which are only partly included within the current PAs system, should be priority sites for the conservation of Alpine high‐elevation species and habitats, where habitat degradation/alteration by human activities should be prevented to ensure future suitability for alpine species.