Species distribution models (SDMs) are statistical tools that relate species observations to environmental conditions to retrieve ecological niches and predict species' potential geographic ...distributions. The quality and robustness of SDMs clearly depend on good modelling practices including ascertaining the ecological relevance of predictors for the studied species and choosing an appropriate spatial resolution (or ‘grain size'). While past studies showed improved model performance with increasing resolution for sessile organisms, there is still no consensus regarding how inappropriate resolution of predictors can impede understanding and mapping of multiple facets of diversity. Here, we modelled the distribution of 1180 plant species across the European Alps for two sets of predictors (climate and soil) at resolutions ranging from 100‐m to 40‐km. We assessed predictors' importance for each resolution, calculated taxonomic (TD), relative phylogenetic (rPD) and functional diversity (rFD) accordingly, and compared the resulting diversities across space. In accordance with previous studies, we found the predictive performance to generally decrease with decreasing predictor resolution. Overall, multifaceted diversity was found to be strongly affected by resolution, particularly rPD, as exhibited by weak to average linear relationships between 100‐m and 1‐km resolutions (0.13 ≤ R2 ≤ 0.57). Our results demonstrate the necessity of using highly resolved predictors to explain and predict sessile species distributions, especially in mountain environments. Using coarser resolution predictors might cause multifaceted diversity to be strongly mispredicted, with important consequences for biodiversity management and conservation.
The Cretaceous breakup of Gondwana strongly modified the global distribution of shallow tropical seas reshaping the geographic configuration of marine basins. However, the links between tropical reef ...availability, plate tectonic processes and marine biodiversity distribution patterns are still unknown. Here, we show that a spatial diversification model constrained by absolute plate motions for the past 140 million years predicts the emergence and movement of diversity hotspots on tropical reefs. The spatial dynamics of tropical reefs explains marine fauna diversification in the Tethyan Ocean during the Cretaceous and early Cenozoic, and identifies an eastward movement of ancestral marine lineages towards the Indo-Australian Archipelago in the Miocene. A mechanistic model based only on habitat-driven diversification and dispersal yields realistic predictions of current biodiversity patterns for both corals and fishes. As in terrestrial systems, we demonstrate that plate tectonics played a major role in driving tropical marine shallow reef biodiversity dynamics.
Above- and below-ground herbivory are key ecosystem processes that can be substantially altered by environmental changes. However, direct comparisons of the coupled variations of above- and ...below-ground herbivore communities along elevation gradients remain sparse. Here, we studied the variation in assemblages of two dominant groups of herbivores, namely, above-ground orthoptera and belowground nematodes, in grasslands along six elevation gradients in the Swiss Alps. By examining variations of community properties of herbivores and their food plants along montane clines, we sought to determine whether the structure and functional properties of these taxonomic groups change with elevation. We found that orthoptera decreased in both species richness and abundance with elevation. In contrast with aboveground herbivores, the taxonomic richness and the total abundance of nematode did not covary with elevation. We further found a stronger shift in above- than below-ground functional properties along elevation, where the mandibular strength of orthoptera matched a shift in leaf toughness. Nematodes showed a weaker pattern of declined sedentary behavior and increased mobility with elevation. In contrast to the direct exposal of aboveground organisms to the surface climate, conditions may be buffered belowground, which together with the influence of edaphic factors on the biodiversity of soil biota, may explain the differences between elevational patterns of above- and below-ground communities. Our study emphasizes the necessity to consider both the above- and below-ground compartments to understand the impact of current and future climatic variation on ecosystems, from a functional perspective of species interactions.
Coral bleaching events threaten coral reef habitats globally and cause severe declines of local biodiversity and productivity. Related to high sea surface temperatures (SST), bleaching events are ...expected to increase as a consequence of future global warming. However, response to climate change is still uncertain as future low‐latitude climatic conditions have no present‐day analogue. Sea surface temperatures during the Eocene epoch were warmer than forecasted changes for the coming century, and distributions of corals during the Eocene may help to inform models forecasting the future of coral reefs. We coupled contemporary and Eocene coral occurrences with information on their respective climatic conditions to model the thermal niche of coral reefs and its potential response to projected climate change. We found that under the RCP8.5 climate change scenario, the global suitability for coral reefs may increase up to 16% by 2100, mostly due to improved suitability of higher latitudes. In contrast, in its current range, coral reef suitability may decrease up to 46% by 2100. Reduction in thermal suitability will be most severe in biodiversity hotspots, especially in the Indo‐Australian Archipelago. Our results suggest that many contemporary hotspots for coral reefs, including those that have been refugia in the past, spatially mismatch with future suitable areas for coral reefs posing challenges to conservation actions under climate change.
In the age of big data, scientific progress is fundamentally limited by our capacity to extract critical information. Here, we map fine-grained spatiotemporal distributions for thousands of species, ...using deep neural networks (DNNs) and ubiquitous citizen science data. Based on 6.7 M observations, we jointly model the distributions of 2477 plant species and species aggregates across Switzerland with an ensemble of DNNs built with different cost functions. We find that, compared to commonly-used approaches, multispecies DNNs predict species distributions and especially community composition more accurately. Moreover, their design allows investigation of understudied aspects of ecology. Including seasonal variations of observation probability explicitly allows approximating flowering phenology; reweighting predictions to mirror cover-abundance allows mapping potentially canopy-dominant tree species nationwide; and projecting DNNs into the future allows assessing how distributions, phenology, and dominance may change. Given their skill and their versatility, multispecies DNNs can refine our understanding of the distribution of plants and well-sampled taxa in general.
Asynchronous migration of insect herbivores and their host plants towards higher elevations following climate warming is expected to generate novel plant–insect interactions. While the disassociation ...of specialised interactions can challenge species' persistence, consequences for specialised low‐elevation insect herbivores encountering novel high‐elevation plants under climate change remain largely unknown. To explore the ability of two low‐elevation Lepidoptera species, Melitaea celadussa and Zygaena filipendulae, to undergo shifts from low‐ to high‐elevation host plants, we combined a translocation experiment performed at two elevations in the Swiss Alps with experiments conducted under controlled conditions. Specifically, we exposed M. celadussa and Z. filipendulae to current low‐ and congeneric high‐elevation host plants, to test how shifts in host plant use impact oviposition probability, number of eggs clutches laid, caterpillar feeding preference and growth, pupation rate and wing size. While our study shows that both M. celadussa and Z. filipendulae can oviposit and feed on novel high‐elevation host plants, we reveal strong preferences towards ovipositing and feeding on current low‐elevation host plants. In addition, shifts from current low‐ to novel high‐elevation host plants reduced pupation rates as well as wing size for M. celadussa, while caterpillar growth was unaffected by host plant identity for both species. Our study suggests that populations of M. celadussa and Z. filipendulae have the ability to undergo host plant shifts under climate change. However, these shifts may impact the ability of populations to respond to rapid climate change by altering developmental processes and morphology. Our study highlights the importance of considering altered biotic interactions when predicting consequences for natural populations facing novel abiotic and biotic environments.
Our study is the first to our knowledge exploring consequences for specialised low‐elevation insect herbivores facing novel, congeneric, high‐elevation plants. Importantly, our study highlights that considering altered biotic interactions, such as those between specialised insects and their host plants, is crucial to predict how species will respond to climate change.
Species currently track suitable abiotic and biotic conditions under ongoing climate change. Adjustments of trophic interactions may provide a mechanism for population persistence, an option that is ...rarely included in model projections. Here, we model the future distribution, of butterflies in the western Alps of Switzerland under climate change, simulating potential diet expansion resulting from adaptive behavior or new host opportunities. We projected the distribution of 60 butterfly and 298 plant species with species distribution models (SDMs) under three climate change scenarios. From known host plants, we allowed a potential diet expansion based on phylogenetic constraints. We assessed whether diet expansion could reduce the rate of expected regional species extinction under climate change. We found that the risk of species extinctions decreased with a concave upward decreasing shape when expanding the host plant range. A diet expansion to even a few phylogenetically closely related host plants would significantly decrease extinction rates. Yet, even when considering expansion toward all plant species available in the study area, the overall regional extinction risk would remain high. Ecological or evolutionary shifts to new host plants may attenuate extinction risk, but the severe decline of suitable abiotic conditions is still expected to drive many species to local extinction.
European grasslands face strong declines in extent and quality. Many grassland types are priority habitats for national and European conservation strategies. Countrywide, high spatial resolution maps ...of their distribution are often lacking. Here, we modelled the spatial distribution of 20 permanent grassland habitats at the level of phytosociological alliances across Switzerland at 10x10 m resolution. First, we applied ensemble models to provide distribution maps of the individual habitat types, using training data from various sources. Copernicus Sentinel satellite imagery and variables describing climate, soil and topography were used as predictors. The performance of these models was assessed based on the true skill statistics with a split‐sampling of the data. Second, the individual maps were combined into countrywide maps of the most and second most likely habitat type, respectively, using an expert‐based weighting approach. The performance of the combined map for the most likely habitat type was assessed via an independent testing dataset and a comparison of the predicted habitat‐type proportions with extrapolations from field surveys. Most individual maps had useful to excellent predictive performance (TSS ≥ 0.6). For most grid cells in the combined maps, the most and second most likely habitat types were either ecologically closely related or representing two grassland types along a nutrient gradient. The same was true for omission errors. We found good agreement between the predicted and estimated proportions from field surveys. The area of raised bogs appears to be underestimated, while dry grasslands showed highest agreement. This work highlights the potential of earth observation data at fine spatial and temporal resolution to map habitats at broad scales, thereby providing the foundation for diverse conservation applications. A particular challenge remains in capturing the transition from nutrient‐poor to nutrient‐rich grasslands, which is highly important for biodiversity conservation.
We modelled the spatial distribution of 20 permanent grassland habitats at the level of phytosociological alliances across Switzerland at 10x10 m resolution. Ensemble models provide distribution maps of individual habitat types, using training data from various sources. Predictors were Copernicus Sentinel satellite imagery and variables describing climate, soil and topography. Performance of these maps was assessed with the True Skill Statistics and split‐sampling of the data. The individual maps were combined into countrywide maps of the most and second most likely habitat type, respectively, using an expert‐based weighting approach. The performance of the combined map for the most likely habitat type was assessed via an independent testing dataset and a comparison of the predicted habitat‐type proportions with extrapolations from field surveys. This work highlights the potential of earth observation data at fine spatial and temporal resolution to map habitats at broad scales, providing the foundation for diverse conservation applications.
Identifying the main determinants of tropical marine biodiversity is essential for devising appropriate conservation measures mitigating the ongoing degradation of coral reef habitats. Based on a ...gridded distribution database and phylogenetic information, we compared the phylogenetic structure of assemblages for three tropical reef fish families (Labridae: wrasses, Pomacentridae: damselfishes and Chaetodontidae: butterflyfishes) using the net relatedness (NRI) and nearest taxon (NTI) indices. We then related these indices to contemporary and historical environmental conditions of coral reefs using spatial regression analyses. Higher levels of phylogenetic clustering were found for fish assemblages in the Indo-Australian Archipelago (IAA), and more particularly when considering the NTI index. The phylogenetic structure of the Pomacentridae, and to a lower extent of the Chaeotodontidae and Labridae, was primarily associated with the location of refugia during the Quaternary period. Phylogenetic clustering in the IAA may partly result from vicariance events associated with coral reef fragmentation during the glacial periods of the Quaternary. Variation in the patterns among fish families further suggest that dispersal abilities may have interacted with past habitat availability in shaping the phylogenetic structure of tropical reef fish assemblages.
Livestock farmers rely on a high and stable grassland productivity for fodder production to sustain their livelihoods. Future drought events related to climate change, however, threaten grassland ...functionality in many regions across the globe. The introduction of sustainable grassland management could buffer these negative effects. According to the biodiversity–productivity hypothesis, productivity positively associates with local biodiversity. The biodiversity–insurance hypothesis states that higher biodiversity enhances the temporal stability of productivity. To date, these hypotheses have mostly been tested through experimental studies under restricted environmental conditions, hereby neglecting climatic variations at a landscape‐scale. Here, we provide a landscape‐scale assessment of the contribution of species richness, functional composition, temperature, and precipitation on grassland productivity. We found that the variation in grassland productivity during the growing season was best explained by functional trait composition. The community mean of plant preference for nutrients explained 24.8% of the variation in productivity and the community mean of specific leaf area explained 18.6%, while species richness explained only 2.4%. Temperature and precipitation explained an additional 22.1% of the variation in productivity. Our results indicate that functional trait composition is an important predictor of landscape‐scale grassland productivity.
We provide a landscape‐scale assessment on the relative effect of plant species richness and plant trait composition on the productivity and variance in grassland productivity under varying climatic conditions in Switzerland. We find a relatively strong effect of functional traits on grassland productivity, while species richness slightly influences productivity. The relationships between functional traits on grassland productivity found in our study indicate the importance of including functional trait variables to explain productivity on a landscape scale.
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