More than range exposure: global otters’ vulnerability to climate change

Climate change impact on species is commonly assessed by predicting species’ range change, a measure of a species’ extrinsic exposure. However, this is only one dimension of species’ vulnerability to climate change. Spatial arrangement of suitable habitats (e.g., fragmentation), their degree of protection or human disturbance, as well as species’ intrinsic sensitivity, such as climatic tolerances, are often neglected. Here, we consider components of species’ intrinsic sensitivity to climate change (climatic niche specialization and marginality) together with components of extrinsic exposure (changes in range extent, fragmentation, coverage of protected areas, and human footprint) to develop an integrated vulnerability index to climate change for world’s freshwater otters. As top freshwater predators, otters are among the most vulnerable mammals, with most species being threatened by habitat loss and degradation. All dimensions of climate change exposure were based on present and future predictions of species distributions. Annual mean temperature, mean diurnal temperature range, mean temperature of the wettest quarter, precipitation during the wettest quarter, and precipitation seasonality prove the most important variables for otters. All species are vulnerable to climate change, with global vulnerability index ranging from -0,19 for Lontra longicaudis to -36,9 for Aonyx congicus. However, we found that, for a given species, climate change can have both positive and negative effects on different components of extrinsic exposure, and that measures of species’ sensitivity are not necessarily congruent with measures of exposure. For instance, the range of all African species would be negatively affected by climate change, but their different sensitivity offers a more (Hydrictis maculicollis, Aonyx capensis) or less (Aonyx congicus) pessimistic perspective on their ability to cope with climate change. Also, highly sensitive species like the South-American Pteronura brasiliensis, Lontra provocax, and Lutra perspicillata might face no exposure to climate change. For the Asian Lutra sumatrana, climate change would instead lead to an increased, less fragmented, and more protected range extent, but the range extent would also be shifted into areas with higher human disturbances. Our study represents a balanced example of how to develop an index aimed at comparatively evaluating vulnerability to climate change of different species by combining different aspects of sensitivity and exposure, providing additional information on which to base more efficient conservation strategies

Contrasted host specificity of gut and endosymbiont bacterial communities in alpine grasshoppers and crickets.

Bacteria colonize the body of macroorganisms to form associations ranging from parasitic to mutualistic. Endosymbiont and gut symbiont communities are distinct microbiomes whose compositions are influenced by host ecology and evolution. Although the composition of horizontally acquired symbiont communities can correlate to host species identity (i.e. harbor host specificity) and host phylogeny (i.e. harbor phylosymbiosis), we hypothesize that the microbiota structure of vertically inherited symbionts (e.g. endosymbionts like Wolbachia) is more strongly associated with the host species identity and phylogeny than horizontally acquired symbionts (e.g. most gut symbionts). Here, using 16S metabarcoding on 336 guts from 24 orthopteran species (grasshoppers and crickets) in the Alps, we observed that microbiota correlated to host species identity, i.e. hosts from the same species had more similar microbiota than hosts from different species. This effect was ~5 times stronger for endosymbionts than for putative gut symbionts. Although elevation correlated with microbiome composition, we did not detect phylosymbiosis for endosymbionts and putative gut symbionts: closely related host species did not harbor more similar microbiota than distantly related species. Our findings indicate that gut microbiota of studied orthopteran species is more correlated to host identity and habitat than to the host phylogeny. The higher host specificity in endosymbionts corroborates the idea that-everything else being equal-vertically transmitted microbes harbor stronger host specificity signal, but the absence of phylosymbiosis suggests that host specificity changes quickly on evolutionary time scales

Unifying niche shift studies: insights from biological invasions.

Assessing whether the climatic niche of a species may change between different geographic areas or time periods has become increasingly important in the context of ongoing global change. However, approaches and findings have remained largely controversial so far, calling for a unification of methods. Here, we build on a review of empirical studies of invasion to formalize a unifying framework that decomposes niche change into unfilling, stability, and expansion situations, taking both a pooled range and range-specific perspective on the niche, while accounting for climatic availability and climatic analogy. This framework provides new insights into the nature of climate niche shifts and our ability to anticipate invasions, and may help in guiding the design of experiments for assessing causes of niche changes

Selecting predictors to maximize the transferability of species distribution models: lessons from cross-continental plant invasions

Aim: Niche-based models of species distribution (SDMs) are commonly used to predict impacts of global change on biodiversity but the reliability of these predictions in space and time depends on their transferability. We tested how the strategy to choose predictors impacts the SDMs' transferability at a cross-continental scale. Location: North America, Eurasia and Australia Method: We used a systematic approach including 50 Holarctic plant invaders and 27 initial predictor variables, considering 10 different strategies to variable selection, accounting for predictors' proximality, multicollinearity and climate analogy. We compared the average performance per strategy, some of them using a large number of random predictor combinations. Next, we looked for the single best model for each species across all possible predictor combinations, by pooling models across all strategies. Transferability was considered as the predictive success of SDMs calibrated in native range and projected onto the invaded range. Results: Two strategies showed better SDMs' transferability on average: a set of predictors known for their ecologically-meaningful effects on plant distribution, and the two first axes of a principal component analysis calibrated on all predictor variables (Spc2). From the >2000 combinations of predictors per species across strategies, the best set of predictors yielded SDMs with good transferability for 45 species (90%). These best combinations consisted in a random selection of 8 predictors (45 sp) and in Spc2 (5 sp). We also found that internal cross-validation was not sufficient to fully inform about SDMs' transferability to a distinct range. Main conclusion: Transferring SDMs at the macroclimatic scale, and thus anticipating invasions, is possible for the large majority of invasive plants considered in this study, but the predictions' accuracy relies strongly on the choice of predictors. From our results, we recommend including either the state-of-the-art proximal variables or a reduced and orthogonalised set to obtain robust SDMs' projections

Changes in reproductive investment with altitude in an alpine plant

Aims In perennial species, the allocation of resources to reproduction results in a reduction of allocation to vegetative growth and, therefore, impacts future reproductive success. As a consequence, variation in this trade-off is among the most important driving forces in the life-history evolution of perennial plants and can lead to locally adapted genotypes. In addition to genetic variation, phenotypic plasticity might also contribute to local adaptation of plants to local conditions by mediating changes in reproductive allocation. Knowledge on the importance of genetic and environmental effects on the trade-off between reproduction and vegetative growth is therefore essential to understand how plants may respond to environmental changes. Methods We conducted a transplant experiment along an altitudinal gradient from 425 m to 1921 m in the front range of the Western Alps of Switzerland to assess the influence of both altitudinal origin of populations and altitude of growing site on growth, reproductive allocation and local adaptation in Poa alpina. The proportion of the number of reproductive tillers by the total number of tillers - was used as a proxy for reproductive allocation. Important findings In our study, the investment in reproduction increased with plant size. Plant growth and the relative importance of reproductive investment decreased in populations originating from higher altitudes compared to populations originating from lower altitudes. The changes in reproductive investment were mainly explained by differences in plant size. In contrast to genetic effects, phenotypic plasticity of all traits measured was low and not related to altitude. As a result, the population from the lowest altitude of origin performed best at all sites. Our results indicate that in P. alpina genetic differences in growth and reproductive investment are related to local conditions affecting growth, i.e. interspecific competition and soil moisture content

Current-induced two-level fluctuations in pseudo spin-valves (Co/Cu/Co) nanostructures

Two-level fluctuations of the magnetization state of pseudo spin-valve pillars Co(10 nm)/Cu(10 nm)/Co(30 nm) embedded in electrodeposited nanowires (~40 nm in diameter, 6000 nm in length) are triggered by spin-polarized currents of 10^7 A/cm^2 at room temperature. The statistical properties of the residence times in the parallel and antiparallel magnetization states reveal two effects with qualitatively different dependences on current intensity. The current appears to have the effect of a field determined as the bias field required to equalize these times. The bias field changes sign when the current polarity is reversed. At this field, the effect of a current density of 10^7 A/cm^2 is to lower the mean time for switching down to the microsecond range. This effect is independent of the sign of the current and is interpreted in terms of an effective temperature for the magnetization.Comment: 4 pages, 5 figures, revised version, to be published in Phys. Rev. Let

Will climate change increase the risk of plant invasions into mountains?

Mountain ecosystems have been less adversely affected by invasions of non-native plants than most other ecosystems, partially because most invasive plants in the lowlands are limited by climate and cannot grow under harsher high-elevation conditions. However, with ongoing climate change, invasive species may rapidly move upwards and threaten mid-, and then high-elevation mountain ecosystems. We evaluated this threat by modeling the current and future habitat suitability for 48 invasive plant species in Switzerland and New South Wales, Australia. Both regions had contrasting climate interactions with elevation, resulting in possible different responses of species distributions to climate change. Using a species distribution modeling approach that combines data from two spatial scales, we built high-resolution species distribution models (≤ 250 m) that account for the global climatic niche of species and also finer variables depicting local climate and disturbances. We found that different environmental drivers limit the elevation range of invasive species in each of the two regions, leading to region-specific species responses to climate change. The optimal suitability for plant invaders is predicted to markedly shift from the lowland to the montane or subalpine zone in Switzerland, whereas the upward shift is far less pronounced in New South Wales where montane and subalpine elevations are already suitable. The results suggest that species most likely to invade high elevations in Switzerland will be cold-tolerant, whereas species with an affinity to moist soils are most likely to invade higher elevations in Australia. Other plant traits were only marginally associated with elevation limits. These results demonstrate that a more systematic consideration of future distributions of invasive species is required in conservation plans of not yet invaded mountainous ecosystems

Spatial modelling of soil water holding capacity improves models of plant distributions in mountain landscapes

Aims The aims of this study were: 1) to test a new methodology to overcome the issue of the predictive capacity of soil water availability in geographic space due to measurement scarcity, 2) to model and generalize soil water availability spatially to a whole region, and 3) to test its predictive capacity in plant SDMs. Methods First, we modelled the measured Soil Water Holding Capacity (SWHC at different pFs) of 24 soils in a focal research area, using a weighted ensemble of small bivariate models (ESM). We then used these models to predict 256 locations of a larger region and used the differences in these pF predictions to calculate three different indices of soil water availability for plants (SWAP. These SWAP variables were added one by one to a set of conventional topo-climatic predictors to model 104 plant species distributions. Results We showed that adding SWAP to the SDMs could improve our ability to predict plant species distributions, and more specifically, pF1.8–pF4.2 became the third most important predictor across all plant models. Conclusions Soil water availability can contribute a significant increase in the predictive power of plant distribution models, by identifying important additional abiotic information to describe plant ecological niches

Generalizing soil properties in geographic space: Approaches used and ways forward.

Soil is one of the most complex systems on Earth, functioning at the interface between the lithosphere, biosphere, hydrosphere, and atmosphere and generating a multitude of functions. Moreover, soil constitutes the belowground environment from which plants capture water and nutrients. Despite their great importance, soil properties are often not sufficiently considered in other disciplines, especially in spatial studies of plant distributions. Most soil properties are available as point data and, to be used in spatial analyses, need to be generalised over entire regions (i.e. digital soil mapping). Three categories of statistical approaches can be used for such purpose: geostatistical approaches (GSA), predictive-statistical approaches (PSA), and hybrid approaches (HA) that combine the two previous ones. How then to choose the best approach in a given soil study context? Does it depend on the soil properties to be spatialized, the study area's characteristics, and/or the availability of soil data? The main aims of this study was to review the use of these three approaches to derive maps of soil properties in relation to the soil parameters, the study area characteristics, and the number of soil samples. We evidenced that the approaches that tend to show the best performance for spatializing soil properties were not necessarily the ones most used in practice. Although PSA was the most widely used, it tended to be outperformed by HA in many cases, but the latter was far less used. However, as the study settings were not always properly described and not all situations were represented in the set of papers analysed, more comparative studies would be needed across a wider range of regions, soil properties, and spatial scales to provide robust conclusions on the best spatialization methods in a specific context

Improving spatial predictions of taxonomic, functional and phylogenetic diversity

In this study, we compare two community modelling approaches to determine their ability to predict the taxonomic, functional and phylogenetic properties of plant assemblages along a broad elevation gradient and at a fine resolution. The first method is the standard stacking individual species distribution modelling (SSDM) approach, which applies a simple environmental filter to predict species assemblages. The second method couples the SSDM and macroecological modelling (MEMSSDM-MEM) approaches to impose a limit on the number of species co-occurring at each site. Because the detection of diversity patterns can be influenced by different levels of phylogenetic or functional trees, we also examine whether performing our analyses from broad to more exact structures in the trees influences the performance of the two modelling approaches when calculating diversity indices. We found that coupling the SSDM with the MEM improves the overall predictions for the three diversity facets compared with those of the SSDM alone. The accuracy of the SSDM predictions for the diversity indices varied greatly along the elevation gradient, and when considering broad to more exact structure in the functional and phylogenetic trees, the SSDM-MEM predictions were more stable. SSDM-MEM moderately but significantly improved the prediction of taxonomic diversity, which was mainly driven by the corrected number of predicted species. The performance of both modelling frameworks increased when predicting the functional and phylogenetic diversity indices. In particular, fair predictions of the taxonomic composition by SSDM-MEM led to increasingly accurate predictions of the functional and phylogenetic indices, suggesting that the compositional errors were associated with species that were functionally or phylogenetically close to the correct ones; however, this did not always hold for the SSDM predictions.Synthesis. In this study, we tested the use of a recently published approach that couples species distribution and macroecological models to provide the first predictions of the distribution of multiple facets of plant diversity: taxonomic, functional and phylogenetic. Moderate but significant improvements were obtained; thus, our results open promising avenues for improving our ability to predict the different facets of biodiversity in space and time across broad environmental gradients when functional and phylogenetic information is available