Modeling the distribution of coprophagous beetle species in the Western Swiss Alps

Coprophagous beetles are essential for fecal matter removal and are thus considered key ecosystem services providers. Yet, our knowledge of these beetles’ distribution and ecology remains very limited. Here, we used Species Distribution Models (SDM) to investigate the species-environment relationships (i.e. their niche) and predict the geographic distribution of coprophagous beetles in the Western Swiss Alps. We used our own sampled data and existing national data from the Swiss faunal database to calibrate, for each species, a regional and a national SDM respectively. In both models, the best predictors were temperature and rock cover proportion, while a soil characteristic (∂13C) indicating its organic content and texture was important in the regional models and precipitations in the Swiss models. The model performed better for species specialized on low or high altitudes than for generalist species occurring in a large altitudinal range. The model performances were neither influenced by the size, nor by the nesting behavior (laying eggs inside or below the excrements) of the species. We also showed that species richness decreased with altitude. This study opens new perspective for a better knowledge of coprophagous beetle’s ecology and a useful tool for their conservation in mountain regions

High Diversity among Feather-Degrading Bacteria from a Dry Meadow Soil

The aim of this study was to determine the diversity of cultivable bacteria able to degrade feathers and present in soil under temperate climate. We obtained 33 isolates from soil samples, which clustered in 13 ARDRA groups. These isolates were able to grow on solid medium with pigeon feathers as sole carbon and nitrogen source. One representative isolate of each ARDRA group was selected for identification and feather degradation tests. The phylogenetic analysis of 16S rDNA gene fragments revealed that only 4 isolates were gram positives. Two other isolates belonged to the Cytophaga-Flavobacterium group, and the remaining to Proteobacteria. High keratinolysis activity was found for strains related to Bacillus, Cytophagales, Actinomycetales, and Proteobacteria. The 13 selected strains showed variable efficiency in degrading whole feathers and 5 strains were able to degrade maximum 40% to 98% of the whole feathers. After 4 weeks incubation, five strains grown on milled feathers produced more than 0.5 U keratinase per mL. Keratinase activities across the 13 strains were positively correlated with the percentage of feather fragmentation and protein concentratio

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

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

¿Existe un sesgo en la participación y visibilidad de las mujeres en ecología? Una comparación entre los congresos ibérico y suizo

Women are still under-represented in science and technology because there is a bias in the different evaluation processes from the admission of oral communications at conferences to the access to more qualified positions. In this study, we compared the participation and visibility of female ecologists in the IV Iberian Ecological Conference (CIE4) with the Annual Swiss Conference on Ecology, Evolution, Systematics, Biogeography and Conservation (Biology16) where a method of blind evaluation was applied. In both conferences, and after active selection by conference committees, male delegates presented proportionately more regular oral contributions than female ones, although these differences were marginally significant. In the Biology16, this bias was due to lower female applicants for oral contributions, and in the CIE4, to a lower selection rate of female oral contributions. In the CIE4, the higher male presence in oral contributions was consistent with male greater visibility, whereas female visibility was higher in the Biology16. This different visibility was caused by contrasting selection for invited speakers; being male researches preferentially invited at the CIE4, but female ones at the Biology16. Implementing a blind review system of contributions and active policies to promote the participation of women as invited speakers may reduce the differences in visibility and could contribute in the medium term to eliminate the bias against women in the selection of oral contributions at the Iberian conferences

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

Plastid DNA variation in Prunus serotina var. serotina (Rosaceae), a North American tree invading Europe

Black cherry (Prunus serotina) is a tree from North America, where it is often used for economical purposes, whereas it is widespread and invasive in Europe. Plastid DNA variation was first investigated in both its native and invasive ranges using microsatellite loci and sequences of three intergenic spacers (trnT-trnL, trnD-trnT and trnS-trnG). This analysis was focused on P. serotina var. serotina, with the inclusion of samples of closely related taxa. Length variation at a microsatellite locus (ccmp5) and a few sequence polymorphisms were identified among P. serotina samples. Four new primer pairs were then designed to specifically amplify variable regions and a combination of five markers was finally proposed for phylogeographic studies in P. serotina. These loci allow identification of six chlorotypes in P. serotina var. serotina, which may be particularly useful to depict the maternal origins of European invasive population

Climatic suitability ranking of biological control candidates: a biogeographic approach for ragweed management in Europe

Biological control using natural antagonists has been a most successful management tool against alien invasive plants that threaten biodiversity. The selection of candidate agents remains a critical step in a biocontrol program before more elaborate and time-consuming experiments are conducted. Here, we propose a biogeographic approach to identify candidates and combinations of candidates to potentially cover a large range of the invader. We studied Ambrosia artemisiifolia (common ragweed), native to North America (NA) and invasive worldwide, and six NA biocontrol candidates for the introduced Europe (EU) range of ragweed, both under current and future bioclimatic conditions. For the first time, we constructed species distribution models based on worldwide occurrences and important bioclimatic variables simultaneously for a plant invader and its biocontrol candidates in view of selecting candidates that potentially cover a large range of the target invader. Ordination techniques were used to explore climatic constraints of each species and to perform niche overlap tests with ragweed. We show a large overlap in climatic space between candidates and ragweed, but a considerable discrepancy in geographic range overlap between EU (31.4%) and NA (83.3%). This might be due to niche unfilling and expansion of ragweed in EU and the fact that habitats with high ragweed occurrences in EU are rare in NA and predicted to be unsuitable for the candidates. Total geographic range of all candidates combined is expected to decrease under climate change in both ranges, but they will respond differently. The relative geographic coverage of a plant invader by biocontrol candidates at home is largely transferable to the introduced range, even when the invader shifts its niche. Our analyses also identified which combination of candidates is expected to cover the most area and for which abiotic conditions to select in order to develop climatically adapted strains for particular regions, where ragweed is currently unlikely to be controlled

Numerical ragweed pollen forecasts using different source maps: a comparison for France.

One of the key input parameters for numerical pollen forecasts is the distribution of pollen sources. Generally, three different methodologies exist to assemble such distribution maps: (1) plant inventories, (2) land use data in combination with annual pollen counts, and (3) ecological modeling. We have used six exemplary maps for all of these methodologies to study their applicability and usefulness in numerical pollen forecasts. The ragweed pollen season of 2012 in France has been simulated with the numerical weather prediction model COSMO-ART using each of the distribution maps in turn. The simulated pollen concentrations were statistically compared to measured values to derive a ranking of the maps with respect to their performance. Overall, approach (2) resulted in the best correspondence between observed and simulated pollen concentrations for the year 2012. It is shown that maps resulting from ecological modeling that does not include a sophisticated estimation of the plant density have a very low predictive skill. For inventory maps and the maps based on land use data and pollen counts, the results depend very much on the observational site. The use of pollen counts to calibrate the map enhances the performance of the model considerably