Predicting the impacts of climate change on genetic diversity in an endangered lizard species.

Many endangered species persist as a series of isolated populations, with some populations more genetically diverse than others. If climate change disproportionately threatens the most diverse populations, the species' ability to adapt (and hence its long-term viability) may be affected more severely than would be apparent by its numerical reduction. In the present study, we combine genetic data with modelling of species distributions under climate change to document this situation in an endangered lizard (Eulamprus leuraensis) from montane southeastern Australia. The species is known from only about 40 isolated swamps. Genetic diversity of lizard populations is greater in some sites than others, presumably reflecting consistently high habitat suitability over evolutionary time. Species distribution modelling suggests that the most genetically diverse populations are the ones most at risk from climate change, so that global warming will erode the species' genetic variability faster than it curtails the species' geographic distribution.

Knowing the past to predict the future: land-use change and the distribution of invasive bullfrogs

Biological invasions and land-use changes are two major causes of the global modifications of biodiversity. Habitat suitability models are the tools of choice to predict potential distributions of invasive species. Although land-use is a key driver of alien species invasions, it is often assumed that land-use is constant in time. Here we combine historical and present day information, to evaluate whether land-use changes could explain the dynamic of invasion of the American bullfrog Rana catesbeiana (=Lithobathes catesbeianus) in Northern Italy, from the 1950s to present-day. We used maxent to build habitat suitability models, on the basis of past (1960s, 1980s) and present-day data on land-uses and species distribution. For example, we used models built using the 1960s data to predict distribution in the 1980s, and so on. Furthermore, we used land-use scenarios to project suitability in the future. Habitat suitability models predicted well the spread of bullfrogs in the subsequent temporal step. Models considering land-use changes predicted invasion dynamics better than models assuming constant land-use over the last 50 years. Scenarios of future land-use suggest that suitability will remain similar in the next years. Habitat suitability models can help to understand and predict the dynamics of invasions; however, land-use is not constant in time: land-use modifications can strongly affect invasions; furthermore, both land management and the suitability of a given land-use class may vary in time. An integration of land-use changes in studies of biological invasions can help to improve management strategies.

Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

Thermal niches are more conserved at cold than warm limits in arctic-alpine plant species

Aim Understanding the stability of realised niches is crucial for predicting the responses of species to climate change. One approach is to evaluate the niche differences of populations of the same species that occupy regions that are geographically disconnected. Here, we assess niche conservatism along thermal gradients for 26 plant species with a disjunct distribution between the Alps and the Arctic. Location European Alps and Norwegian Finnmark. Methods We collected a comprehensive dataset of 26 arctic-alpine plant occurrences in two regions. We assessed niche conservatism through a multi-species comparison and analysed species rankings at cold and warm thermal limits along two distinct gradients corresponding to (1) air temperatures at 2 meters above ground level and (2) elevation distances to the treeline (TLD) for the two regions. We assessed whether observed relationships were close to those predicted under thermal limit conservatism. Results We found a weak similarity in species ranking at the warm thermal limits. The range of warm thermal limits for the 26 species was much larger in the Alps than in Finnmark. We found a stronger similarity in species ranking and correspondence at the cold thermal limit along the gradients of 2-m temperature and TLD. Yet, along the 2-m temperature gradient, the cold thermal limits of species in the Alps were lower on average than those in Finnmark. Main conclusion We found low conservatism of the warm thermal limits but a stronger conservatism of the cold thermal limits. We suggest that biotic interactions at the warm thermal limit likely modulate species responses more strongly than at the cold limit. The differing biotic context between the two regions is likely responsible for the observed differences in realised niches.

History matters: relating paths and rates of landscape change to butterfly species decline

Western European landscapes have drastically changed since the 1950s, with agricultural intensifications and the spread of urban settlements considered the most important drivers of this land-use/land-cover change. Losses of habitat for fauna and flora have been a direct consequence of this development. In the present study, we relate butterfly occurrence to land-use/land-cover changes over five decades between 1951 and 2000. The study area covers the entire Swiss territory. The 10 explanatory variables originate from agricultural statistics and censuses. Both state as well as rate was used as explanatory variables. Species distribution data were obtained from natural history collections. We selected eight butterfly species: four species occur on wetlands and four occur on dry grasslands. We used cluster analysis to track land-use/land-cover changes and to group communes based on similar trajectories of change. Generalized linear models were applied to identify factors that were significantly correlated with the persistence or disappearance of butterfly species. Results showed that decreasing agricultural areas and densities of farms with more than 10 ha of cultivated land are significantly related with wetland species decline, and increasing densities of livestock seem to have favored disappearance of dry grassland species. Moreover, we show that species declines are not only dependent on land-use/land-cover states but also on the rates of change; that is, the higher the transformation rate from small to large farms, the higher the loss of dry grassland species. We suggest that more attention should be paid to the rates of landscape change as feasible drivers of species change and derive some management suggestions.

Break zones in the distributions of alleles and species in alpine plants

Aim  We test for the congruence between allele-based range boundaries (break zones) in silicicolous alpine plants and species-based break zones in the silicicolous flora of the European Alps. We also ask whether such break zones coincide with areas of large elevational variation.Location  The European Alps.Methods  On a regular grid laid across the entire Alps, we determined areas of allele- and species-based break zones using respective clustering algorithms, identifying discontinuities in cluster distributions (breaks), and quantifying integrated break densities (break zones). Discontinuities were identified based on the intra-specific genetic variation of 12 species and on the floristic distribution data from 239 species, respectively. Coincidence between the two types of break zones was tested using Spearman's correlation. Break zone densities were also regressed on topographical complexity to test for the effect of elevational variation.Results  We found that two main break zones in the distribution of alleles and species were significantly correlated. Furthermore, we show that these break zones are in topographically complex regions, characterized by massive elevational ranges owing to high mountains and deep glacial valleys. We detected a third break zone in the distribution of species in the eastern Alps, which is not correlated with topographic complexity, and which is also not evident from allelic distribution patterns. Species with the potential for long-distance dispersal tended to show larger distribution ranges than short-distance dispersers.Main conclusions  We suggest that the history of Pleistocene glaciations is the main driver of the congruence between allele-based and species-based distribution patterns, because occurrences of both species and alleles were subject to the same processes (such as extinction, migration and drift) that shaped the distributions of species and genetic lineages. Large elevational ranges have had a profound effect as a dispersal barrier for alleles during post-glacial immigration. Because plant species, unlike alleles, cannot spread via pollen but only via seed, and thus disperse less effectively, we conclude that species break zones are maintained over longer time spans and reflect more ancient patterns than allele break zones.Conny Thiel-Egenter and Nadir Alvarez contributed equally to this paper and are considered joint first authors.

Distribution des fourmis des bois et espèces apprentées (Hymenoptera, Formicidae, genre Formica) dans le canton de Vaud

This article shows the current distribution of seven ant species of the genus Formica (Hymenoptera, Formicidae, Formicinae) in the canton Waadt. Five species of wood ants (Formica subgenus Formica s.str.: F. rufa, F. polyctena, F. pratensis, F. lugubris et F. paralugubris) and two close species F (Formica) truncorum) et F. (Raptiformica) snaguinea) were investigated. The records originate from different surveys between 1996 and 2009 and offer the opportunity of an up to date overview of the species distribution.

Multicenter Brazilian Study of Oral Candida Species Isolated from Aids Patients

Oropharyngeal candidiasis continues to be considered the most common opportunistic disease in Aids patients. This study was designed to investigate species distribution, serotype and antifungal susceptibility profile among Candida spp. isolated from the oral cavity of Aids patients recruited from six Brazilian university centers. Oral swabs from 130 Aids patients were plated onto CHROMagar Candida medium and 142 isolates were recovered. Yeast isolates were identified by classical methods and serotyped using the Candida Check® system-Iatron. Antifungal susceptibility testing was performed according to the NCCLS microbroth assay. C. albicans was the most frequently isolated species (91%), and 70% of the isolates belonged to serotype A. We detected 12 episodes of co-infection (9%), including co-infection with both serotypes of C. albicans. Non-albicans species were isolated from 12 episodes, 50% of them exhibited DDS or resistance to azoles. Otherwise, only 8 out 130 isolates of C. albicans exhibited DDS or resistance to azoles. Brazilian Aids patients are infected mainly by C. albicans serotype A, most of them susceptible to all antifungal drugs.

Where will conflicts between alien and rare species occur after climate and land-use change? A test with a novel combined modelling approach

Protecting native biodiversity against alien invasive species requires powerful methods to anticipate these invasions and to protect native species assumed to be at risk. Here, we describe how species distribution models (SDMs) can be used to identify areas predicted as suitable for rare native species and also predicted as highly susceptible to invasion by alien species, at present and under future climate and land-use scenarios. To assess the condition and dynamics of such conflicts, we developed a combined predictive modelling (CPM) approach, which predicts species distributions by combining two SDMs fitted using subsets of predictors classified as acting at either regional or local scales. We illustrate the CPM approach for an alien invader and a rare species associated to similar habitats in northwest Portugal. Combined models predict a wider variety of potential species responses, providing more informative projections of species distributions and future dynamics than traditional, non-combined models. They also provide more informative insight regarding current and future rare-invasive conflict areas. For our studied species, conflict areas of highest conservation relevance are predicted to decrease over the next decade, supporting previous reports that some invasive species may contract their geographic range and impact due to climate change. More generally, our results highlight the more informative character of the combined approach to address practical issues in conservation and management programs, especially those aimed at mitigating the impact of invasive plants, land-use and climate changes in sensitive regions

Description of Simulium damascenoi (Diptera: Simuliidae) male and the black-fly species from the State of Amapá, Brazil

Five species are included in the Simulium siolii group, which is placed in the subgenus Psaroniocompsa (Diptera: Simuliidae). Of these five species, only two (Simulium siolii Py-Daniel and Simulium tergospinosum Hamada) have been described in all their life stages, except eggs. Knowledge of the taxonomic characters of all life stages of a species is important in order to clarify interspecific and higher-level taxonomic relationships. The objectives of the present study are to describe the male of Simulium damascenoi Py-Daniel, to provide a list of black-fly species their bionomics and distributions in the state of Amapá, Brazil, and to provide an identification key for larvae and pupae for these species.

Systematics of Anopheles lanei Galvão and Amaral, a species of the subgenus Nyssorhynchus Blanchard (Diptera: Culicidae)

Anopheles (Nyssorhynchus) lanei Galvão and Amaral is here redescribed using morphological characteristics of adult, male and female, fourth instar larva and pupa. The larva, pupa, and male genitalia are illustrated. Diagnostic morphological characters of adults, male genitalia, fourth instar larva and pupa are provided to distinguish An. lanei from other species of the Argyritarsis section. Species distribution data are based on the published literature records and bionomics data are based on both literature records and field data.

Modelling habitat-suitability using museum collections: an example with three sympatric Apodemus species from the Alps

Aim, Location Although the alpine mouse Apodemus alpicola has been given species status since 1989, no distribution map has ever been constructed for this endemic alpine rodent in Switzerland. Based on redetermined museum material and using the Ecological-Niche Factor Analysis (ENFA), habitat-suitability maps were computed for A. alpicola, and also for the co-occurring A. flavicollis and A. sylvaticus. Methods In the particular case of habitat suitability models, classical approaches (GLMs, GAMs, discriminant analysis, etc.) generally require presence and absence data. The presence records provided by museums can clearly give useful information about species distribution and ecology and have already been used for knowledge-based mapping. In this paper, we apply the ENFA which requires only presence data, to build a habitat-suitability map of three species of Apodemus on the basis of museum skull collections. Results Interspecific niche comparisons showed that A. alpicola is very specialized concerning habitat selection, meaning that its habitat differs unequivocally from the average conditions in Switzerland, while both A. flavicollis and A. sylvaticus could be considered as 'generalists' in the study area. Main conclusions Although an adequate sampling design is the best way to collect ecological data for predictive modelling, this is a time and money consuming process and there are cases where time is simply not available, as for instance with endangered species conservation. On the other hand, museums, herbariums and other similar institutions are treasuring huge presence data sets. By applying the ENFA to such data it is possible to rapidly construct a habitat suitability model. The ENFA method not only provides two key measurements regarding the niche of a species (i.e. marginality and specialization), but also has ecological meaning, and allows the scientist to compare directly the niches of different species.

Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking approaches

Aim This study compares the direct, macroecological approach (MEM) for modelling species richness (SR) with the more recent approach of stacking predictions from individual species distributions (S-SDM). We implemented both approaches on the same dataset and discuss their respective theoretical assumptions, strengths and drawbacks. We also tested how both approaches performed in reproducing observed patterns of SR along an elevational gradient.Location Two study areas in the Alps of Switzerland.Methods We implemented MEM by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S-SDM was implemented by modelling each species distribution individually and then stacking the obtained prediction maps in three different ways - summing binary predictions, summing random draws of binomial trials and summing predicted probabilities - to obtain a final species count.Results The direct MEM approach yields nearly unbiased predictions centred around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by the S-SDM approaches. This method also cannot provide any information on species identity and, thus, community composition. It does, however, accurately reproduce the hump-shaped pattern of SR observed along the elevational gradient. The S-SDM approach summing binary maps can predict individual species and thus communities, but tends to overpredict SR. The two other S-SDM approaches the summed binomial trials based on predicted probabilities and summed predicted probabilities - do not overpredict richness, but they predict many competing end points of assembly or they lose the individual species predictions, respectively. Furthermore, all S-SDM approaches fail to appropriately reproduce the observed hump-shaped patterns of SR along the elevational gradient.Main conclusions Macroecological approach and S-SDM have complementary strengths. We suggest that both could be used in combination to obtain better SR predictions by following the suggestion of constraining S-SDM by MEM predictions.

Predicting spatial patterns of plant biodiversity : from species to communities

Understanding the distribution and composition of species assemblages and being able to predict them in space and time are highly important tasks io investigate the fate of biodiversity in the current global changes context. Species distribution models are tools that have proven useful to predict the potential distribution of species by relating their occurrences to environmental variables. Species assemblages can then be predicted by combining the prediction of individual species models. In the first part of my thesis, I tested the importance of new environmental predictors to improve species distribution prediction. I showed that edaphic variables, above all soil pH and nitrogen content could be important in species distribution models. In a second chapter, I tested the influence of different resolution of predictors on the predictive ability of species distribution models. I showed that fine resolution predictors could ameliorate the models for some species by giving a better estimation of the micro-topographic condition that species tolerate, but that fine resolution predictors for climatic factors still need to be ameliorated. The second goal of my thesis was to test the ability of empirical models to predict species assemblages' characteristics such as species richness or functional attributes. I showed that species richness could be modelled efficiently and that the resulting prediction gave a more realistic estimate of the number of species than when obtaining it by stacking outputs of single species distribution models. Regarding the prediction of functional characteristics (plant height, leaf surface, seed mass) of plant assemblages, mean and extreme values of functional traits were better predictable than indices reflecting the diversity of traits in the community. This approach proved interesting to understand which environmental conditions influence particular aspects of the vegetation functioning. It could also be useful to predict climate change impacts on the vegetation. In the last part of my thesis, I studied the capacity of stacked species distribution models to predict the plant assemblages. I showed that this method tended to over-predict the number of species and that the composition of the community was not predicted exactly either. Finally, I combined the results of macro- ecological models obtained in the preceding chapters with stacked species distribution models and showed that this approach reduced significantly the number of species predicted and that the prediction of the composition is also ameliorated in some cases. These results showed that this method is promising. It needs now to be tested on further data sets. - Comprendre la manière dont les plantes se répartissent dans l'environnement et s'organisent en communauté est une question primordiale dans le contexte actuel de changements globaux. Cette connaissance peut nous aider à sauvegarder la diversité des espèces et les écosystèmes. Des méthodes statistiques nous permettent de prédire la distribution des espèces de plantes dans l'espace géographique et dans le temps. Ces modèles de distribution d'espèces, relient les occurrences d'une espèce avec des variables environnementales pour décrire sa distribution potentielle. Cette méthode a fait ses preuves pour ce qui est de la prédiction d'espèces individuelles. Plus récemment plusieurs tentatives de cumul de modèles d'espèces individuelles ont été réalisées afin de prédire la composition des communautés végétales. Le premier objectif de mon travail est d'améliorer les modèles de distribution en testant l'importance de nouvelles variables prédictives. Parmi différentes variables édaphiques, le pH et la teneur en azote du sol se sont avérés des facteurs non négligeables pour prédire la distribution des plantes. Je démontre aussi dans un second chapitre que les prédicteurs environnementaux à fine résolution permettent de refléter les conditions micro-topographiques subies par les plantes mais qu'ils doivent encore être améliorés avant de pouvoir être employés de manière efficace dans les modèles. Le deuxième objectif de ce travail consistait à étudier le développement de modèles prédictifs pour des attributs des communautés végétales tels que, par exemple, la richesse en espèces rencontrée à chaque point. Je démontre qu'il est possible de prédire par ce biais des valeurs de richesse spécifiques plus réalistes qu'en sommant les prédictions obtenues précédemment pour des espèces individuelles. J'ai également prédit dans l'espace et dans le temps des caractéristiques de la végétation telles que sa hauteur moyenne, minimale et maximale. Cette approche peut être utile pour comprendre quels facteurs environnementaux promeuvent différents types de végétation ainsi que pour évaluer les changements à attendre au niveau de la végétation dans le futur sous différents régimes de changements climatiques. Dans une troisième partie de ma thèse, j'ai exploré la possibilité de prédire les assemblages de plantes premièrement en cumulant les prédictions obtenues à partir de modèles individuels pour chaque espèce. Cette méthode a le défaut de prédire trop d'espèces par rapport à ce qui est observé en réalité. J'ai finalement employé le modèle de richesse en espèce développé précédemment pour contraindre les résultats du modèle d'assemblage de plantes. Cela a permis l'amélioration des modèles en réduisant la sur-prédiction et en améliorant la prédiction de la composition en espèces. Cette méthode semble prometteuse mais de nouveaux tests sont nécessaires pour bien évaluer ses capacités.

Adapting global conservation strategies to climate change at the European scale: the otter as a flagship species

Climate change has created the need for new strategies in conservation planning that account for the dynamics of factors threatening endangered species. Here we assessed climate change threat to the European otter, a flagship species for freshwater ecosystems, considering how current conservation areas will perform in preserving the species in a climatically changed future. We used an ensemble forecasting approach considering six modelling techniques applied to eleven subsets of otter occurrences across Europe. We performed a pseudo-independent and an internal evaluation of predictions. Future projections of species distribution were made considering the A2 and B2 scenarios for 2080 across three climate models: CCCMA-CGCM2, CSIRO-MK2 and HCCPR HAD-CM3. The current and the predicted otter distributions were used to identify priority areas for the conservation of the species, and overlapped to existing network of protected areas. Our projections show that climate change may profoundly reshuffle the otter's potential distribution in Europe, with important differences between the two scenarios we considered. Overall, the priority areas for conservation of the otter in Europe appear to be unevenly covered by the existing network of protected areas, with the current conservation efforts being insufficient in most cases. For a better conservation, the existing protected areas should be integrated within a more general conservation and management strategy incorporating climate change projections. Due to the important role that the otter plays for freshwater habitats, our study further highlights the potential sensitivity of freshwater habitats in Europe to climate change.