Changing landscapes of Switzerland: assessing effects of historic and future land uses and land covers on the occurrence of selected butterfly species

Summary Landscapes are continuously changing. Natural forces of change such as heavy rainfall and fires can exert lasting influences on their physical form. However, changes related to human activities have often shaped landscapes more distinctly. In Western Europe, especially modern agricultural practices and the expanse of overbuilt land have left their marks in the landscapes since the middle of the 20th century. In the recent years men realised that mare and more changes that were formerly attributed to natural forces might indirectly be the result of their own action. Perhaps the most striking landscape change indirectly driven by human activity we can witness in these days is the large withdrawal of Alpine glaciers. Together with the landscapes also habitats of animal and plant species have undergone vast and sometimes rapid changes that have been hold responsible for the ongoing loss of biodiversity. Thereby, still little knowledge is available about probable effects of the rate of landscape change on species persistence and disappearance. Therefore, the development and speed of land use/land cover in the Swiss communes between the 1950s and 1990s were reconstructed using 10 parameters from agriculture and housing censuses, and were further correlated with changes in butterfly species occurrences. Cluster analyses were used to detect spatial patterns of change on broad spatial scales. Thereby, clusters of communes showing similar changes or transformation rates were identified for single decades and put into a temporally dynamic sequence. The obtained picture on the changes showed a prevalent replacement of non-intensive agriculture by intensive practices, a strong spreading of urban communes around city centres, and transitions towards larger farm sizes in the mountainous areas. Increasing transformation rates toward more intensive agricultural managements were especially found until the 1970s, whereas afterwards the trends were commonly negative. However, transformation rates representing the development of residential buildings showed positive courses at any time. The analyses concerning the butterfly species showed that grassland species reacted sensitively to the density of livestock in the communes. This might indicate the augmented use of dry grasslands as cattle pastures that show altered plant species compositions. Furthermore, these species also decreased in communes where farms with an agricultural area >5ha have disappeared. The species of the wetland habitats were favoured in communes with smaller fractions of agricultural areas and lower densities of large farms (>10ha) but did not show any correlation to transformation rates. It was concluded from these analyses that transformation rates might influence species disappearance to a certain extent but that states of the environmental predictors might generally outweigh the importance of the corresponding rates. Information on the current distribution of species is evident for nature conservation. Planning authorities that define priority areas for species protection or examine and authorise construction projects need to know about the spatial distribution of species. Hence, models that simulate the potential spatial distribution of species have become important decision tools. The underlying statistical analyses such as the widely used generalised linear models (GLM) often rely on binary species presence-absence data. However, often only species presence data have been colleted, especially for vagrant, rare or cryptic species such as butterflies or reptiles. Modellers have thus introduced randomly selected absence data to design distribution models. Yet, selecting false absence data might bias the model results. Therefore, we investigated several strategies to select more reliable absence data to model the distribution of butterfly species based on historical distribution data. The results showed that better models were obtained when historical data from longer time periods were considered. Furthermore, model performance was additionally increased when long-term data of species that show similar habitat requirements as the modelled species were used. This successful methodological approach was further applied to assess consequences of future landscape changes on the occurrence of butterfly species inhabiting dry grasslands or wetlands. These habitat types have been subjected to strong deterioration in the recent decades, what makes their protection a future mission. Four spatially explicit scenarios that described (i) ongoing land use changes as observed between 1985 and 1997, (ii) liberalised agricultural markets, and (iii) slightly and (iv) strongly lowered agricultural production provided probable directions of landscape change. Current species-environment relationships were derived from a statistical model and used to predict future occurrence probabilities in six major biogeographical regions in Switzerland, comprising the Jura Mountains, the Plateau, the Northern and Southern Alps, as well as the Western and Eastern Central Alps. The main results were that dry grasslands species profited from lowered agricultural production, whereas overgrowth of open areas in the liberalisation scenario might impair species occurrence. The wetland species mostly responded with decreases in their occurrence probabilities in the scenarios, due to a loss of their preferred habitat. Further analyses about factors currently influencing species occurrences confirmed anthropogenic causes such as urbanisation, abandonment of open land, and agricultural intensification. Hence, landscape planning should pay more attention to these forces in areas currently inhabited by these butterfly species to enable sustainable species persistence. In this thesis historical data were intensively used to reconstruct past developments and to make them useful for current investigations. Yet, the availability of historical data and the analyses on broader spatial scales has often limited the explanatory power of the conducted analyses. Meaningful descriptors of former habitat characteristics and abundant species distribution data are generally sparse, especially for fine scale analyses. However, this situation can be ameliorated by broadening the extent of the study site and the used grain size, as was done in this thesis by considering the whole of Switzerland with its communes. Nevertheless, current monitoring projects and data recording techniques are promising data sources that might allow more detailed analyses about effects of long-term species reactions on landscape changes in the near future. This work, however, also showed the value of historical species distribution data as for example their potential to locate still unknown species occurrences. The results might therefore contribute to further research activities that investigate current and future species distributions considering the immense richness of historical distribution data. Résumé Les paysages changent continuellement. Des farces naturelles comme des pluies violentes ou des feux peuvent avoir une influence durable sur la forme du paysage. Cependant, les changements attribués aux activités humaines ont souvent modelé les paysages plus profondément. Depuis les années 1950 surtout, les pratiques agricoles modernes ou l'expansion des surfaces d'habitat et d'infrastructure ont caractérisé le développement du paysage en Europe de l'Ouest. Ces dernières années, l'homme a commencé à réaliser que beaucoup de changements «naturels » pourraient indirectement résulter de ses propres activités. Le changement de paysage le plus apparent dont nous sommes témoins de nos jours est probablement l'immense retraite des glaciers alpins. Avec les paysages, les habitats des animaux et des plantes ont aussi été exposés à des changements vastes et quelquefois rapides, tenus pour coresponsable de la continuelle diminution de la biodiversité. Cependant, nous savons peu des effets probables de la rapidité des changements du paysage sur la persistance et la disparition des espèces. Le développement et la rapidité du changement de l'utilisation et de la couverture du sol dans les communes suisses entre les années 50 et 90 ont donc été reconstruits au moyen de 10 variables issues des recensements agricoles et résidentiels et ont été corrélés avec des changements de présence des papillons diurnes. Des analyses de groupes (Cluster analyses) ont été utilisées pour détecter des arrangements spatiaux de changements à l'échelle de la Suisse. Des communes avec des changements ou rapidités comparables ont été délimitées pour des décennies séparées et ont été placées en séquence temporelle, en rendrent une certaine dynamique du changement. Les résultats ont montré un remplacement répandu d'une agriculture extensive des pratiques intensives, une forte expansion des faubourgs urbains autour des grandes cités et des transitions vers de plus grandes surfaces d'exploitation dans les Alpes. Dans le cas des exploitations agricoles, des taux de changement croissants ont été observés jusqu'aux années 70, alors que la tendance a généralement été inversée dans les années suivantes. Par contre, la vitesse de construction des nouvelles maisons a montré des courbes positives pendant les 50 années. Les analyses sur la réaction des papillons diurnes ont montré que les espèces des prairies sèches supportaient une grande densité de bétail. Il est possible que dans ces communes beaucoup des prairies sèches aient été fertilisées et utilisées comme pâturages, qui ont une autre composition floristique. De plus, les espèces ont diminué dans les communes caractérisées par une rapide perte des fermes avec une surface cultivable supérieure à 5 ha. Les espèces des marais ont été favorisées dans des communes avec peu de surface cultivable et peu de grandes fermes, mais n'ont pas réagi aux taux de changement. Il en a donc été conclu que la rapidité des changements pourrait expliquer les disparitions d'espèces dans certains cas, mais que les variables prédictives qui expriment des états pourraient être des descripteurs plus importants. Des informations sur la distribution récente des espèces sont importantes par rapport aux mesures pour la conservation de la nature. Pour des autorités occupées à définir des zones de protection prioritaires ou à autoriser des projets de construction, ces informations sont indispensables. Les modèles de distribution spatiale d'espèces sont donc devenus des moyens de décision importants. Les méthodes statistiques courantes comme les modèles linéaires généralisés (GLM) demandent des données de présence et d'absence des espèces. Cependant, souvent seules les données de présence sont disponibles, surtout pour les animaux migrants, rares ou cryptiques comme des papillons ou des reptiles. C'est pourquoi certains modélisateurs ont choisi des absences au hasard, avec le risque d'influencer le résultat en choisissant des fausses absences. Nous avons établi plusieurs stratégies, basées sur des données de distribution historique des papillons diurnes, pour sélectionner des absences plus fiables. Les résultats ont démontré que de meilleurs modèles pouvaient être obtenus lorsque les données proviennent des périodes de temps plus longues. En plus, la performance des modèles a pu être augmentée en considérant des données de distribution à long terme d'espèces qui occupent des habitats similaires à ceux de l'espèce cible. Vu le succès de cette stratégie, elle a été utilisée pour évaluer les effets potentiels des changements de paysage futurs sur la distribution des papillons des prairies sèches et marais, deux habitats qui ont souffert de graves détériorations. Quatre scénarios spatialement explicites, décrivant (i) l'extrapolation des changements de l'utilisation de sol tels qu'observés entre 1985 et 1997, (ii) la libéralisation des marchés agricoles, et une production agricole (iii) légèrement amoindrie et (iv) fortement diminuée, ont été utilisés pour générer des directions de changement probables. Les relations actuelles entre la distribution des espèces et l'environnement ont été déterminées par le biais des modèles statistiques et ont été utilisées pour calculer des probabilités de présence selon les scénarios dans six régions biogéographiques majeures de la Suisse, comportant le Jura, le Plateau, les Alpes du Nord, du Sud, centrales orientales et centrales occidentales. Les résultats principaux ont montré que les espèces des prairies sèches pourraient profiter d'une diminution de la production agricole, mais qu'elles pourraient aussi disparaître à cause de l'embroussaillement des terres ouvertes dû à la libéralisation des marchés agricoles. La probabilité de présence des espèces de marais a décrû à cause d'une perte générale des habitats favorables. De plus, les analyses ont confirmé que des causes humaines comme l'urbanisation, l'abandon des terres ouvertes et l'intensification de l'agriculture affectent actuellement ces espèces. Ainsi ces forces devraient être mieux prises en compte lors de planifications paysagères, pour que ces papillons diurnes puissent survivre dans leurs habitats actuels. Dans ce travail de thèse, des données historiques ont été intensivement utilisées pour reconstruire des développements anciens et pour les rendre utiles à des recherches contemporaines. Cependant, la disponibilité des données historiques et les analyses à grande échelle ont souvent limité le pouvoir explicatif des analyses. Des descripteurs pertinents pour caractériser les habitats anciens et des données suffisantes sur la distribution des espèces sont généralement rares, spécialement pour des analyses à des échelles fores. Cette situation peut être améliorée en augmentant l'étendue du site d'étude et la résolution, comme il a été fait dans cette thèse en considérant toute la Suisse avec ses communes. Cependant, les récents projets de surveillance et les techniques de collecte de données sont des sources prometteuses, qui pourraient permettre des analyses plus détaillés sur les réactions à long terme des espèces aux changements de paysage dans le futur. Ce travail a aussi montré la valeur des anciennes données de distribution, par exemple leur potentiel pour aider à localiser des' présences d'espèces encore inconnues. Les résultats peuvent contribuer à des activités de recherche à venir, qui étudieraient les distributions récentes ou futures d'espèces en considérant l'immense richesse des données de distribution historiques.

Do habitat suitability models reliably predict the recovery areas of threatened species?

1. Identifying those areas suitable for recolonization by threatened species is essential to support efficient conservation policies. Habitat suitability models (HSM) predict species' potential distributions, but the quality of their predictions should be carefully assessed when the species-environment equilibrium assumption is violated.2. We studied the Eurasian otter Lutra lutra, whose numbers are recovering in southern Italy. To produce widely applicable results, we chose standard HSM procedures and looked for the models' capacities in predicting the suitability of a recolonization area. We used two fieldwork datasets: presence-only data, used in the Ecological Niche Factor Analyses (ENFA), and presence-absence data, used in a Generalized Linear Model (GLM). In addition to cross-validation, we independently evaluated the models with data from a recolonization event, providing presences on a previously unoccupied river.3. Three of the models successfully predicted the suitability of the recolonization area, but the GLM built with data before the recolonization disagreed with these predictions, missing the recolonized river's suitability and badly describing the otter's niche. Our results highlighted three points of relevance to modelling practices: (1) absences may prevent the models from correctly identifying areas suitable for a species spread; (2) the selection of variables may lead to randomness in the predictions; and (3) the Area Under Curve (AUC), a commonly used validation index, was not well suited to the evaluation of model quality, whereas the Boyce Index (CBI), based on presence data only, better highlighted the models' fit to the recolonization observations.4. For species with unstable spatial distributions, presence-only models may work better than presence-absence methods in making reliable predictions of suitable areas for expansion. An iterative modelling process, using new occurrences from each step of the species spread, may also help in progressively reducing errors.5. Synthesis and applications. Conservation plans depend on reliable models of the species' suitable habitats. In non-equilibrium situations, such as the case for threatened or invasive species, models could be affected negatively by the inclusion of absence data when predicting the areas of potential expansion. Presence-only methods will here provide a better basis for productive conservation management practices.

Modelling the influence of change in fire regime on the local distribution of a Mediterranean pyrophytic plant species (Cistus salviifolius) at its northern range limit

Aims: To assess the potential distribution of an obligate seeder and active pyrophyte, Cistus salviifolius, a vulnerable species in the Swiss Red List; to derive scenarios by changing the fire return interval; and to discuss the results from a conservation perspective. A more general aim is to assess the impact of fire as a natural factor influencing the vegetation of the southern slopes of the Alps. Locations: Alps, southern Switzerland. Methods: Presence-absence data to fit the model were obtained from the most recent field mapping of C. salviifolius. The quantitative environmental predictors used in this study include topographic, climatic and disturbance (fire) predictors. Models were fitted by logistic regression and evaluated by jackknife and bootstrap approaches. Changes in fire regime were simulated by increasing the time-return interval of fire (simulating longer periods without fire). Two scenarios were considered: no fire in the past 15 years; or in the past 35 years. Results: Rock cover, slope, topographic position, potential evapotranspiration and time elapsed since the last fire were selected in the final model. The Nagelkerke R-2 of the model for C. salviifolius was 0.57 and the Jackknife area under the curve evaluation was 0.89. The bootstrap evaluation revealed model robustness. By increasing the return interval of fire by either up to 15 years, or 35 years, the modelled C. salviifolius population declined by 30-40%, respectively. Main conclusions: Although fire plays a significant role, topography and rock cover appear to be the most important predictors, suggesting that the distribution of C. salviifolius in the southern Swiss Alps is closely related to the availability of supposedly competition-free sites, such as emerging bedrock, ridge locations or steep slopes. Fire is more likely to play a secondary role in allowing C. salviifolius to extend its occurrence temporarily, by increasing germination rates and reducing the competition from surrounding vegetation. To maintain a viable dormant seed bank for C. salviifolius, conservation managers should consider carrying out vegetation clearing and managing wild fire propagation to reduce competition and ensure sufficient recruitment for this species.

Accuracy of plant assemblage predictions from species distribution models varies along environmental gradients

Aim: Climatic niche modelling of species and community distributions implicitly assumes strong and constant climatic determinism across geographic space. This assumption had however never been tested so far. We tested it by assessing how stacked-species distribution models (S-SDMs) perform for predicting plant species assemblages along elevation. Location: Western Swiss Alps. Methods: Using robust presence-absence data, we first assessed the ability of topo-climatic S-SDMs to predict plant assemblages in a study area encompassing a 2800 m wide elevation gradient. We then assessed the relationships among several evaluation metrics and trait-based tests of community assembly rules. Results: The standard errors of individual SDMs decreased significantly towards higher elevations. Overall, the S-SDM overpredicted far more than they underpredicted richness and could not reproduce the humpback curve along elevation. Overprediction was greater at low and mid-range elevations in absolute values but greater at high elevations when standardised by the actual richness. Looking at species composition, the evaluation metrics accounting for both the presence and absence of species (overall prediction success and kappa) or focusing on correctly predicted absences (specificity) increased with increasing elevation, while the metrics focusing on correctly predicted presences (Jaccard index and sensitivity) decreased. The best overall evaluation - as driven by specificity - occurred at high elevation where species assemblages were shown to be under significant environmental filtering of small plants. In contrast, the decreased overall accuracy in the lowlands was associated with functional patterns representing any type of assembly rule (environmental filtering, limiting similarity or null assembly). Main Conclusions: Our study reveals interesting patterns of change in S-SDM errors with changes in assembly rules along elevation. Yet, significant levels of assemblage prediction errors occurred throughout the gradient, calling for further improvement of SDMs, e.g., by adding key environmental filters that act at fine scales and developing approaches to account for variations in the influence of predictors along environmental gradients.

Can we disentangle predator-prey interactions from species distributions at a macro-scale? A case study with a raptor species.

There is a debate on whether an influence of biotic interactions on species distributions can be reflected at macro-scale levels. Whereas the influence of biotic interactions on spatial arrangements is beginning to be studied at local scales, similar studies at macro-scale levels are scarce. There is no example disentangling, from other similarities with related species, the influence of predator-prey interactions on species distributions at macro-scale levels. In this study we aimed to disentangle predator-prey interactions from species distribution data following an experimental approach including a factorial design. As a case of study we selected the short-toed eagle because of its known specialization on certain prey reptiles. We used presence-absence data at a 100 Km2 spatial resolution to extract the explanatory capacity of different environmental predictors (five abiotic and two biotic predictors) on the short-toed eagle species distribution in Peninsular Spain. Abiotic predictors were relevant climatic and topographic variables, and relevant biotic predictors were prey richness and forest density. In addition to the short-toed eagle, we also obtained the predictor's explanatory capacities for i) species of the same family Accipitridae (as a reference), ii) for other birds of different families (as controls) and iii) species with randomly selected presences (as null models). We run 650 models to test for similarities of the short-toed eagle, controls and null models with reference species, assessed by regressions of explanatory capacities. We found higher similarities between the short-toed eagle and other species of the family Accipitridae than for the other two groups. Once corrected by the family effect, our analyses revealed a signal of predator-prey interaction embedded in species distribution data. This result was corroborated with additional analyses testing for differences in the concordance between the distributions of different bird categories and the distributions of either prey or non-prey species of the short-toed eagle. Our analyses were useful to disentangle a signal of predator-prey interactions from species distribution data at a macro-scale. This study highlights the importance of disentangling specific features from the variation shared with a given taxonomic level.

Model development for capercaillie (Tetrao urogallus) habitat in the Jura Mountains (Western Switzerland)

Capercaillie, Tetrao urogallus, is a threatened species in central Europe, and Swiss populations declined 40 to 50 % between 1970 and 1985. Capercaillie are sensitive to forest structure, and loss of habitat is a major cause of their decline. Knowledge of habitat characteristics is therefore essential for capercaillie conservation. Here, we present models predicting capercaillie probability of occurrence, based on relevant structural habitat variables. Models were built using multiple logistic regression analyses on capercaillie presence/absence data. Vegetation survey was carried out in July 1999 in a 170-km2 forested area (Jura mountains, canton de Vaud, western Switzerland) inhabited by capercaillie and presence/absence of the species was assessed according to dropping presence/absence. The survey was based on 10-m-radius sample plots each in a 1-km2 forest patch (n = 76 with capercaillie droppings, n = 80 without). A first model included seven out of 27 measured habitat variables and a second model only four. The latter model best represents practical needs. It includes three variables which had a negative impact on capercaillie presence: tree and shrub covers and spruce, Picea excelsa, shrub cover, and one which had a positive effect: bilberry, Vaccinium myrtillus, cover, highlighting that capaercaillie selected open forest with high bilberry abundance. The model can be used to map potential capercaillie habitat distribution and to manage the habitat in favour of capercaillie (protection and adapted forestry practices) in the Swiss Jura mountains.

Modelling ecological niches with support vector machines

1. The ecological niche is a fundamental biological concept. Modelling species' niches is central to numerous ecological applications, including predicting species invasions, identifying reservoirs for disease, nature reserve design and forecasting the effects of anthropogenic and natural climate change on species' ranges. 2. A computational analogue of Hutchinson's ecological niche concept (the multidimensional hyperspace of species' environmental requirements) is the support of the distribution of environments in which the species persist. Recently developed machine-learning algorithms can estimate the support of such high-dimensional distributions. We show how support vector machines can be used to map ecological niches using only observations of species presence to train distribution models for 106 species of woody plants and trees in a montane environment using up to nine environmental covariates. 3. We compared the accuracy of three methods that differ in their approaches to reducing model complexity. We tested models with independent observations of both species presence and species absence. We found that the simplest procedure, which uses all available variables and no pre-processing to reduce correlation, was best overall. Ecological niche models based on support vector machines are theoretically superior to models that rely on simulating pseudo-absence data and are comparable in empirical tests. 4. Synthesis and applications. Accurate species distribution models are crucial for effective environmental planning, management and conservation, and for unravelling the role of the environment in human health and welfare. Models based on distribution estimation rather than classification overcome theoretical and practical obstacles that pervade species distribution modelling. In particular, ecological niche models based on machine-learning algorithms for estimating the support of a statistical distribution provide a promising new approach to identifying species' potential distributions and to project changes in these distributions as a result of climate change, land use and landscape alteration.

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

Importance of abiotic stress as a range-limit determinant for European plants: insights from species' responses to climatic gradients

Aim We examined whether species occurrences are primarily limited by physiological tolerance in the abiotically more stressful end of climatic gradients (the asymmetric abiotic stress limitation (AASL) hypothesis) and the geographical predictions of this hypothesis: abiotic stress mainly determines upper-latitudinal and upper-altitudinal species range limits, and the importance of abiotic stress for these range limits increases the further northwards and upwards a species occurs. Location Europe and the Swiss Alps. Methods The AASL hypothesis predicts that species have skewed responses to climatic gradients, with a steep decline towards the more stressful conditions. Based on presence-absence data we examined the shape of plant species responses (measured as probability of occurrence) along three climatic gradients across latitudes in Europe (1577 species) and altitudes in the Swiss Alps (284 species) using Huisman-Olff-Fresco, generalized linear and generalized additive models. Results We found that almost half of the species from Europe and one-third from the Swiss Alps showed responses consistent with the predictions of the AASL hypothesis. Cold temperatures and a short growing season seemed to determine the upper-latitudinal and upper-altitudinal range limits of up to one-third of the species, while drought provided an important constraint at lower-latitudinal range limits for up to one-fifth of the species. We found a biome-dependent influence of abiotic stress and no clear support for abiotic stress as a stronger upper range-limit determinant for species with higher latitudinal and altitudinal distributions. However, the overall influence of climate as a range-limit determinant increased with latitude. Main conclusions Our results support the AASL hypothesis for almost half of the studied species, and suggest that temperature-related stress controls the upper-latitudinal and upper-altitudinal range limits of a large proportion of these species, while other factors including drought stress may be important at the lower range limits.

A multi-temporal approach to model endangered species distribution in Europe: the case of the Eurasian otter in Italy

We analysed the relationship between changes in land cover patterns and the Eurasian otter occurrence over the course of about 20 years (1985-2006) using multi-temporal Species Distribution Models (SDMs). The study area includes five river catchments covering most of the otter's Italian range. Land cover and topographic data were used as proxies of the ecological requirements of the otter within a 300-m buffer around river courses. We used species presence, pseudo-absence data, and environmental predictors to build past (1985) and current (2006) SDMs by applying an ensemble procedure through the BIOMOD modelling package. The performance of each model was evaluated by measuring the area under the curve (AUC) of the receiver-operating characteristic (ROC). Multi-temporal analyses of species distribution and land cover maps were performed by comparing the maps produced for 1985 and 2006. The ensemble procedure provided a good overall modelling accuracy, revealing that elevation and slope affected the otter's distribution in the past; in contrast, land cover predictors, such as cultivations and forests, were more important in the present period. During the transition period, 20.5% of the area became suitable, with 76% of the new otter presence data being located in these newly available areas. The multi-temporal analysis suggested that the quality of otter habitat improved in the last 20 years owing to the expansion of forests and to the reduction of cultivated fields in riparian belts. The evidence presented here stresses the great potential of riverine habitat restoration and environmental management for the future expansion of the otter in Italy

Bald eagle (Haliaeetus leucocephalus) population increases in Placentia Bay, Newfoundland: evidence for habitat saturation?

Across North America, Bald Eagle (Haliaeetus leucocephalus) populations appear to be recovering following bans of DDT. A limited number of studies from across North America have recorded a surplus of nonbreeding adult Bald Eagles in dense populations when optimal habitat and food become limited. Placentia Bay, Newfoundland is one of these. The area has one of the highest densities of Bald Eagles in eastern North America, and has recently experienced an increase in the proportion of nonbreeding adults within the population. We tested whether the observed Bald Eagle population trends in Placentia Bay, Newfoundland during the breeding seasons 1990-2009 are due to habitat saturation. We found no significant differences in habitat or food resource characteristics between occupied territories and pseudo-absence data or between nest sites with high vs. low nest activity/occupancy rates. Therefore there is no evidence for habitat saturation for Bald Eagles in Placentia Bay and alternative hypotheses for the high proportion of nonbreeding adults should be considered. The Newfoundland population provides an interesting case for examination because it did not historically appear to be affected by pollution. An understanding of Bald Eagle population dynamics in a relatively pristine area with a high density can be informative for restoration and conservation of Bald Eagle populations elsewhere.

Evaluation of the realism of climate reconstruction using the Coexistence Approach with modern pollen samples from the Tibetan Plateau

We apply the Coexistence Approach (CoA) to reconstruct mean annual precipitation (MAP), mean annual temperature (MAT), mean temperature of thewarmestmonth (MTWA) and mean temperature of the coldest month (MTCO) at 44 pollen sites on the Qinghai–Tibetan Plateau. The modern climate ranges of the taxa are obtained (1) from county-level presence/absence data and (2) from data on the optimum and range of each taxon from Lu et al. (2011). The CoA based on the optimumand range data yields better predictions of observed climate parameters at the pollen sites than that based on the county-level data. The presence of arboreal pollen, most of which is derived fromoutside the region, distorts the reconstructions. More reliable reconstructions are obtained using only the non-arboreal component of the pollen assemblages. The root mean-squared error (RMSE) of the MAP reconstructions are smaller than the RMSE of MAT, MTWA and MTCO, suggesting that precipitation gradients are the most important control of vegetation distribution on the Qinghai–Tibetan Plateau. Our results show that CoA could be used to reconstruct past climates in this region, although in areas characterized by open vegetation the most reliable estimates will be obtained by excluding possible arboreal contaminants.

Associações de espécies de peixes em ambientes lóticos da bacia do rio Iguatemi, Estado do Mato Grosso do Sul

The aim of this paper is to describe the patterns of associations between fish species and their distribution in lotic habitats at basin level. Samples were accomplished in 27 localities of Iguatemi river basin, distributed in four environments (Iguatemi river, Jogui river, Puitã river and streams). The presence/absence data of those species which occurred in 2 or more sites were submitted at multivariate methods with the aim to describe the major species associations. The species distribution was considered determinative in these communities (C-score = 17,33; P = 0,000), with significant difference among the studied environments (ANOSIM r = 0,082; P = 0,012), with verified difference between Iguatemi river and streams (P = 0,001) and also streams and Jogui river (P = 0,014). We verified a strong segregation among species from headstreams and more discharge river stretches or even larger streams.

Reinforcing and expanding the predictions of the disturbance vicariance hypothesis in Amazonian harlequin frogs: A molecular phylogenetic and climate envelope modelling approach

The disturbance vicariance hypothesis (DV) has been proposed to explain speciation in Amazonia, especially its edge regions, e. g. in eastern Guiana Shield harlequin frogs (Atelopus) which are suggested to have derived from a cool-adapted Andean ancestor. In concordance with DV predictions we studied that (i) these amphibians display a natural distribution gap in central Amazonia; (ii) east of this gap they constitute a monophyletic lineage which is nested within a pre-Andean/western clade; (iii) climate envelopes of Atelopus west and east of the distribution gap show some macroclimatic divergence due to a regional climate envelope shift; (iv) geographic distributions of climate envelopes of western and eastern Atelopus range into central Amazonia but with limited spatial overlap. We tested if presence and apparent absence data points of Atelopus were homogenously distributed with Ripley's K function. A molecular phylogeny (mitochondrial 16S rRNA gene) was reconstructed using Maximum Likelihood and Bayesian Inference to study if Guianan Atelopus constitute a clade nested within a larger genus phylogeny. We focused on climate envelope divergence and geographic distribution by computing climatic envelope models with MaxEnt based on macroscale bioclimatic parameters and testing them by using Schoener's index and modified Hellinger distance. We corroborated existing DV predictions and, for the first time, formulated new DV predictions aiming on species' climate envelope change. Our results suggest that cool-adapted Andean Atelopus ancestors had dispersed into the Amazon basin and further onto the eastern Guiana Shield where, under warm conditions, they were forced to change climate envelopes. © 2010 The Author(s).

Progressive recovery of a tropical deforested stream community after a flash flood

AIM: In this study, we evaluated and compared community attributes from a tropical deforested stream, located in a pasture area, in a period before (PRED I) and three times after (POSD I, II, and III) a flash flood, in order to investigate the existence of temporal modifications in community structure that suggests return to conditions previous to the flash flood. METHODS: Biota samples included algae, macrophytes, macroinvertebrates, and fish assemblages. Changes in stream physical structure we also evaluated. Similarity of the aquatic biota between pre and post-disturbance periods was examined by exploratory ordination, known as Non-Metric Multidimensional Scaling associated with Cluster Analysis, using quantitative and presence/absence Bray-Curtis similarity coefficients. Presence and absence data were used for multivariate correlation analysis (Relate Analysis) in order to investigate taxonomic composition similarity of biota between pre and post-disturbance periods. RESULTS: Our results evidenced channel simplification and an expressive decrease in richness and abundance of all taxa right after the flood, followed by subsequent increases of these parameters in the next three samples, indicating trends towards stream community recovery. Bray-Curtis similarity coefficients evidenced a greater community structure disparity among the period right after the flood and the subsequent ones. Multivariate correlation analysis evidenced a greater correlation between macroinvertebrates and algae/macrophytes, demonstrating the narrow relation between their recolonization dynamics. CONCLUSIONS: Despite overall community structure tended to return to previous conditions, recolonization after the flood was much slower than that reported in literature. Finally, the remarkably high flood impact along with the slow recolonization could be a result of the historical presence of anthropic impacts in the region, such as siltation, riparian forest complete depletion, and habitat simplification, which magnified the effects of a natural disturbance.