Assessing the effects of pseudo-absences on predictive distribution model performance

Climate change impact on ecosystem functions provided by birds in southeastern Amazonia

Although the impacts of climate change on biodiversity are increasing worldwide, few studies have attempted to forecast these impacts on Amazon Tropical Forest. In this study, we estimated the impact of climate change on Amazonian avian assemblages considering range shifts, species loss, vulnerability of ecosystem functioning, future effectiveness of current protected areas and potential climatically stable areas for conservation actions. Species distribution modelling based on two algorithms and three different scenarios of climate change was used to forecast 501 avian species, organized on main ecosystem functions (frugivores, insectivores and nectarivores) for years 2050 and 2070. Considering the entire study area, we estimated that between 4 and 19% of the species will find no suitable habitat. Inside the currently established protected areas, species loss could be over 70%. Our results suggest that frugivores are the most sensitive guild, which could bring consequences on seed dispersal functions and on natural regeneration. Moreover, we identified the western and northern parts of the study area as climatically stable. Climate change will potentially affect avian assemblages in southeastern Amazonia with detrimental consequences to their ecosystem functions. Information provided here is essential to conservation practitioners and decision makers to help on planning their actions.

Multi-Scenario Species Distribution Modeling

Correlative species distribution models (SDMs) are increasingly being used to predict suitable insect habitats. There is also much criticism of prediction discrepancies among different SDMs for the same species and the lack of effective communication about SDM prediction uncertainty. In this paper, we undertook a factorial study to investigate the effects of various modeling components (species-training-datasets, predictor variables, dimension-reduction methods, and model types) on the accuracy of SDM predictions, with the aim of identifying sources of discrepancy and uncertainty. We found that model type was the major factor causing variation in species-distribution predictions among the various modeling components tested. We also found that different combinations of modeling components could significantly increase or decrease the performance of a model. This result indicated the importance of keeping modeling components constant for comparing a given SDM result. With all modeling components, constant, machine-learning models seem to outperform other model types. We also found that, on average, the Hierarchical Non-Linear Principal Components Analysis dimension-reduction method improved model performance more than other methods tested. We also found that the widely used confusion-matrix-based model-performance indices such as the area under the receiving operating characteristic curve (AUC), sensitivity, and Kappa do not necessarily help select the best model from a set of models if variation in performance is not large. To conclude, model result discrepancies do not necessarily suggest lack of robustness in correlative modeling as they can also occur due to inappropriate selection of modeling components. In addition, more research on model performance evaluation is required for developing robust and sensitive model evaluation methods. Undertaking multi-scenario species-distribution modeling, where possible, is likely to mitigate errors arising from inappropriate modeling components selection, and provide end users with better information on the resulting model prediction uncertainty.

Evidences for a shared history for spectacled salamanders, haplotypes and climate

The so-called glacial refugia, formed during the Pleistocene climatic oscillations, played a major role in shaping the distribution of European species, triggering migrations or isolating populations. Many of these events were recently investigated by genetic data, mainly for the European Last Glacial stage, in the Iberic, Italian and Greek-Balkan peninsulas. The amphibian genus Salamandrina, the most ancient living salamandrid lineage, was widespread in Europe until the climatic oscillations of Miocene probably forced it to shelter in the only suitable territory at that time, the Apennines. Nowadays this genus is endemic of peninsular Italy with two parapatric species, S. perspicillata and S. terdigitata, sharing an area of secondary contact formed after the Last Glacial Maximum. Climate is generally identified as the key factor for the interpretation of genetic data. In this research, we directly measure climate influences on the two Salamandrina known species through Ensemble Modelling techniques and post-modelling GIS analyses, integrating updated genetic data in this process. Our results confirm the hypotheses of southwards (and subsequent northwards) shifts, identify glacial refugia and corridors used for the post-glacial re-colonization. Finally, we map a contact zone deserving more sampling effort to disentangle the introgression and hybridization observed.

Predicted extinction of unique genetic diversity in marine forests of Cystoseira spp

Climate change is inducing shifts in species ranges across the globe. These can affect the genetic pools of species, including loss of genetic variability and evolutionary potential. In particular, geographically enclosed ecosystems, like the Mediterranean Sea, have a higher risk of suffering species loss and genetic erosion due to barriers to further range shifts and to dispersal. In this study, we address these questions for three habitat-forming seaweed species, Cystoseira tamariscifolia, C. amentacea and C. compressa, throughout their entire ranges in the Atlantic and Mediterranean regions. We aim to 1) describe their population genetic structure and diversity, 2) model the present and predict the future distribution and 3) assess the consequences of predicted future range shifts for their population genetic structure, according to two contrasting future climate change scenarios. A net loss of suitable areas was predicted in both climatic scenarios across the range of distribution of the three species. This loss was particularly severe for C. amentacea in the Mediterranean Sea (less 90% in the most extreme climatic scenario), suggesting that the species could become potentially at extinction risk. For all species, genetic data showed very differentiated populations, indicating low inter-population connectivity, and high and distinct genetic diversity in areas that were predicted to become lost, causing erosion of unique evolutionary lineages. Our results indicated that the Mediterranean Sea is the most threatened region, where future suitable Cystoseira habitats will become more limited. This is likely to have wider ecosystem impacts as there is a lack of species with the same ecological niche and functional role in the Mediterranean. The projected accelerated loss of already fragmented and disturbed populations and the long-term genetic effects highlight the urge for local scale management strategies that sustain the capacity of these habitat-forming species to persist despite climatic impacts while waiting for global emission reductions.

Coupling GIS spatial analysis and Ensemble Niche Modelling to investigate climate change-related threats to the Sicilian pond turtle Emys trinacris, an endangered species from the Mediterranean

The pond turtle Emys trinacris is an endangered endemic species of Sicily showing a fragmented distribution throughout the main island. In this study, we applied "Ensemble Niche Modelling", combining more classical statistical techniques as Generalized Linear Models and Multivariate Adaptive Regression Splines with machine-learning approaches as Boosted Regression Trees and Maxent, to model the potential distribution of the species under current and future climatic conditions. Moreover, a "gap analysis" performed on both the species' presence sites and the predictions from the Ensemble Models is proposed to integrate outputs from these models, in order to assess the conservation status of this threatened species in the context of biodiversity management. For this aim, four "Representative Concentration Pathways", corresponding to different greenhouse gases emissions trajectories were considered to project the obtained models to both 2050 and 2070. Areas lost, gained or remaining stable for the target species in the projected models were calculated. E. trinacris' potential distribution resulted to be significantly dependent upon precipitation-linked variables, mainly precipitation of wettest and coldest quarter. Future negative effects for the conservation of this species, because of more unstable precipitation patterns and extreme meteorological events, emerged from our analyses. Further, the sites currently inhabited by E. trinacris are, for more than a half, out of the Protected Areas network, highlighting an inadequate management of the species by the authorities responsible for its protection. Our results, therefore, suggest that in the next future the Sicilian pond turtle will need the utmost attention by the scientific community to avoid the imminent risk of extinction. Finally, the gap analysis performed in GIS environment resulted to be a very informative post-modeling technique, potentially applicable to the management of species at risk and to Protected Areas' planning in many contexts.

Evaluating Efficacy of Landsat-Derived Environmental Covariates for Predicting Malaria Distribution in Rural Villages of Vhembe District, South Africa

Malaria in South Africa is still a problem despite existing efforts to eradicate the disease. In the Vhembe District Municipality, malaria prevalence is still high, with a mean incidence rate of 328.2 per 100,0000 persons/year. This study aimed at evaluating environmental covariates, such as vegetation moisture and vegetation greenness, associated with malaria vector distribution for better predictability towards rapid and efficient disease management and control. The 2005 malaria incidence data combined with Landsat 5 ETM were used in this study. A total of nine remotely sensed covariates were derived, while pseudo-absences in the ratio of 1:2 (presence/absence) were generated at buffer distances of 0.5-20 km from known presence locations. A stepwise logistic regression model was applied to analyse the spatial distribution of malaria in the area. A buffer distance of 10 km yielded the highest classification accuracy of 82% at a threshold of 0.9. This model was significant (ρ < 0.05) and yielded a deviance (D²) of 36%. The significantly positive relationship (ρ < 0.05) between the soil-adjusted vegetation index and malaria distribution at all buffer distances suggests that malaria vector (Anopheles arabiensis) prefer productive and greener vegetation. The significant negative relationship between water/moisture index (a₁ index) and malaria distribution in buffer distances of 0.5, 10, and 20 km suggest that malaria distribution increases with a decrease in shortwave reflectance signal. The study has shown that suitable habitats of malaria vectors are generally found within a radius of 10 km in semi-arid environments, and this insight can be useful to aid efforts aimed at putting in place evidence-based preventative measures against malaria infections. Furthermore, this result is important in understanding malaria dynamics under the current climate and environmental changes. The study has also demonstrated the use of Landsat data and the ability to extract environmental conditions which favour the distribution of malaria vector (An. arabiensis) such as the canopy moisture content in vegetation, which serves as a surrogate for rainfall.

Projected climate changes threaten ancient refugia of kelp forests in the North Atlantic

Intraspecific genetic variability is critical for species adaptation and evolution and yet it is generally overlooked in projections of the biological consequences of climate change. We ask whether ongoing climate changes can cause the loss of important gene pools from North Atlantic relict kelp forests that persisted over glacial-interglacial cycles. We use ecological niche modelling to predict genetic diversity hotspots for eight species of large brown algae with different thermal tolerances (Arctic to warm temperate), estimated as regions of persistence throughout the Last Glacial Maximum (20,000 YBP), the warmer Mid-Holocene (6,000 YBP), and the present. Changes in the genetic diversity within ancient refugia were projected for the future (year 2100) under two contrasting climate change scenarios (RCP2.6 and RCP8.5). Models predicted distributions that matched empirical distributions in cross-validation, and identified distinct refugia at the low latitude ranges, which largely coincide among species with similar ecological niches. Transferred models into the future projected polewards expansions and substantial range losses in lower latitudes, where richer gene pools are expected (in Nova Scotia and Iberia for cold affinity species and Gibraltar, Alboran, and Morocco for warm-temperate species). These effects were projected for both scenarios but were intensified under the extreme RCP8.5 scenario, with the complete borealization (circum-Arctic colonization) of kelp forests, the redistribution of the biogeographical transitional zones of the North Atlantic, and the erosion of global gene pools across all species. As the geographic distribution of genetic variability is unknown for most marine species, our results represent a baseline for identification of locations potentially rich in unique phylogeographic lineages that are also climatic relics in threat of disappearing.

Habitat suitability and connectivity for an endangered brown bear population in the Iranian Caucasus

Context The identification of suitable habitats and the assessment of connectivity are important to preserve key areas for small isolated, endangered populations. The brown bear, Ursus arctos, needs connectivity to supply the primary habitat requirements including food, water, shelter and space and to provide gene flow among all populations in the Iranian Caucasus. Aims In the present study, we investigated the status and habitat requirements of an endangered brown bear population within the Iranian Caucasus. Methods We applied an approach of consensus species distribution modelling to estimate the distribution of suitable habitats for brown bears using uncorrelated environmental variables. We then used the concept of circuit theory on resultant breeding patches to evaluate regional patterns of connectivity among these patches. Key results We predicted that ~9.10% of the study area is suitable for the brown bear at present. Ten patches (7.95% of the study area) were detected as suitable for breeding populations, where some populations are not able to survive without connectivity. The results indicated that habitat connectivity is sometimes widely affected by a high concentration of human activities such as roads, settlements and mining activities. Our findings showed that existing conservation areas could not safeguard the connectivity of brown bear habitats across the Iranian Caucasus. Conclusions Our results can help target fine-scaled planning approaches for the maintenance of bear meta-population structure, as well as facilitate the movement of individuals by protecting different landscape features. Implications The populations of brown bear are among the first to be harmed by the loss of habitat and connectivity, and, thus, this species is an appropriate focal species for linkage design that is beneficial for threatened populations of other co-existing species such as Persian leopard, grey wolf and Eurasian lynx. Moreover, the brown bear is among the most popular flagship species for conservation planning, which might increase public support for the restoration of habitat and linkages.

Unraveling climate influences on the distribution of the parapatric newts Lissotriton vulgaris meridionalis and L. italicus

Background

Climate is often considered as a key ecological factor limiting the capability of expansion of most species and the extent of suitable habitats. In this contribution, we implement Species Distribution Models (SDMs) to study two parapatric amphibians, Lissotriton vulgaris meridionalis and L. italicus, investigating if and how climate has influenced their present and past (Last Glacial Maximum and Holocene) distributions. A database of 901 GPS presence records was generated for the two newts. SDMs were built through Boosted Regression Trees and Maxent, using the Worldclim bioclimatic variables as predictors.

Results

Precipitation-linked variables and the temperature annual range strongly influence the current occurrence patterns of the two Lissotriton species analyzed. The two newts show opposite responses to the most contributing variables, such as BIO7 (temperature annual range), BIO12 (annual precipitation), BIO17 (precipitation of the driest quarter) and BIO19 (precipitation of the coldest quarter). The hypothesis of climate influencing the distributions of these species is also supported by the fact that the co-occurrences within the sympatric area fall in localities characterized by intermediate values of these predictors. Projections to the Last Glacial Maximum and Holocene scenarios provided a coherent representation of climate influences on the past distributions of the target species. Computation of pairwise variables interactions and the discriminant analysis allowed a deeper interpretation of SDMs’ outputs. Further, we propose a multivariate environmental dissimilarity index (MEDI), derived through a transformation of the multivariate environmental similarity surface (MESS), to deal with extrapolation-linked uncertainties in model projections to past climate. Finally, the niche equivalency and niche similarity tests confirmed the link between SDMs outputs and actual differences in the ecological niches of the two species.

Conclusions

The different responses of the two species to climatic factors have significantly contributed to shape their current distribution, through contractions, expansions and shifts over time, allowing to maintain two wide allopatric areas with an area of sympatry in Central Italy. Moreover, our SDMs hindcasting shows many concordances with previous phylogeographic studies carried out on the same species, thus corroborating the scenarios of potential distribution during the Last Glacial Maximum and the Holocene emerging from the models obtained.

Electronic supplementary material

The online version of this article (10.1186/s12983-017-0239-4) contains supplementary material, which is available to authorized users.

Lowland extirpation of anuran populations on a tropical mountain

Background

Climate change and infectious diseases threaten animal and plant species, even in natural and protected areas. To cope with these changes, species may acclimate, adapt, move or decline. Here, we test for shifts in anuran distributions in the Luquillo Mountains (LM), a tropical montane forest in Puerto Rico by comparing species distributions from historical (1931–1989)and current data (2015/2016).

Methods

Historical data, which included different methodologies, were gathered through the Global Biodiversity Information Facility (GBIF) and published literature, and the current data were collected using acoustic recorders along three elevational transects.

Results

In the recordings, we detected the 12 native frog species known to occur in LM. Over a span of ∼25 years, two species have become extinct and four species suffered extirpation in lowland areas. As a consequence, low elevation areas in the LM (<300 m) have lost at least six anuran species.

Discussion

We hypothesize that these extirpations are due to the effects of climate change and infectious diseases, which are restricting many species to higher elevations and a much smaller area. Land use change is not responsible for these changes because LM has been a protected reserve for the past 80 years. However, previous studies indicate that (1) climate change has increased temperatures in Puerto Rico, and (2) Batrachochytrium dendrobatidis (Bd) was found in 10 native species and early detection of Bd coincides with anurans declines in the LM. Our study confirms the general impressions of amphibian population extirpations at low elevations, and corroborates the levels of threat assigned by IUCN.

Evidence for rangewide panmixia despite multiple barriers to dispersal in a marine mussel

Oceanographic features shape the distributional and genetic patterns of marine species by interrupting or promoting connections among populations. Although general patterns commonly arise, distributional ranges and genetic structure are species-specific and do not always comply with the expected trends. By applying a multimarker genetic approach combined with Lagrangian particle simulations (LPS) we tested the hypothesis that oceanographic features along northeastern Atlantic and Mediterranean shores influence dispersal potential and genetic structure of the intertidal mussel Perna perna. Additionally, by performing environmental niche modelling we assessed the potential and realized niche of P. perna along its entire native distributional range and the environmental factors that best explain its realized distribution. Perna perna showed evidence of panmixia across >4,000 km despite several oceanographic breaking points detected by LPS. This is probably the result of a combination of life history traits, continuous habitat availability and stepping-stone dynamics. Moreover, the niche modelling framework depicted minimum sea surface temperatures (SST) as the major factor shaping P. perna distributional range limits along its native areas. Forthcoming warming SST is expected to further change these limits and allow the species to expand its range polewards though this may be accompanied by retreat from warmer areas.

Spatial models to account for variation in observer effort in bird atlases

To assess the importance of variation in observer effort between and within bird atlas projects and demonstrate the use of relatively simple conditional autoregressive (CAR) models for analyzing grid‐based atlas data with varying effort. Pennsylvania and West Virginia, United States of America. We used varying proportions of randomly selected training data to assess whether variations in observer effort can be accounted for using CAR models and whether such models would still be useful for atlases with incomplete data. We then evaluated whether the application of these models influenced our assessment of distribution change between two atlas projects separated by twenty years (Pennsylvania), and tested our modeling methodology on a state bird atlas with incomplete coverage (West Virginia). Conditional Autoregressive models which included observer effort and landscape covariates were able to make robust predictions of species distributions in cases of sparse data coverage. Further, we found that CAR models without landscape covariates performed favorably. These models also account for variation in observer effort between atlas projects and can have a profound effect on the overall assessment of distribution change. Accounting for variation in observer effort in atlas projects is critically important. CAR models provide a useful modeling framework for accounting for variation in observer effort in bird atlas data because they are relatively simple to apply, and quick to run.

Palaeoclimatic conditions in the Mediterranean explain genetic diversity of Posidonia oceanica seagrass meadows

Past environmental conditions in the Mediterranean Sea have been proposed as main drivers of the current patterns of distribution of genetic structure of the seagrass Posidonia oceanica, the foundation species of one of the most important ecosystems in the Mediterranean Sea. Yet, the location of cold climate refugia (persistence regions) for this species during the Last Glacial Maximum (LGM) is not clear, precluding the understanding of its biogeographical history. We used Ecological Niche Modelling together with existing phylogeographic data to locate Pleistocene refugia in the Mediterranean Sea and to develop a hypothetical past biogeographical distribution able to explain the genetic diversity presently found in P. oceanica meadows. To do that, we used an ensemble approach of six predictive algorithms and two Ocean General Circulation Models. The minimum SST in winter and the maximum SST in summer allowed us to hindcast the species range during the LGM. We found separate glacial refugia in each Mediterranean basin and in the Central region. Altogether, the results suggest that the Central region of the Mediterranean Sea was the most relevant cold climate refugium, supporting the hypothesis that long-term persistence there allowed the region to develop and retain its presently high proportion of the global genetic diversity of P. oceanica.

Environmental niche divergence among three dune shrub sister species with parapatric distributions

BACKGROUND AND AIMS

The geographical distributions of species are constrained by their ecological requirements. The aim of this work was to analyse the effects of environmental conditions, historical events and biogeographical constraints on the diversification of the three species of the western Mediterranean shrub genus Stauracanthus , which have a parapatric distribution in the Iberian Peninsula.

METHODS

Ecological niche factor analysis and generalized linear models were used to measure the response of all Stauracanthus species to the environmental gradients and map their potential distributions in the Iberian Peninsula. The bioclimatic niche overlap between the three species was determined by using Schoener's index. The genetic differentiation of the Iberian and northern African populations of Stauracanthus species was characterized with GenalEx. The effects on genetic distances of the most important environmental drivers were assessed through Mantel tests and non-metric multidimensional scaling.

KEY RESULTS

The three Stauracanthus species show remarkably similar responses to climatic conditions. This supports the idea that all members of this recently diversified clade retain common adaptations to climate and consequently high levels of climatic niche overlap. This contrasts with the diverse edaphic requirements of Stauracanthus species. The populations of the S. genistoides-spectabilis clade grow on Miocene and Pliocene fine-textured sedimentary soils, whereas S. boivinii , the more genetically distant species, occurs on older and more coarse-textured sedimentary substrates. These patterns of diversification are largely consistent with a stochastic process of geographical range expansion and fragmentation coupled with niche evolution in the context of spatially complex environmental fluctuations.

CONCLUSIONS

: The combined analysis of the distribution, realized environmental niche and phylogeographical relationships of parapatric species proposed in this work allows integration of the biogeographical, ecological and evolutionary processes driving the evolution of species adaptations and how they determine their current geographical ranges.

High unexpected genetic diversity of a narrow endemic terrestrial mollusc

The Iberian Peninsula has an extensive record of species displaying strong genetic structure as a result of their survival in isolated pockets throughout the Pleistocene ice ages. We used mitochondrial and nuclear sequence data to analyze phylogeographic patterns in endemic land snails from a valley of central Portugal (Vale da Couda), putatively assigned to Candidula coudensis, that show an exceptionally narrow distributional range. The genetic survey presented here shows the existence of five main mitochondrial lineages in Vale da Couda that do not cluster together suggesting independent evolutionary histories. Our results also indicate a departure from the expectation that species with restricted distributions have low genetic variability. The putative past and contemporary models of geographic distribution of Vale da Couda lineages are compatible with a scenario of species co-existence in more southern locations during the last glacial maximum (LGM) followed by a post-LGM northern dispersal tracking the species optimal thermal, humidity and soil physical conditions.

Major shifts at the range edge of marine forests: the combined effects of climate changes and limited dispersal

Global climate change is likely to constrain low latitude range edges across many taxa and habitats. Such is the case for NE Atlantic marine macroalgal forests, important ecosystems whose main structuring species is the annual kelp Saccorhiza polyschides. We coupled ecological niche modelling with simulations of potential dispersal and delayed development stages to infer the major forces shaping range edges and to predict their dynamics. Models indicated that the southern limit is set by high winter temperatures above the physiological tolerance of overwintering microscopic stages and reduced upwelling during recruitment. The best range predictions were achieved assuming low spatial dispersal (5 km) and delayed stages up to two years (temporal dispersal). Reconstructing distributions through time indicated losses of ~30% from 1986 to 2014, restricting S. polyschides to upwelling regions at the southern edge. Future predictions further restrict populations to a unique refugium in northwestern Iberia. Losses were dependent on the emissions scenario, with the most drastic one shifting ~38% of the current distribution by 2100. Such distributional changes might not be rescued by dispersal in space or time (as shown for the recent past) and are expected to drive major biodiversity loss and changes in ecosystem functioning.

Potential Impacts of Climate Change on Native Plant Distributions in the Falkland Islands

The Falkland Islands are predicted to experience up to 2.2°C rise in mean annual temperature over the coming century, greater than four times the rate over the last century. Our study investigates likely vulnerabilities of a suite of range-restricted species whose distributions are associated with archipelago-wide climatic variation. We used present day climate maps calibrated using local weather data, 2020–2080 climate predictions from regional climate models, non-climate variables derived from a digital terrain model and a comprehensive database on local plant distributions. Weighted mean ensemble models were produced to assess changes in range sizes and overlaps between the current range and protected areas network. Target species included three globally threatened Falkland endemics, Nassauvia falklandica, Nastanthus falklandicus and Plantago moorei; and two nationally threatened species, Acaena antarctica and Blechnum cordatum. Our research demonstrates that temperature increases predicted for the next century have the potential to significantly alter plant distributions across the Falklands. Upland species, in particular, were found to be highly vulnerable to climate change impacts. No known locations of target upland species or the southwestern species Plantago moorei are predicted to remain environmentally suitable in the face of predicted climate change. We identify potential refugia for these species and associated gaps in the current protected areas network. Species currently restricted to the milder western parts of the archipelago are broadly predicted to expand their ranges under warmer temperatures. Our results emphasise the importance of implementing suitable adaptation strategies to offset climate change impacts, particularly site management. There is an urgent need for long-term monitoring and artificial warming experiments; the results of this study will inform the selection of the most suitable locations for these. Results are also helping inform management recommendations for the Falkland Islands Government who seek to better conserve their biodiversity and meet commitments to multi-lateral environmental agreements.

Overlooked habitat of a vulnerable gorgonian revealed in the Mediterranean and Eastern Atlantic by ecological niche modelling

Factors shaping the distribution of mesophotic octocorals (30-200 m depth) remain poorly understood, potentially leaving overlooked coral areas, particularly near their bathymetric and geographic distributional limits. Yet, detailed knowledge about habitat requirements is crucial for conservation of sensitive gorgonians. Here we use Ecological Niche Modelling (ENM) relating thirteen environmental predictors and a highly comprehensive presence dataset, enhanced by SCUBA diving surveys, to investigate the suitable habitat of an important structuring species, Paramuricea clavata, throughout its distribution (Mediterranean and adjacent Atlantic). Models showed that temperature (11.5-25.5 °C) and slope are the most important predictors carving the niche of P. clavata. Prediction throughout the full distribution (TSS 0.9) included known locations of P. clavata alongside with previously unknown or unreported sites along the coast of Portugal and Africa, including seamounts. These predictions increase the understanding of the potential distribution for the northern Mediterranean and indicate suitable hard bottom areas down to >150 m depth. Poorly sampled habitats with predicted presence along Algeria, Alboran Sea and adjacent Atlantic coasts encourage further investigation. We propose that surveys of target areas from the predicted distribution map, together with local expert knowledge, may lead to discoveries of new P. clavata sites and identify priority conservation areas.

Patchiness of forest landscape can predict species distribution better than abundance: the case of a forest-dwelling passerine, the short-toed treecreeper, in central Italy

Environmental heterogeneity affects not only the distribution of a species but also its local abundance. High heterogeneity due to habitat alteration and fragmentation can influence the realized niche of a species, lowering habitat suitability as well as reducing local abundance. We investigate whether a relationship exists between habitat suitability and abundance and whether both are affected by fragmentation. Our aim was to assess the predictive power of such a relationship to derive advice for environmental management. As a model species we used a forest specialist, the short-toed treecreeper (Family: Certhiidae; Certhia brachydactyla Brehm, 1820), and sampled it in central Italy. Species distribution was modelled as a function of forest structure, productivity and fragmentation, while abundance was directly estimated in two central Italian forest stands. Different algorithms were implemented to model species distribution, employing 170 occurrence points provided mostly by the MITO2000 database: an artificial neural network, classification tree analysis, flexible discriminant analysis, generalized boosting models, generalized linear models, multivariate additive regression splines, maximum entropy and random forests. Abundance was estimated also considering detectability, through N-mixture models. Differences between forest stands in both abundance and habitat suitability were assessed as well as the existence of a relationship. Simpler algorithms resulted in higher goodness of fit than complex ones. Fragmentation was highly influential in determining potential distribution. Local abundance and habitat suitability differed significantly between the two forest stands, which were also significantly different in the degree of fragmentation. Regression showed that suitability has a weak significant effect in explaining increasing value of abundance. In particular, local abundances varied both at low and high suitability values. The study lends support to the concept that the degree of fragmentation can contribute to alter not only the suitability of an area for a species, but also its abundance. Even if the relationship between suitability and abundance can be used as an early warning of habitat deterioration, its weak predictive power needs further research. However, we define relationships between a species and some landscape features (i.e., fragmentation, extensive rejuvenation of forests and tree plantations) which could be easily controlled by appropriate forest management planning to enhance environmental suitability, at least in an area possessing high conservation and biodiversity values.

Where to Dig for Fossils: Combining Climate-Envelope, Taphonomy and Discovery Models

Fossils represent invaluable data to reconstruct the past history of life, yet fossil-rich sites are often rare and difficult to find. The traditional fossil-hunting approach focuses on small areas and has not yet taken advantage of modelling techniques commonly used in ecology to account for an organism's past distributions. We propose a new method to assist finding fossils at continental scales based on modelling the past distribution of species, the geological suitability of fossil preservation and the likelihood of fossil discovery in the field, and apply it to several genera of Australian megafauna that went extinct in the Late Quaternary. Our models predicted higher fossil potentials for independent sites than for randomly selected locations (mean Kolmogorov-Smirnov statistic = 0.66). We demonstrate the utility of accounting for the distribution history of fossil taxa when trying to find the most suitable areas to look for fossils. For some genera, the probability of finding fossils based on simple climate-envelope models was higher than the probability based on models incorporating current conditions associated with fossil preservation and discovery as predictors. However, combining the outputs from climate-envelope, preservation, and discovery models resulted in the most accurate predictions of potential fossil sites at a continental scale. We proposed potential areas to discover new fossils of Diprotodon, Zygomaturus, Protemnodon, Thylacoleo, and Genyornis, and provide guidelines on how to apply our approach to assist fossil hunting in other continents and geological settings.

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.

Worldwide Alien Invasion: A Methodological Approach to Forecast the Potential Spread of a Highly Invasive Pollinator

The ecological impacts of alien species invasion are a major threat to global biodiversity. The increasing number of invasion events by alien species and the high cost and difficulty of eradicating invasive species once established require the development of new methods and tools for predicting the most susceptible areas to invasion. Invasive pollinators pose serious threats to biodiversity and human activity due to their close relationship with many plants (including crop species) and high potential competitiveness for resources with native pollinators. Although at an early stage of expansion, the bumblebee species Bombus terrestris is becoming a representative case of pollinator invasion at a global scale, particularly given its high velocity of invasive spread and the increasing number of reports of its impacts on native bees and crops in many countries. We present here a methodological framework of habitat suitability modeling that integrates new approaches for detecting habitats that are susceptible to Bombus terrestris invasion at a global scale. Our approach did not include reported invaded locations in the modeling procedure; instead, those locations were used exclusively to evaluate the accuracy of the models in predicting suitability over regions already invaded. Moreover, a new and more intuitive approach was developed to select the models and evaluate different algorithms based on their performance and predictive convergence. Finally, we present a comprehensive global map of susceptibility to Bombus terrestris invasion that highlights priority areas for monitoring.

Future climate change is predicted to shift long-term persistence zones in the cold-temperate kelp Laminaria hyperborea

Global climate change is shifting species distributions worldwide. At rear edges (warmer, low latitude range margins), the consequences of small variations in environmental conditions can be magnified, producing large negative effects on species ranges. A major outcome of shifts in distributions that only recently received attention is the potential to reduce the levels of intra-specific diversity and consequently the global evolutionary and adaptive capacity of species to face novel disturbances. This is particularly important for low dispersal marine species, such as kelps, that generally retain high and unique genetic diversity at rear ranges resulting from long-term persistence, while ranges shifts during climatic glacial/interglacial cycles. Using ecological niche modelling, we (1) infer the major environmental forces shaping the distribution of a cold-temperate kelp, Laminaria hyperborea (Gunnerus) Foslie, and we (2) predict the effect of past climate changes in shaping regions of long-term persistence (i.e., climatic refugia), where this species might hypothetically harbour higher genetic diversity given the absence of bottlenecks and local extinctions over the long term. We further (3) assessed the consequences of future climate for the fate of L. hyperborea using different scenarios of greenhouse gas emissions (RCP 2.6 and RCP 8.5). Results show NW Iberia, SW Ireland and W English Channel, Faroe Islands and S Iceland, as regions where L. hyperborea may have persisted during past climate extremes until present day. All predictions for the future showed expansions to northern territories coupled with the significant loss of suitable habitats at low latitude range margins, where long-term persistence was inferred (e.g., NW Iberia). This pattern was particularly evident in the most agressive scenario of climate change (RCP 8.5), likely driving major biodiversity loss, changes in ecosystem functioning and the impoverishment of the global gene pool of L. hyperborea. Because no genetic baseline is currently available for this species, our results may represent a first step in informing conservation and mitigation strategies.

Dengue: recent past and future threats

This article explores four key questions about statistical models developed to describe the recent past and future of vector-borne diseases, with special emphasis on dengue: (1) How many variables should be used to make predictions about the future of vector-borne diseases? (2) Is the spatial resolution of a climate dataset an important determinant of model accuracy? (3) Does inclusion of the future distributions of vectors affect predictions of the futures of the diseases they transmit? (4) Which are the key predictor variables involved in determining the distributions of vector-borne diseases in the present and future? Examples are given of dengue models using one, five or 10 meteorological variables and at spatial resolutions of from one-sixth to two degrees. Model accuracy is improved with a greater number of descriptor variables, but is surprisingly unaffected by the spatial resolution of the data. Dengue models with a reduced set of climate variables derived from the HadCM3 global circulation model predictions for the 1980s are improved when risk maps for dengue's two main vectors (Aedes aegypti and Aedes albopictus) are also included as predictor variables; disease and vector models are projected into the future using the global circulation model predictions for the 2020s, 2040s and 2080s. The Garthwaite-Koch corr-max transformation is presented as a novel way of showing the relative contribution of each of the input predictor variables to the map predictions.

Effects of Climate Change on Habitat Availability and Configuration for an Endemic Coastal Alpine Bird

North America's coastal mountains are particularly vulnerable to climate change, yet harbour a number of endemic species. With little room "at the top" to track shifting climate envelopes, alpine species may be especially negatively affected by climate-induced habitat fragmentation. We ask how climate change will affect the total amount, mean patch size, and number of patches of suitable habitat for Vancouver Island White-tailed Ptarmigan (Lagopus leucura saxatilis; VIWTP), a threatened, endemic alpine bird. Using a Random Forest model and a unique dataset consisting of citizen science observations combined with field surveys, we predict the distribution and configuration of potential suitable summer habitat for VIWTP under baseline and future (2020s, 2050s, and 2080s) climates using three general circulation models and two greenhouse gas scenarios. VIWTP summer habitat is predicted to decline by an average of 25%, 44%, and 56% by the 2020s, 2050s, and 2080s, respectively, under the low greenhouse gas scenario and 27%, 59%, and 74% under the high scenario. Habitat patches are predicted to become fragmented, with a 52-79% reduction in mean patch size. The average elevation of suitable habitat patches is expected to increase, reflecting a loss of patches at lower elevations. Thus ptarmigan are in danger of being "squeezed off the mountain", as their remaining suitable habitat will be increasingly confined to mountaintops in the center of the island. The extent to which ptarmigan will be able to persist in increasingly fragmented habitat is unclear. Much will depend on their ability to move throughout a more heterogeneous landscape, utilize smaller breeding areas, and survive increasingly variable climate extremes. Our results emphasize the importance of continued monitoring and protection for high elevation specialist species, and suggest that White-tailed Ptarmigan should be considered an indicator species for alpine ecosystems in the face of climate change.

Ecological niche models of invasive seaweeds

Ecological niche models (ENMs) are commonly used to calculate habitat suitability from species' occurrence and macroecological data. In invasive species biology, ENMs can be applied to anticipate whether invasive species are likely to establish in an area, to identify critical routes and arrival points, to build risk maps and to predict the extent of potential spread following an introduction. Most studies using ENMs focus on terrestrial organisms and applications in the marine realm are still relatively rare. Here, we review some common methods to build ENMs and their application in seaweed invasion biology. We summarize methods and concepts involved in the development of niche models, show examples of how they have been applied in studies on algae and discuss the application of ENMs in invasive algae research and to predict effects of climate change on seaweed distributions.

The global distribution of Crimean-Congo hemorrhagic fever

BACKGROUND

Crimean-Congo hemorrhagic fever (CCHF) is a tick-borne infection caused by a virus (CCHFV) from the Bunyaviridae family. Domestic and wild vertebrates are asymptomatic reservoirs for the virus, putting animal handlers, slaughter-house workers and agricultural labourers at highest risk in endemic areas, with secondary transmission possible through contact with infected blood and other bodily fluids. Human infection is characterized by severe symptoms that often result in death. While it is known that CCHFV transmission is limited to Africa, Asia and Europe, definitive global extents and risk patterns within these limits have not been well described.

METHODS

We used an exhaustive database of human CCHF occurrence records and a niche modeling framework to map the global distribution of risk for human CCHF occurrence.

RESULTS

A greater proportion of shrub or grass land cover was the most important contributor to our model, which predicts highest levels of risk around the Black Sea, Turkey, and some parts of central Asia. Sub-Saharan Africa shows more focalized areas of risk throughout the Sahel and the Cape region.

CONCLUSIONS

These new risk maps provide a valuable starting point for understanding the zoonotic niche of CCHF, its extent and the risk it poses to humans.

Genes Left Behind: Climate Change Threatens Cryptic Genetic Diversity in the Canopy-Forming Seaweed Bifurcaria bifurcata

The global redistribution of biodiversity will intensify in the coming decades of climate change, making projections of species range shifts and of associated genetic losses important components of conservation planning. Highly-structured marine species, notably brown seaweeds, often harbor unique genetic variation at warmer low-latitude rear edges and thus are of particular concern. Here, a combination of Ecological Niche Models (ENMs) and molecular data is used to forecast the potential near-future impacts of climate change for a warm-temperate, canopy forming seaweed, Bifurcaria bifurcata. ENMs for B. bifurcata were developed using marine and terrestrial climatic variables, and its range projected for 2040-50 and 2090-2100 under two greenhouse emission scenarios. Geographical patterns of genetic diversity were assessed by screening 18 populations spawning the entire distribution for two organelle genes and 6 microsatellite markers. The southern limit of B. bifurcata was predicted to shift northwards to central Morocco by the mid-century. By 2090-2100, depending on the emission scenario, it could either retreat further north to western Iberia or be relocated back to Western Sahara. At the opposing margin, B. bifurcata was predicted to expand its range to Scotland or even Norway. Microsatellite diversity and endemism were highest in Morocco, where a unique and very restricted lineage was also identified. Our results imply that B. bifurcata will maintain a relatively broad latitudinal distribution. Although its persistence is not threatened, the predicted extirpation of a unique southern lineage or even the entire Moroccan diversity hotspot will erase a rich evolutionary legacy and shrink global diversity to current (low) European levels. NW Africa and similarly understudied southern regions should receive added attention if expected range changes and diversity loss of warm-temperate species is not to occur unnoticed.

Oceanographic Conditions Limit the Spread of a Marine Invader along Southern African Shores

Invasive species can affect the function and structure of natural ecological communities, hence understanding and predicting their potential for spreading is a major ecological challenge. Once established in a new region, the spread of invasive species is largely controlled by their dispersal capacity, local environmental conditions and species interactions. The mussel Mytilus galloprovincialis is native to the Mediterranean and is the most successful marine invader in southern Africa. Its distribution there has expanded rapidly and extensively since the 1970s, however, over the last decade its spread has ceased. In this study, we coupled broad scale field surveys, Ecological Niche Modelling (ENM) and Lagrangian Particle Simulations (LPS) to assess the current invaded distribution of M. galloprovincialis in southern Africa and to evaluate what prevents further spread of this species. Results showed that all environmentally suitable habitats in southern Africa have been occupied by the species. This includes rocky shores between Rocky Point in Namibia and East London in South Africa (approx. 2800 km) and these limits coincide with the steep transitions between cool-temperate and subtropical-warmer climates, on both west and southeast African coasts. On the west coast, simulations of drifting larvae almost entirely followed the northward and offshore direction of the Benguela current, creating a clear dispersal barrier by advecting larvae away from the coast. On the southeast coast, nearshore currents give larvae the potential to move eastwards, against the prevalent Agulhas current and beyond the present distributional limit, however environmental conditions prevent the establishment of the species. The transition between the cooler and warmer water regimes is therefore the main factor limiting the northern spread on the southeast coast; however, biotic interactions with native fauna may also play an important role.

Consensus forecasting of species distributions: the effects of niche model performance and niche properties

Ensemble forecasting is advocated as a way of reducing uncertainty in species distribution modeling (SDM). This is because it is expected to balance accuracy and robustness of SDM models. However, there are little available data regarding the spatial similarity of the combined distribution maps generated by different consensus approaches. Here, using eight niche-based models, nine split-sample calibration bouts (or nine random model-training subsets), and nine climate change scenarios, the distributions of 32 forest tree species in China were simulated under current and future climate conditions. The forecasting ensembles were combined to determine final consensual prediction maps for target species using three simple consensus approaches (average, frequency, and median [PCA]). Species' geographic ranges changed (area change and shifting distance) in response to climate change, but the three consensual projections did not differ significantly with respect to how much or in which direction, but they did differ with respect to the spatial similarity of the three consensual predictions. Incongruent areas were observed primarily at the edges of species' ranges. Multiple stepwise regression models showed the three factors (niche marginality and specialization, and niche model accuracy) to be related to the observed variations in consensual prediction maps among consensus approaches. Spatial correspondence among prediction maps was the highest when niche model accuracy was high and marginality and specialization were low. The difference in spatial predictions suggested that more attention should be paid to the range of spatial uncertainty before any decisions regarding specialist species can be made based on map outputs. The niche properties and single-model predictive performance provide promising insights that may further understanding of uncertainties in SDM.

Silvicolous on a small scale: possibilities and limitations of habitat suitability models for small, elusive mammals in conservation management and landscape planning

Species distribution and endangerment can be assessed by habitat-suitability modelling. This study addresses methodical aspects of habitat suitability modelling and includes an application example in actual species conservation and landscape planning. Models using species presence-absence data are preferable to presence-only models. In contrast to species presence data, absences are rarely recorded. Therefore, many studies generate pseudo-absence data for modelling. However, in this study model quality was higher with null samples collected in the field. Next to species data the choice of landscape data is crucial for suitability modelling. Landscape data with high resolution and ecological relevance for the study species improve model reliability and quality for small elusive mammals like Muscardinus avellanarius. For large scale assessment of species distribution, models with low-detailed data are sufficient. For regional site-specific conservation issues like a conflict-free site for new wind turbines, high-detailed regional models are needed. Even though the overlap with optimally suitable habitat for M. avellanarius was low, the installation of wind plants can pose a threat due to habitat loss and fragmentation. To conclude, modellers should clearly state the purpose of their models and choose the according level of detail for species and environmental data.

Modelling the potential spatial distribution of mosquito species using three different techniques

BACKGROUND

Models for the spatial distribution of vector species are important tools in the assessment of the risk of establishment and subsequent spread of vector-borne diseases. The aims of this study are to define the environmental conditions suitable for several mosquito species through species distribution modelling techniques, and to compare the results produced with the different techniques.

METHODS

Three different modelling techniques, i.e., non-linear discriminant analysis, random forest and generalised linear model, were used to investigate the environmental suitability in the Netherlands for three indigenous mosquito species (Culiseta annulata, Anopheles claviger and Ochlerotatus punctor). Results obtained with the three statistical models were compared with regard to: (i) environmental suitability maps, (ii) environmental variables associated with occurrence, (iii) model evaluation.

RESULTS

The models indicated that precipitation, temperature and population density were associated with the occurrence of Cs. annulata and An. claviger, whereas land surface temperature and vegetation indices were associated with the presence of Oc. punctor. The maps produced with the three different modelling techniques showed consistent spatial patterns for each species, but differences in the ranges of the predictions. Non-linear discriminant analysis had lower predictions than other methods. The model with the best classification skills for all the species was the random forest model, with specificity values ranging from 0.89 to 0.91, and sensitivity values ranging from 0.64 to 0.95.

CONCLUSIONS

We mapped the environmental suitability for three mosquito species with three different modelling techniques. For each species, the maps showed consistent spatial patterns, but the level of predicted environmental suitability differed; NLDA gave lower predicted probabilities of presence than the other two methods. The variables selected as important in the models were in agreement with the existing knowledge about these species. All model predictions had a satisfactory to excellent accuracy; best accuracy was obtained with random forest. The insights obtained can be used to gain more knowledge on vector and non-vector mosquito species. The output of this type of distribution modelling methods can, for example, be used as input for epidemiological models of vector-borne diseases.

Landscape features and reservoir occurrence affecting the risk for equine infection with Borna disease virus

Borna disease (BD) is a severe endemic and fatal disorder caused by the neurotropic Borna disease virus (BDV) which mainly occurs in horses and sheep. Borna disease virus belongs to the order Mononegavirales, which includes many reservoir-bound viruses with high zoonotic and pathogenic properties including the filoviruses and lyssaviruses. Clinically manifest BD occurs in endemic areas of Germany, Switzerland, Liechtenstein, and Austria. A seasonal accumulation of cases in spring and summer, incidences that vary from year to year, and the recent detection of BDV in bicolored shrews (Crocidura leucodon) in Swiss endemic areas argue for a natural reservoir. We established a geographic information system analysis of the distribution of 485 equine BD cases in Bavarian (Germany) endemic areas and of the occurrence of 285 records of C. leucodon captured in Bavaria. Boosted regression trees were used to identify driving factors of habitat choice and virus prevalence. The distribution model of C. leucodon and the prevalence model for BDV had very good accuracy. Mean annual precipitation <900 mm, mean annual temperatures of 8 C, elevation <350 m, low forest cover, and a high percentage of urban fabric and arable land describe the optimal habitat for C. leucodon. Occurrence probability of C. leucodon was significantly higher in Bavarian BDV-endemic areas than in random areas in Bavaria. The prevalence of BD was higher in urban areas with annual mean precipitation of 800-900 mm, annual mean temperature of 8 C, and elevation >500 m. Our results indicate that the distribution model can accurately predict BD occurrence. Based on these results, practical safety precautions could be derived. The BDV model represents a suitable system for reservoir-bound, neurotropic Mononegavirales because it allows analyzing ecologic and biologic aspects that determine virus abundance, maintenance in reservoir species, and transmission to end host species.