Climate change and the future distributions of aquatic macrophytes across boreal catchments

Aim Aquatic–terrestrial ecotones are vulnerable to climate change, and degradation of the emergent aquatic macrophyte zone would have severe ecological consequences for freshwater, wetland and terrestrial ecosystems. Our aim was to uncover future changes in boreal emergent aquatic macrophyte zones by modelling the occurrence and percentage cover of emergent aquatic vegetation under different climate scenarios in Finland by the 2050s. Location Finland, northern Europe. Methods Data derived from different GIS sources were used to estimate future emergent aquatic macrophyte distributions in all catchments in Finland (848 in total). We used generalized additive models (GAM) with a full stepwise selection algorithm and Akaike information criterion to explore the main environmental determinates (climate and geomorphology) of emergent aquatic macrophyte distributions, which were derived from the national subclass of CORINE land‐cover classification. The accuracy of the distribution models (GAMs) was cross‐validated, using percentage of explained deviance and the area under the curve derived from the receiver‐operating characteristic plots. Results Our results indicated that emergent aquatic macrophytes will expand their distributions northwards from the current catchments and percentage cover will increase in all of the catchments in all climate scenarios. Growing degree‐days was the primary determinant affecting distributions of emergent aquatic macrophytes. Inclusion of geomorphological variables clearly improved model performance in both model exercises compared with pure climate variables. Main conclusions Emergent aquatic macrophyte distributions will expand due to climate change. Many emergent aquatic plant species have already expanded their distributions during the past decades, and this process will continue in the years 2051–80. Emergent aquatic macrophytes pose an increasing overgrowth risk for sensitive macrophyte species in boreal freshwater ecosystems, which should be acknowledged in management and conservation actions. We conclude that predictions based on GIS data can provide useful ‘first‐filter’ estimates of changes in aquatic–terrestrial ecotones.     

The fate of European breeding birds under climate,land‐use and dispersal scenarios

Many species have already shifted their distributions in response to recent climate change. Here, we aimed at predicting the future breeding distributions of European birds under climate, land‐use, and dispersal scenarios. We predicted current and future distributions of 409 species within an ensemble forecast framework using seven species distribution models (SDMs), five climate scenarios and three emission and land‐use scenarios. We then compared results from SDMs using climate‐only variables, habitat‐only variables or both climate and habitat variables. In order to account for a species’ dispersal abilities, we used natal dispersal estimates and developed a probabilistic method that produced a dispersal scenario intermediate between the null and full dispersal scenarios generally considered in such studies. We then compared results from all scenarios in terms of future predicted range changes, range shifts, and variations in species richness. Modeling accuracy was better with climate‐only variables than with habitat‐only variables, and better with both climate and habitat variables. Habitat models predicted smaller range shifts and smaller variations in range size and species richness than climate models. Using both climate and habitat variables, it was predicted that the range of 71% of the species would decrease by 2050, with a 335 km median shift. Predicted variations in species richness showed large decreases in the southern regions of Europe, as well as increases, mainly in Scandinavia and northern Russia. The partial dispersal scenario was significantly different from the full dispersal scenario for 25% of the species, resulting in the local reduction of the future predicted species richness of up to 10%. We concluded that the breeding range of most European birds will decrease in spite of dispersal abilities close to a full dispersal hypothesis, and that given the contrasted predictions obtained when modeling climate change only and land‐use change only, both scenarios must be taken into consideration.     

A comparative analysis reveals little evidence for niche conservatism in aquatic macrophytes among four areas on two continents

One of the most intriguing questions in current ecology is the extent to which the ecological niches of species are conserved in space and time. Niche conservatism has mostly been studied using coarse‐scale data of species' distributions, although it is at the local habitat scales where species' responses to ecological variables primarily take place. We investigated the extent to which niches of aquatic macrophytes are conserved among four study regions (i.e. Finland, Sweden and the US states of Minnesota and Wisconsin) on two continents (i.e. Europe and North America) using data for 11 species common to all the four study areas. We studied how ecological variables (i.e. local, climate and spatial variables) explain variation in the distributions of these common species in the four areas using species distribution modelling. In addition, we examined whether species' niche parameters vary among the study regions. Our results revealed large variation in both species' responses to the studied ecological variables and in species' niche parameters among the areas. We found little evidence for niche conservatism in aquatic macrophytes, though local environmental conditions among the studied areas were largely similar. This suggests that niche shifts, rather than different environmental conditions, were responsible for variable responses of aquatic macrophytes to local ecological variables. Local habitat niches of aquatic macrophytes are mainly driven by variations in local environmental conditions, whereas their climate niches are more or less conserved among regions. This highlights the need to study niche conservatism using local‐scale data to better understand whether species' niches are conserved, because different niches (e.g. local versus climate) operating at various scales may show different degrees of conservatism. The extent to which species' niches are truly conserved has wide practical implications, including for instance, predicting changes in species' distributions in response to global change.     

Potential Changes in the Distributions of Western North America Tree and Shrub Taxa under Future Climate Scenarios

Increases in atmospheric greenhouse gases are driving significant changes in global climate. To project potential vegetation response to future climate change, this study uses response surfaces to describe the relationship between bioclimatic variables and the distribution of tree and shrub taxa in western North America. The response surfaces illustrate the probability of the occurrence of a taxon at particular points in climate space. Climate space was defined using three bioclimatic variables: mean temperature of the coldest month, growing degree days, and a moisture index. Species distributions were simulated under present climate using observed data (1951–80, 30-year mean) and under future climate (2090–99, 10-year mean) using scenarios generated by three general circulation models—HADCM2, CGCM1, and CSIRO. The scenarios assume a 1% per year compound increase in greenhouse gases and changes in sulfate (SO₄) aerosols based on the Intergovernmental Panel on Climate Change (IPCC) IS92a scenario. The results indicate that under future climate conditions, potential range changes could be large for many tree and shrub taxa. Shifts in the potential ranges of species are simulated to occur not only northward but in all directions, including southward of the existing ranges of certain species. The simulated potential distributions of some species become increasingly fragmented under the future climate scenarios, while the simulated potential distributions of other species expand. The magnitudes of the simulated range changes imply significant impacts to ecosystems and shifts in patterns of species diversity in western North America. Received 12 May 2000; accepted 20 December 2000.     

Increasing potential risk of a global aquatic invader in Europe in contrast to other continents under future climate change

Background

Anthropogenically-induced climate change can alter the current climatic habitat of non-native species and can have complex effects on potentially invasive species. Predictions of the potential distributions of invasive species under climate change will provide critical information for future conservation and management strategies. Aquatic ecosystems are particularly vulnerable to invasive species and climate change, but the effect of climate change on invasive species distributions has been rather neglected, especially for notorious global invaders.

Methodology/Principal Findings

We used ecological niche models (ENMs) to assess the risks and opportunities that climate change presents for the red swamp crayfish (Procambarus clarkii), which is a worldwide aquatic invasive species. Linking the factors of climate, topography, habitat and human influence, we developed predictive models incorporating both native and non-native distribution data of the crayfish to identify present areas of potential distribution and project the effects of future climate change based on a consensus-forecast approach combining the CCCMA and HADCM3 climate models under two emission scenarios (A2a and B2a) by 2050. The minimum temperature from the coldest month, the human footprint and precipitation of the driest quarter contributed most to the species distribution models. Under both the A2a and B2a scenarios, P. clarkii shifted to higher latitudes in continents of both the northern and southern hemispheres. However, the effect of climate change varied considerately among continents with an expanding potential in Europe and contracting changes in others.

Conclusions/Significance

Our findings are the first to predict the impact of climate change on the future distribution of a globally invasive aquatic species. We confirmed the complexities of the likely effects of climate change on the potential distribution of globally invasive species, and it is extremely important to develop wide-ranging and effective control measures according to predicted geographical shifts and changes.     

The influence of coarse‐scale environmental features on current and predicted future distributions of narrow‐range endemic crayfish populations

1. A major limitation to effective management of narrow‐range crayfish populations is the paucity of information on the spatial distribution of crayfish species and a general understanding of the interacting environmental variables that drive current and future potential distributional patterns. 2. Maximum Entropy Species Distribution Modeling Software (MaxEnt) was used to predict the current and future potential distributions of four endemic crayfish species in the Ouachita Mountains. Current distributions were modelled using climate, geology, soils, land use, landform and flow variables thought to be important to lotic crayfish. Potential changes in the distribution were forecast by using models trained on current conditions and projecting onto the landscape predicted under climate‐change scenarios. 3. The modelled distribution of the four species closely resembled the perceived distribution of each species but also predicted populations in streams and catchments where they had not previously been collected. Soils, elevation and winter precipitation and temperature most strongly related to current distributions and represented 65–87% of the predictive power of the models. Model accuracy was high for all models, and model predictions of new populations were verified through additional field sampling. 4. Current models created using two spatial resolutions (1 and 4.5 km²) showed that fine‐resolution data more accurately represented current distributions. For three of the four species, the 1‐km² resolution models resulted in more conservative predictions. However, the modelled distributional extent of Orconectes leptogonopodus was similar regardless of data resolution. Field validations indicated 1‐km² resolution models were more accurate than 4.5‐km² resolution models. 5. Future projected (4.5‐km² resolution models) model distributions indicated three of the four endemic species would have truncated ranges with low occurrence probabilities under the low‐emission scenario, whereas two of four species would be severely restricted in range under moderate–high emissions. Discrepancies in the two emission scenarios probably relate to the exclusion of behavioural adaptations from species‐distribution models. 6. These model predictions illustrate possible impacts of climate change on narrow‐range endemic crayfish populations. The predictions do not account for biotic interactions, migration, local habitat conditions or species adaptation. However, we identified the constraining landscape features acting on these populations that provide a framework for addressing habitat needs at a fine scale and developing targeted and systematic monitoring programmes.     

Impact of Climate Change on Potential Distribution of Chinese Caterpillar Fungus (Ophiocordyceps sinensis) in Nepal Himalaya

Climate change has already impacted ecosystems and species and substantial impacts of climate change in the future are expected. Species distribution modeling is widely used to map the current potential distribution of species as well as to model the impact of future climate change on distribution of species. Mapping current distribution is useful for conservation planning and understanding the change in distribution impacted by climate change is important for mitigation of future biodiversity losses. However, the current distribution of Chinese caterpillar fungus, a flagship species of the Himalaya with very high economic value, is unknown. Nor do we know the potential changes in suitable habitat of Chinese caterpillar fungus caused by future climate change. We used MaxEnt modeling to predict current distribution and changes in the future distributions of Chinese caterpillar fungus in three future climate change trajectories based on representative concentration pathways (RCPs: RCP 2.6, RCP 4.5, and RCP 6.0) in three different time periods (2030, 2050, and 2070) using species occurrence points, bioclimatic variables, and altitude. About 6.02% (8,989 km²) area of the Nepal Himalaya is suitable for Chinese caterpillar fungus habitat. Our model showed that across all future climate change trajectories over three different time periods, the area of predicted suitable habitat of Chinese caterpillar fungus would expand, with 0.11–4.87% expansion over current suitable habitat. Depending upon the representative concentration pathways, we observed both increase and decrease in average elevation of the suitable habitat range of the species.     

On the use of climate covariates in aquatic species distribution models: are we at risk of throwing out the baby with the bath water?

Species distribution models (SDMs) in river ecosystems can incorporate climate information by using air temperature and precipitation as surrogate measures of instream conditions or by using independent models of water temperature and hydrology to link climate to instream habitat. The latter approach is preferable but constrained by the logistical burden of developing water temperature and hydrology models. We therefore assessed whether regional scale, freshwater SDM predictions are fundamentally different when climate data versus instream temperature and hydrology are used as covariates. Maximum entropy (MaxEnt) SDMs were built for 15 freshwater fishes using one of two covariate sets: 1) air temperature and precipitation (climate variables) in combination with physical habitat variables; or 2) water temperature, hydrology (instream variables) and physical habitat. Three procedures were then used to compare results from climate vs instream models. First, equivalence tests assessed average pairwise differences (site‐specific comparisons throughout each species’ range) among climate and instream models. Second, ‘congruence’ tests determined how often the same stream segments were assigned high habitat suitability by climate and instream models. Third, Schoener's D and Warren's I niche overlap statistics quantified range‐wide similarity in predicted habitat suitability from climate vs instream models. Equivalence tests revealed small, pairwise differences in habitat suitability between climate and instream models (mean pairwise differences in MaxEnt raw scores for all species < 3 × 10^–4). Congruence tests showed a strong tendency for climate and instream models to predict high habitat suitability at the same stream segments (median congruence = 68%). D and I statistics reflected a high margin of overlap among climate and instream models (median D = 0.78, median I = 0.96). Overall, we found little support for the hypothesis that SDM predictions are fundamentally different when climate versus instream covariates are used to model fish species’ distributions at the scale of the Columbia Basin.     

Projected distributions of Southern Ocean albatrosses,petrels and fisheries as a consequence of climatic change

Given the major ongoing influence of environmental change on the oceans, there is a need to understand and predict the future distributions of marine species in order to plan appropriate mitigation to conserve vulnerable species and ecosystems. In this study we use tracking data from seven large seabird species of the Southern Ocean (black‐browed albatross Thalassarche melanophris, grey‐headed albatross T. chrysostoma, northern giant petrel Macronectes halli, southern giant petrel M. giganteus, Tristan albatross Diomedea dabbenena, wandering albatross D. exulans and white‐chinned petrel Procellaria aequinoctialis, and on fishing effort in two types of fisheries (characterised by low or high‐bycatch rates), to model the associations with environmental variables (bathymetry, chlorophyll‐a concentration, sea surface temperature and wind speed) through ensemble species distribution models. We then projected these distributions according to four climate change scenarios built by the Intergovernmental Panel for Climate Change for 2050 and 2100. The resulting projections were consistent across scenarios, indicating that there is a strong likelihood of poleward shifts in distribution of seabirds, and several range contractions (resulting from a shift in the northern, but no change in the southern limit of the range in four species). Current trends for southerly shifts in fisheries distributions are also set to continue under these climate change scenarios at least until 2100; some of these may reflect habitat loss for target species that are already over‐fished. It is of particular concern that a shift in the distribution of several highly threatened seabird species would increase their overlap with fisheries where there is a high‐bycatch risk. Under such scenarios, the associated shifts in distribution of seabirds and increases in bycatch risk will require much‐improved fisheries management in these sensitive areas to minimise impacts on populations in decline.     

Alpine bird distributions along elevation gradients: the consistency of climate and habitat effects across geographic regions

Many species have shown recent shifts in their distributions in response to climate change. Patterns in species occurrence or abundance along altitudinal gradients often serve as the basis for detecting such changes and assessing future sensitivity. Quantifying the distribution of species along altitudinal gradients acts as a fundamental basis for future studies on environmental change impacts, but in order for models of altitudinal distribution to have wide applicability, it is necessary to know the extent to which altitudinal trends in occurrence are consistent across geographically separated areas. This was assessed by fitting models of bird species occurrence across altitudinal gradients in relation to habitat and climate variables in two geographically separated alpine regions, Piedmont and Trentino. The ten species studied showed non-random altitudinal distributions which in most cases were consistent across regions in terms of pattern. Trends in relation to altitude and differences between regions could be explained mostly by habitat or a combination of habitat and climate variables. Variation partitioning showed that most variation explained by the models was attributable to habitat, or habitat and climate together, rather than climate alone or geographic region. The shape and position of the altitudinal distribution curve is important as it can be related to vulnerability where the available space is limited, i.e. where mountains are not of sufficient altitude for expansion. This study therefore suggests that incorporating habitat and climate variables should be sufficient to construct models with high transferability for many alpine species.     

Temperate Mountain Forest Biodiversity under Climate Change: Compensating Negative Effects by Increasing Structural Complexity

Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km² grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species’ occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species’ occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change.     

An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change

An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one.     

Predicting co-distribution patterns of parrots and woody plants under global changes: The case of the Lilac-crowned Amazon and Neotropical dry forests

Global climate and land-use changes are the most significant causes of the current habitat loss and biodiversity crisis. Although there is information measuring these global changes, we lack a full understanding of how they impact community assemblies and species interactions across ecosystems. Herein, we assessed the potential distribution of eight key woody plant species associated with the habitat of the endangered Lilac-crowned Amazon (Amazon finschi) under global changes scenarios (2050′s and 2070′s), to answer the following questions: (1) how do predicted climate and land-use changes impact these species’ individual distributions and co-distribution patterns?; and (2) how effective is the existing Protected Area network for safeguarding the parrot species, the plant species, and their biological interactions? Our projections were consistent identifying the species that are most vulnerable to climate change. The distribution ranges of most of the species tended to decrease under future climates. These effects were strongly exacerbated when incorporating land-use changes into models. Even within existing protected areas, >50 % of the species’ remaining distribution and sites with the highest plant richness were predicted to be lost in the future under these combined scenarios. Currently, both individual species ranges and sites of highest richness of plants, shelter a high proportion (ca. 40 %) of the Lilac-crowned Amazon distribution. However, this spatial congruence could be reduced in the future, potentially disrupting the ecological associations among these taxa. We provide novel evidence for decision-makers to enhance conservation efforts to attain the long-term protection of this endangered Mexican endemic parrot and its habitat.     

Relative importance of hydrological variables in predicting the habitat suitability of Euryale ferox Salisb.

Aims Aquatic ecosystems are a priority for conservation as they have become rapidly degraded with land-use changes. Predicting the habitat range of an endangered species provides crucial information for biodiversity conservation in such rapidly changing environments. However, the complex network structure of aquatic ecosystems restricts spatial prediction variables and has hitherto limited the use of habitat models to predict species occurrence in aquatic ecosystems. We used the maximum entropy model to evaluate the potential distribution of an endangered aquatic species, Euryale ferox Salisb. We tested the relative influence of (i) climatic variables, (ii) topographic variables, and (iii) hydrological variables derived from remote sensing data to improve the prediction of occurrence of aquatic plant species.Methods We considered the southern part of the Korean Peninsula as the modeling extent for the potential distribution of E. ferox. Occurrence records for E. ferox were collected from the literature and field surveys. We applied maximum entropy modeling using remotely sensed environmental variables and evaluated their relative importance as prediction variables with variation partitioning.Important findings The species distribution model predicted potential habitats of E. ferox that matched the actual distribution well. Floodplain wetlands and shallow reservoirs were the favored habitats of E. ferox. Quantitative loss and fragmentation of wetland habitats appeared to be a major reason for the decrease of E. ferox populations. Our results also imply that hydrological variables (i.e. normalized difference water index) derived from remote sensing data greatly increased model prediction (relative contribution: 10.5–37.0%) in the aquatic ecosystem. However, interspecific competition within a similar niche environment should be considered to increase the accuracy of the distribution model.     

Will northern fish populations be in hot water because of climate change?

Predicted increases in water temperature in response to climate change will have large implications for aquatic ecosystems, such as altering thermal habitat and potential range expansion of fish species. Warmwater fish species, such as smallmouth bass, Micropterus dolomieu , may have access to additional favourable thermal habitat under increased surface-water temperatures, thereby shifting the northern limit of the distribution of the species further north in Canada and potentially negatively impacting native fish communities. We assembled a database of summer surface-water temperatures for over 13 000 lakes across Canada. The database consists of lakes with a variety of physical, chemical and biological properties. We used general linear models to develop a nation-wide maximum lake surface-water temperature model. The model was extended to predict surface-water temperatures suitable to smallmouth bass and under climate-change scenarios. Air temperature, latitude, longitude and sampling time were good predictors of present-day maximum surface-water temperature. We predicted lake surface-water temperatures for July 2100 using three climate-change scenarios. Water temperatures were predicted to increase by as much as 18 °C by 2100, with the greatest increase in northern Canada. Lakes with maximum surface-water temperatures suitable for smallmouth bass populations were spatially identified. Under several climate-change scenarios, we were able to identify lakes that will contain suitable thermal habitat and, therefore, are vulnerable to invasion by smallmouth bass in 2100. This included lakes in the Arctic that were predicted to have suitable thermal habitat by 2100.     

Cetacean range and climate in the eastern North Atlantic: future predictions and implications for conservation

There is increasing evidence that the distributions of a large number of species are shifting with global climate change as they track changing surface temperatures that define their thermal niche. Modelling efforts to predict species distributions under future climates have increased with concern about the overall impact of these distribution shifts on species ecology, and especially where barriers to dispersal exist. Here we apply a bio‐climatic envelope modelling technique to investigate the impacts of climate change on the geographic range of ten cetacean species in the eastern North Atlantic and to assess how such modelling can be used to inform conservation and management. The modelling process integrates elements of a species' habitat and thermal niche, and employs “hindcasting” of historical distribution changes in order to verify the accuracy of the modelled relationship between temperature and species range. If this ability is not verified, there is a risk that inappropriate or inaccurate models will be used to make future predictions of species distributions. Of the ten species investigated, we found that while the models for nine could successfully explain current spatial distribution, only four had a good ability to predict distribution changes over time in response to changes in water temperature. Applied to future climate scenarios, the four species‐specific models with good predictive abilities indicated range expansion in one species and range contraction in three others, including the potential loss of up to 80% of suitable white‐beaked dolphin habitat. Model predictions allow identification of affected areas and the likely time‐scales over which impacts will occur. Thus, this work provides important information on both our ability to predict how individual species will respond to future climate change and the applicability of predictive distribution models as a tool to help construct viable conservation and management strategies.     

To Be Or Not to Be? Variable selection can change the projected fate of a threatened species under future climate

Species distribution models (SDMs) are commonly used to project future changes in the geographic ranges of species, to estimate extinction rates and to plan biodiversity conservation. However, these models can produce a range of results depending on how they are parameterized, and over‐reliance on a single model may lead to overconfidence in maps of future distributions. The choice of predictor variable can have a greater influence on projected future habitat than the range of climate models used. We demonstrate this in the case of the Ptunarra Brown Butterfly, a species listed as vulnerable in Tasmania, Australia. We use the Maxent model to develop future projections for this species based on three variable sets; all 35 commonly used so‐called ‘bioclimatic’ variables, a subset of these based on expert knowledge, and a set of monthly climate variables relevant to the species’ primary activity period. We used a dynamically downscaled regional climate model based on three global climate models. Depending on the choice of variable set, the species is projected either to experience very little contraction of habitat or to come close to extinction by the end of the century due to lack of suitable climate. The different conclusions could have important consequences for conservation planning and management, including the perceived viability of habitat restoration. The output of SDMs should therefore be used to define the range of possible trajectories a species may be on, and ongoing monitoring used to inform management as changes occur.     

Modelling seasonal changes in the distribution of Common Quail Coturnix coturnix in farmland landscapes using remote sensing

Species’ distribution models are widely used in landscape ecology but usually lack explicit information about species’ responses to ecosystem dynamics, leading to uncertainty when applied to the prediction of seasonal change in distributions. In this study, we aimed to build a species’ distribution model for the Common Quail Coturnix coturnix, a farmland species that shows changes in its distribution in response to seasonal changes in habitat suitability. During the course of three breeding seasons we collected temporal replicates of presence–absence data in 13 sampling locations in four countries (Morocco, Portugal, Spain and France). We used generalized linear mixed models to relate the species’ presence or absence to environmental variables and to the normalized difference vegetation index at each sampling location through the seasons, the latter variable being an indicator of within‐ and between‐season habitat changes. The preferred model showed that occurrence was highly dependent on habitat changes associated with crop seasonality, as measured by the normalized difference vegetation index. Common Quail selected areas with dense vegetation and warm climate and tracked spatial changes in these two parameters. The model allows accurate mapping of within‐ and between‐season distribution changes. Such changes are related to habitat variations caused mainly by drought and agricultural practices. Our results demonstrate that seasonal changes in farmland ecosystems can be incorporated into a simple distribution model, and our approach could be applied to other species to predict the effects of agricultural changes on the distribution of birds inhabiting farmland landscapes.     

Selecting from correlated climate variables: a major source of uncertainty for predicting species distributions under climate change

Correlative species distribution models are frequently used to predict species’ range shifts under climate change. However, climate variables often show high collinearity and most statistical approaches require the selection of one among strongly correlated variables. When causal relationships between species presence and climate parameters are unknown, variable selection is often arbitrary, or based on predictive performance under current conditions. While this should only marginally affect current range predictions, future distributions may vary considerably when climate parameters do not change in concert. We investigated this source of uncertainty using four highly correlated climate variables together with a constant set of landscape variables in order to predict current (2010) and future (2050) distributions of four mountain bird species in central Europe. Simulating different parameterization decisions, we generated a) four models including each of the climate variables singly, b) a model taking advantage of all variables simultaneously and c) an un‐weighted average of the predictions of a). We compared model accuracy under current conditions, predicted distributions under four scenarios of climate change, and – for one species – evaluated back‐projections using historical occurrence data. Although current and future variable‐correlations remained constant, and the models’ accuracy under contemporary conditions did not differ, future range predictions varied considerably in all climate change scenarios. Averaged models and models containing all climate variables simultaneously produced intermediate predictions; the latter, however, performed best in back‐projections. This pattern, consistent across different modelling methods, indicates a benefit from including multiple climate predictors in ambiguous situations. Variable selection proved to be an important source of uncertainty for future range predictions, difficult to control using contemporary information. Small, but diverging changes of climate variables, masked by constant overall correlation patterns, can cause substantial differences between future range predictions which need to be accounted for, particularly when outcomes are intended for conservation decisions.