Investigating habitat-specific plant species pools under climate change

We used 474 European plant species to analyse the impacts of climate and land-use change on the composition of habitat-specific species pools in Germany. We quantified changes in the probability of occurrence of species in a grid cell using an ensemble of three statistical modelling techniques, namely generalized linear models (GLMs), generalized additive models (GAMs) and random forests (RFs), under three scenarios (average change +2.2, +2.9, and +3.8 °C up to 2080). We evaluated the impact on single species occurrence and resulting species pools considering their affiliation to ten major terrestrial habitat types in both current (1961–90) and future projections (2051–80). Current habitat-specific species pools declined in size across all scenarios, e.g. by 24 ± 13% (mean ± s.d.) under the most severe scenario. We show that species responses may strongly vary among scenarios and different habitats with a minimum average projected range loss of 14% (±18%; species typical to urban habitats under moderate climate change assumptions, average temperature increase +2.2 °C) to a maximum average projected range loss of 56% (±29%; species assemblages from mountain communities below the alpine zone at +3.8 °C). A separate analysis of species composition in habitat-specific species pools revealed a significant interaction between the scenario and the major habitat classes. We found a higher risk for habitat types with high conservation value characterised by a significant association between number of nationally endangered species and projected range loss in major habitats. Thus, habitat-specific management and application of measures favouring dispersal are required for mitigation of climate change impacts.     

Potential effects of climate change on plant species in the Faroe Islands

Aim To identify the effect of climate change on selected plant species representative of the main vegetation types in the Faroe Islands. Due to a possible weakening of the North Atlantic Current, it is difficult to predict whether the climate in the Faroe Islands will be warmer or colder as a result of global warming. Therefore, two scenarios are proposed. The first scenario assumes an increase in summer and winter temperature of 2 °C, and the second a decrease in summer and winter temperature of 2 °C. Location Temperate, low alpine and alpine areas in the northern and central part of the Faroe Islands. Methods The responses of 12 different plant species in the Faroe Islands were tested against measured soil temperature, expressed as T_min, T_max, snow cover and growing degree days (GDD), using generalised linear modelling (GLM). Results The tolerance to changes in winter soil temperature (0.3–0.8 °C) was found to be lower than the tolerance to changing summer soil temperature (0.7–1.0 °C), and in both cases lower than the predicted climate changes. Conclusions The species most affected by a warming scenario are those that are found with a limited distribution restricted to the uppermost parts of the mountains, especially Salix herbacea, Racomitrium fasciculare, and Bistorta vivipara. For other species, the effect will mainly be a general upward migration. The most vulnerable species are those with a low tolerance, especially Calluna vulgaris, and also Empetrum nigrum, and Nardus stricta. If the climate in the Faroe Islands should become colder, the most vulnerable species are those at low altitudes. A significantly lower temperature would be expected to produce a serious reduction in the extent of Vaccinium myrtillus and Galium saxatilis. Species like Empetrum nigrum, Nardus stricta, and Calluna vulgaris may also be vulnerable. In any case, these species can be expected to migrate downwards.     

Projected impacts of climate change on regional capacities for global plant species richness

Climate change represents a major challenge to the maintenance of global biodiversity. To date, the direction and magnitude of net changes in the global distribution of plant diversity remain elusive. We use the empirical multi-variate relationships between contemporary water-energy dynamics and other non-climatic predictor variables to model the regional capacity for plant species richness (CSR) and its projected future changes. We find that across all analysed Intergovernmental Panel on Climate Change emission scenarios, relative changes in CSR increase with increased projected temperature rise. Between now and 2100, global average CSR is projected to remain similar to today (+0.3%) under the optimistic B1/+1.8°C scenario, but to decrease significantly (−9.4%) under the ‘business as usual’ A1FI/+4.0°C scenario. Across all modelled scenarios, the magnitude and direction of CSR change are geographically highly non-uniform. While in most temperate and arctic regions, a CSR increase is expected, the projections indicate a strong decline in most tropical and subtropical regions. Countries least responsible for past and present greenhouse gas emissions are likely to incur disproportionately large future losses in CSR, whereas industrialized countries have projected moderate increases. Independent of direction, we infer that all changes in regional CSR will probably induce on-site species turnover and thereby be a threat to native floras.     

Influence of nonclimatic factors on the habitat prediction of tree species and an assessment of the impact of climate change

To determine the influence of nonclimatic factors on predicting the habitats of tree species and an assessment of climate change impacts over a broad geographical extent at about 1 km resolution, we investigated the predictive performance for models with climatic factors only (C-models) and models with climatic and nonclimatic factors (CN-models) using seven tree species in Japan that exhibit different ecological characteristics such as habitat preference and successional traits. Using a generalized additive model, the prediction performance was compared by prediction accuracy [area under the operating characteristic curve (AUC)], goodness of fit, and potential habitat maps. The results showed that the CN-models had higher predictive accuracy, higher goodness of fit, smaller empty habitats, and more finely defined borders of potential habitat than those of the C-models for all seven species. The degree of the total contribution of the nonclimatic variables to prediction performance also varied among the seven species. These results suggest that nonclimatic factors also play an important role in predicting species occurrence when measured to this extent and resolution, that the magnitude of model improvement is larger for species with specific habitat preferences, and that the C-models cannot predict the land-related habitats that exist for almost all species. Climate change impacts were overestimated by C-models for all species. Therefore, C-model outcomes may lead to locally ambiguous assessment of the impact of climate change on species distribution. CN-models provide a more accurate and detailed assessment for conservation planning.     

Dispersal based climate change sensitivity scores for European species

Assessments of climate change impacts on species are needed for anticipating potential biodiversity losses. Climate change impacts on species are often simulated with climate envelope models, but most climate envelope models do not account for dispersal limitations. Most studies only consider two extreme (and unrealistic) dispersal options: no dispersal versus full dispersal. This study attempts to include dispersal limitation into the calculation of climate change sensitivity scores for a range of vertebrate and plant species. We calculate climate change sensitivity scores -expressed as an index- by using the 'spatial turnover' of a species under climate change, defined as the projected difference between current and future area occupied by a species within a region, and include a dispersal factor to account for dispersal limitations. We calculate climate sensitivity scores with three dispersal factors: d₀ (no dispersal), d₁ (full dispersal) and with an estimated value of d calculated directly from species specific dispersal data and literature estimates (d_e). We compared climate sensitivity scores across species groups and European bio-geographical regions in order to determine whether explicitly accounting for dispersal limitations causes significant differences in sensitivity for climate change. Our results show that the climate sensitivity scores calculated with d_e differ slightly from d₀ (no dispersal), but differ significantly from d₁ (full dispersal) for the less mobile species groups (amphibian, reptiles, plants). This indicates that assuming full dispersal significantly overestimates the future distribution in Europe under climate change for these species, whereas assuming no dispersal may slightly underestimates this. However, this conclusion could not be drawn for the more mobile birds and mammas: climate sensitivity scores calculated with d_e are approximately intermediate of those calculated with d₀ (no dispersal) and d₁ (full dispersal). This indicates that assuming either no or full dispersal results in poor estimates of the future distribution of these species in Europe under climate change, and that dispersal capacity should therefore always be considered when assessing climate change impacts on these species. Disaggregating climate sensitivity scores per European bio-geographical regions reveals that regional climate sensitivity scores are similar to the European level.     

Potential impacts of climate change on Sub-Saharan African plant priority area selection

The Global Strategy for Plant Conservation (GSPC) aims to protect 50% of the most important areas for plant diversity by 2010. This study selects sets of 1-degree grid cells for 37 sub-Saharan African countries on the basis of a large database of plant species distributions. We use two reserve selection algorithms that attempt to satisfy two of the criteria set by the GSPC. The grid cells selected as important plant cells (IPCs) are compared between algorithms and in terms of country and continental rankings between cells. The conservation value of the selected grid cells are then considered in relation to their future species complement given the predicted climate change in three future periods (2025, 2055, and 2085). This analysis uses predicted climate suitability for individual species from a previous modelling exercise.
We find that a country-by-country conservation approach is suitable for capturing most, but not all, continentally IPCs. The complementarity-based reserve selection algorithms suggest conservation of a similar set of grid cells, suggesting that areas of high plant diversity and rarity may be well protected by a single pattern of conservation activity.
Although climatic conditions are predicted to deteriorate for many species under predicted climate change, the cells selected by the algorithms are less affected by climate change predictions than non-selected cells. For the plant species that maintain areas of climatic suitability in the future, the selected set will include cells with climate that is highly suitable for the species in the future. The selected cells are also predicted to conserve a large proportion of the species richness remaining across the continent under climate change, despite the network of cells being less optimal in terms of future predicted distributions.
Limitations to the modelling are discussed in relation to the policy implications for those implementing the GSPC.     

Probabilistic accounting of uncertainty in forecasts of species distributions under climate change

Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing models (model uncertainty), and uncertainty in future climate conditions (climate uncertainty) to produce site‐specific frequency distributions of occurrence probabilities across a species' range. We illustrated the method by forecasting suitable habitat for bull trout (Salvelinus confluentus) in the Interior Columbia River Basin, USA, under recent and projected 2040s and 2080s climate conditions. The 95% interval of total suitable habitat under recent conditions was estimated at 30.1–42.5 thousand km; this was predicted to decline to 0.5–7.9 thousand km by the 2080s. Projections for the 2080s showed that the great majority of stream segments would be unsuitable with high certainty, regardless of the climate data set or bull trout model employed. The largest contributor to uncertainty in total suitable habitat was climate uncertainty, followed by parameter uncertainty and model uncertainty. Our approach makes it possible to calculate a full distribution of possible outcomes for a species, and permits ready graphical display of uncertainty for individual locations and of total habitat.     

Effects of climate change on the distribution of plant species and plant functional strategies on the Canary Islands

Aim

Oceanic islands possess unique floras with high proportions of endemic species. Island floras are expected to be severely affected by changing climatic conditions as species on islands have limited distribution ranges and small population sizes and face the constraints of insularity to track their climatic niches. We aimed to assess how ongoing climate change affects the range sizes of oceanic island plants, identifying species of particular conservation concern.

Location

Canary Islands, Spain.

Methods

We combined species occurrence data from single-island endemic, archipelago endemic and nonendemic native plant species of the Canary Islands with data on current and future climatic conditions. Bayesian Additive Regression Trees were used to assess the effect of climate change on species distributions; 71% (n = 502 species) of the native Canary Island species had models deemed good enough. To further assess how climate change affects plant functional strategies, we collected data on woodiness and succulence.

Results

Single-island endemic species were projected to lose a greater proportion of their climatically suitable area (x ̃ = −0.36) than archipelago endemics (x ̃ = −0.28) or nonendemic native species (x ̃ = −0.26), especially on Lanzarote and Fuerteventura, which are expected to experience less annual precipitation in the future. Moreover, herbaceous single-island endemics were projected to gain less and lose more climatically suitable area than insular woody single-island endemics. By contrast, we found that succulent single-island endemics and nonendemic natives gain more and lose less climatically suitable area.

Main Conclusions

While all native species are of conservation importance, we emphasise single-island endemic species not characterised by functional strategies associated with water use efficiency. Our results are particularly critical for other oceanic island floras that are not constituted by such a vast diversity of insular woody species as the Canary Islands.     

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.     

Improving species distribution models for climate change studies: variable selection and scale

Statistical species distribution models (SDMs) are widely used to predict the potential changes in species distributions under climate change scenarios. We suggest that we need to revisit the conceptual framework and ecological assumptions on which the relationship between species distributions and environment is based. We present a simple conceptual framework to examine the selection of environmental predictors and data resolution scales. These vary widely in recent papers, with light inconsistently included in the models. Focusing on light as a necessary component of plant SDMs, we briefly review its dependence on aspect and slope and existing knowledge of its influence on plant distribution. Differences in light regimes between north‐ and south‐facing aspects in temperate latitudes can produce differences in temperature equivalent to moves 200 km polewards. Local topography may create refugia that are not recognized in many climate change SDMs using coarse‐scale data. We argue that current assumptions about the selection of predictors and data resolution need further testing. Application of these ideas can clarify many issues of scale, extent and choice of predictors, and potentially improve the use of SDMs for climate change modelling of biodiversity.     

样地数量对气候变化背景下树种分布预测的影响

基于不同景观破碎化程度下的中性景观,探讨了气候变化背景下样地数量对景观尺度树种分布预测的影响.采用模型耦合的方法进行树种分布预测,设置了3个样地数量预案与1个参考预案.分别在每一破碎化程度下检验3种样地数量预案的预测结果与参考预案之间的差异.结果表明:样地数量会影响树种分布预测结果,具有不同生活史属性的树种对样地数量的需求不同,对普适性树种进行分布预测需要的样地数量较多;除极度特异种外,景观的破碎化程度也会影响样地数量对树种分布预测的影响;随着模拟时间的增加,样地数量对景观尺度树种分布预测的作用会发生变化,对于一些普适种树种来说,长期模拟需要较多的样地.     

Effects of a short-term climate change experiment on a sub-Antarctic keystone plant species

The cushion plant Azorella selago is widespread across the sub‐Antarctic, and is considered a keystone species in the dominant fellfield vegetation. However, the impact of current changes in climate in the region (increasing temperature and declining rainfall) on this species is unknown. Here, the response of A. selago to reduced rainfall (a direct effect of climate change) and increased shading (a predicted indirect effect of increasing temperatures, via enhanced growth and wider distribution of more responsive competitors and epiphytes) was experimentally determined. Reduced rainfall increased stem mortality and accelerated autumnal senescence. Furthermore, under this treatment senescence was unequally distributed across individual plants, hypothesized to be a consequence of an interactive effect between rainfall and wind patterns. Shaded stems grew more, and carried larger leaves with lower trichome densities, than their exposed equivalents. As a result, shaded plants were less compact and their surface integrity reduced. The species' response to combined drying and shading was generally similar to its response to shading alone, suggesting that, at least over the short term, the indirect effects of climate change could be more severe than the direct effects. Thus, despite the species' slow growth rate and the short duration of the experiment, persistent direct and indirect effects were observed, both with potential longer‐term consequences for A. selago populations. Climate change is, therefore, likely to impact negatively on this long‐lived keystone species, with significant implications for the structure and functioning of fellfield systems.     

The impact of global climate change on genetic diversity within populations and species

Genetic diversity provides the basic substrate for evolution, yet few studies assess the impacts of global climate change (GCC) on intraspecific genetic variation. In this review, we highlight the importance of incorporating neutral and non‐neutral genetic diversity when assessing the impacts of GCC, for example, in studies that aim to predict the future distribution and fate of a species or ecological community. Specifically, we address the following questions: Why study the effects of GCC on intraspecific genetic diversity? How does GCC affect genetic diversity? How is the effect of GCC on genetic diversity currently studied? Where is potential for future research? For each of these questions, we provide a general background and highlight case studies across the animal, plant and microbial kingdoms. We further discuss how cryptic diversity can affect GCC assessments, how genetic diversity can be integrated into studies that aim to predict species' responses on GCC and how conservation efforts related to GCC can incorporate and profit from inclusion of genetic diversity assessments. We argue that studying the fate of intraspecifc genetic diversity is an indispensable and logical venture if we are to fully understand the consequences of GCC on biodiversity on all levels.     

Contribution of crop model structure,parameters and climate projections to uncertainty in climate change impact assessments

Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple‐ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple‐ensemble probabilistic assessment, the median of simulated yield change was ?4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981–2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple‐ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources.     

Possible effects of habitat fragmentation and climate change on the range of forest plant species

Global circulation models predict an increase in mean annual temperature between 2.1 and 4.6 °C by 2080 in the northern temperate zone. The associated changes in the ratio of extinctions and colonizations at the boundaries of species ranges are expected to result in northward range shifts for a lot of species. However, net species colonization at northern boundary ranges, necessary for a northward shift and for range conservation, may be hampered because of habitat fragmentation. We report the results of two forest plant colonization studies in two fragmented landscapes in central Belgium. Almost all forest plant species (85%) had an extremely low success of colonizing spatially segregated new suitable forest habitats after c . 40 years. In a landscape with higher forest connectivity, colonization success was higher but still insufficient to ensure large-scale colonization. Under the hypothesis of net extinction at southern range boundaries, forest plant species dispersal limitation will prevent net colonization at northern range boundaries required for range conservation.     

National and European perspectives on climate change sensitivity of the habitats directive characteristic plant species

The main goal of the Habitats Directive, a key document for European conservation, is to maintain a ‘favourable’ conservation status of selected species and habitats. In the face of near-future climatic change this goal may become difficult to achieve. Here, we evaluate the sensitivity to climate change of 84 plant species that characterise the Danish habitat types included in the Habitats Directive. A fuzzy bioclimatic envelope model, linking European and Northwest African species’ distribution data with climate, was used to predict climatically suitable areas for these species in year 2100 under two-climate change scenarios. Climate sensitivity was evaluated at both Danish and European scales to provide an explicit European perspective on the impacts predicted for Denmark. In all 69–99% of the species were predicted to become negatively affected by climate change at either scale. Application of international Red List criteria showed that 43–55% and 17–69% would become vulnerable in Denmark and Europe, respectively. Northwest African atlas data were used to improve the ecological accuracy of the future predictions. For comparison, using only European data added 0–7% to these numbers. No species were predicted to become extinct in Europe, but 4–7% could be lost from Denmark. Some species were predicted to become positively affected in Denmark, but negatively affected in Europe. In addition to nationally endangered species, this group would be an important focus for a Danish conservation strategy. A geographically differentiated Danish conservation strategy is suggested as the eastern part of Denmark was predicted to be more negatively affected than the western part. No differences in the sensitivity of the Habitats Directive habitats were found. We conclude that the conservation strategy of the Habitats Directive needs to integrate the expected shifts in species’ distributions due to climate change.     

The impact of climate change on birds

Weather is of major importance for the population dynamics of birds, but the implications of climate change have only recently begun to be addressed. There is already compelling evidence that birds have been affected by recent climate changes. This review suggests that although there is a substantial body of evidence for changes in the phenology of birds, particularly of the timing of migration and of nesting, the consequences of these responses for a species' population dynamics is still an area requiring in-depth research. The potential for phenological miscuing (responding inappropriately to climate change, including a lack of response) and for phenological disjunction (in which a bird species becomes out of synchrony with its environment) are beginning to be demonstrated, and are also important areas for further research. The study of climatically induced distributional change is currently at a predictive modelling stage, and will need to develop methods for testing these predictions. Overall, there is a range of intrinsic and extrinsic factors that could potentially inhibit adaptation to climate change and these are a high priority for research.     

Refining predictions of climate change impacts on plant species distribution through the use of local statistics

Bioclimate envelope models are often used to predict changes in species distribution arising from changes in climate. These models are typically based on observed correlations between current species distribution and climate data. One limitation of this basic approach is that the relationship modelled is assumed to be constant in space; the analysis is global with the relationship assumed to be spatially stationary. Here, it is shown that by using a local regression analysis, which allows the relationship under study to vary in space, rather than conventional global regression analysis it is possible to increase the accuracy of bioclimate envelope modelling. This is demonstrated for the distribution of Spotted Meddick in Great Britain using data relating to three time periods, including predictions for the 2080s based on two climate change scenarios. Species distribution and climate data were available for two of the time periods studied and this allowed comparison of bioclimate envelope model outputs derived using the local and global regression analyses. For both time periods, the area under the receiver operating characteristics curve derived from the analysis based on local statistics was significantly higher than that from the conventional global analysis; the curve comparisons were also undertaken with an approach that recognised the dependent nature of the data sets compared. Marked differences in the future distribution of the species predicted from the local and global based analyses were evident and highlight a need for further consideration of local issues in modelling ecological variables.     

Small-scale plant species distribution in snowbeds and its sensitivity to climate change

Alpine snowbeds are characterized by a long-lasting snow cover and low soil temperature during the growing season. Both these key abiotic factors controlling plant life in snowbeds are sensitive to anthropogenic climate change and will alter the environmental conditions in snowbeds to a considerable extent until the end of this century. In order to name winners and losers of climate change among the plant species inhabiting snowbeds, we analyzed the small-scale species distribution along the snowmelt and soil temperature gradients within alpine snowbeds in the Swiss Alps. The results show that the date of snowmelt and soil temperature were relevant abiotic factors for small-scale vegetation patterns within alpine snowbed communities. Species richness in snowbeds was reduced to about 50% along the environmental gradients towards later snowmelt date or lower daily maximum temperature. Furthermore, the occurrence pattern of the species along the snowmelt gradient allowed the establishment of five species categories with different predictions of their distribution in a warmer world. The dominants increased their relative cover with later snowmelt date and will, therefore, lose abundance due to climate change, but resist complete disappearance from the snowbeds. The indifferents and the transients increased in species number and relative cover with higher temperature and will profit from climate warming. The snowbed specialists will be the most suffering species due to the loss of their habitats as a consequence of earlier snowmelt dates in the future and will be replaced by the avoiders of late-snowmelt sites. These forthcoming profiteers will take advantage from an increasing number of suitable habitats due to an earlier start of the growing season and increased temperature. Therefore, the characteristic snowbed vegetation will change to a vegetation unit dominated by alpine grassland species. The study highlights the vulnerability of the established snowbed vegetation to climate change and requires further studies particularly about the role of biotic interactions in the predicted invasion and replacement process.