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.     

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.     

Potential impacts of climate change on the distributions and diversity patterns of European mammals

The Intergovernmental Panel on Climate Change (IPCC) predicts an increase in global temperatures of between 1.4°C and 5.8°C during the 21st century, as a result of elevated CO₂ levels. Using bioclimatic envelope models, we evaluate the potential impact of climate change on the distributions and species richness of 120 native terrestrial non-volant European mammals under two of IPCC’s future climatic scenarios. Assuming unlimited and no migration, respectively, our model predicts that 1% or 5–9% of European mammals risk extinction, while 32–46% or 70–78% may be severely threatened (lose > 30% of their current distribution) under the two scenarios. Under the no migration assumption endemic species were predicted to be strongly negatively affected by future climatic changes, while widely distributed species would be more mildly affected. Finally, potential mammalian species richness is predicted to become dramatically reduced in the Mediterranean region but increase towards the northeast and for higher elevations. Bioclimatic envelope models do not account for non-climatic factors such as land-use, biotic interactions, human interference, dispersal or history, and our results should therefore be seen as first approximations of the potential magnitude of future climatic changes.     

Climate change, phenology and species detectability in a monitoring scheme

The knowledge of the state of biodiversity on the globe is based on a large number of monitoring schemes. Quite often the results of these schemes are sensitive to the timing of monitoring due to the phenology of species, which in turn may affect the detectability of species during censuses. As global warming has been shown to cause changes in phenology, there is an increasing risk that species detectability will be altered if the timing of monitoring is not adapted to this change. I tested how sensitive species detectability is to the timing of censuses and whether there are potential climate-driven temporal changes in the detectability of 73 Finnish land bird species monitored using single-visit line-transects in 1987–2010. This was done by investigating seasonal and annual patterns in the proportion of birds in the main belt and those detected by displaying activity. Over 20 of the study species showed significant changes in detectability within the census season. However, only three species showed a significant trend in annual detectability. According to multi-species analyses there was a slight but significant increasing trend in the proportion of displaying birds and a slight decreasing trend in the proportion of birds in the main belt. However, the observed species-specific annual changes in displaying activity or in proportion of birds in main belt were not associated with the observed population trends of species during the same period. Nevertheless, the findings highlight a strong potential risk that species detectability can change if climate change escalates in the future. I recommend researchers to investigate how sensitive their monitoring systems are for phenological changes and prepare tools for taking potential changes in detectability into account.     

Ancient woodland indicators signal the climate change risk for dispersal-limited species

The climate change risk to biodiversity operates alongside a range of anthropogenic pressures. These include habitat loss and fragmentation, which may prevent species from migrating between isolated habitat patches in order to track their suitable climate space. Predictive modelling has advanced in scope and complexity to integrate: (i) projected shifts in climate suitability, with (ii) spatial patterns of landscape habitat quality and rates of dispersal. This improved ecological realism is suited to data-rich model species, though its broader generalisation comes with accumulated uncertainties, e.g. incomplete knowledge of species response to variable habitat quality, parameterisation of dispersal kernels etc. This study adopts ancient woodland indicator species (lichen epiphytes) as a guild that couples relative simplicity with biological rigour. Subjectively-assigned indicator species were statistically tested against a binary habitat map of woodlands of known continuity (>250 yr), and bioclimatic models were used to demonstrate trends in their increased/decreased environmental suitability under conditions of ‘no dispersal’. Given the expectation of rapid climate change on ecological time-scales, no dispersal for ancient woodland indicators becomes a plausible assumption. The risk to ancient woodland indicators is spatially structured (greater in a relative continental compared to an oceanic climatic zone), though regional differences are weakened by significant variation (within regions) in woodland extent. As a corollary, ancient woodland indicators that are sensitive to projected climate change scenarios may be excellent targets for monitoring climate change impacts for biodiversity at a site-scale, including the outcome of strategic habitat management (climate change adaptation) designed to offset risk for dispersal-limited species.     

Reducing uncertainty in projections of extinction risk from climate change

Aim Concern over the implications of climate change for biodiversity has led to the use of species–climate ‘envelope’ models to forecast risks of species extinctions under climate change scenarios. Recent studies have demonstrated significant variability in model projections and there remains a need to test the accuracy of models and to reduce uncertainties. Testing of models has been limited by a lack of data against which projections of future ranges can be tested. Here we provide a first test of the predictive accuracy of such models using observed species’ range shifts and climate change in two periods of the recent past. Location Britain. Methods Observed range shifts for 116 breeding bird species in Britain between 1967 and 1972 (t₁) and 1987–91 (t₂) are used. We project range shifts between t₁ and t₂ for each species based on observed climate using 16 alternative models (4 methods × 2 data parameterizations × 2 rules to transform probabilities of occurrence into presence and absence records). Results Modelling results were extremely variable, with projected range shifts varying both in magnitude and in direction from observed changes and from each other. However, using approaches that explore the central tendency (consensus) of model projections, we were able to improve agreement between projected and observed shifts significantly. Conclusions Our results provide the first empirical evidence of the value of species–climate ‘envelope’ models under climate change and demonstrate reduction in uncertainty and improvement in accuracy through selection of the most consensual projections.     

The effects of climate change on the phenology of selected Estonian plant, bird and fish populations

This paper summarises the trends of 943 phenological time-series of plants, fishes and birds gathered from 1948 to 1999 in Estonia. More than 80% of the studied phenological phases have advanced during springtime, whereas changes are smaller during summer and autumn. Significant values of plant and bird phases have advanced 5–20 days, and fish phases have advanced 10–30 days in the spring period. Estonia’s average air temperature has become significantly warmer in spring, while at the same time a slight decrease in air temperature has been detected in autumn. The growing season has become significantly longer in the maritime climate area of Western Estonia. The investigated phenological and climate trends are related primarily to changes in the North Atlantic Oscillation Index (NAOI) during the winter months. Although the impact of the winter NAOI on the phases decreases towards summer, the trends of the investigated phases remain high. The trends of phenophases at the end of spring and the beginning of summer may be caused by the temperature inertia of the changing winter, changes in the radiation balance or the direct consequences of human impacts such as land use, heat islands or air pollution.     

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.     

The importance of biotic interactions for modelling species distributions under climate change

Aim There is a debate as to whether biotic interactions exert a dominant role in governing species distributions at macroecological scales. The prevailing idea is that climate is the key limiting factor; thus models that use present‐day climate–species range relationships are expected to provide reasonable means to quantify the impacts of climate change on species distributions. However, there is little empirical evidence that biotic interactions would not constrain species distributions at macroecological scales. We examine this idea, for the first time, and provide tests for two null hypotheses: (H₀ 1) – biotic interactions do not exert a significant role in explaining current distributions of a particular species of butterfly (clouded Apollo, Parnassius mnemosyne) in Europe; and (H₀ 2) – biotic interactions do not exert a significant role in predictions of altered species’ ranges under climate change. Location Europe. Methods Generalized additive modelling (GAM) was used to investigate relationships between species and climate; species and host plants; and species and climate + host plants. Because models are sensitive to the variable selection strategies utilised, four alternative approaches were used: AIC (Akaike's Information Criterion), BIC (Bayesian Information Criterion), BRUTO (Adaptive Backfitting), and CROSS (Cross Selection). Results In spite of the variation in the variables selected with different methods, both hypotheses (H₀ 1 and H₀ 2) were falsified, providing support for the proposition that biotic interactions significantly affect both the explanatory and predictive power of bioclimatic envelope models at macro scales. Main conclusions Our results contradict the widely held view that the effects of biotic interactions on individual species distributions are not discernible at macroecological scales. Results are contingent on the species, type of interaction and methods considered, but they call for more stringent evidence in support of the idea that purely climate‐based modelling would be sufficient to quantify the impacts of climate change on species distributions.     

Response of the terrestrial biosphere to global climate change and human perturbation

Despite 20 years of intensive effort to understand the global carbon cycle, the budget for carbon dioxide in the atmosphere is unbalanced. To explain why atmospheric CO₂ is not increasing as rapidly as it should be, various workers have suggested that land vegetation acts as a sink for carbon dioxide. Here, I examine various possibilities and find that the evidence for a sink of sufficient magnitude on land is poor. Moreover, it is unlikely that the land vegetation will act as a sink in the postulated warmer global climates of the future. In response to rapid human population growth, destruction of natural ecosystems in the tropics remains a large net source of CO₂ for the atmosphere, which is only partially compensated by the potential for carbon storage in temperate and boreal regions. Direct and inadvertent human effects on land vegetation might increase the magnitude of regional CO₂ storage on land, but they are unlikely to play a significant role in moderating the potential rate of greenhouse warming in the future.     

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.     

Modelling the responses of Andean and Amazonian plant species to climate change: the effects of georeferencing errors and the importance of data filtering

Aim Species distribution models are a potentially powerful tool for predicting the effects of global change on species distributions and the resulting extinction risks. Distribution models rely on relationships between species occurrences and climate and may thus be highly sensitive to georeferencing errors in collection records. Most errors will not be caught using standard data filters. Here we assess the impacts of georeferencing errors and the importance of improved data filtering for estimates of the elevational distributions, habitat areas and predicted relative extinction risks due to climate change of nearly 1000 Neotropical plant species. Location The Amazon basin and tropical Andes, South America. Methods We model the elevational distributions, or ‘envelopes’, of 932 Amazonian and Andean plant species from 35 families after performing standard data filtering, and again using only data that have passed through an additional layer of data filtering. We test for agreement in the elevations recorded with the collection and the elevation inferred from a digital elevation model (DEM) at the collection coordinates. From each dataset we estimate species range areas and extinction risks due to the changes in habitat area caused by a 4.5 °C increase in temperature. Results Amazonian and Andean plant species have a median elevational range of 717 m. Using only standard data filters inflates range limits by a median of 433 m (55%). This is equivalent to overestimating the temperature tolerances of species by over 3 °C – only slightly less than the entire regional temperature change predicted over the next 50–100 years. Georeferencing errors tend to cause overestimates in the amount of climatically suitable habitat available to species and underestimates in species extinction risks due to global warming. Georeferencing error artefacts are sometimes so great that accurately predicting whether species habitat areas will decrease or increase under global warming is impossible. The drawback of additional data filtering is large decreases in the number of species modelled, with Andean species being disproportionately eliminated. Main conclusions Even with rigorous data filters, distribution models will mischaracterize the climatic conditions under which species occur due to errors in the collection data. These errors affect predictions of the effects of climate change on species ranges and biodiversity, and are particularly problematic in mountainous areas. Additional data filtering reduces georeferencing errors but eliminates many species due to a lack of sufficient ‘clean’ data, thereby limiting our ability to predict the effects of climate change in many ecologically important and sensitive regions such as the Andes Biodiversity Hotspot.     

Predicting species distribution and abundance responses to climate change: why it is essential to include biotic interactions across trophic levels

Current predictions on species responses to climate change strongly rely on projecting altered environmental conditions on species distributions. However, it is increasingly acknowledged that climate change also influences species interactions. We review and synthesize literature information on biotic interactions and use it to argue that the abundance of species and the direction of selection during climate change vary depending on how their trophic interactions become disrupted. Plant abundance can be controlled by aboveground and belowground multitrophic level interactions with herbivores, pathogens, symbionts and their enemies. We discuss how these interactions may alter during climate change and the resulting species range shifts. We suggest conceptual analogies between species responses to climate warming and exotic species introduced in new ranges. There are also important differences: the herbivores, pathogens and mutualistic symbionts of range-expanding species and their enemies may co-migrate, and the continuous gene flow under climate warming can make adaptation in the expansion zone of range expanders different from that of cross-continental exotic species. We conclude that under climate change, results of altered species interactions may vary, ranging from species becoming rare to disproportionately abundant. Taking these possibilities into account will provide a new perspective on predicting species distribution under climate change.     

Animal board invited review: Genomic-based improvement of cattle in response to climate change

Climate change brings challenges to cattle production, such as the need to adapt to new climates and pressure to reduce greenhouse emissions (GHG). In general, the improvement of traits in current breeding goals is favourably correlated with the reduction of GHG. Current breeding goals and tools for increasing cattle production efficiency have reduced GHG. The same amount of production can be achieved by a much smaller number of animals. Genomic selection (GS) may offer a cost-effective way of using an efficient breeding approach, even in low- and middle-income countries. As climate change increases the intensity of heatwaves, adaptation to heat stress leads to lower efficiency of production and, thus, is unfavourable to the goal of reducing GHG. Furthermore, there is evidence that heat stress during cow pregnancy can have many generation-long lowering effects on milk production. Both adaptation and reduction of GHG are among the difficult-to-measure traits for which GS is more efficient and suitable than the traditional non-genomic breeding evaluation approach. Nevertheless, the commonly used within-breed selection may be insufficient to meet the new challenges; thus, cross-breeding based on selecting highly efficient and highly adaptive breeds may be needed. Genomic introgression offers an efficient approach for cross-breeding that is expected to provide high genetic progress with a low rate of inbreeding. However, well-adapted breeds may have a small number of animals, which is a source of concern from a genetic biodiversity point of view. Furthermore, low animal numbers also limit the efficiency of genomic introgression. Sustainable cattle production in countries that have already intensified production is likely to emphasise better health, reproduction, feed efficiency, heat stress and other adaptation traits instead of higher production. This may require the application of innovative technologies for phenotyping and further use of new big data techniques to extract information for breeding.     

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.     

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.     

Contemporary perspectives on the niche that can improve models of species range shifts under climate change

Pioneering efforts to predict shifts in species distribution under climate change used simple models based on the correlation between contemporary environmental factors and distributions. These models make predictions at coarse spatial scales and assume the constancy of present correlations between environment and distribution. Adaptive management of climate change impacts requires models that can make more robust predictions at finer spatio-temporal scales by accounting for processes that actually affect species distribution on heterogeneous landscapes. Mechanistic models of the distribution of both species and vegetation types have begun to emerge to meet these needs. We review these developments and highlight how recent advances in our understanding of relationships among the niche concept, species diversity and community assembly point the way towards more effective models for the impacts of global change on species distribution and community diversity.     

Climate change, conservation and management: an assessment of the peer-reviewed scientific journal literature

Recent reviews of the conservation literature indicate that significant biases exist in the published literature regarding the regions, ecosystems and species that have been examined by researchers. Despite the global threat of climatic change, similar biases may be occurring within the sub-discipline of climate-change ecology. Here we hope to foster critical thought and discussion by considering the directions taken by conservation researchers when addressing climate change. To form a quantitative basis for our perspective, we assessed 248 papers from the climate change literature that considered the conservation management of biodiversity and ecosystems. We found that roughly half of the studies considered climate change in isolation from other threatening processes. We also found that the majority of surveyed scientific publications were conducted in the temperate forests of Europe and North America. Regions such as Latin America that are rich in biodiversity but may have low adaptive capacity to climate change were not well represented. We caution that such biases in research effort may be distracting our attention away from vulnerable regions, ecosystems and species. Specifically we suggest that the under-representation of research from regions low in adaptive capacity and rich in biodiversity requires international collaboration by those experienced in climate-change research, with researchers from less wealthy nations who are familiar with local issues, ecosystems and species. Furthermore, we caution that the propensity of ecologists to work in essentially unmodified ecosystems may fundamentally hamper our ability to make useful recommendations in a world that is experiencing significant global change.