Modelling biome shifts and tree cover change for 2050 in West Africa

Aim Africa is expected to face severe changes in climatic conditions. Our objectives are: (1) to model trends and the extent of future biome shifts that may occur by 2050, (2) to model a trend in tree cover change, while accounting for human impact, and (3) to evaluate uncertainty in future climate projections. Location West Africa. Methods We modelled the potential future spatial distribution of desert, grassland, savanna, deciduous and evergreen forest in West Africa using six bioclimatic models. Future tree cover change was analysed with generalized additive models (GAMs). We used climate data from 17 general circulation models (GCMs) and included human population density and fire intensity to model tree cover. Consensus projections were derived via weighted averages to: (1) reduce inter‐model variability, and (2) describe trends extracted from different GCM projections. Results The strongest predicted effect of climate change was on desert and grasslands, where the bioclimatic envelope of grassland is projected to expand into the desert by an area of 2 million km². While savannas are predicted to contract in the south (by 54 ± 22 × 10⁴ km²), deciduous and evergreen forest biomes are expected to expand (64 ± 13 × 10⁴ km² and 77 ± 26 × 10⁴ km²). However, uncertainty due to different GCMs was particularly high for the grassland and the evergreen biome shift. Increasing tree cover (1–10%) was projected for large parts of Benin, Burkina Faso, Côte d’Ivoire, Ghana and Togo, but a decrease was projected for coastal areas (1–20%). Furthermore, human impact negatively affected tree cover and partly changed the direction of the projected change from increase to decrease. Main conclusions Considering climate change alone, the model results of potential vegetation (biomes) show a ‘greening’ trend by 2050. However, the modelled effects of human impact suggest future forest degradation. Thus, it is essential to consider both climate change and human impact in order to generate realistic future tree cover projections.     

Potential impacts of climatic change on the breeding and non-breeding ranges and migration distance of European Sylvia warblers

Aim  To explore the potential impacts of climatic change on species with different migratory strategies using Sylvia warblers breeding in Europe as a ‘model’ species group. Location  Europe and Africa. Methods  Climate response surfaces and generalized additive models (GAMs) were used to model relationships between species recorded breeding and non‐breeding ranges and recent climate. Species potential future breeding and non‐breeding ranges were simulated for three scenarios of late 21st‐century climate. The simulated potential future and present ranges were compared in terms of their relative extent and overlap, as well as their location. The impact of any shifts in potential range location on migration distance were quantified. Results  Potential breeding ranges consistently showed a shift northwards, whereas potential non‐breeding ranges showed no consistent directional shift, even when trans‐Saharan migrants were considered separately from resident/short‐distance or partial migrants. Future potential range extent relative to simulated recent range extent varied considerably among species, although on average range extent increased. Overlap between future and recent simulated range was generally low, averaging < 36% for both breeding and non‐breeding ranges. Overlap was consistently less for range‐restricted than for widespread species. Migration distance increased generally, by about twice as much in the case of trans‐Saharan migrant species than for short‐distance migrants. In many cases potential future non‐breeding areas were simulated in regions far from the species present non‐breeding area, suggesting that new migration strategies and routes may need to be developed in response to climatic change. Main conclusions  Migratory species can be expected to suffer greater negative impacts from climatic change than species that are resident or undertake only short‐distance or partial migrations. Trans‐Saharan migrants face the greatest potential increases in migration distances, whereas range‐restricted species are expected to experience major population reductions because of the limited, or in some cases lack of, overlap between their present and potential future ranges.     

The relative importance of deforestation,precipitation change,and temperature sensitivity in determining the future distributions and diversity of Amazonian plant species

Tropical forests are threatened by many human disturbances – two of the most important of which are deforestation and climate change. To mitigate the impacts of these disturbances, it is important to understand their potential effects on the distributions of species. In the tropics, such understanding has been hindered by poor knowledge of the current distributions and range limits of most species. Here, we use herbarium collection records to model the current and future distributions of ca. 3000 Amazonian plant species. We project these distributions into the future under a range of different scenarios related to the magnitude of climate change and extent of deforestation as well as the response of species to changes in temperature, precipitation, and atmospheric concentrations of CO₂ . We find that the future of Amazonian diversity will be dependant primarily on the ability of species to tolerate or adapt to rising temperatures. If the thermal niches of tropical plant species are fixed and incapable of expanding under rapid warming, then the negative effects of climate change will overshadow the effects of deforestation, greatly reducing the area of suitable habitat available to most species and potentially leading to massive losses of biodiversity throughout the Amazon. If tropical species are generally capable of tolerating warmer temperatures, rates of habitat loss will be greatly reduced but many parts of Amazonia may still experience rapid losses of diversity, with the effects of enhanced seasonal water stress being similar in magnitude to the effects of deforestation.     

Inclusion of soil data improves the performance of bioclimatic envelope models for insect species distributions in temperate Europe

Aim To analyse the effect of the inclusion of soil and land‐cover data on the performance of bioclimatic envelope models for the regional‐scale prediction of butterfly (Rhopalocera) and grasshopper (Orthoptera) distributions. Location Temperate Europe (Belgium). Methods Distributional data were extracted from butterfly and grasshopper atlases at a resolution of 5 km for the period 1991–2006 in Belgium. For each group separately, the well‐surveyed squares (n = 366 for butterflies and n = 322 for grasshoppers) were identified using an environmental stratification design and were randomly divided into calibration (70%) and evaluation (30%) datasets. Generalized additive models were applied to the calibration dataset to estimate occurrence probabilities for 63 butterfly and 33 grasshopper species, as a function of: (1) climate, (2) climate and land‐cover, (3) climate and soil, and (4) climate, land‐cover and soil variables. Models were evaluated as: (1) the amount of explained deviance in the calibration dataset, (2) Akaike’s information criterion, and (3) the number of omission and commission errors in the evaluation dataset. Results Information on broad land‐cover classes or predominant soil types led to similar improvements in the performance relative to the climate‐only models for both taxonomic groups. In addition, the joint inclusion of land‐cover and soil variables in the models provided predictions that fitted more closely to the species distributions than the predictions obtained from bioclimatic models incorporating only land‐cover or only soil variables. The combined models exhibited higher discrimination ability between the presence and absence of species in the evaluation dataset. Main conclusions These results draw attention to the importance of soil data for species distribution models at regional scales of analysis. The combined inclusion of land‐cover and soil data in the models makes it possible to identify areas with suitable climatic conditions but unsuitable combinations of vegetation and soil types. While contingent on the species, the results indicate the need to consider soil information in regional‐scale species–climate impact models, particularly when predicting future range shifts of species under climate change.     

Predicting invasions in Australia by a Neotropical shrub under climate change: the challenge of novel climates and parameter estimation

Aim  To test how well species distributions and abundance can be predicted following invasion and climate change when using only species distribution and abundance data to estimate parameters.
Location  Models were developed for the species' native range in the Americas and applied to Australia.
Methods  We developed a predictive model for an invasive neotropical shrub ( Parkinsonia aculeata) using a popular ecophysiological bioclimatic modelling technique (CLIMEX) fitted against distribution and abundance data in the Americas. The effect of uncertainty in model parameter estimates on predictions in Australia was tested. Alternative data sources were used when model predictions were sensitive to uncertainty in parameter estimates. The resulting best-fit model was run under two climate change scenarios.
Results  Of the 19 parameters used, 9 could not be fitted using data from the native range. However, only parameters that lowered temperature or increased moisture requirements for growth noticeably altered the model prediction in Australia. Differences in predictions were dramatic, and reflect climates in Australia that were not represented in the Americas (novel climates). However, these poorly fitted parameters could be fitted post hoc using alternative data sources prior to predicting responses to climate change.
Conclusions  Novel climates prevented the development of a predictive model which relied only on native-range distribution and abundance data because certain parameters could not be fitted. In fact, predictions were more sensitive to parameter uncertainty than to climate change scenarios. Where uncertainty in parameter estimates affected predictions, it could be addressed through the inclusion of alternative data sources. However, this may not always be possible, for example in the absence of post-invasion data.     

Climate change at the landscape scale: predicting fine-grained spatial heterogeneity in warming and potential refugia for vegetation

Current predictions of how species will respond to climate change are based on coarse‐grained climate surfaces or idealized scenarios of uniform warming. These predictions may erroneously estimate the risk of extinction because they neglect to consider spatially heterogenous warming at the landscape scale or identify refugia where species can persist despite unfavourable regional climate. To address this issue, we investigated the heterogeneity in warming that has occurred in a 10 km × 10 km area from 1972 to 2007. We developed estimates by combining long‐term daily observations from a limited number of weather stations with a more spatially comprehensive dataset (40 sites) obtained during 2005–2006. We found that the spatial distribution of warming was greater inland, at lower elevations, away from streams, and at sites exposed to the northwest (NW). These differences corresponded with changes in weather patterns, such as an increasing frequency of hot, dry NW winds. As plant species were biased in the topographic and geographic locations they occupied, these differences meant that some species experienced more warming than others, and are at greater risk from climate change. This species bias could not be detected at coarser scales. The uneven seasonal nature of warming (e.g. more warming in winter, minimums increased more than maximums) means that climate change predictions will vary according to which predictors are selected in species distribution models. Models based on a limited set of predictors will produce erroneous predictions when the correct limiting factor is not selected, and this is difficult to avoid when temperature predictors are correlated because they are produced using elevation‐sensitive interpolations. The results reinforce the importance of downscaling coarse‐grained (∼50 km) temperature surfaces, and suggest that the accuracy of this process could be improved by considering regional weather patterns (wind speed, direction, humidity) and topographic exposure to key wind directions.     

The data void in modeling current and future distributions of tropical species

Conserving biodiversity in the face of climate change requires a predictive ecology of species distributions. Nowhere is this need more acute than in the tropics, which harbor the majority of Earth's species and face rapid and large climate and land‐use changes. However, the study of species distributions and their responses to climate change in high diversity tropical regions is potentially crippled by a lack of basic data. We analyzed a database representing more than 800 000 unique geo‐referenced natural history collections to determine what fraction of tropical plant species has sufficient numbers of available collections for use in the habitat or niche models commonly used to predict species responses to climate change. We found that more than nine out of 10 species from the three principle tropical realms are so poorly collected (n < 20 records) that they are essentially invisible to modern modeling and conservation tools. In order to predict the impact of climate change on tropical species, efforts must be made to increase the amount of data available from tropical countries through a combination of collecting new specimens and digitizing existing records.     

Climate change, anthropogenic disturbance and the northward range expansion of Lactuca serriola (Asteraceae)

Aim The distribution range of Lactuca serriola, a species native to the summer‐dry mediterranean climate, has expanded northwards during the last 250 years. This paper assesses the influence of climate on the range expansion of this species and highlights the importance of anthropogenic disturbance to its spread. Location Central and Northern Europe. Methods Data on the geographic distribution of L. serriola were assembled through a literature search as well as through floristic and herbarium surveys. Maps of the spread of L. serriola in Central and Northern Europe were prepared based on herbarium data. The spread was assessed more precisely in Germany, Austria and Great Britain by pooling herbarium and literature data. We modelled the bioclimatic niche of the species using occurrence and climatic data covering the last century to generate projections of suitable habitats under the climatic conditions of five time periods. We tested whether the observed distribution of L. serriola could be explained for each time period, assuming that the climatic niche of the species was conserved across time. Results The species has spread northwards since the beginning of the 19th century. We show that climate warming in Europe increased the number of sites suitable for the species at northern latitudes. Until the late 1970s, the distribution of the species corresponded to the climatically suitable sites available. For the last two decades, however, we could not show any significant relationship between the increase in suitable sites and the distributional range change of L. serriola. However, we highlight potential areas the species could spread to in the future (Great Britain, southern Scandinavia and the Swedish coast). It is predominantly non‐climatic influences of global change that have contributed to its rapid spread. Main conclusions The observation that colonizing species are not filling their climatically suitable range might imply that, potentially, other ruderal species could expand far beyond their current range. Our work highlights the importance of historical floristic and herbarium data for understanding the expansion of a species. Such historical distributional data can provide valuable information for those planning the management of contemporary environmental problems, such as species responses to environmental change.     

Predicting current and future global distributions of whale sharks

The Vulnerable (IUCN) whale shark spans warm and temperate waters around the globe. However, their present‐day and possible future global distribution has never been predicted. Using 30 years (1980–2010) of whale shark observations recorded by tuna purse‐seiners fishing in the Atlantic, Indian and Pacific Oceans, we applied generalized linear mixed‐effects models to test the hypothesis that similar environmental covariates predict whale shark occurrence in all major ocean basins. We derived global predictors from satellite images for chlorophyll a and sea surface temperature, and bathymetric charts for depth, bottom slope and distance to shore. We randomly generated pseudo‐absences within the area covered by the fisheries, and included fishing effort as an offset to account for potential sampling bias. We predicted sea surface temperatures for 2070 using an ensemble of five global circulation models under a no climate‐policy reference scenario, and used these to predict changes in distribution. The full model (excluding standard deviation of sea surface temperature) had the highest relative statistical support (wAIC_c = 0.99) and explained ca. 60% of the deviance. Habitat suitability was mainly driven by spatial variation in bathymetry and sea surface temperature among oceans, although these effects differed slightly among oceans. Predicted changes in sea surface temperature resulted in a slight shift of suitable habitat towards the poles in both the Atlantic and Indian Oceans (ca. 5°N and 3–8°S, respectively) accompanied by an overall range contraction (2.5–7.4% and 1.1–6.3%, respectively). Predicted changes in the Pacific Ocean were small. Assuming that whale shark environmental requirements and human disturbances (i.e. no stabilization of greenhouse gas emissions) remain similar, we show that warming sea surface temperatures might promote a net retreat from current aggregation areas and an overall redistribution of the species.     

Impact of landscape predictors on climate change modelling of species distributions: a case study with Eucalyptus fastigata in southern New South Wales,Australia

Aim We consider three questions. (1) How different are the predicted distribution maps when climate‐only and climate‐plus‐terrain models are developed from high‐resolution data? (2) What are the implications of differences between the models when predicting future distributions under climate change scenarios, particularly for climate‐only models at coarse resolution? (3) Does the use of high‐resolution data and climate‐plus‐terrain models predict an increase in the number of local refugia? Location South‐eastern New South Wales, Australia. Methods We developed two species distribution models for Eucalyptus fastigata under current climate conditions using generalized additive modelling. One used only climate variables as predictors (mean annual temperature, mean annual rainfall, mean summer rainfall); the other used both climate and landscape (June daily radiation, topographic position, lithology, nutrients) variables as predictors. Predictions of the distribution under current climate and climate change were then made for both models at a pixel resolution of 100 m. Results The model using climate and landscape variables as predictors explained a significantly greater proportion of the deviance than the climate‐only model. Inclusion of landscape variables resulted in the prediction of much larger areas of existing optimal habitat. An overlay of predicted future climate on the current climate space indicated that extrapolation of the statistical models was not occurring and models were therefore more robust. Under climate change, landscape‐defined refugia persisted in areas where the climate‐only model predicted major declines. In areas where expansion was predicted, the increase in optimal habitat was always greater with landscape predictors. Recognition of extensive optimal habitat conditions and potential refugia was dependent on the use of high‐resolution landscape data. Main conclusions Using only climate variables as predictors for assessing species responses to climate change ignores the accepted conceptual model of plant species distribution. Explicit statements justifying the selection of predictors based on ecological principles are needed. Models using only climate variables overestimate range reduction under climate change and fail to predict potential refugia. Fine‐scale‐resolution data are required to capture important climate/landscape interactions. Extrapolation of statistical models to regions in climate space outside the region where they were fitted is risky.     

Climate change and the future restructuring of Neotropical anuran biodiversity

Climate change is likely to impact multiple dimensions of biodiversity. Species range shifts are expected and may drive changes in the composition of species assemblages. In some regions, changes in climate may precipitate the loss of geographically restricted, niche specialists and facilitate their replacement by more widespread, niche generalists, leading to decreases in β-diversity and biotic homogenization. However, in other regions climate change may drive local extinctions and range contraction, leading to increases in β-diversity and biotic heterogenization. Regional topography should be a strong determinant of such changes as mountainous areas often are home to many geographically restricted species, whereas lowlands and plains are more often inhabited by widespread generalists. Climate warming, therefore, may simultaneously bring about opposite trends in β-diversity in mountainous highlands versus relatively flat lowlands. To test this hypothesis, we used species distribution modelling to map the present-day distributions of 2669 Neotropical anuran species, and then generated projections of their future distributions assuming future climate change scenarios. Using traditional metrics of β-diversity, we mapped shifts in biotic homogenization across the entire Neotropical region. We used generalized additive models to then evaluate how changes in β-diversity were associated with shifts in species richness, phylogenetic diversity and one measure of ecological generalism. Consistent with our hypothesis, we find increasing biotic homogenization in most highlands, associated with increased numbers of generalists and, to a lesser extent, losses of specialists, leading to an overall increase in alpha diversity, but lower mean phylogenetic diversity. In the lowlands, biotic heterogenization was more common, and primarily driven by local extinctions of generalists, leading to lower α-diversity, but higher mean phylogenetic diversity. Our results suggest that impacts of climate change on β-diversity are likely to vary regionally, but will generally lead to lower diversity, with increases in β-diversity offset by decreases in α-diversity.     

Climate and host plant availability impact the future distribution of the bean leaf beetle (Cerotoma trifurcata)

The bean leaf beetle, Cerotoma trifurcata, has become a major pest of soybean throughout its North American range. With a changing climate, there is the potential for this pest to further expand its distribution and become an increasingly severe pest in certain regions. To examine this possibility, we developed bioclimatic envelope models for both the bean leaf beetle, and its most important agronomic host plant, soybean (Glycine max). These two models were combined to examine the potential future pest status of the beetle using climate change projections from multiple general circulation models (GCMs) and climate change scenarios. Despite the broad tolerances of soybean, incorporation of host plant availability substantially decreased the suitable and favourable areas for the bean leaf beetle as compared to an evaluation based solely on the climate envelope of the beetle, demonstrating the importance of incorporating biotic interactions in these predictions. The use of multiple GCM–scenario combinations also revealed differences in predictions depending on the choice of GCM, with scenario choice having less of an impact. While the Norwegian model predicted little northward expansion of the beetle from its current northern range limit of southern Ontario and overall decreases in suitable and favourable areas over time, the Canadian and Russian models predict that much of Ontario and Quebec will become suitable for the beetle in the future, as well as Manitoba under the Russian model. The Russian model also predicts expansion of the suitable and favourable areas for the beetle over time. Two predictions that do not depend on our choice of GCM include a decrease in suitability of the Mississippi Delta region and continued favourability of the southeastern United States.     

The ability of climate envelope models to predict the effect of climate change on species distributions

Climate envelope models (CEMs) have been used to predict the distribution of species under current, past, and future climatic conditions by inferring a species' environmental requirements from localities where it is currently known to occur. CEMs can be evaluated for their ability to predict current species distributions but it is unclear whether models that are successful in predicting current distributions are equally successful in predicting distributions under different climates (i.e. different regions or time periods). We evaluated the ability of CEMs to predict species distributions under different climates by comparing their predictions with those obtained with a mechanistic model (MM). In an MM the distribution of a species is modeled based on knowledge of a species' physiology. The potential distributions of 100 plant species were modeled with an MM for current conditions, a past climate reconstruction (21 000 years before present) and a future climate projection (double preindustrial CO₂ conditions). Point localities extracted from the currently suitable area according to the MM were used to predict current, future, and past distributions with four CEMs covering a broad range of statistical approaches: Bioclim (percentile distributions), Domain (distance metric), GAM (general additive modeling), and Maxent (maximum entropy). Domain performed very poorly, strongly underestimating range sizes for past or future conditions. Maxent and GAM performed as well under current climates as under past and future climates. Bioclim slightly underestimated range sizes but the predicted ranges overlapped more with the ranges predicted with the MM than those predicted with GAM did. Ranges predicted with Maxent overlapped most with those produced with the MMs, but compared with the ranges predicted with GAM they were more variable and sometimes much too large. Our results suggest that some CEMs can indeed be used to predict species distributions under climate change, but individual modeling approaches should be validated for this purpose, and model choice could be made dependent on the purpose of a particular study.     

Global diversity patterns of larger benthic foraminifera under future climate change

Global warming threatens the viability of tropical coral reefs and associated marine calcifiers, including symbiont-bearing larger benthic foraminifera (LBF). The impacts of current climate change on LBF are debated because they were particularly diverse and abundant during past warm periods. Studies on the responses of selected LBF species to changing environmental conditions reveal varying results. Based on a comprehensive review of the scientific literature on LBF species occurrences, we applied species distribution modeling using Maxent to estimate present-day and future species richness patterns on a global scale for the time periods 2040–2050 and 2090–2100. For our future projections, we focus on Representative Concentration Pathway 6.0 from the Intergovernmental Panel on Climate Change, which projects mean surface temperature changes of +2.2°C by the year 2100. Our results suggest that species richness in the Central Indo-Pacific is two to three times higher than in the Bahamian ecoregion, which we have identified as the present-day center of LBF diversity in the Atlantic. Our future predictions project a dramatic temperature-driven decline in low-latitude species richness and an increasing widening bimodal latitudinal pattern of species diversity. While the central Indo-Pacific, now the stronghold of LBF diversity, is expected to be most pushed outside of the currently realized niches of most species, refugia may be largely preserved in the Atlantic. LBF species will face large-scale non-analogous climatic conditions compared to currently realized climate space in the near future, as reflected in the extensive areas of extrapolation, particularly in the Indo-Pacific. Our study supports hypotheses that species richness and biogeographic patterns of LBF will fundamentally change under future climate conditions, possibly initiating a faunal turnover by the late 21st century.     

Potential effects of future climate change on global reptile distributions and diversity

Aim

Until recently, complete information on global reptile distributions has not been widely available. Here, we provide the first comprehensive climate impact assessment for reptiles on a global scale.

Location

Global, excluding Antarctica.

Time period

1995, 2050 and 2080.

Major taxa studied

Reptiles.

Methods

We modelled the distribution of 6296 reptile species and assessed potential global and realm-specific changes in species richness, the change in global species richness across climate space, and species-specific changes in range extent, overlap and position under future climate change. To assess the future climatic impact on 3768 range-restricted species, which could not be modelled, we compared the future change in climatic conditions between both modelled and non-modelled species.

Results

Reptile richness was projected to decline significantly over time, globally but also for most zoogeographical realms, with the greatest decreases in Brazil, Australia and South Africa. Species richness was highest in warm and moist regions, with these regions being projected to shift further towards climate extremes in the future. Range extents were projected to decline considerably in the future, with a low overlap between current and future ranges. Shifts in range centroids differed among realms and taxa, with a dominant global poleward shift. Non-modelled species were significantly stronger affected by projected climatic changes than modelled species.

Main conclusions

With ongoing future climate change, reptile richness is likely to decrease significantly across most parts of the world. This effect, in addition to considerable impacts on species range extent, overlap and position, was visible across lizards, snakes and turtles alike. Together with other anthropogenic impacts, such as habitat loss and harvesting of species, this is a cause for concern. Given the historical lack of global reptile distributions, this calls for a re-assessment of global reptile conservation efforts, with a specific focus on anticipated future climate change.