Extinction risk from climate change
University of Leeds1, University of Cambridge2, Royal Society for the Protection of Birds3, Macquarie University4, Durham University5, University of the Witwatersrand6, Conservation International7, Stellenbosch University8, World Conservation Monitoring Centre9, National Autonomous University of Mexico10, University of Kansas11, James Cook University12
TL;DR: Estimates of extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.
Abstract: Climate change over the past approximately 30 years has produced numerous shifts in the distributions and abundances of species and has been implicated in one species-level extinction. Using projections of species' distributions for future climate scenarios, we assess extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface. Exploring three approaches in which the estimated probability of extinction shows a power-law relationship with geographical range size, we predict, on the basis of mid-range climate-warming scenarios for 2050, that 15-37% of species in our sample of regions and taxa will be 'committed to extinction'. When the average of the three methods and two dispersal scenarios is taken, minimal climate-warming scenarios produce lower projections of species committed to extinction ( approximately 18%) than mid-range ( approximately 24%) and maximum-change ( approximately 35%) scenarios. These estimates show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.
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TL;DR: This work examines how parasite development within the mosquito (Extrinsic Incubation Period) is expected to vary over time and space depending on the diurnal temperature range and baseline mean temperature in Kenya and across Africa.
Abstract: Temperature is an important determinant of malaria transmission. Recent work has shown that mosquito and parasite biology are influenced not only by average temperature, but also by the extent of the daily temperature variation. Here we examine how parasite development within the mosquito (Extrinsic Incubation Period) is expected to vary over time and space depending on the diurnal temperature range and baseline mean temperature in Kenya and across Africa. Our results show that under cool conditions, the typical approach of using mean monthly temperatures alone to characterize the transmission environment will underestimate parasite development. In contrast, under warmer conditions, the use of mean temperatures will overestimate development. Qualitatively similar patterns hold using both outdoor and indoor temperatures. These findings have important implications for defining malaria risk. Furthermore, understanding the influence of daily temperature dynamics could provide new insights into ectotherm ecology both now and in response to future climate change.
195 citations
TL;DR: This study develops and applies a new generic modelling approach (AdaptR) that incorporates adaptive capacity through physiological limits, phenotypic plasticity, evolutionary adaptation and dispersal into a species distribution modelling framework, and suggests some species could be less vulnerable than previously thought.
Abstract: Based on the sensitivity of species to ongoing climate change, and numerous challenges they face tracking suitable conditions, there is growing interest in species' capacity to adapt to climatic stress. Here, we develop and apply a new generic modelling approach (AdaptR) that incorporates adaptive capacity through physiological limits, phenotypic plasticity, evolutionary adaptation and dispersal into a species distribution modelling framework. Using AdaptR to predict change in the distribution of 17 species of Australian fruit flies (Drosophilidae), we show that accounting for adaptive capacity reduces projected range losses by up to 33% by 2105. We identify where local adaptation is likely to occur and apply sensitivity analyses to identify the critical factors of interest when parameters are uncertain. Our study suggests some species could be less vulnerable than previously thought, and indicates that spatiotemporal adaptive models could help improve management interventions that support increased species' resilience to climate change.
194 citations
TL;DR: In this article, an empirically-derived model of the interaction between habitat loss and climate was used to predict the implications of this for biodiversity loss and conservation priorities at a global scale.
194 citations
Cites background from "Extinction risk from climate change..."
...Loss and fragmentation of habitat may also severely hinder the movement of species and their ability to cope with climate change through tracking of suitable climatic conditions (Brook et al., 2009; Keith et al., 2008; Thomas et al., 2004)....
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TL;DR: In this paper, a longitudinal analysis of 27,000 individual trees over 6-18 years was conducted to identify which species are vulnerable to climate change and in what ways, including the heretofore overlooked impact on fecundity.
Abstract: Forest responses to climate change will depend on demographic impacts in the context of competition. Current models used to predict species responses, termed climate envelope models (CEMs), are controversial, because (i) calibration and prediction are based on correlations in space (CIS) between species abundance and climate, rather than responses to climate change over time (COT), and (ii) they omit competition. To determine the relative importance of COT, CIS, and competition for light, we applied a longitudinal analysis of 27 000 individual trees over 6–18 years subjected to experimental and natural variation in risk factors. Sensitivities and climate and resource tracking identify which species are vulnerable to these risk factors and in what ways. Results show that responses to COT differ from those predicted based on CIS. The most important impact is the effect of spring temperature on fecundity, rather than any input variable on growth or survival. Of secondary importance is growing season moisture. Species in the genera Pinus, Ulmus, Magnolia, and Fagus are particularly vulnerable to climate variation. However, the effect of competition on growth and mortality risk exceeds the effects of climate variation in space or time for most species. Because sensitivities to COT and competition are larger than CIS, current models miss the most important effects. By directly comparing sensitivity to climate in time and space, together with competition, the approach identifies which species are sensitive to climate change and why, including the heretofore overlooked impact on fecundity.
194 citations
TL;DR: In this article, the authors compared different schemes and measures for testing model performance using 79 species from the North American Breeding Bird Survey (NBS) and found that higher levels of independence between test and training data lead to lower assessments of prediction accuracy.
Abstract: Distribution models are used to predict the likelihood of occurrence or abundance of a species at locations where census data are not available. An integral part of modelling is the testing of model performance. We compared different schemes and measures for testing model performance using 79 species from the North American Breeding Bird Survey. The four testing schemes we compared featured increasing independence between test and training data: resubstitution, random data hold-out and two spatially segregated data hold-out designs. The different testing measures also addressed different levels of information content in the dependent variable: regression R 2 for absolute abundance, squared correlation coefficient r 2 for relative abundance and AUC/Somer’s D for presence/absence. We found that higher levels of independence between test and training data lead to lower assessments of prediction accuracy. Even for data collected independently, spatial autocorrelation leads to dependence between random hold-out test data and training data, and thus to inflated measures of model performance. While there is a general awareness of the importance of autocorrelation to model building and hypothesis testing, its consequences via violation of independence between training and testing data have not been addressed systematically and comprehensively before. Furthermore, increasing information content (from correctly classifying presence/absence, to predicting relative abundance, to predicting absolute abundance) leads to decreasing predictive performance. The current tests for presence/absence distribution models are typically overly optimistic because a) the test and training data are not independent and b) the correct classification of presence/absence has a relatively low information content and thus capability to address ecological and conservation questions compared to a prediction of abundance. Meaningful evaluation of model performance requires testing on spatially independent data, if the intended application of the model is to predict into new geographic or climatic space, which arguably is the case for most applications of distribution models.
194 citations
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TL;DR: A ‘silver bullet’ strategy on the part of conservation planners, focusing on ‘biodiversity hotspots’ where exceptional concentrations of endemic species are undergoing exceptional loss of habitat, is proposed.
Abstract: Conservationists are far from able to assist all species under threat, if only for lack of funding. This places a premium on priorities: how can we support the most species at the least cost? One way is to identify 'biodiversity hotspots' where exceptional concentrations of endemic species are undergoing exceptional loss of habitat. As many as 44% of all species of vascular plants and 35% of all species in four vertebrate groups are confined to 25 hotspots comprising only 1.4% of the land surface of the Earth. This opens the way for a 'silver bullet' strategy on the part of conservation planners, focusing on these hotspots in proportion to their share of the world's species at risk.
24,867 citations
"Extinction risk from climate change..." refers background in this paper
...Second, for cerrado vegetation in Brazil, high rates of habitat destructio...
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TL;DR: In this article, the authors present an overview of the climate system and its dynamics, including observed climate variability and change, the carbon cycle, atmospheric chemistry and greenhouse gases, and their direct and indirect effects.
Abstract: Summary for policymakers Technical summary 1. The climate system - an overview 2. Observed climate variability and change 3. The carbon cycle and atmospheric CO2 4. Atmospheric chemistry and greenhouse gases 5. Aerosols, their direct and indirect effects 6. Radiative forcing of climate change 7. Physical climate processes and feedbacks 8. Model evaluation 9. Projections of future climate change 10. Regional climate simulation - evaluation and projections 11. Changes in sea level 12. Detection of climate change and attribution of causes 13. Climate scenario development 14. Advancing our understanding Glossary Index Appendix.
13,366 citations
TL;DR: A diagnostic fingerprint of temporal and spatial ‘sign-switching’ responses uniquely predicted by twentieth century climate trends is defined and generates ‘very high confidence’ (as laid down by the IPCC) that climate change is already affecting living systems.
Abstract: Causal attribution of recent biological trends to climate change is complicated because non-climatic influences dominate local, short-term biological changes. Any underlying signal from climate change is likely to be revealed by analyses that seek systematic trends across diverse species and geographic regions; however, debates within the Intergovernmental Panel on Climate Change (IPCC) reveal several definitions of a 'systematic trend'. Here, we explore these differences, apply diverse analyses to more than 1,700 species, and show that recent biological trends match climate change predictions. Global meta-analyses documented significant range shifts averaging 6.1 km per decade towards the poles (or metres per decade upward), and significant mean advancement of spring events by 2.3 days per decade. We define a diagnostic fingerprint of temporal and spatial 'sign-switching' responses uniquely predicted by twentieth century climate trends. Among appropriate long-term/large-scale/multi-species data sets, this diagnostic fingerprint was found for 279 species. This suite of analyses generates 'very high confidence' (as laid down by the IPCC) that climate change is already affecting living systems.
9,761 citations
"Extinction risk from climate change..." refers background in this paper
...gif" NDATA ITEM> ]> Climate change over the past ∼30 years has produced numerous shifts in the distributions and abundances of specie...
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University of Buenos Aires1, University of Alaska Fairbanks2, University of Chile3, University of California, Berkeley4, Environmental Defense Fund5, National Autonomous University of Mexico6, Technische Universität München7, New Mexico State University8, Duke University9, Arizona State University10, University of Notre Dame11, Stanford University12, Colorado State University13, Commonwealth Scientific and Industrial Research Organisation14
TL;DR: This study identified a ranking of the importance of drivers of change, aranking of the biomes with respect to expected changes, and the major sources of uncertainties in projections of future biodiversity change.
Abstract: Scenarios of changes in biodiversity for the year 2100 can now be developed based on scenarios of changes in atmospheric carbon dioxide, climate, vegetation, and land use and the known sensitivity of biodiversity to these changes. This study identified a ranking of the importance of drivers of change, a ranking of the biomes with respect to expected changes, and the major sources of uncertainties. For terrestrial ecosystems, land-use change probably will have the largest effect, followed by climate change, nitrogen deposition, biotic exchange, and elevated carbon dioxide concentration. For freshwater ecosystems, biotic exchange is much more important. Mediterranean climate and grassland ecosystems likely will experience the greatest proportional change in biodiversity because of the substantial influence of all drivers of biodiversity change. Northern temperate ecosystems are estimated to experience the least biodiversity change because major land-use change has already occurred. Plausible changes in biodiversity in other biomes depend on interactions among the causes of biodiversity change. These interactions represent one of the largest uncertainties in projections of future biodiversity change.
8,401 citations
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26 May 1995TL;DR: In this article, the authors present a hierarchical dynamic puzzle to understand the relationship between habitat diversity and species diversity and the evolution of the relationships between habitats diversity and diversity in evolutionary time.
Abstract: Preface 1 The road ahead 2 Patterns in space 3 Temporal patterns 4 Dimensionless patterns 5 Speciation 6 Extinction 7 Evolution of the relationship between habitat diversity and species diversity 8 Species-area curves in ecological time 9 Species-area curves in evolutionary time 10 Paleobiological patterns 11 Other patterns with dynamic roots 12 Energy flow and diversity 13 A hierarchical dynamic puzzle References Index
4,812 citations