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: To determine the threshold at which forest-dependent bird species become threatened with extinction, the range sizes of threatened and nonthreatened species are compared and a simple, repeatable, and practical protocol to quantify range size is presented.
Abstract: Small geographical range size is the single best predictor of threat of extinction in terrestrial species. Knowing how small a species' range has to be before authorities consider it threatened with extinction would allow prediction of a species' risk from continued deforestation and warming climates and provide a baseline for conservation and management strategies aspiring to mitigate these threats. To determine the threshold at which forest-dependent bird species become threatened with extinction, we compared the range sizes of threatened and nonthreatened species. In doing so, we present a simple, repeatable, and practical protocol to quantify range size. We started with species' ranges published in field guides or comparable sources. We then trimmed these ranges, that is, we included only those parts of the ranges that met the species' requirements of elevation and types of forest preferred. Finally, we further trimmed the ranges to the amount of forest cover that remains. This protocol generated an estimate of the remaining suitable range for each species. We compared these range estimates with those from the World Conservation Union Red List. We used the smaller of the two estimates to determine the threshold, 11,000 km2, below which birds should be considered threatened. Species considered threatened that have larger ranges than this qualified under other (nonspatial) red list criteria. We identified a suite of species (18) that have not yet qualified as threatened but that have perilously small ranges--about 11% of the nonthreatened birds we analyzed. These birds are likely at risk of extinction and reevaluation of their status is urgently needed.
147 citations
TL;DR: It is found that fall stream flow is the best predictor of average survival across all populations, and stream width and stream temperature are identified as key habitat factors that shape the responses of individual populations to climate.
Abstract: Summary
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We explored differential population responses to climate in 18 populations of threatened spring–summer Chinook salmon Onchorynchus tshawytscha in the Salmon River basin, Idaho.
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Using data from a long-term mark–release–recapture study of juvenile survival, we found that fall stream flow is the best predictor of average survival across all populations.
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To determine whether all populations responded similarly to climate, we used a cluster analysis to group populations that had similar annual fluctuations in survival. The populations grouped into four clusters, and different environmental factors were important for different clusters.
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Survival in two of the clusters was negatively correlated with summer temperature, and survival in the other two clusters was positively correlated with minimum fall stream flow, which in turn depends on snow pack from the previous winter.
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Using classification and regression tree analysis, we identified stream width and stream temperature as key habitat factors that shape the responses of individual populations to climate.
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Climate change will likely have different impacts on different populations within this metapopulation, and recognizing this diversity is important for accurately assessing risks.
146 citations
TL;DR: Large‐scale initiatives regarding data availability and quality, technological development, and capacity building should allow high‐quality modeling on a scale commensurate with the enormous potential of and need for these techniques.
Abstract: Recent advances allow harnessing enormous stores of biological and environmental data to model species niches and geographic distributions. Natural history museums hold specimens that represent the only information available for most species. Ecological niche models (sometimes termed species distribution models) combine such information with digital environmental data (especially climatic) to offer key insights for conservation biology, management of invasive species, zoonotic human diseases, and other pressing environmental problems. Five major pitfalls seriously hinder such research, especially for cross-space or cross-time uses: (1) incorrect taxonomic identifications; (2) lacking or inadequate databasing and georeferences; (3) effects of sampling bias across geography; (4) violation of assumptions related to selection of the study region; and (5) problems regarding model evaluation to identify optimal model complexity. Large-scale initiatives regarding data availability and quality, technological development, and capacity building should allow high-quality modeling on a scale commensurate with the enormous potential of and need for these techniques.
146 citations
TL;DR: Based on worldwide scholars' 3,004 papers published in 658 academic journals in the Web of Science database from 1991 to 2012, the authors quantitatively analyzes the global scientific performance and hot research areas in this field by adopting bibliometric method.
Abstract: Based on worldwide scholars’ 3,004 papers published in 658 academic journals in the Web of Science database on the topic of climate change vulnerability from 1991 to 2012, this paper quantitatively analyzes the global scientific performance and hot research areas in this field by adopting bibliometric method. The results show that (1) the vulnerability researches on climate change have experienced a rapid growth since 2006, and the publications are widely distributed in a large number of source journals, while the top two productive institutions are the University of East Anglia and Potsdam Institute for Climate Impact Research; (2) the cooperation at author level is on the rise, and there are closer relationships in institutional and national levels; (3) the most widely focused research topics in this field include health issues in the socioeconomic system, food security in the field of agricultural system and the issue of water resource management, etc.; (4) according to the papers from the top journals, we find that the research areas for climate change vulnerability in those publications are located in the ecological diversity, ecosystem service, water resource management and electric power supply, etc.
146 citations
TL;DR: This work shows how to identify when aggregation is the problem, where it has caused controversy, and proposes three ways to address it, and explains why niche differences hidden at the species level become apparent upon disaggregation to the individual level.
Abstract: As ecological data are usually analysed at a scale different from the one at which the process of interest operates, interpretations can be confusing and controversial. For example, hypothesised differences between species do not operate at the species level, but concern individuals responding to environmental variation, including competition with neighbours. Aggregated data from many individuals subject to spatio-temporal variation are used to produce species-level averages, which marginalise away the relevant (process-level) scale. Paradoxically, the higher the dimensionality, the more ways there are to differ, yet the more species appear the same. The aggregate becomes increasingly irrelevant and misleading. Standard analyses can make species look the same, reverse species rankings along niche axes, make the surprising prediction that a species decreases in abundance when a competitor is removed from a model, or simply preclude parameter estimation. Aggregation explains why niche differences hidden at the species level become apparent upon disaggregation to the individual level, why models suggest that individual-level variation has a minor impact on diversity when disaggregation shows it to be important, and why literature-based synthesis can be unfruitful. We show how to identify when aggregation is the problem, where it has caused controversy, and propose three ways to address it.
146 citations
References
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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
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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
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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