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Journal ArticleDOI

Extinction risk from climate change

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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Citations
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Journal ArticleDOI
TL;DR: In this paper, the use of the maximum entropy method (Maxent) for modeling species geographic distributions with presence-only data was introduced, which is a general-purpose machine learning method with a simple and precise mathematical formulation.

13,120 citations


Cites background from "Extinction risk from climate change..."

  • ...This is important for applications such as invasive-species management (e.g.,Peterson and Robins, 2003) and predicting the impact of climate change (e.g.,Thomas et al., 2004)....

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Journal ArticleDOI
TL;DR: This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
Abstract: Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.

7,589 citations

Journal ArticleDOI
TL;DR: An overview of recent advances in species distribution models, and new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales are suggested.
Abstract: In the last two decades, interest in species distribution models (SDMs) of plants and animals has grown dramatically. Recent advances in SDMs allow us to potentially forecast anthropogenic effects on patterns of biodiversity at different spatial scales. However, some limitations still preclude the use of SDMs in many theoretical and practical applications. Here, we provide an overview of recent advances in this field, discuss the ecological principles and assumptions underpinning SDMs, and highlight critical limitations and decisions inherent in the construction and evaluation of SDMs. Particular emphasis is given to the use of SDMs for the assessment of climate change impacts and conservation management issues. We suggest new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales. Addressing all these issues requires a better integration of SDMs with ecological theory.

5,620 citations


Cites background from "Extinction risk from climate change..."

  • ...The application of SDMs to climate change analyses was highlighted by a recent, massive study assessing global species extinction risk (Thomas et al. 2004)....

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  • ...Second, in most projections, species dispersal is inappropriately taken into consideration, relying either on a no dispersal , an unlimited dispersal scenarios, or both (e.g. Thomas et al. 2004; Thuiller 2004)....

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Journal ArticleDOI
TL;DR: This paper presents a tuning method that uses presence-only data for parameter tuning, and introduces several concepts that improve the predictive accuracy and running time of Maxent and describes a new logistic output format that gives an estimate of probability of presence.
Abstract: Accurate modeling of geographic distributions of species is crucial to various applications in ecology and conservation. The best performing techniques often require some parameter tuning, which may be prohibitively time-consuming to do separately for each species, or unreliable for small or biased datasets. Additionally, even with the abundance of good quality data, users interested in the application of species models need not have the statistical knowledge required for detailed tuning. In such cases, it is desirable to use "default settings", tuned and validated on diverse datasets. Maxent is a recently introduced modeling technique, achieving high predictive accuracy and enjoying several additional attractive properties. The performance of Maxent is influenced by a moderate number of parameters. The first contribution of this paper is the empirical tuning of these parameters. Since many datasets lack information about species absence, we present a tuning method that uses presence-only data. We evaluate our method on independently collected high-quality presence-absence data. In addition to tuning, we introduce several concepts that improve the predictive accuracy and running time of Maxent. We introduce "hinge features" that model more complex relationships in the training data; we describe a new logistic output format that gives an estimate of probability of presence; finally we explore "background sampling" strategies that cope with sample selection bias and decrease model-building time. Our evaluation, based on a diverse dataset of 226 species from 6 regions, shows: 1) default settings tuned on presence-only data achieve performance which is almost as good as if they had been tuned on the evaluation data itself; 2) hinge features substantially improve model performance; 3) logistic output improves model calibration, so that large differences in output values correspond better to large differences in suitability; 4) "target-group" background sampling can give much better predictive performance than random background sampling; 5) random background sampling results in a dramatic decrease in running time, with no decrease in model performance.

5,314 citations

Journal ArticleDOI
19 Aug 2011-Science
TL;DR: A meta-analysis shows that species are shifting their distributions in response to climate change at an accelerating rate, and that the range shift of each species depends on multiple internal species traits and external drivers of change.
Abstract: The distributions of many terrestrial organisms are currently shifting in latitude or elevation in response to changing climate Using a meta-analysis, we estimated that the distributions of species have recently shifted to higher elevations at a median rate of 110 meters per decade, and to higher latitudes at a median rate of 169 kilometers per decade These rates are approximately two and three times faster than previously reported The distances moved by species are greatest in studies showing the highest levels of warming, with average latitudinal shifts being generally sufficient to track temperature changes However, individual species vary greatly in their rates of change, suggesting that the range shift of each species depends on multiple internal species traits and external drivers of change Rapid average shifts derive from a wide diversity of responses by individual species

3,986 citations

References
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Journal ArticleDOI
15 Apr 1999-Nature
TL;DR: This article investigated whether changes in highland forests at Monteverde, Costa Rica, are related to the increase in air temperatures that followed a step-like warming of tropical oceans in 1976.
Abstract: Recent warming has caused changes in species distribution and abundance1,2,3, but the extent of the effects is unclear. Here we investigate whether such changes in highland forests at Monteverde, Costa Rica, are related to the increase in air temperatures that followed a step-like warming of tropical oceans in 1976 (refs4, 5). Twenty of 50 species of anurans (frogs and toads) in a 30-km2 study area, including the locally endemic golden toad (Bufo periglenes), disappeared following synchronous population crashes in 1987 (6–8). Our results indicate that these crashes probably belong to a constellation of demographic changes that have altered communities of birds, reptiles and amphibians in the area and are linked to recent warming. The changes are all associated with patterns of dry-season mist frequency, which is negatively correlated with sea surface temperatures in the equatorial Pacific and has declined dramatically since the mid-1970s. The biological and climatic patterns suggest that atmospheric warming has raised the average altitude at the base of the orographic cloud bank, as predicted by the lifting-cloud-base hypothesis9,10.

1,412 citations


"Extinction risk from climate change..." refers background in this paper

  • ...and has been implicated in one species-level extinctio...

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Journal ArticleDOI
01 Jun 1996-Ecology

1,206 citations

Journal ArticleDOI
13 Jun 2003-Science
TL;DR: In this article, the advantages and disadvantages of different methods of carbon sequestration are discussed, and the authors conclude that in the short and medium term, carbon capture and storage would almost certainly be cheaper than a full transition to nuclear, wind, or solar energy.
Abstract: Carbon capture and storage (or sequestration) is receiving increasing attention as one tool for reducing carbon dioxide concentrations in the atmosphere. In his Perspective, Lackner discusses the advantages and disadvantages of different methods of carbon sequestration. He advises against sequestration in environmentally active carbon pools such as the oceans, because it may merely trade one environmental problem for another. Better sequestration options include underground injection and (possibly underground) neutralization. Taking into account carbon capture, transport, and storage, the author concludes that in the short and medium term, sequestration would almost certainly be cheaper than a full transition to nuclear, wind, or solar energy.

1,087 citations


"Extinction risk from climate change..." refers background in this paper

  • ...In other words, minimizing greenhouse gas emissions and sequestering carbo...

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Journal ArticleDOI
11 Apr 2002-Nature
TL;DR: Using a genetic algorithm and museum specimen occurrence data, ecological niche models are developed for 1,870 species occurring in Mexico and projected onto two climate surfaces modelled for 2055, suggesting that severe ecological perturbations may result.
Abstract: Global climates are changing rapidly, with unexpected consequences. Because elements of biodiversity respond intimately to climate as an important driving force of distributional limitation, distributional shifts and biodiversity losses are expected. Nevertheless, in spite of modelling efforts focused on single species or entire ecosystems, a few preliminary surveys of fauna-wide effects, and evidence of climate change-mediated shifts in several species, the likely effects of climate change on species' distributions remain little known, and fauna-wide or community-level effects are almost completely unexplored. Here, using a genetic algorithm and museum specimen occurrence data, we develop ecological niche models for 1,870 species occurring in Mexico and project them onto two climate surfaces modelled for 2055. Although extinctions and drastic range reductions are predicted to be relatively few, species turnover in some local communities is predicted to be high (>40% of species), suggesting that severe ecological perturbations may result.

854 citations

Journal ArticleDOI
TL;DR: This program includes far-reaching plans to prevent, plan, monitor, and study species’ invasions, with a general, synthetic, predictive, proactive approach to species invasions lacking.
Abstract: O 3 February 1999, President Clinton signed an executive order dealing with invasive species in the United States. The order was designed to lay the foundation for a program “to prevent the introduction of invasive species and provide for their control and to minimize the economic, ecological, and human health impacts that invasive species cause” (Clinton 1999). This program includes far-reaching plans to prevent, plan, monitor, and study species’ invasions. Such high-level attention emphasizes the enormity of the problem facing the United States, and in fact the entire world: With ever-growing international commerce, reduced barriers to trade, and increasing human influence, species are moving around, and natural systems are suffering drastic changes. The dimensions of the problem are indeed impressive. Alien plants, animals, and microbes have poured into the United States from all directions. Natural systems have been disrupted, species extinguished, transportation and agriculture compromised, and resources damaged (Carlton 1997–1998, Ogutu-Ohwayo 1997–1998, Richardson 1997–1998, Shiva 1997–1998). In fact, most modern agriculture is based on nonnative organisms; problems arise because questions of when and why some escape and become nuisances remain unanswered. More generally, no proactive approach to combating such species is available—invasive species are dealt with one at a time, as they become problematic. Scientific approaches to a synthetic, and ultimately proactive, understanding of species invasions have developed along several lines, but most have been frustrated by the complex and unpredictable nature of such invasions—which species will invade and which invaders will become serious problems? For example, considerable effort has gone into identifying characteristics of species likely to invade, or of invaders likely to become pests (e.g., Lawton and Brown 1986, Smallwood and Salmon 1992, Carlton 1996). Another line of inquiry and effort has focused on modeling spatial patterns of range expansion after initial invasion (e.g., Mollison 1986, Williamson and Brown 1986, Reeves and Usher 1989, Hastings 1996, Shigesada and Kawasaki 1997, Holway 1998). All in all, though, a general, synthetic, predictive, proactive approach to species invasions is lacking (Mack 1996) but is desperately needed (Hobbs and Mooney 1998).

717 citations