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Yvonne C. Collingham

Other affiliations: University of York
Bio: Yvonne C. Collingham is an academic researcher from Durham University. The author has contributed to research in topics: Climate change & Range (biology). The author has an hindex of 27, co-authored 38 publications receiving 10469 citations. Previous affiliations of Yvonne C. Collingham include University of York.

Papers
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Journal ArticleDOI
08 Jan 2004-Nature
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.

7,089 citations

Journal ArticleDOI
TL;DR: It is confirmed that the average species richness of British butterflies has increased since 1970–82, but much more slowly than predicted from changes of climate: on average, only one-third of the predicted increase has taken place.
Abstract: Species-energy theory indicates that recent climate warming should have driven increases in species richness in cool and species-poor parts of the Northern Hemisphere. We confirm that the average species richness of British butterflies has increased since 1970–82, but much more slowly than predicted from changes of climate: on average, only one-third of the predicted increase has taken place. The resultant species assemblages are increasingly dominated by generalist species that were able to respond quickly. The time lag is confirmed by the successful introduction of many species to climatically suitable areas beyond their ranges. Our results imply that it may be decades or centuries before the species richness and composition of biological communities adjusts to the current climate.

351 citations

Journal ArticleDOI
TL;DR: In this article, the authors surveyed the four species of butterflies that reach their southern limits in Britain and found that the southern/warm range margins of some species are as sensitive to climate change as are northern/cool margins.
Abstract: Polewards expansions of species' distributions have been attributed to climate warming, but evidence for climate-driven local extinctions at warm (low latitude/elevation) boundaries is equivocal. We surveyed the four species of butterflies that reach their southern limits in Britain. We visited 421 sites where the species had been recorded previously to determine whether recent extinctions were primarily due to climate or habitat changes. Coenonympha tullia had become extinct at 52% of study sites and all losses were associated with habitat degradation. Aricia artaxerxes was extinct from 50% of sites, with approximately one-third to half of extinctions associated with climate-related factors and the remainder with habitat loss. For Erebia aethiops (extinct from 24% of sites), approximately a quarter of the extinctions were associated with habitat and three-quarters with climate. For Erebia epiphron, extinctions (37% of sites) were attributed mainly to climate with almost no habitat effects. For the three species affected by climate, range boundaries retracted 70–100 km northwards (A. artaxerxes, E. aethiops) and 130–150 m uphill (E. epiphron) in the sample of sites analysed. These shifts are consistent with estimated latitudinal and elevational temperature shifts of 88 km northwards and 98 m uphill over the 19-year study period. These results suggest that the southern/warm range margins of some species are as sensitive to climate change as are northern/cool margins. Our data indicate that climate warming has been of comparable importance to habitat loss in driving local extinctions of northern species over the past few decades; future climate warming is likely to jeopardize the long-term survival of many northern and mountain species.

345 citations

Journal ArticleDOI
01 Mar 2007-Ecology
TL;DR: Investigation of direct and indirect effects of climate variables, host-plant richness, and habitat diversity on butterfly species richness across Britain suggests that different mechanistic hypotheses to explain species richness may be more appropriate for habitat generalists and specialists.
Abstract: Many factors, including climate, resource availability, and habitat diversity, have been proposed as determinants of global diversity, but the links among them have rarely been studied. Using structural equation modeling (SEM), we investigated direct and indirect effects of climate variables, host-plant richness, and habitat diversity on butterfly species richness across Britain, at 20-km grid resolution. These factors were all important determinants of butterfly diversity, but their relative contributions differed between habitat generalists and specialists, and whether the effects were direct or indirect. Climate variables had strong effects on habitat generalists, whereas host-plant richness and habitat diversity contributed relatively more for habitat specialists. Considering total effects (direct and indirect together), climate variables had the strongest link to butterfly species richness for all groups of species. The results suggest that different mechanistic hypotheses to explain species richness may be more appropriate for habitat generalists and specialists, with generalists hypothesized to show direct physiological limitations and specialists additionally being constrained by trophic interactions (climate affecting host-plant richness).

333 citations

Journal ArticleDOI
16 Jan 2008-PLOS ONE
TL;DR: The magnitude of the potential impacts estimated for European breeding birds emphasises the importance of climatic change.
Abstract: Background Climatic change is expected to lead to changes in species' geographical ranges. Adaptation strategies for biodiversity conservation require quantitative estimates of the magnitude, direction and rates of these potential changes. Such estimates are of greatest value when they are made for large ensembles of species and for extensive (sub-continental or continental) regions. Methodology/Principal Findings For six climate scenarios for 2070–99 changes have been estimated for 431 European breeding bird species using models relating species' distributions in Europe to climate. Mean range centroid potentially shifted 258–882 km in a direction between 341° (NNW) and 45° (NE), depending upon the climate scenario considered. Potential future range extent averaged 72–89% of the present range, and overlapped the present range by an average of 31–53% of the extent of the present range. Even if potential range changes were realised, the average number of species breeding per 50×50 km grid square would decrease by 6·8–23·2%. Many species endemic or near-endemic to Europe have little or no overlap between their present and potential future ranges; such species face an enhanced extinction risk as a consequence of climatic change. Conclusions/Significance Although many human activities exert pressures upon wildlife, the magnitude of the potential impacts estimated for European breeding birds emphasises the importance of climatic change. The development of adaptation strategies for biodiversity conservation in the face of climatic change is an urgent need; such strategies must take into account quantitative evidence of potential climatic change impacts such as is presented here.

319 citations


Cited by
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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

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: In this article, the authors suggest that the term "fragmentation" should be reserved for the breaking apart of habitat, independent of habitat loss, and that fragmentation per se has much weaker effects on biodiversity that are at least as likely to be positive as negative.
Abstract: ■ Abstract The literature on effects of habitat fragmentation on biodiversity is huge. It is also very diverse, with different authors measuring fragmentation in different ways and, as a consequence, drawing different conclusions regarding both the magnitude and direction of its effects. Habitat fragmentation is usually defined as a landscape-scale process involving both habitat loss and the breaking apart of habitat. Results of empirical studies of habitat fragmentation are often difficult to interpret because (a) many researchers measure fragmentation at the patch scale, not the landscape scale and (b) most researchers measure fragmentation in ways that do not distinguish between habitat loss and habitat fragmentation per se, i.e., the breaking apart of habitat after controlling for habitat loss. Empirical studies to date suggest that habitat loss has large, consistently negative effects on biodiversity. Habitat fragmentation per se has much weaker effects on biodiversity that are at least as likely to be positive as negative. Therefore, to correctly interpret the influence of habitat fragmentation on biodiversity, the effects of these two components of fragmentation must be measured independently. More studies of the independent effects of habitat loss and fragmentation per se are needed to determine the factors that lead to positive versus negative effects of fragmentation per se. I suggest that the term “fragmentation” should be reserved for the breaking apart of habitat, independent of habitat loss.

6,341 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

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