Yvonne C. Collingham

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.

An indicator of the impact of climatic change on European bird populations.

Abstract: Rapid climatic change poses a threat to global biodiversity. There is extensive evidence that recent climatic change has affected animal and plant populations, but no indicators exist that summarise impacts over many species and large areas. We use data on long-term population trends of European birds to develop such an indicator. We find a significant relationship between interspecific variation in population trend and the change in potential range extent between the late 20th and late 21st centuries, forecasted by climatic envelope models. Our indicator measures divergence in population trend between bird species predicted by climatic envelope models to be favourably affected by climatic change and those adversely affected. The indicator shows a rapid increase in the past twenty years, coinciding with a period of rapid warming.

Projected impacts of climate change on a continent-wide protected area network

Abstract: Despite widespread concern, the continuing effectiveness of networks of protected areas under projected 21st century climate change is uncertain. Shifts in species' distributions could mean these resources will cease to afford protection to those species for which they were originally established. Using modelled projected shifts in the distributions of sub-Saharan Africa's entire breeding avifauna, we show that species turnover across the continent's Important Bird Area (IBA) network is likely to vary regionally and will be substantial at many sites (> 50% at 42% of IBAs by 2085 for priority species). Persistence of suitable climate space across the network as a whole, however, is notably high, with 88-92% of priority species retaining suitable climate space in >or= 1 IBA(s) in which they are currently found. Only 7-8 priority species lose climatic representation from the network. Hence, despite the likelihood of significant community disruption, we demonstrate that rigorously defined networks of protected areas can play a key role in mitigating the worst impacts of climate change on biodiversity.

Potential impacts of climatic change upon geographical distributions of birds

Abstract: Potential climatic changes of the near future have important characteristics that differentiate them from the largest magnitude and most rapid of climatic changes of the Quaternary. These potential climatic changes are thus a cause for considerable concern in terms of their possible impacts upon biodiversity. Birds, in common with other terrestrial organisms, are expected to exhibit one of two general responses to climatic change: they may adapt to the changed conditions without shifting location, or they may show a spatial response, adjusting their geographical distribution in response to the changing climate. The Quaternary geological record provides examples of organisms that responded to the climatic fluctuations of that period in each of these ways, but also indicates that the two are not alternative responses but components of the same overall predominantly spatial response. Species unable to achieve a sufficient response by either or both of these mechanisms will be at risk of extinction; the Quaternary record documents examples of such extinctions. Relationships between the geographical distributions of birds and present climate have been modelled for species breeding in both Europe and Africa. The resulting models have very high goodness-of-fit and provide a basis for assessing the potential impacts of anthropogenic climatic changes upon avian species richness in the two continents. Simulations made for a range of general circulation model projections of late 21st century climate lead to the conclusion that the impacts upon birds are likely to be substantial. The boundaries of many species’ potential geographical distributions are likely to be shifted 1000 km. There is likely to be a general decline in avian species richness, with the mean extent of species’ potential geographical distributions likely to decrease. Species with restricted distributions and specialized species of particular biomes are likely to suffer the greatest impacts. Migrant species are likely to suffer especially large impacts as climatic change alters both their breeding and wintering areas, as well as critical stopover sites, and also potentially increases the distances they must migrate seasonally. Without implementation of new conservation measures, these impacts will be severe and are likely to be exacerbated by land-use change and associated habitat fragmentation. Unless strenuous efforts are made to address the root causes of anthropogenic climatic change, much current effort to conserve biodiversity will be in vain.

Impacts of habitat fragmentation and patch size upon migration rates

Abstract: A spatially explicit model (MIGRATE) was used to investigate the effects of habitat loss and fragmentation on the ability of species to migrate in response to climate change. Illustrative simulations were run using parameters that represent the reproductive and dispersal characteristics of the wind-dispersed tree Tilia cordata (small-leaved lime). Hierarchically structured landscapes with different patch sizes and overall habitat suitability levels were generated at a 1-km resolution for a 200 × 800 km area. Simulated migration rates slowed markedly when habitat availability fell below ∼25% of the landscape area, especially in landscapes composed of fewer larger patches. The implication of these results for the management of landscapes for species conservation is discussed.

Predicting the spatial distribution of non‐indigenous riparian weeds: issues of spatial scale and extent

Abstract: 1. The existence of a hierarchical scheme of environmental controls on the spatial distribution of plant species was explored for three non-indigenous weeds, Fallopia japonica, Heracleum mantegazzianum and Impatiens glandulifera, in the British Isles. 2. Logistic regression analyses of the presence/absence of the three weed species examined the relative importance of 60 environmental variables, encompassing land cover, geology and climate. Analyses were undertaken using variables assessed at a hectad (10 × 10 km) or tetrad (2 × 2 km) resolution at national (England and Wales) and regional (County Durham, UK) spatial extents. 3. The ranges of all three species in the British Isles are currently increasing, and the non-equilibrium nature of their distribution limited the goodness-of-fit of logistic models. Interpretation of whether a species has expanded to occupy entirely its potential spatial range was scale-dependent, and species' distributions, when viewed at coarser spatial scales, may be more likely to be interpreted as having reached stasis. 4. Spatial autocorrelation was more evident at the finer tetrad spatial resolution for both F. japonica and I. glandulifera, but not evident at all for H. mantegazzianum. Only the distribution of I. glandulifera revealed significant spatial autocorrelation among hectads at the national scale. These patterns appear related to the different dispersal mechanisms of the three species. 5. The majority of the environmental variables identified as important at the tetrad resolution for County Durham were also important at the hectad resolution for England and Wales for both F. japonica and I. glandulifera, but not for H. mantegazzianum. However, for all three species the environmental variables identified as significant were consistent with qualitative descriptions of the species' habitat characteristics. There was no evidence of a hierarchy of environmental controls. 6. At the regional extent, scaling-up species' distributions from tetrads to hectads was relatively successful, but scaling-down was not. The coarser resolution models were too unrefined to model fine-scale distributions successfully. Similarly, at a coarse hectad resolution, regional models were poor predictors of national species' distributions. It therefore appears that scaling-up from fine to coarse resolution is appropriate when spatial extent is held constant, and focusing-down from large to small spatial extents is appropriate when data resolution is held constant.

Novel methods improve prediction of species' distributions from occurrence data

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.

Effects of Habitat Fragmentation on Biodiversity

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.

Predicting species distribution: offering more than simple habitat models.

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.

Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation

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.