Kathryn J. Fiorella, Rapacciuolo G, Christopher Trisos
The inability to quantify which threats matter most across species and ecosystems is a problem for policymaking and resource allocation (see S. L. Maxwell et al. Nature 536, 143–145; 2016). Biodiversity conservation could learn from public-health metrics and go beyond simply counting the number of recorded threats to quantify the contribution of each one to species loss
Maggi Kelly, Kelly Easterday, Rapacciuolo G, Michelle S. Koo, Patrick McIntyre, James Thorne
Research efforts that synthesize historical and contemporary ecological data with modeling approaches improve our understanding of the complex response of species, communities, and landscapes to changing biophysical conditions through time and in space. Historical ecological data are particularly important in this respect. There are remaining barriers that limit such data synthesis, and technological improvements that make multiple diverse datasets more readily available for integration and synthesis are needed. This paper presents one case study of the Wieslander Vegetation Type Mapping project in California and highlights the importance of rescuing, digitizing and sharing historical datasets. We review the varied ecological uses of the historical collection: the vegetation maps have been used to understand legacies of land use change and plan for the future; the plot data have been used to examine changes to chaparral and forest communities around the state and to predict community structure and shifts under a changing climate; the photographs have been used to understand changing vegetation structure; and the voucher specimens in combination with other specimen collections have been used for large scale distribution modeling efforts. The digitization and sharing of the data via the web has broadened the scope and scale of the types of analysis performed. Yet, additional research avenues can be pursued using multiple types of VTM data, and by linking VTM data with contemporary data. The digital VTM collection is an example of a data infrastructure that expands the potential of large scale research through the integration and synthesis of data drawn from numerous data sources; its journey from analog to digital is a cautionary tale of the importance of finding historical data, digitizing it with best practices, linking it with other datasets, and sharing it with the research community.
Pearse WD, Chase MW, Crawley MJ, Dolphin K, Fay MF, Joseph JA, Powney G, Preston CD, Rapacciuolo G, Roy DB, and Purvis A
Conservation biologists have only finite resources, and so must prioritise some species over others. The EDGE-listing approach ranks species according to their combined evolutionary distinctiveness and degree of threat, but ignores the uncertainty surrounding both threat and evolutionary distinctiveness. We develop a new family of measures for species, which we name EDAM, that incorporates evolutionary distinctiveness, the magnitude of decline, and the accuracy with which decline can be predicted. Further, we show how the method can be extended to explore phyogenetic uncertainty. Using the vascular plants of Britain as a case study, we find that the various EDAM measures emphasise different species and parts of Britain, and that phylogenetic uncertainty can strongly affect the prioritisation scores of some species
Rapacciuolo G, Maher SP, Schneider AC, Hammond TT, Jabis MD, Walsh RE, Iknayan KJ, Walden GK, Oldfather MF, Ackerly DD, Beissinger SR
Understanding recent biogeographic responses to climate change is fundamental for improving our predictions of likely future responses and guiding conservation planning at both local and global scales. Studies of observed biogeographic responses to 20th century climate change have principally examined effects related to ubiquitous increases in temperature – collectively termed a warming fingerprint. Although the importance of changes in other aspects of climate – particularly precipitation and water availability – is widely acknowledged from a theoretical standpoint and supported by paleontological evidence, we lack a practical understanding of how these changes interact with temperature to drive biogeographic responses. Further complicating matters, differences in life history and ecological attributes may lead species to respond differently to the same changes in climate. Here, we examine whether recent biogeographic patterns across California are consistent with a warming fingerprint. We describe how various components of climate have changed regionally in California during the 20th century and review empirical evidence of biogeographic responses to these changes, particularly elevational range shifts. Many responses to climate change do not appear to be consistent with a warming fingerprint, with downslope shifts in elevation being as common as upslope shifts across a number of taxa and many demographic and community responses being inconsistent with upslope shifts. We identify a number of potential direct and indirect mechanisms for these responses, including the influence of aspects of climate change other than temperature (e.g., the shifting seasonal balance of energy and water availability), differences in each taxon's sensitivity to climate change, trophic interactions, and land-use change. Finally, we highlight the need to move beyond a warming fingerprint in studies of biogeographic responses by considering a more multifaceted view of climate, emphasizing local-scale effects, and including a priori knowledge of relevant natural history for the taxa and regions under study
Rapacciuolo G, Roy DB, Gillings S, Purvis A
The use of data documenting how species' distributions have changed over time is crucial for testing how well correlative species distribution models (SDMs) predict species' range changes. So far, however, little attention has been given to developing a reliable methodological framework for using such data. We develop a new tool – the temporal validation (TV) plot – specifically aimed at making use of species' distribution records at two times for a comprehensive assessment of the prediction accuracy of SDMs over time. We extend existing presence–absence calibration plots to make use of distribution records from two time periods. TV plots visualize the agreement between change in modelled probabilities of presence and the probability of observing sites gained or lost between time periods. We then present three measures of prediction accuracy that can be easily calculated from TV plots. We present our methodological framework using a virtual species in a simplified landscape and then provide a real-world case study using distribution records for two species of breeding birds from two time periods of intensive recording effort across Great Britain. Together with existing approaches, TV plots and their associated measures offer a simple tool for testing how well SDMs model species' observed range changes – perhaps the best way available to assess their ability to predict likely future changes.
Powney GD, Rapacciuolo G, Preston CD, Purvis A, Roy DB
Species distributions are changing, and knowing whether certain character traits predispose species to decline or increase during times of environmental change can shed light on the main drivers of distribution change. Here we conduct a trait-based analysis of range change in the flora of Britain since the 1930s using some of the best plant distribution and trait data available in Europe. We use phylogenetically-informed models based on a recently published, dated, species level plant phylogeny. Traits associated with habitat specialism and competitive ability were related to range change, with more competitive habitat generalists faring better than habitat specialists. We attribute this result to the greater ability of generalists to adapt to environmental perturbation, but also to the negative impacts of agricultural intensification on the flora of Britain, in particular the loss of open, dry habitats. We discovered spatial variation in the main drivers of plant range change and find support for previous evidence that agricultural intensification has been a major driver of distribution change in the flora of Britain over the past 70 years, particularly in southern England.
Rapacciuolo G, Roy DB, Gillings S, Fox R, Walker K, Purvis A
Conservation planners often wish to predict how species distributions will change in response to environmental changes. Species distribution models (SDMs) are the primary tool for making such predictions. Many methods are widely used; however, they all make simplifying assumptions, and predictions can therefore be subject to high uncertainty. With global change well underway, field records of observed range shifts are increasingly being used for testing SDM transferability. We used an unprecedented distribution dataset documenting recent range changes of British vascular plants, birds, and butterflies to test whether correlative SDMs based on climate change provide useful approximations of potential distribution shifts. We modelled past species distributions from climate using nine single techniques and a consensus approach, and projected the geographical extent of these models to a more recent time period based on climate change; we then compared model predictions with recent observed distributions in order to estimate the temporal transferability and prediction accuracy of our models. We also evaluated the relative effect of methodological and taxonomic variation on the performance of SDMs. Models showed good transferability in time when assessed using widespread metrics of accuracy. However, models had low accuracy to predict where occupancy status changed between time periods, especially for declining species. Model performance varied greatly among species within major taxa, but there was also considerable variation among modelling frameworks. Past climatic associations of British species distributions retain a high explanatory power when transferred to recent time – due to their accuracy to predict large areas retained by species – but fail to capture relevant predictors of change. We strongly emphasize the need for caution when using SDMs to predict shifts in species distributions: high explanatory power on temporally-independent records – as assessed using widespread metrics – need not indicate a model’s ability to predict the future.
Oliver TH, Gillings S, Girardello M, Rapacciuolo G, Brereton TM, Siriwardena GM, Roy DB, Pywell R, Fuller RJ
Species distribution models (SDMs) are increasingly used in applied conservation biology, yet the predictive ability of these models is often tested only on detection/non-detection data. The probability of long-term population persistence, however, depends not only upon patch occupancy but upon more fundamental population parameters such as mean population density and stability over time. Here, we test estimated probability of occurrence scores generated from SDMs built using species occupancy data against independent empirical data on population density and stability for 20 bird and butterfly species across 1941 sites over 15 years. We devised a measure of population stability over time which was independent of mean density and time-series duration, yet positively correlated with risk of local extinction. This may be a useful surrogate measure of population persistence for use in applied conservation. We found that probability of occurrence scores were significantly positively correlated with mean population density for both butterflies and birds. In contrast, probability of occurrence scores were at best weakly positively correlated with population stability. Referring to established ecological theory, we discuss why SDMs may be appropriate for predicting population density but not stability. Species distribution models are often constructed using species occupancy data because, for the majority of species and regions, these are the best data available. The models are then often used for projecting species’ distributions in the future and identifying areas where management could be targeted to improve species’ prospects. However, our results suggest that an overreliance on these SDMs may result in an exclusive focus on landscape management approaches that promote patch occupancy and density, but may overlook features important for long-term population persistence such as population stability. Other landscape metrics that take into account habitat heterogeneity or configuration may be required to predict population stability. To understand species persistence under rapid environmental change, count data from standardised monitoring schemes are an invaluable resource. These data provide additional insights into the factors affecting species’ extinction risks, which cannot easily be inferred from species’ occupancy data.