• Bring the captive closer to the wild: redefining the role of ex situ conservation

      Pritchard, Diana J.; Fa, John E.; Oldfield, Sara; Harrop, Stuart R.; University of Sussex; Durrell Wildlife Conservation Trust; Imperial College London; Botanical Gardens Conservation International; University of Kent (Wiley Blackwell, 2011)
      In situ conservation is central to contemporary global biodiversity protection and is the predominant emphasis of international regulation and funding strategies. Ex situ approaches, in contrast, have been relegated to a subsidiary role and their direct contributions to conservation have been limited. We draw on a variety of sources to make the case for an enhanced role for ex situ conservation. We note the advances occurring within institutions specializing in ex situ conservation and stress that, although much remains to be done, many constraints are being addressed. We argue that the evidence of increasing extinction rates, exacerbated by climate change, challenges the wisdom of a heavy dependence on in situ strategies and necessitates increased development of ex situ approaches. A number of different techniques that enable species and their habitats to survive should now be explored. These could build on the experience of management systems that have already demonstrated the effective integration of in situ and ex situ techniques and hybrid approaches.
    • Experimentally testing the accuracy of an extinction estimator: Solow's optimal linear estimation model

      Clements, Christopher F.; Worsfold, Nicholas T.; Warren, Philip H.; Collen, Ben; Clark, Nick; Blackburn, Tim M.; Petchey, Owen L.; Butler, Simon; University of Sheffield; University of York; et al. (Wiley Blackwell, 2013)
      Mathematical methods for inferring time to extinction have been widely applied but poorly tested. Optimal linear estimation (also called the 'Weibull' or 'Weibull extreme value' model) infers time to extinction from a temporal distribution of species sightings. Previous studies have suggested optimal linear estimation provides accurate estimates of extinction time for some species; however, an in-depth test of the technique is lacking. The use of data from wild populations to gauge the error associated with estimations is often limited by very approximate estimates of the actual extinction date and poor sighting records. Microcosms provide a system in which the accuracy of estimations can be tested against known extinction dates, whilst incorporating a variety of extinction rates created by changing environmental conditions, species identity and species richness. We present the first use of experimental microcosm data to exhaustively test the accuracy of one sighting-based method of inferring time of extinction under a range of search efforts, search regimes, sighting frequencies and extinction rates. Our results show that the accuracy of optimal linear estimation can be affected by both observer-controlled parameters, such as change in search effort, and inherent features of the system, such as species identity. Whilst optimal linear estimation provides generally accurate and precise estimates, the technique is susceptible to both overestimation and underestimation of extinction date. Microcosm experiments provide a framework within which the accuracy of extinction predictors can be clearly gauged. Variables such as search effort, search regularity and species identity can significantly affect the accuracy of estimates and should be taken into account when testing extinction predictors in the future.
    • A framework for assessing threats and benefits to species responding to climate change

      Thomas, Chris D.; Hill, Jane K.; Anderson, Barbara J.; Bailey, Sallie; Beale, Colin M.; Bradbury, Richard B.; Bulman, Caroline R.; Crick, Humphrey Q. P.; Eigenbrod, Felix; Griffiths, Hannah M.; et al. (Wiley Blackwell, 2011-04)
      Current national and international frameworks for assessing threats to species have not been developed in the context of climate change, and are not framed in a way that recognises new opportunities that arise from climate change. The framework presented here separates the threats and benefits of climate change for individual species. Threat is assessed by the level of climate-related decline within a species’ recently occupied (e.g. pre-1970s) historical distribution, based on observed (e.g. repeat census) and/or projected changes (e.g. modelled bioclimate space). Benefits are assessed in terms of observed and/or projected increases outside the recently occupied historical range. Exacerbating factors (e.g. small population size, low dispersal capacity) that might increase levels of threat or limit expansion in response to climate change are taken into consideration within the framework. Protocols are also used to identify levels of confidence (and hence research and/or monitoring needs) in each species’ assessment.