Shawn is researching ways to better assess changes in the state of global biodiversity. His goal is to develop new methods of applying sampled approaches to biodiversity indices to improve their accuracy, efficiency and scope. Shawn has a Masters in biological oceanography from the University of Kiel, Germany, where he studied the distribution and ecology of midwater fish larvae in the northeast Atlantic. He also holds a BSc in biology from Simon Fraser University, located on the beautiful west coast of Canada, near his hometown of Vancouver. He developed an interest in biodiversity conservation after he spent time in southeast Asia and saw first hand the effects of rampant environmental destruction. When he heard about the Inspire4Nature project he jumped at the chance to get involved.
PhD project: Advancing sampled approaches to established metrics for assessing trends in biodiversity
Biodiversity is in decline. However, most of our understanding about the status of species and habitats comes from a relatively narrow set of genera or regions. While we know that vertebrate species are increasingly at risk of extinction, for most species we have much sparser information. Sampled approaches, such as the Sampled Red List Index (Baillie et al. 2008), use existing information to try to estimate how many species we need to assess to effectively determine the trends in extinction risk for larger groups (e.g. reptiles; Böhm et al. 2013). However, even this approach requires considerable effort in generating and collating species assessments and may not be sustainable.
Other indices suffer from similar problems. The data underlying the Living Planet Index are geographically and taxonomically biased (McRae et al. 2017) and may be limited for groups of interest. Understanding how many populations (or species) are required to make robust estimates of the trends for a particular group or region is critical. Applying sampled approaches to indices such as the Living Planet index will address this question and reveal the potential of sampled abundance indices.
Further, novel approaches are now attempting to predict extinction risk (Bland et al. 2016) or abundance trends for species or populations. In this project, we aim to combine these approaches, exploring the application of new sampling approaches for global biodiversity indicators and attempting to understand for which species such predictive assessments are appropriate, and for which we need further expert information. Understanding how predictability relates to species traits or geographical factors may allow us to revise our sampling regime to focus on those groups that will most usefully inform the index.
The main outcomes of this project will be the development of new approaches to assessing little known groups of species – assessing both their extinction risk and average trends in abundance. These approaches will contribute to the development of both the Living Planet Index and Sampled Red List Index, as well as other biodiversity indicators.
Related references:
- Böhm, M et al. (2013) The conservation status of the world’s reptiles, Biological Conservation. 157, 372-385
- Boakes, EH, et al. (2010) Distorted Views of Biodiversity: Spatial and Temporal Bias in Species Occurrence Data. PLOS Biology 8(6)
- Baillie, JEM et al. (2008) Toward monitoring global biodiversity. Conservation Letters, 1: 18–26
- Bland, L.M, et al. (2015) Predicting the conservation status of data-deficient species. Conservation Biology, 29: 250–259
- McRae L, et al. (2017) The Diversity-Weighted Living Planet Index: Controlling for Taxonomic Bias in a Global Biodiversity Indicator. PLoS ONE 12(1)
Academic Host
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University College London London, UK |
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David Murrell Supervisor |
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Zoological Society of London London, UK |
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Monika Bohm Supervisor | ||||
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Robin Freeman Collaborator |
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Mike Hoffmann Collaborator |
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Louise McRae Collaborator |
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International Institute for Applied Systems Analysis Laxenburg, Austria | ||||
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Piero Visconti Collaborator | ||||