RHINOMITE · A test of Bayesian decision analysis and the implications for conservation
FP7 — People (Marie Curie Actions)
- Duration
- 2011-02-21 → 2013-02-20
- EU contribution
- €174,241
- Participants
- 1
- Scheme
- MC-IIF
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Results in brief
A test of Bayesian decision analysis and the implications for conservation
Following project departure away from Bayesian population models, we based our research design around integral projection model (IPM)s (see Coulson, 2012), which are similar to Bayesian approaches in flavour but allow insight into both demography and evolution by linking species life history to a trait, such as body size. IPMs also allow for an easy and insightful decision framework, simply by allowing the simulation of multiple management strategies. The first research achievement was an invited paper to the 'Raffles Bulletin of Zoology', where the fellow (Traill) explored global ungulate species richness, and drivers of localised extirpation. We then developed a generalised IPM for ungulates based on data across numerous ungulate species sourced from both the literature and data available from long-term studies on ungulate populations. This work, in review at 'American Naturalist' allows insight into both the ecological and evolutionary outcomes of management intervention on an ungulate species of any size, up to approximately 500 kg. This allows biologists working on say African ungulates, where vital rate data are unavailable, opportunity to test the effects of hunting, or translocation on species population demography (such as population growth rate, female reproductive output), as well as trait change, such as body size. Further to that, we collaborated with researchers at Sherbrooke University in Canada to develop a two-sex IPM for bighorn sheep (Ovis canadensis). We used a 40-year individual-based dataset to parameterise the model, and this in turn allowed insight into the effects of trophy hunting on bighorn sheep, including shifts in body size following selective harvest. This work has been written-up as a research paper and following co-author approval will be submitted to 'PLoS Biology'. Another manuscript is also being prepared based on differences in age-structured or non-structured models, again with outcomes for decision-making. Research findings have been presented at three international conferences, and the fellow has been awarded a further fellowship to travel to the University of Queensland, Australia.
Data: CORDIS, © European Union
Project objective
Conservation biologists work hard to prevent species extinction and rely on robust quantitative methods to achieve these ends. Decision frameworks allow assessment of alternate management strategies for threatened species, and may rely on simulated population models where data are unavailable or unreliable. Bayesian inference can be used to inform decision frameworks, and has come to the attention of many biologists because the Baye’s approach allows expert opinion or informed priors to update models where data are otherwise unavailable. These require further testing, and this is often difficult where data for long-lived species are difficult to collect. Here I will use short-lived soil mite (Sancassania berlesei) populations in a laboratory environment to replicate subpopulations critically endangered black rhino (Diceros bicornis). By confronting Bayesian models with real data, I hope to test the robustness of priors in Bayesian models, compare this approach to more traditional frequentist approaches and gain insight into the usefulness of Bayesian in decision-making. I propose to take this further and use the knowledge gained to develop and configure a decision making framework for the management of black rhino populations across southern Africa.
Original text from CORDIS.
Participants
- IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE · LondonCoordinatorUnited Kingdom
Links
Data: CORDIS, © European Union