Using local ecological knowledge to monitor species populations and their threats
Brittain, S. (2018). Using local ecological knowledge to monitor species populations and their threats. 5th European Congress of Conservation Biology. doi: 10.17011/conference/eccb2018/107717
Tekijät
Päivämäärä
2018Tekijänoikeudet
© the Authors, 2018
Protein from forest wildlife is crucial to rural food security and livelihoods across the tropics and local extirpation of hunted species is widespread. For many wildlife species, monitoring over large spatiotemporal scales remains a serious challenge. At the root of this challenge lies tension between monitoring methods that prioritise accuracy, and those that emphasize long-term practicality. This trade-off between effectiveness and cost is a pervasive and unresolved problem in biodiversity monitoring. One possible solution has been to draw on the experience of local people in order rapidly to condense information over areas and timescales that cannot be tackled using conventional surveys. However, while there are some good examples of the integration of local participation into ecological monitoring, it remains underdeveloped.
My research aims to gain a better understanding of the role and implications of accuracy and bias when using local ecological knowledge for wildlife population monitoring, using interview-based occupancy analysis of bushmeat species and threats in a protected area (the Dja Faunal Reserve) in Cameroon as a case study.
At the ECCB, I aim to present the results of my first data chapter, which compares the results of occupancy analysis for 14 different species obtained from semi-structured interviews, daily hunter diaries and camera traps. This comparison chapter forms the basis for my subsequent work on the power of interview based occupancy models to detect change, and applying interview based occupancy analysis to monitor the distribution and relative abundance of hunting offtake.
Another part of my work which I would like to present looks at assessing expert knowledge. Experts are often asked to make judgements when time and resources are stretched [1] . The social expectation hypothesis expects highly regarded and experienced experts to give more robust advice. Applying the methods outlined by Burgman et al (2011) to groups of hunters regarded as experts in bushmeat species in my study villages, I assess the relationship between perceived expertness and their ability to make precise and accurate judgements on the distribution and relative abundance of bushmeat species in the community forest adjacent to the village.
My focus on understanding and correcting for bias and uncertainty in observational data, a data type widely used in ecology and conservation, allows for a better understanding of observational data more broadly, and how to address these issues for the overall benefit of ecology and conservation. At a smaller scale, I am developing and evaluating a method that is potentially cost effective and accurate, much needed in conservation and ecology to overcome the challenges to robust monitoring.
[1] Burgman MA, McBride M, Ashton R, Speirs-Bridge A, Flander L, et al. (2011) Expert Status and Performance. PLoS ONE 6(7): e22998. doi:10.1371/
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Julkaisija
Open Science Centre, University of JyväskyläKonferenssi
ECCB2018: 5th European Congress of Conservation Biology. 12th - 15th of June 2018, Jyväskylä, Finland
Alkuperäislähde
https://peerageofscience.org/conference/eccb2018/107717/Metadata
Näytä kaikki kuvailutiedotKokoelmat
- ECCB 2018 [712]
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