Robust Wildlife Population Monitoring Under Challenging Conditions
Period: October 2015- October 2019
Funder: NERC CASE
PhD Project: Stephanie Brittain
Collaborators: ZSL Cameroon
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.
This research aims to gain a better understanding of the role and implications of different sources and types of uncertainty 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. The projects focus on understanding and correcting for bias and uncertainty in observational data, a data type widely used in ecology and conservation, will allow 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.
All wildlife population monitoring methods suffer from a degree of imperfect detectability, yet there is a substantial lack of focus on uncertainty and bias as an issue in ecology and conservation, leading to potentially misleading conclusions being drawn. Tension exists between the need for methods that prioritize long-term practicality and those that prioritize precision; monitoring methods can be expensive, time consuming and require specialized training or technology, rendering monitoring over large spatiotemporal scales a serious challenge, especially for budget restricted projects. This is made worse in remote or challenging habitats such as dense forest where detectability is low and terrain is difficult to traverse.
Recently, interview-based surveys have been incorporated with occupancy analysis, which potentially provide an unbiased estimation of species distribution and relative abundance through models that account for false positive and negative detections (MacKenzie et al. 2002). Despite its growing popularity, there is very little research on the sources of bias and the accuracy of the data obtained using interview data for occupancy modelling.
Outline of scope of research
This research aims to gain a better understanding of the role and implications of different sources and types of uncertainty 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.
The research objectives are to 1) Review the current use of local ecological knowledge for Interview-based occupancy analysis within conservation; 2) Investigate how interview-based occupancy analysis is affected by different types of uncertainty/bias within the case study; 3) Explore the trade-offs between cost, precision and accuracy when using interview-based occupancy analysis; 4) Quantify the status of, and threats to, hunted species in the Dja region, using interview-based occupancy analysis as a method and 5) Identify barriers to and the potential for the successful implementation of interview-based occupancy analysis for population monitoring in the Dja region and more broadly.
Summary of planned activities:
- Produce a report for ZSL Cameroon about the threats to biodiversity in the Dja Faunal Reserve
- Produce a guidance report for the future implementation of interview based occupancy analysis
- Provide recommendations for the future use of observational data for wildlife population monitoring in ecology and conservation
- Publish papers on the findings of my thesis data chapters
- February 2016: Scoping trip
- June-August 2016: Phase 1 data collection
- February-May 2017: Phase 2 data collection
Following the second phase of data collection, the first outputs are planned for August 2017
If you would like to find out more about the research please contact Stephanie Brittain: email@example.com