2018 ESA Annual Meeting (August 5 -- 10)

COS 14-2 - Participatory approaches for quantitative analysis in wildlife research

Monday, August 6, 2018: 1:50 PM
339, New Orleans Ernest N. Morial Convention Center
Yichao Zeng1, Vanessa Hull1 and Jindong Zhang2, (1)Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL, (2)College of Life Science, China West Normal University, Nanchong, China
Background/Question/Methods

Participatory methods refer to a suite of approaches in which the knowledge of various experts or user groups about a given ecological system are evaluated and used to analyze pressing ecological questions. The advantage of participatory methods is that they can compensate for scant empirical data in a variety of fields, including wildlife ecology and management. As wildlife research becomes increasingly quantitative and predictive, there is an urgent need to understand how to take advantage of participatory methods to enhance quantitative analysis (e.g., on wildlife distributions, population dynamics). However, current knowledge on the contributions of participatory methods to wildlife research is fragmentary. Here we conduct a literature review and synthesis to address how participatory methods have been applied to make quantitative inferences on wildlife for conservation and management purposes. We synthesize the diverse sources of expert knowledge, model types, and inferences and also explore strengths and weaknesses of these approaches in diverse contexts around the world. We also recommend key directions for future development in this field and demonstrate the potential of cutting edge approaches using a pilot dataset on participatory mapping of threats by rural managers and residents in a UNESCO reserve for giant pandas in China.

Results/Conclusions

  1. Participatory methods were mostly used to measure response variables (e.g. presences, densities of species) in previous studies, but the use of participatory methods to measure explanatory variables is underappreciated.
  2. There was a clear bias toward more participatory studies on large, wide-ranging mammals that are relatively abundant (e.g. ungulates), possibly due to their higher overall numbers and contact with humans.
  3. Bayesian approaches, which by nature are flexible and ideal for integrating prior beliefs with empirical evidence, were common among more recent studies and may represent a cutting edge that should be further developed in the future.
  4. Our pilot study using participatory mapping to elucidate human threats in a giant panda reserve revealed new information on recent human impacts evolving on the landscape such as livestock grazing and herb collection that are otherwise difficult to capture. Our synthesis, together with the pilot study, highlights the potential for participatory mapping as a way of measuring human-related explanatory factors in spatially-explicit modeling frameworks which can be applied to diverse systems around the world.