Research output per year
Research output per year
My interests lie in understanding how human behaviour and decision-making affect the outcomes of conservation interventions in complex social-ecological systems.
Understanding the effects of community-based conservation in East Africa
My research in this area explores the social and ecological effects of community-based conservation interventions in East Africa. In Tanzania, I contribute to the PIMA project ("Poverty and ecosystem Impacts of payment for wildlife conservation initiatives in Africa") which seeks to understand the social and ecological impacts of Wildlife Management Areas (WMAs). The project is a 3 year, international interdisciplinary collaboration involving University College London (UCL), theUniversity of Copenhagen, Imperial College London, the Tanzania Wildlife Research Institute, the UNEP World Conservation Monitoring Centre, and the Tanzania Natural Resources Forum. PIMA is funded by ESPA: the Ecosystem Services for Poverty Alleviation research programme, a joint undertaking of the UK government's Department for International Development (DfID), the Natural Environment Research Council (NERC) and the Economic and Social Research Council (ESRC).
Across the border in Kenya, I study the effects of conservancy establishment on households’ livelihood-choices, and how these household-level decisions interact with ecological processes. This work contributed to the ESPA-funded BEST project (“Biodiversity, Ecosystem services, Social sustainability and Tipping points in African drylands”), a collaboration with colleagues from University College London, the Zoological Society of London and the International Livestock Research Institute.
Rule-breaking, enforcement and sensitive behaviour in conservation
Systems of rules and agreements are a ubiquitous feature of conservation interventions, and conservation success is often heavily dependent on the degree to which compliance is achieved. Despite their importance, however, the effectiveness of rules and enforcement remain poorly understood and under-researched in conservation. My work in this area aims to understand how enforcement measures affect individual incentives, and the consequences for conservation.
I am also very interested in the broader problem of how to study sensitive behaviour in conservation, particularly the usefulness of data collected by ranger patrols and the potential of specialised interview methodologies such as the Randomised Response Technique and the Unmatched Count Technique for learning about rule-breaking.
Bushmeat in Madagascar
The hunting and consumption of bushmeat is increasingly being recognised as both an emerging threat to Madagascar’s wild animals and a crucial component of local people’s livelihoods (e.g. BBC News, New York Times). In collaboration with colleagues from Bangor University and the Malagasy NGO, Madagasikara Voakajy, this work focused on understanding the scale of harvesting of several commonly-hunted species that make important contributions to rural livelihoods. I have also studied the effectiveness of occupancy-based survey methods as an alternative to abundance-based methods for monitoring lemur species.
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Aidan Keane (Invited speaker)
Activity: Participating in or organising an event types › Participation in conference
SNH, Scottish Natural Heritage
1/09/21 → 31/08/25
Project: Research
1/09/18 → 31/08/22
Project: Research
30/04/16 → 18/05/18
Project: Research
Slater, H. (Creator), Fisher, J. (Creator), Keane, A. (Creator) & Holmes, G. (Creator), Edinburgh DataShare, 2 Apr 2024
DOI: 10.7488/ds/7692
Dataset
Slater, H. (Creator), Keane, A. (Creator), Sandbrook, C. (Creator), Holmes, G. (Creator) & Fisher, J. (Creator), Edinburgh DataShare, 1 Jul 2024
DOI: 10.7488/ds/7739
Dataset