Introducing IPOACHED: A conservation criminology-based framework to understand wildlife species targeted by poachers in protected areas

The criminogenic dimensions of conservation are highly relevant to contemporary protected area management. Research on crime target suitability in the field of criminology has built new understanding regarding how the characteristics of the crime targets affect their suitability for being targeted by offenders. In the last decade, criminologists have sought to apply and adapt target suitability frameworks to explain wildlife related crimes. This study seeks to build upon the extant knowledge base and advance adaptation and application of target suitability research. First, we drew on research, fieldwork, and empirical evidence from conservation science to develop a poaching-stage model with a focus on live specimens or wild animals- rather than a market stage and wildlife product-focused target suitability model. Second, we collected data in the Intensive Protection Zone of Bukit Barisan Selatan National Park (BBSNP), Sumatra, Indonesia through surveys with local community members (n=400), and a three-day focus group with conservation practitioners (n= 25). Our target suitability model, IPOACHED, predicts that species that are in-demand, passive, obtainable, all-purpose, conflict-prone, hideable, extractable, and disposable are more suitable species for poaching and therefore more vulnerable. When applying our IPOACHED model, we find that the most common response to species characteristics that drive poaching in BBSNP was that they are in-demand, with support for cultural or symbolic value (n=101 of respondents, 25%), ecological value (n=164, 35%), and economic value (n=234, 59%). There was moderate support for the conflict-prone dimension of the IPOACHED model (n=70, 18%). Other factors, such as a species lack of passiveness, obtainability and extractability, hamper poaching regardless of value. Our model serves as an explanatory or predictive tool for understanding poaching within a conservation-based management unit (e.g., a protected area) rather than for a specific use market (e.g., pets). Conservation researchers and practitioners can use and adapt our model and survey instruments to help explain and predict poaching of species through the integration of knowledge and opinions from local communities and conservation professionals, with the ultimate goal of preventing wildlife poaching.

Current and Future Approaches to Mitigate Conflict between Humans and Asian Elephants: The Potential Use of Aversive Geofencing Devices

Simple Summary

Conflict between humans and Asian elephants is a major conservation issue. Here we discuss common tools used to manage human-elephant conflict (HEC) in Asia and the potential of animal-borne satellite-linked shock collars or Aversive Geofencing Devices (AGDs) for managing problem elephants. Most current HEC mitigation tools lack the ability to be modified to accommodate needs of elephants and therefore are sometimes unsuccessful. AGDs currently used to manage livestock movement can be adapted to mitigate HEC to overcome this problem. AGDs can constantly monitor animal movements and be programmed to deliver sound warnings followed by electric shock whenever animals attempt to move across virtual boundaries demarcated by managers. Elephants fitted with AGDs are expected to learn to avoid the electric shock by associating it with the warning sound and move away from specified areas. Based on the potential shown by studies conducted using AGDs on other wild species, we suggest that experiments should be conducted with captive elephants to determine the efficacy and welfare impact of AGDs on elephants. Further, assessing public opinion on using AGDs on elephants will also be important. If elephants can learn to avoid virtual boundaries set by AGDs, it could help to significantly reduce HEC incidents.

Abstract

Asian elephants are a principal cause of human-wildlife conflict. This results in the death/injury of elephants and humans and large-scale crop and property damage. Most current human-elephant conflict (HEC) mitigation tools lack the flexibility to accommodate the ecological needs of elephants and are ineffective at reducing HEC in the long-term. Here we review common HEC mitigation tools used in Asia and the potential of Aversive Geofencing Devices (AGDs) to manage problem elephants. AGDs can be configured to monitor animal movements in real-time and deliver auditory warnings followed by electric stimuli whenever animals attempt to move across user-specified virtual boundaries. Thus, AGDs are expected to condition elephants to avoid receiving shocks and keep them away from virtually fenced areas, while providing alternative routes that can be modified if required. Studies conducted using AGDs with other species provide an overview of their potential in conditioning wild animals. We recommend that the efficacy and welfare impact of AGDs be evaluated using captive elephants along with public perception of using AGDs on elephants as a means of addressing the inherent deficiencies of common HEC mitigation tools. If elephants could be successfully conditioned to avoid virtual fences, then AGDs could resolve many HEC incidents throughout Asia.

Drivers of Three Most Charismatic Mammalian Species Distribution across a Multiple-Use Tropical Forest Landscape of Sumatra, Indonesia

Tropical Rainforest Heritage sites of Sumatra are some of the most irreplaceable landscapes in the world for biodiversity conservation. These landscapes harbor many endangered Asiatic mammals all suffering multifaceted threats due to anthropogenic activities. Three charismatic mammals in Sumatra: Elephas maximus sumatranus, Pongo abelii, and Panthera tigris sumatrae are protected and listed as Critically Endangered (CR) within the IUCN Red List. Nevertheless, their current geographic distribution remains unclear, and the impact of environmental factors on these species are mostly unknown. This study predicts the potential range of those species on the island of Sumatra using anthropogenic, biophysical, topographic, and climatic parameters based on the ensemble machine learning algorithms. We also investigated the effects of habitat loss from current land use, ecosystem availability, and importance of Indonesian protected areas. Our predictive model had relatively excellent performance (Sørensen: 0.81-0.94) and can enhance knowledge on the current species distributions. The most critical environmental predictors for the distribution of the three species are conservation status and temperature seasonality. This study revealed that more than half of the species distributions occurred in non-protected areas, with proportional coverage being 83%, 72%, and 54% for E.m. sumatranus, P. abelii, and P.t. sumatrae, respectively. Our study further provides reliable information on places where conservation efforts must be prioritized, both inside and outside of the protected area networks, to safeguard the ongoing survival of these Indonesian large charismatic mammals.