Conservation Risks: When Will Rhinos be Extinct?

Abstract

We develop a risk intelligence system for biodiversity enterprises. Such enterprises depend on a supply of endangered species for their revenue. Many of these enterprises, however, cannot purchase a supply of this resource and are largely unable to secure the resource against theft in the form of poaching. Because replacements are not available once a species becomes extinct, insurance products are not available to reduce the risk exposure of these enterprises to an extinction event. For many species, the dynamics of anthropogenic impacts driven by economic as well as noneconomic values of associated wildlife products along with their ecological stressors can help meaningfully predict extinction risks. We develop an agent/individual-based economic-ecological model that captures these effects and apply it to the case of South African rhinos. Our model uses observed rhino dynamics and poaching statistics. It seeks to predict rhino extinction under the present scenario. This scenario has no legal horn trade, but allows live African rhino trade and legal hunting. Present rhino populations are small and threatened by a rising onslaught of poaching. This present scenario and associated dynamics predicts continued decline in rhino population size with accelerated extinction risks of rhinos by 2036. Our model supports the computation of extinction risks at any future time point. This capability can be used to evaluate the effectiveness of proposed conservation strategies at reducing a species' extinction risk. Models used to compute risk predictions, however, need to be statistically estimated. We point out that statistically fitting such models to observations will involve massive numbers of observations on consumer behavior and time-stamped location observations on thousands of animals. Finally, we propose Big Data algorithms to perform such estimates and to interpret the fitted model's output.

Animal-borne behaviour classification for sheep (Dohne Merino) and Rhinoceros (Ceratotherium simum and Diceros bicornis)

“…This might allow quick response in an attempt to catch poachers red handed. At present, our specific focus is the monitoring of rhinoceros to assist conservation efforts, since these animals are currently subject to an unprecedented and sustained poaching onslaught [38]. Our field tests indicate that both the behaviour and GPS location can be monitored in real time as illustrated in Fig.…”

Combating Rhino Horn Trafficking: The Need to Disrupt Criminal Networks

“…We also obtained data on rhinos poached annually since 1998 from the Environmental Crime Investigation Unit of SANParks, specifically, rhino poaching data as summarized by Ken Maggs, ken.maggs@sanparks.org. We used this data to parameterize the individual-based sub-model of rhinos [30]. …”

Automatic Acquisition and Sustainable Use of Political-Ecological Data

“…As mentioned above, Haas & Ferreira (2016a) build a stochastic, political-ecological model of the rhino management system by coupling together an agent-based submodel of consumer demand for rhino horn, a submodel of rhino poachers, and an individual-based submodel of South African rhino population dynamics. After fitting this model to data, these authors use it to show that changes in demand for rhino horn affect poaching effort which in-turn, affects rhino population dynamics.…”

“…Other types of data, although not directly related, are part of causal processes such as wildlife product themes that point to motivations that drive demand for wildlife products. An early model of a wildlife product consumer's decision making is given in Haas & Ferreira (2016a). This model does not attempt to capture the goals that such a consumer is trying to attain such as social status or health guarantees -but rather focuses only on how the consumer's price sensitivity may affect their decision to purchase rhino horn or not.…”