Finding politically feasible conservation policies: the case of wildlife trafficking

Abstract

Abstract. Conservation management is of increasing importance in ecology as most ecosystems nowadays are essentially managed ecosystems. Conservation managers work within a political-ecological system when they develop and attempt to implement a conservation plan that is designed to meet particular conservation goals. In this article, we develop a decision support tool that can identify a conservation policy for a managed wildlife population that is both sustainable and politically feasible. Part of our tool consists of a simulation model composed of interacting influence diagrams. We build, fit, and use our tool on the case of rhino horn trafficking between South Africa and Asia. Using these diagrams, we show how a rhino poacher's belief system can be modified by such a policy and locate it in a perceived risks-benefits space before and after policy implementation. We statistically fit our model to observations on group actions and rhino abundance. We then use this fitted model to compute a politically feasible conservation policy.

Automatic Acquisition and Sustainable Use of Political-Ecological Data

“…For example, Haas & Ferreira (2018) develop a political-ecological model composed of an agent-based submodel of poachers interacting with an individual based submodel of the south African rhino population, an agent-based submodel of southeast Asian rhino horn consumers who purchase the poached rhino horn from these poachers, and a submodel antipoaching forces working to curb this poaching activity. Combinations of antipoaching initiatives and economic opportunities for the poachers need to be evaluated as to their probable effectiveness at changing local people's inclination to poach rhinos and the consequent effect on the rhino population (see Haas & Ferreira 2018). To do this, political-ecological data is needed to statistically validate such a large political-ecological model.…”

“…Focusing on the poachers, Haas & Ferreira (2018) use poaching action data to estimate the parameters that represent the decision of a poacher to poach a rhino along with the effect that such poaching has on rhino abundance as captured by the above-mentioned submodel of the South African rhino population.…”

“…To make this calculation, a stochastic simulation model of the managed political-ecological system needs to be fitted to political-ecological data and then run forward in time under ongoing and proposed management policies to arrive at the species' extinction probability 50 animal generations into the future. Haas & Ferreira (2018) performed a shortened version of this calculation for the South African rhino population. There, rhino abundance data had been acquired through expensive helicopter surveys and was allowed to be included in a publication only through the existence of a collaborative research project between SANParks, South Africa and an academic.…”

Developing political-ecological theory: The need for Many-Task Computing

“…A literature search uncovered only two articles describing the statistical estimation of a socio-ecological model’s parameters, namely, [23], and [17]. Several articles, however, were found on the estimation of either strictly social models or strictly ecological models.…”

“…An ID is a bayesian belief network with deterministic input nodes. For instance, the political-ecological system models of Haas and Ferreira ([16], [36], and [17]) are computationally implemented through their attendant simulators.…”