Spatiotemporal management under heterogeneous damage and uncertain parameters. An agent-based approach.
Creators: name: Holderieath, Jason
name: Holderieath, Jason
Publisher: name: Unknown
Year: 2016
Subjects: subject: Agricultural and Food Policy
subject: Environmental Economics and Policy
subject: Institutional and Behavioral Economics
subject: Land Economics/Use
subject: feral swine
subject: wild pigs
subject: ABM
subject: agent-based modeling
subject: wildlife

description: Species are often viewed as either beneficial or detrimental. The determination of beneficial or detrimental depends on the evaluator, often with disagreement within disciplines such as agriculture or wildlife biology. One common argument against a species revolves around its status as native or non-native, with the latter as a negative characteristic. Defining native and non-native is highly subjective, with a common North American delineation as an introduction before and after Columbus, respectively (Nelson 2010). However, in the past, native species such as the American buffalo (Bison bison) have been targets of eradication campaigns and even today white-tailed deer (Odocoileus virginianus) and Canadian geese (Branta Canadensis) populations are managed to limit the damage they inflict on agriculture. It is also acknowledged that these example species have intrinsic value in the ecosystem and value as a recreationally hunted species in the case of white-tailed deer and Canadian geese. Non-native species can be viewed beneficially, as most agricultural species are introduced, for recreational use, and even as a replacement for extirpated native species (Schlaepfer, Sax and Olden 2011; Zivin, Hueth and Zilberman 2000). In the US, one contentious species is feral swine (Sus scrofa). Federal removal and control efforts are underway as some private landowners encourage their growth on their property (Bevins et al. 2014; Bannerman and Cole 2014). Feral swine are a vector for diseases, cause ecosystem damage, and inflict physical losses to agriculture (Pimentel, Zuniga and Morrison 2005; Cozzens 2010; Seward et al. 2004). However, feral swine are a valuable recreational species. With benefits and costs often accruing to different people, conflict over management is inevitable. As in most externality problems, property lines do not inhibit damage. Unique to most externality problems is the way the damage causing agent can multiply and spread unaided once introduced. Stakeholders include agricultural landowners, recreational landowners, private conservationists, and government entities. Agriculturalists may be sensitive to crop damage and unwilling to sell hunting licenses on their property to offset the damage. Recreational users may enjoy the opportunity to hunt feral swine or may be sensitive to habitat damage and predation of other game species. Private individuals may also own land with the expressed purpose of native habitat conservation. This division between agriculturalist, recreationists, and conservationists is in reality too strong. Landowners are often a mix of the three. Landowners may also exhibit inconsistent preferences or a lack of information, implying a need to relax rationality assumptions. Rational choice theory, or the rationality assumptions, require that a consumer's actions exhibit completeness, transitivity, and perfect information. Finally, government entities are responsible for many goals including preservation of native species, maintenance of protective structures such as levees, and preventing outbreaks of dangerous diseases. These varying objectives can result in inconsistent policymaker actions (Karp et al. 2015). Management decisions by one stakeholder will affect the outcomes of all stakeholders. The variety of opinions and the interaction between landowners, government agencies, and the swine themselves make an optimal policy solution, here defined as the policy solution with the highest total welfare gain, hard to determine. Previous work has ignored interaction between people and swine, spatial issues, temporal characteristics of feral swine spread, or the variety of values held among stakeholders. To address these shortcomings, an agent-based modeling approach is used to determine the optimal management solution, as well as how varying stakeholder opinions and rationality can change the optimal solution. Agent-based modeling promises to be able to model a rich diversity in objectives across time and space (Heckbert, Baynes and Reeson 2010). Applications of agent-based modeling demonstrate its capabilities with interactive heterogeneous agents and spatiotemporally explicit modeling (Evans and Kelley 2004; Schreinemachers et al. 2009; Berger and Troost 2014). Agents can be modeled maintaining traditional compatibility with economic theory (e.g. utility maximizing rational agents), with varying degrees of rationality and awareness of their surroundings, and established tools such as linear programming can be used to help agents make decisions (Berger 2001; Schreinemachers et al. 2009). ABMs have been shown to be suited for analysis of policy intended to address previously unseen events such as the effects of climate change or a new trade agreement (Berger 2001; Berger and Troost 2014). This paper will demonstrate the importance of the interaction between individuals across time and space over management decisions in a way that has not previously been published. Management paths have been established for heterogeneous groups of agriculturalists, recreational land users, private conservationists and governmental entities with varying motivations. The setting for the simulations is a hypothetical rural environment with the potential for feral swine and damage to crops, livestock, and habitat. Results from these simulations are being compared to situations with individuals of heterogeneous preferences. Preliminary results indicate that both locality and individual characteristics matter in determining the optimal outcome. The code for the ABM is being written in a program that provides striking visuals in addition to the quantitative data needed for analysis. These visualizations, the research goals, and the subject matter of feral swine have not failed to generate substantial discussion when presented. The model, properly calibrated, can be used to simulate a potential management area to determine the best path forward. Results of the analysis are expected to inform policymakers to help guide hunting license protocol and public management efforts to manage feral swine in a humane, environmentally sustainable, and socially responsible manner.