A linked model of animal ecology and human behavior for the management of wildlife tourism

Wildlife tourism attractions are characterized as having intricately coupled human-wildlife interactions. Accordingly, the ability to mitigate negative impacts of tourism on wildlife necessitates research into the ecology of the system and of the human dimensions, since plans aimed at optimizing wildlife fitness must also be acceptable to tourists. We developed an integrated systems dynamics model for the management of tourist-stingray interactions at ‘Stingray City Sandbar’ (SCS), Cayman Islands. The model predicts the state of the tourism attraction over time in relation to stingray population size, stingray life expectancy, and tourist visitation under various management scenarios. Stingray population data in the model comprised growth rates and survival estimates (from mark-and-recapture data) and mortality estimates. Inputted changes in their respective rates under different management scenarios were informed by previous research. Original research on the demand of heterogeneous tourist segments for management regulations via a stated choice model was used to calculate changes in the tourist population growth rate from data supplied by the Caymanian government. The management attributes to which tourists were responsive also have anticipated effects on stingray ecology (migration and mortality), and vice versa, thus linking the two components. We found that the model's predictions over a 25-year time span were sensitive to the stingray population growth rate and alternate management options. Under certain management scenarios, it was possible to maximize both the tourist segment in favor of no management and stingray numbers while reducing stingray health. However, the most effective relative strategy included a reduction in visitor density, restricted stingray interactions, and an imposition of a small fee. Over time, although fewer stingrays were predicted to remain at SCS, they would live longer and experience fewer stochastic disease events, and the desirable tourist segment was predicted to predominate. By understanding how management will affect tourist activities and their subsequent impacts on both wildlife health and visitor satisfaction, one can explore the management alternatives that would optimize both.