Eliciting cognitive processes underlying patterns of human–wildlife interactions for agent-based modelling

摘要: Abstract Integrating humans in our perception of ecosystems is critical importance to adequately protect natural resources. This poses the challenge understanding human decision making context decisions potentially threatening nature's integrity. We developed a spatially explicit agent-based model that simulates commercial whale-watching vessel movements based on representation captains’ process when observing marine mammals and around Saguenay–St. Lawrence Marine Park Quebec, Canada. focus here part global model, submodel whale having been validated independently ( Lamontagne, 2009 ). The objective this study select validate using pattern-oriented modelling approach (POM): three models cognitive heuristics (satisficing, tallying Take Best) along with null (random choice) were tested. These concurrent built upon knowledge extracted from data collected during field investigations, including interviews captains park wardens, onboard shore-based observations, analyses multi-year dataset sampled excursions. Model selection performed by statistically comparing simulated real patterns boat trajectories (excursion length), spatial hotspots (kernel home range 50%), excursion content (species observed, time allocated different activities). revealed Best heuristic was best performing model. used distribution number boats vicinity (2000 m) each as secondary pattern ability reproduce observations. Given prevalence species attribute choice which observe, heuristic's deal non-compensatory information partly explains its overall performance. Moreover, implementation communication abilities between modelled led emergence persistent observation sites park, well-known collective spatiotemporal characteristic industry; thus validating fundamental assumption cooperation an important mechanism behind dynamics. relatively good performance satisficing supports both evidence literature bounded rationality likely use collections (adaptive toolbox) solve problems contexts. POM strategy appears suitable build up informative ABM regarding management activities environment so further developments will be assessed following same approach.