An Agent-Based Model of the Spatial Distribution and Density of the Santa Cruz Island Fox

Agent-Based Modeling and Simulation in Mathematics and Biology Education

“…Arguably the greatest appeal of ABMs, and at the same time a treacherous pitfall, is their enormous flexibility, which is attributatble to the fact that any number of rules can be imposed on the agents, and that the environment may be very simple but can also be exceedingly complicated. For instance, the environment may exhibit gradients or even different individually programmable patches (Barth 2012 ; Gooding 2019 ) including importing geographic information systems (GIS) data to define the characteristics of each patch (see Scott ( 2019 ) for an example with a detailed explanation of how GIS data are incorporated into an ABM). In particular, the repeated addition of new elements to a model can quickly increase the complexity of the model, thereby possibly distracting from the core drivers of the system’s behavior, obscuring the importance of each of the rules the agents must follow, and generally making interpretations of results more difficult.…”

“…However, spatial phenomena in biology seldom occur in homogeneous conditions. As examples, consider the formation of tumors with angiogenesis and necrosis; the local patterns of cell-to-cell signaling that governs the embryonic development; the spread of the red fire ant ( Solenopsis invicta ) from Mobile, AL, its alleged port of entry into the USA, all along the Gulf and East Coasts; or the population size and dynamics of the Santa Cruz island fox ( Urocyon littoralis santacruzae ) being driven by territory size which in turn depends on local vegetation (Scott 2019 ). Until relatively recently, the conundrum of space was often dealt with in the final chapter of mathematical modeling in biology.…”