Nest predation on dabbling duck nests is an important problem in the prairie potholeregion of North Dakota. There are many factors that contribute to the high predation rates. One of them is landscape composition and physiognomy. Many authors have reported that different landscape attributes such as patch size and cover density affect predation rates. However, the data often conflict as to what landscape attributes are important and when. Of the many nest predators in the prairie pothole region, red foxes are considered the most damaging.
I created MOAB (Model Of Animal Behavior), a generalizable model of animal behavior to examine the interaction of predator foraging behavior and landscape attributes. MOAB is a spatially explicit individual-based model. MOAB is generalizable because it uses the artificial intelligence technology of expert systems to create the rule sets animals use to determine their behavior. To change the behavior of a species or create a new species you change the rules and use the graphical user interface to change the species parameters. MOAB has been tested on both the Macintosh and Windows computer platforms. MOAB can import and export habitat type and food distribution files.
MOAB was used to simulate red fox nest depredation with a variety of food densities and distributions and various habitat configurations. Results of red fox nest predation revealed the following:
DESCRIPTION OF MOAB
MOAB is an application for the creation of individual-based models of animal behavior that can be used to simulate dabbling duck (Tribe Anatini) nest depredation by medium-sized mammals (red fox-Vulpes vulpes and striped skunk-Mephitis mephitis) in the prairie pothole ecosystem of North America. However, MOAB has the built in flexibility to allow it to be used to model nest depredation and mammalian foraging behavior with different species in other ecosystems. MOAB users can create or replicate heterogeneous landscape patterns, put resources on that landscape, and place individual animals of a given species on that landscape to simulate their foraging behavior. The heuristic rules for animal behavior are maintained in a user-modifiable expert system. Because of these features MOAB can be used to create various models to explore hypotheses about the influence of landscape pattern on animal movement and foraging behavior.
To meet the design goals, MOAB has three features: a graphical user interface (GUI); an object oriented programming (OOP) construction; and behavior rules controlled by an expert system. These features make it possible to create models for other regions where the interaction of terrestrial animals and landscapes are of interest. Currently, MOAB simulates two species, red fox (Vulpes vulpes) and striped skunk (Mephitis mephitis), simultaneously. Models can be created to simulate many more species. However, when multiple species are simulated they all must move around the landscape at approximately the same spatial-temporal scale. MOAB provides for two different ways to simulate animal behavior, using a set of random movement rules or an expert system.
RANDOM MOVEMENT MODEL
The random movement mode of behavior uses a collection of hierarchical rules of movement, the simplest rule being to pick a direction at random and move in that direction. The most complex random movement rule set uses the animal's internal state variables, food and habitat preferences, and other variables to narrow down its potential decision set. If more than one decision is possible after this process, the animal selects among them at random.
MOAB uses HUMBLE [Xerox 1991], a commercially available expert system shell, combined with a custom made knowledge base. Using HUMBLE users can write their own rules of animal movement and place them in the model [Chapter 3]. The landscape map in MOAB is a simple custom made raster-based GIS in which each cell or location is an intelligent entity. Each cell keeps track of its habitat type, what resources and individuals are present, and a history of events that occurred in the cell. Appropriately formatted habitat and resource maps can be imported into or exported out of MOAB making it possible to incorporate actual landscapes and move habitat and resource maps between different simulations to facilitate hypothesis testing.
MOAB supports graphical displays of data results such as the location of food resources and paths of travel for selected individuals. Summary statistics on animal movement behavior, food density and composition characteristics are available. Animal behavior and movement output can be saved as ASCII files for later modification and analysis by telemetry analysis packages. In addition to MOAB providing the means to change rules of behavior, species and individual parameters can be modified through the GUI. The user can directly modify an individual's age, gender, social relationship (e.g., mate of: ..., young of: ..., parent of: ..., etc.), experience, location, hunger, territory, anxiety, etc. Species-specific parameters that can be modified are: metabolic rate, food preferences, food storage capacity, habitat preferences, interspecific and intraspecific relationships, and diurnal activity patterns.
MOAB was written in Smalltalk, a language that provides for cross platform portability: MOAB should run on any computer that is supported by ObjectWorks™ for Smalltalk, release 4.1. MOAB has been tested on MS Windows and Macintosh platforms.
Code, and compressed versions available on request from author, Jacoby Carter.