Agent-based models have many applications in biology, primarily due to the characteristics of the modeling method. Agent-based modeling is a rule-based, computational modeling methodology that focuses on rules and interactions among the individual components or the agents of the matrix . The goal of this modeling method is to generate populations of the system components of interest and simulate their interactions in a virtual world. Agent-based models start with rules for behavior and seek to reconstruct, through computational instantiation of those behavioral rules, the observed patterns of behavior.
Characteristics Several of the characteristics of agent-based models important to biological studies include:
Modular structure The behavior of an agent-based model is defined by the rules of its agents. Existing agent rules can be modified or new agents can be added without having to modify the entire model.
Emergent properties Through the use of the individual agents that interact locally with rules of behavior, agent-based models result in a synergy that leads to a higher level whole with much more intricate behavior than those of each individual agent.
Abstraction Either by excluding non-essential details or when details are not available, agent-based models can be constructed in the absence of complete knowledge of the system under study. This allows the model to be as simple and verifiable as possible.
Stochasticity Biological systems exhibit behavior that appears to be random. The probability of a particular behavior can be determined for a system as a whole and then be translated into rules for the individual agents.
Modelling different species behaviour In an ecological context, agent-based modeling can be used to model the behaviour of different species such as insects infestations, other invasive species, aphids, aquatic populations, and the evolution of innate foraging behaviors.
Forest insect infestations Agent-based modeling has been used to simulate attack behavior of the mountain pine beetle (MPB), Dendroctonus ponderosae, in order to evaluate how different harvesting policies influence spatial characteristics of the forest and spatial propagation of the MPB infestation over time. About two-thirds of the land in British Columbia, Canada is covered by forests that are constantly being modified by natural disturbances such as fire, disease, and insect infestation. Forest resources make up approximately 15% of the province's economy, so infestations caused by insects such as the MPB can have significant impacts on the economy. The MPB outbreaks are considered a major natural disturbance that can result in widespread mortality of the lodgepole pine tree, one of the most abundant commercial tree species in British Columbia. Insect outbreaks have resulted in the death of trees over areas of several thousand square kilometers.
The agent-based model developed for this study was designed to simulate the MPB attack behavior in order to evaluate how management practices influence the spatial distribution and patterns of insect population and their preferences for attacked and killed trees. Three management strategies were considered by the model: 1) no management, 2) sanitation harvest and 3) salvage harvest. In the model, the Beetle Agent represented the MPB behavior; the Pine Agent represented the forest environment and tree health evolution; the Forest Management Agent represented the different management strategies. The Beetle Agent follows a series of rules to decide where to fly within the forest and to select a healthy tree to attack, feed, and breed. The MPB typically kills host trees in its natural environment in order to successfully reproduce. The beetle larvae feed on the inner bark of mature host trees, eventually killing them. In order for the beetles to reproduce, the host tree must be sufficiently large and have thick inner bark. The MPB outbreaks end when the food supply decreases to the point that there is not enough to sustain the population or when climatic conditions become unfavorable for the beetle. The Pine Agent simulates the resistance of the host tree, specifically the Lodgepole pine tree, and monitors the state and attributes of each stand of trees. At some point in the MPB attack, the number of beetles per tree reaches the host tree capacity. When this point is reached, the beetles release a chemical to direct beetles to attack other trees. The Pine Agent models this behavior by calculating the beetle population density per stand and passes the information to the Beetle Agents. The Forest Management Agent was used, at the stand level, to simulate two common silviculture practices (sanitation and salvage) as well as the strategy where no management practice was employed. With the sanitation harvest strategy, if a stand has an infestation rate greater than a set threshold, the stand is removed as well as any healthy neighbor stand when the average size of the trees exceeded a set threshold. For the salvage harvest strategy, a stand is removed even it is not under a MPB attack if a predetermined number of neighboring stands are under a MPB attack.
The study considered a forested area in the North-Central Interior of British Columbia of approximately 560 hectare. The area consisted primarily of Lodgepole pine with smaller proportions of Douglas fir and White spruce. The model was executed for five time steps, each step representing a single year. Thirty simulation runs were conducted for each forest management strategy considered. The results of the simulation showed that when no management strategy was employed, the highest overall MPB infestation occurred. The results also showed that the salvage harvest management technique resulted in a 25% reduction in the number of forest strands killed by the MPB, as opposed to a 19% reduction by the sanitation harvest management strategy. In summary, the results show that the model can be used as a tool to build forest management policies.
Invasive species Invasive species refers to "non-native" plants and animals that adversely affect the environments they invade. The introduction of invasive species may have environmental, economic, and ecological implications. An agent-based model can developed to evaluate the impacts of port-specific and importer-specific enforcement regimes for a given agricultural commodity that presents invasive species risk with the goal of improving the allocation of enforcement resources and to provide a tool to policy makers to answer further questions concerning border enforcement and invasive species risk.
The agent-based model developed for the study considered three types of agents: invasive species, importers, and border enforcement agents. In the model, the invasive species can only react to their surroundings, while the importers and border enforcement agents are able to make their own decisions based on their own goals and objectives. The invasive species has the ability to determine if it has been released in an area containing the target crop, and to spread to adjacent plots of the target crop. The model incorporates spatial probability maps that are used to determine if an invasive species becomes established. The study focused on shipments of broccoli from Mexico into California through the ports of entry Calexico, California and Otay Mesa, California. The selected invasive species of concern was the crucifer flea beetle (Phyllotreta cruciferae). California is by far the largest producer of broccoli in the United States and so the concern and potential impact of an invasive species introduction through the chosen ports of entry is significant. The model also incorporated a spatially explicit damage function that was used to model invasive species damage in a realistic manner. Agent-based modeling provides the ability to analyze the behavior of heterogeneous actors, so three different types of importers were considered that differed in terms of commodity infection rates (high, medium, and low), pretreatment choice, and cost of transportation to the ports. The model gave predictions on inspection rates for each port of entry and importer and determined the success rate of border agent inspection, not only for each port and importer but also for each potential level of pretreatment (no pretreatment, level one, level two, and level three).
The model was implemented and ran in NetLogo, version 3.1.5. Spatial information on the location of the ports of entry, major highways, and transportation routes was included in the analysis as well as a map of California broccoli crops layered with invasive species establishment probability maps. BehaviorSpace,BehaviorSpace Guide a software tool integrated with NetLogo, was used to test the effects of different parameters (e.g. shipment value, pretreatment cost) in the model. On average, 100 iterations were calculated at each level of the parameter being used, where an iteration represented a one-year run.
The results of the model showed that as inspection efforts increase, importers increase due care, or the pretreatment of shipments, and the total monetary loss of California crops decreases. The model showed that importers respond to an increase in inspection effort in different ways. Some importers responded to increased inspection rate by increasing pretreatment effort, while others chose to avoid shipping to a specific port, or shopped for another port. An important result of the model results is that it can show or provide recommendations to policy makers about the point at which importers may start to shop for ports, such as the inspection rate at which port shopping is introduced and the importers associated with a certain level of pest risk or transportation cost are likely to make these changes. Another interesting outcome of the model is that when inspectors were not able to learn to respond to an importer with previously infested shipments, damage to California broccoli crops was estimated to be $150 million. However, when inspectors were able to increase inspection rates of importers with previous violations, damage to the California broccoli crops was reduced by approximately 12%. The model provides a mechanism to predict the introduction of invasive species from agricultural imports and their likely damage. Equally as important, the model provides policy makers and border control agencies with a tool that can be used to determine the best allocation of inspectional resources.
Aphid population dynamics An agent-based model can be used to study the population dynamics of the bird cherry-oat aphid, Rhopalosiphum padi. The study was conducted in a five square kilometer region of North Yorkshire, a county located in the Yorkshire and the Humber region of England. The agent-based modeling method was chosen because of its focus on the behavior of the individual agents rather than the population as a whole. The authors propose that traditional models that focus on populations as a whole do not take into account the complexity of the concurrent interactions in ecosystems, such as reproduction and competition for resources which may have significant impacts on population trends. The agent-based modeling approach also allows modelers to create more generic and modular models that are more flexible and easier to maintain than modeling approaches that focus on the population as a whole. Other proposed advantages of agent-based models include realistic representation of a phenomenon of interest due to the interactions of a group of autonomous agents, and the capability to integrate quantitative variables, differential equations, and rule based behavior into the same model.