Model testing and assessment: Perspectives from a swarm intelligence, agent-based model of forest insect infestations
Authored by Roger White
Date Published: 2013-05
DOI: 10.1016/j.compenvurbsys.2012.10.004
Sponsors:
Research Council of Canada
Platforms:
Repast
Model Documentation:
Other Narrative
Flow charts
Mathematical description
Model Code URLs:
Model code not found
Abstract
Model testing procedures represent a major challenge in the development of agent-based models (ABMs). However, they are required stages for a model to be accepted and to serve as a forecasting, management or decision-making tool. This study presents a comprehensive approach for testing ForestSimMPB, an agent-based model (ABM) designed to simulate mountain pine beetle (MPB), Dendroctonus ponderosae Hopkins, outbreaks at the scale of individual trees. ForestSimMPB is a complex system model that is using swarming intelligence, capable to represent individuals' behaviours and spatial interactions that influence their surrounding environment. Swarm Intelligence (SI) methods are integrated into the ABM in order to reproduce the collective reasoning and indirect communication of autonomous agents representing MPB behaviour within the forest environment. Model testing approach consist of verification, calibration, sensitivity analysis, validation and qualification stages. Model testing is accomplished by simulating MPB infestations using both the ForestSimMPB model and a Random-ABM model that serves as a null model. Outcomes comparison and assessment are performed using raster-based techniques as well as spatial metrics. Aerial photographs of the British Columbia, Canada study sites are used in this model testing approach. Results indicate that ForestSimMPB model representations of MPB outbreaks are more similar than Random model representations to the spatial distribution of MPB-dead trees. (C) 2012 Elsevier Ltd. All rights reserved.
Tags
Individual-based model
Simulation
Agent-based models
Swarm intelligence
Dynamics
Land-use
calibration
Verification
Validation
Sensitivity-analysis
Cellular-automata model
Complex-systems
Accuracy assessment
Lodgepole pine