A Geosimulation Approach for Data Scarce Environments: Modeling Dynamics of Forest Insect Infestation across Different Landscapes

Abstract

Abstract:Insect infestation behaves as a complex system, characterized by non-linear spatial dynamics and emergent patterns that evolve from smaller to larger spatial scales. The emerald ash borer (EAB) is an invasive species that has infested and killed millions of ash trees across North America. Existing EAB models use traditional statistical approaches that often cannot address the spatiotemporal complexity emerging from EAB infestation processes. Moreover, these studies of insect infestation are limited by a lack of sufficient time series data. The objective of this study is to develop a geosimulation approach to overcome the challenge of data scarcity and represent EAB infestation at a regional scale. Geographic information systems (GIS), multi-criteria evaluation (MCE), and cellular automata (CA) are used to model EAB spread across different hypothetical landscape types. Simulation results represent EAB propagation and indicate different dynamics of spread for each landscape. Urban environments are identified as being at the greatest risk to the infestation. The proposed approach offers a theoretical framework and a modeling tool to represent the propagation of EAB infestation that can be applied with real geospatial datasets and potentially used in forest management strategies.

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Landscape-Scale Forest Reorganization Following Insect Invasion and Harvest Under Future Climate Change Scenarios

“…Since its discovery, economic damages incurred from the quarantines, removal of infested and dead trees, and lost timber and nursery stock have resulted in EAB becoming the costliest non-native insect to invade US forests (Herms and McCullough 2014). Research on EAB has focused on quantifying spread rate based on empirical data from the field (Mercader and others 2009;Siegert and others 2014) and using geospatial simulation modeling to project future spread (BenDor and others 2006;Muirhead and others 2006;Prasad and others 2010;Anderson and Dragicevic 2016). Such forecasts can be used as decision support tools for forest managers and municipal planners interested in reducing the economic impact of EAB through slowing or impeding its spread (Poland and Mccullough 2010;Bossenbroek and others 2015), for example by identifying the role of preemptive ash harvest to mitigate spread and manage forest change.…”

Integrating remote sensing, GIS and dynamic models for landscape-level simulation of forest insect disturbance

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