A Geographic Network Automata Approach for Modeling Dynamic Ecological Systems. Issue 1 (25th November 2018)

• Record Type: Journal Article
• Authors: Anderson, Taylor; Dragićević, Suzana
• Is Part Of: Geographical analysis. Volume 52:Issue 1(2020)
• Page Start: 3
• Page End: 27
• Publication Date: 2018-11-25
• Subjects: Geography -- Methodology -- Periodicals; Electronic journals; 910.00182
• DOI: 10.1111/gean.12183
• Languages: English
• ISSNs: 0016-7363

Abstract

Abstract : Landscape connectivity networks are composed of nodes representing georeferenced habitat patches that link together based on a species' maximum dispersal distance. These static representations cannot capture the complexity in species dispersal where the network of habitat patch nodes changes structure over time as a function of local dispersal dynamics. Therefore, the objective of this study is to integrate geographic information, complexity, and network science to propose a novel Geographic Network Automata (GNA) modeling approach for the simulation of dynamic spatial ecological networks. The proposed GNA modeling approach is applied to the emerald ash borer (EAB) forest insect infestation using geospatial data sets from Michigan, U.S.A. and simulates the evolution of the EAB spatiotemporal dispersal network structures across a large regional scale. The GNA model calibration and sensitivity analysis are performed. The simulated spatial network structures are quantified using graph theory measures. Results indicate that the spatial distribution of habitat patch nodes across the landscape in combination with EAB dispersal processes generate a highly connected small‐world dispersal network that is robust to node removal. The presented GNA model framework is general and flexible so that different types of geospatial phenomena can be modeled, providing valuable insights for management and decision‐making.