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ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #139465
Title: SPATIAL PREDICTION OF INVASION SUCCESS ACROSS HETEROGENEOUS LANDSCAPES USING AN INDIVIDUAL-BASED MODEL

Author
item GOSLEE, S - NEW MEXICO STATE UNIV
item Peters, Debra
item BECK, K - COLORADO STATE UNIVERSITY

Submitted to: Biological Invasions
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/3/2004
Publication Date: 3/1/2006
Citation: Goslee, S.C., Peters, D.P.C., Beck, K.G. 2006. Spatial prediction of invasion success across heterogeneous landscapes using an individual-based model. Biological Invasions. 8:193-200.

Interpretive Summary: Russian knapweed (Acroptilon repens) is a highly aggressive introduced perennial forb. The ability to predict where Russian knapweed is most likely to be successful would make it easier to allocate scarce management resources. We used an individual-based simulation model (ECOTONE) and climate and soils data from a geographic information system to identify the regions of Colorado where Russian knapweed is most likely to become abundant if it is introduced. The principal advantage of the simulation modeling approach over other ways of predicting invasion sites is that it can take the effects of the native vegetation into account. The combination of simulation modeling and geographic information is a very useful tool for investigation and prediction of the future of invasive and native plant species.

Technical Abstract: The limited resources available for managing invasive plant species in native ecosystems and the magnitude of the problem make it essential that we develop methods to prioritize sites for management efforts. We used the individual-based simulation model ECOTONE in conjunction with climate and soil texture data to identify grassland site types where the invasive perennial forb Acroptilon repens is likely to be successful and to create a threat map indicating the potential abundance of A. repens across Colorado. This information can be used to direct management efforts towards the areas at greatest risk, allowing the most effective use of limited resources.The most common approach for identifying invasible regions has been to extrapolate from the locations of existing invasions to find similar sites. Two major drawbacks to this method are the lack of consideration of the role of the existing plant community in inhibiting or facilitating invasion and the assumption that the invading species is at equilibrium with the environment. We suggest the combination of an individual-based simulation model and a geographic information system (GIS) provides a flexible tool to investigate the community and regional dynamics of invasive plant species and allows a synthesis of species-oriented invasion ecology and our accumulated understanding of vegetation dynamics.