Modeling the risk of spread and establishment for Asian longhorned beetle (Anoplophora glabripennis) in Massachusetts from 2008-2009

被引:15
|
作者
Shatz, Andrew J. [1 ]
Rogan, John [1 ]
Sangermano, Florencia [1 ]
Miller, Jennifer [2 ]
Elmes, Arthur [1 ]
机构
[1] Clark Univ, Clark Grad Sch Geog, Worcester, MA 01610 USA
[2] Univ Texas Austin, Dept Geog & Environm, Austin, TX 78712 USA
基金
美国国家科学基金会;
关键词
Asian longhorned beetle; Massachusetts; hybrid model; species distribution model; maximum entropy; spread model; SPECIES DISTRIBUTION MODELS; HABITAT SUITABILITY MODELS; EMERALD ASH BORER; ARGENTINE ANT; DISPERSAL; PREDICTION; CERAMBYCIDAE; COLEOPTERA; INVASIONS; PATTERNS;
D O I
10.1080/10106049.2015.1086901
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Land managers responsible for invasive species removal in the USA require tools to prevent the Asian longhorned beetle (Anoplophora glabripennis) (ALB) from decimating the maple-dominant hardwood forests of Massachusetts and New England. Species distribution models (SDMs) and spread models have been applied individually to predict the invasion distribution and rate of spread, but the combination of both models can increase the accuracy of predictions of species spread over time when habitat suitability is heterogeneous across landscapes. First, a SDM was fit to 2008 ALB presence-only locations. Then, a stratified spread model was generated to measure the probability of spread due to natural and human causes. Finally, the SDM and spread models were combined to evaluate the risk of ALB spread in Central Massachusetts in 2008-2009. The SDM predicted many urban locations in Central Massachusetts as having suitable environments for species establishment. The combined model shows the greatest risk of spread and establishment in suitable locations immediately surrounding the epicentre of the ALB outbreak in Northern Worcester with lower risk areas in suitable locations only accessible through long-range dispersal from access to human transportation networks. The risk map achieved an accuracy of 67% using 2009 ALB locations for model validation. This model framework can effectively provide risk managers with valuable information concerning the timing and spatial extent of spread/establishment risk of ALB and potential strategies needed for effective future risk management efforts.
引用
收藏
页码:813 / 831
页数:19
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