Modelling the multi-scaled nature of pest outbreaks

被引:15
|
作者
Wildemeersch, Matthias [1 ]
Franklin, Oskar [1 ]
Seidl, Rupert [2 ]
Rogelj, Joeri [1 ]
Moorthy, Inian [1 ]
Thurner, Stefan [1 ,3 ,4 ,5 ,6 ]
机构
[1] Int Inst Appl Syst Anal, A-2361 Laxenburg, Austria
[2] Univ Nat Resources & Life Sci, Peter Jordan Str 82, A-1190 Vienna, Austria
[3] Med Univ Vienna, Sect Sci Complex Syst, Spitalgasse 23, A-1090 Vienna, Austria
[4] Santa Fe Inst, 1399 Hyde Pk Rd, Santa Fe, NM 87501 USA
[5] Complex Sci Hub Vienna, Josefstadter Str 39, A-1080 Vienna, Austria
[6] Nanyang Technol Univ, Complex Inst, Nanyang Dr 18, Singapore 637723, Singapore
基金
奥地利科学基金会;
关键词
Landscape management; Network of networks; Pest dynamics; Pest outbreaks; FOREST DISTURBANCES; MOTH OUTBREAKS; BEETLE; NETWORK; DYNAMICS; SYSTEMS; CONNECTIVITY; THRESHOLDS; MANAGEMENT; DRIVERS;
D O I
10.1016/j.ecolmodel.2019.108745
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Recent research suggests that the spread of pest outbreaks is driven by ecological processes acting at different spatial scales. In this work, we establish a network model for the analysis and management of pest outbreaks that takes into account small-scale host-pest interactions as well as landscape topology and connectivity. The model explains outbreak cycles both for geometrid moths and bark beetles, and provides insight into the relative importance and interactions between the multi-scale drivers of outbreak dynamics. Our results demonstrate that outbreak behavior is most sensitive to changes in pest pressure at the local scale, and that accounting for the spatial connectivity of habitat patches is crucial to capturing the spreading behavior through landscapes. In contrast to early warning signals based on retrospective data, our model provides predictions of future outbreak risk based on a mechanistic understanding of the system, which we apply for landscape-scale forest management.
引用
收藏
页数:13
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