Ensemble spatial modeling, considering habitat and biological traits, for predicting the potential distribution of Corythucha ciliata

被引:0
作者
Kim, Tae-Hyeon [1 ]
Byeon, Dae-hyeon [2 ]
Song, Jae-Woo [2 ]
Lee, Wang-Hee [1 ,2 ]
机构
[1] Chungnam Natl Univ, Dept Smart Agr Syst, 99 Daehak Ro,E12, Daejeon 34134, South Korea
[2] Chungnam Natl Univ, Dept Biosyst Machinery Engn, Daejeon, South Korea
关键词
CLIMEX; ensemble modeling; MaxEnt; spatial distribution; sycamore lace bug; SPECIES DISTRIBUTION MODELS; CLIMATE-CHANGE; GEOGRAPHICAL-DISTRIBUTION; SAMPLING BIAS; LACE BUG; MAXENT; HEMIPTERA; ACCURACY; CLIMEX; SAY;
D O I
10.1111/1748-5967.12756
中图分类号
Q96 [昆虫学];
学科分类号
摘要
Ensemble species distribution modeling offers a robust approach to reduce the inherent uncertainties associated with single models, and ultimately providing more accurate predictions of regions with a heightened probability of occurrence. As Corythucha ciliata (Say) damages deciduous trees in diverse environments, including urban, suburban and forested regions, the objective of this study was to predict the potential distribution of C. ciliata by developing an ensemble model that comprehensively considered the biological and habitat traits of the pest using the CLIMEX and MaxEnt models. Although the ensemble model did not have significantly improved performance, compared with the single MaxEnt model, it was robust compared with distribution data. Our predictions suggest that C. ciliata will gradually expand its range from its current distribution in response to climate change, necessitating focused monitoring and pest-control efforts in the predicted regions. This study not only evaluates pest distribution but also provides crucial insights into effective control strategies, which are adaptable to other pest management scenarios.
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页数:15
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  • [1] Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS)
    Allouche, Omri
    Tsoar, Asaf
    Kadmon, Ronen
    [J]. JOURNAL OF APPLIED ECOLOGY, 2006, 43 (06) : 1223 - 1232
  • [2] Avoiding pitfalls when using information-theoretic methods
    Anderson, DR
    Burnham, KP
    [J]. JOURNAL OF WILDLIFE MANAGEMENT, 2002, 66 (03) : 912 - 918
  • [3] Species-specific tuning increases robustness to sampling bias in models of species distributions: An implementation with Maxent
    Anderson, Robert P.
    Gonzalez, Israel, Jr.
    [J]. ECOLOGICAL MODELLING, 2011, 222 (15) : 2796 - 2811
  • [4] The importance of biotic interactions for modelling species distributions under climate change
    Araujo, Miguel B.
    Luoto, Miska
    [J]. GLOBAL ECOLOGY AND BIOGEOGRAPHY, 2007, 16 (06): : 743 - 753
  • [5] Ensemble forecasting of species distributions
    Araujo, Miguel B.
    New, Mark
    [J]. TRENDS IN ECOLOGY & EVOLUTION, 2007, 22 (01) : 42 - 47
  • [6] Species distribution models and ecological theory: A critical assessment and some possible new approaches
    Austin, Mike
    [J]. ECOLOGICAL MODELLING, 2007, 200 (1-2) : 1 - 19
  • [7] Spatial filtering to reduce sampling bias can improve the performance of ecological niche models
    Boria, Robert A.
    Olson, Link E.
    Goodman, Steven M.
    Anderson, Robert P.
    [J]. ECOLOGICAL MODELLING, 2014, 275 : 73 - 77
  • [8] SDMtoolbox 2.0: the next generation Python']Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses
    Brown, Jason L.
    Bennett, Joseph R.
    French, Connor M.
    [J]. PEERJ, 2017, 5
  • [9] SDMtoolbox: a python']python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses
    Brown, Jason L.
    [J]. METHODS IN ECOLOGY AND EVOLUTION, 2014, 5 (07): : 694 - 700
  • [10] Spatial assessment of potential areas at risk from blueberry gall midge distribution in South Korea
    Byeon, Dae-hyeon
    Lee, Wang-Hee
    [J]. JOURNAL OF APPLIED ENTOMOLOGY, 2022, 146 (08) : 957 - 963