Assessing the accuracy of species distribution models more thoroughly

被引：0
|
作者：
Arthur Rylah Institute for Environmental Research, Department of Sustainability and Environment, 123 Brown Street, Heidelberg, VIC 3084, Australia [1 ]
机构：
来源：
World IMACS Congr. MODSIM Int. Congr. Model. Simul.: Interfacing Model. Simul. Math. Comput. Sci., Proc. | / 4234-4240期
关键词：
Accuracy measures - Computer intensive methods - Confidence interval - Generalized additive model - Machine learning methods - Prevalence - Species distribution models - Species distributions;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [41] Assessing global pine wilt disease risk based on ensemble species distribution models
    Aierken, Nuermaimaitijiang
    Wang, Geng
    Chen, Mengyu
    Chai, Guoqi
    Han, Xinyi
    Qian, Zhihe
    Zhang, Xiaoli
    ECOLOGICAL INDICATORS, 2024, 167
  • [42] Assessing the effect of prevalence on the predictive performance of species distribution models using simulated data
    Santika, Truly
    GLOBAL ECOLOGY AND BIOGEOGRAPHY, 2011, 20 (01): : 181 - 192
  • [43] Assessing coastal species distribution models through the integration of terrestrial, oceanic and atmospheric data
    Rickbeil, Gregory J. M.
    Coops, Nicholas C.
    Drever, Mark C.
    Nelson, Trisalyn A.
    JOURNAL OF BIOGEOGRAPHY, 2014, 41 (08) : 1614 - 1625
  • [44] Uncertainty in assessing the impacts of global change with coupled dynamic species distribution and population models
    Conlisk, Erin
    Syphard, Alexandra D.
    Franklin, Janet
    Flint, Lorraine
    Flint, Alan
    Regan, Helen
    GLOBAL CHANGE BIOLOGY, 2013, 19 (03) : 858 - 869
  • [45] Input matters matter: Bioclimatic consistency to map more reliable species distribution models
    Morales-Barbero, Jennifer
    Vega-Alvarez, Julia
    METHODS IN ECOLOGY AND EVOLUTION, 2019, 10 (02): : 212 - 224
  • [46] Data prevalence matters when assessing species' responses using data-driven species distribution models
    Fukuda, Shinji
    De Baets, Bernard
    ECOLOGICAL INFORMATICS, 2016, 32 : 69 - 78
  • [47] Socio-economic variables improve accuracy and change spatial predictions in species distribution models
    Bramorska, Beata
    Komar, Ewa
    Maugeri, Luca
    Ruczyński, Ireneusz
    Żmihorski, Michal
    Science of the Total Environment, 2024, 924
  • [48] Socio-economic variables improve accuracy and change spatial predictions in species distribution models
    Bramorska, Beata
    Komar, Ewa
    Maugeri, Luca
    Ruczynski, Ireneusz
    Zmihorski, Michal
    SCIENCE OF THE TOTAL ENVIRONMENT, 2024, 924
  • [49] The accuracy of plant assemblage prediction from species distribution models varies along environmental gradients
    Pottier, Julien
    Dubuis, Anne
    Pellissier, Loic
    Maiorano, Luigi
    Rossier, Leila
    Randin, Christophe F.
    Vittoz, Pascal
    Guisan, Antoine
    GLOBAL ECOLOGY AND BIOGEOGRAPHY, 2013, 22 (01): : 52 - 63
  • [50] Including imprecisely georeferenced specimens improves accuracy of species distribution models and estimates of niche breadth
    Smith, Adam B.
    Murphy, Stephen J.
    Henderson, David
    Erickson, Kelley D.
    GLOBAL ECOLOGY AND BIOGEOGRAPHY, 2023, 32 (03): : 342 - 355
12345