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A Bayesian network with fuzzy mathematics for species habitat suitability analysis: A case with limited Angelica sinensis (Oliv.) Diels data

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  • Zhang, Quanzhong
  • Wei, Haiyan
  • Liu, Jing
  • Zhao, Zefang
  • Ran, Qiao
  • Gu, Wei

Abstract

There are many different types of species distribution models (SDMs) that are widely used in the field of ecology. In this research, we explored a new advanced mechanism for predicting the distribution of species based on fuzzy membership function, principle of maximum entropy, fuzzy mathematics comprehensive evaluation, and the framework of Bayesian networks. We use fuzzy mathematics and Bayesian network model (FBM) to simulate relationships between species’ habitats and environmental variables, and the relationship may be difficult to quantify effectively. FBM, which combines species data, environmental data, expert experience, and machine learning, could reduce the data and system error. In the case of medicinal plant, Angelica sinensis (Oliv.) Diels, many approaches have been applied, including nine learning sequence of sampling sites, three FBM models, two types of information classification by fuzzy mathematical classification (FMC) and equal interval classification (EIC), and the evaluation of AIC and log-likelihood. Through the comparison of reasoning results between FBM and fuzzy matter element model (FME) in testing sites, the result shows that the combination of objective data and empirical model structure makes FBM have better result output. Besides, FBM sensitivity analysis helps researchers explore in detail the impact of environmental factors on each level of species habitat suitability. The temperature factor has an important influence on the highly suitable, moderately suitable, and lowly suitable habitats of A. sinensis. Through FMC and sensitivity analysis, annual mean temperature (Bio1) in 5.92 °C-9.05 °C and mean temperature of warmest quarter (Bio10) in 14.80 °C-18.60 °C are the highly suitable habitat temperature range of A. sinensis.

Suggested Citation

  • Zhang, Quanzhong & Wei, Haiyan & Liu, Jing & Zhao, Zefang & Ran, Qiao & Gu, Wei, 2021. "A Bayesian network with fuzzy mathematics for species habitat suitability analysis: A case with limited Angelica sinensis (Oliv.) Diels data," Ecological Modelling, Elsevier, vol. 450(C).
    • Handle: RePEc:eee:ecomod:v:450:y:2021:i:c:s0304380021001307
    DOI: 10.1016/j.ecolmodel.2021.109560
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    1. Lu, Chun Yan & Gu, Wei & Dai, Ai Hua & Wei, Hai Yan, 2012. "Assessing habitat suitability based on geographic information system (GIS) and fuzzy: A case study of Schisandra sphenanthera Rehd. et Wils. in Qinling Mountains, China," Ecological Modelling, Elsevier, vol. 242(C), pages 105-115.
    2. ,, 1999. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 15(3), pages 427-432, June.
    3. Uusitalo, Laura, 2007. "Advantages and challenges of Bayesian networks in environmental modelling," Ecological Modelling, Elsevier, vol. 203(3), pages 312-318.
    4. ,, 1999. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 15(4), pages 629-637, August.
    5. Haizhen Wang & Ratthachat Chatpatanasiri & Pairote Sattayatham, 2017. "Stock Trading Using PE ratio: A Dynamic Bayesian Network Modeling on Behavioral Finance and Fundamental Investment," Papers 1706.02985, arXiv.org.
    6. ,, 1999. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 15(5), pages 777-788, October.
    7. Meineri, Eric & Dahlberg, C. Johan & Hylander, Kristoffer, 2015. "Using Gaussian Bayesian Networks to disentangle direct and indirect associations between landscape physiography, environmental variables and species distribution," Ecological Modelling, Elsevier, vol. 313(C), pages 127-136.
    8. Wang, Chong & Matthies, Hermann G., 2019. "Novel model calibration method via non-probabilistic interval characterization and Bayesian theory," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 84-92.
    9. Freeman, Elizabeth A. & Moisen, Gretchen G. & Frescino, Tracey S., 2012. "Evaluating effectiveness of down-sampling for stratified designs and unbalanced prevalence in Random Forest models of tree species distributions in Nevada," Ecological Modelling, Elsevier, vol. 233(C), pages 1-10.
    10. Zefang Zhao & Yanlong Guo & Haiyan Wei & Qiao Ran & Wei Gu, 2017. "Predictions of the Potential Geographical Distribution and Quality of a Gynostemma pentaphyllum Base on the Fuzzy Matter Element Model in China," Sustainability, MDPI, vol. 9(7), pages 1-15, July.
    11. Coll, M. & Pennino, M. Grazia & Steenbeek, J. & Sole, J. & Bellido, J.M., 2019. "Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches," Ecological Modelling, Elsevier, vol. 405(C), pages 86-101.
    12. ,, 1999. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 15(1), pages 151-160, February.
    13. Pliscoff, Patricio & Luebert, Federico & Hilger, Hartmut H. & Guisan, Antoine, 2014. "Effects of alternative sets of climatic predictors on species distribution models and associated estimates of extinction risk: A test with plants in an arid environment," Ecological Modelling, Elsevier, vol. 288(C), pages 166-177.
    14. Koen, Hildegarde & de Villiers, J.P. & Roodt, Henk & de Waal, Alta, 2017. "An expert-driven causal model of the rhino poaching problem," Ecological Modelling, Elsevier, vol. 347(C), pages 29-39.
    15. Hirotugu Akaike, 1987. "Factor analysis and AIC," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 317-332, September.
    16. Hamilton, Serena H. & Pollino, Carmel A. & Jakeman, Anthony J., 2015. "Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data," Ecological Modelling, Elsevier, vol. 299(C), pages 64-78.
    17. Xuhui Zhang & Haiyan Wei & Zefang Zhao & Jing Liu & Quanzhong Zhang & Xiaoyan Zhang & Wei Gu, 2020. "The Global Potential Distribution of Invasive Plants: Anredera cordifolia under Climate Change and Human Activity Based on Random Forest Models," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    18. Gieder, Katherina D. & Karpanty, Sarah M. & Fraser, James D. & Catlin, Daniel H. & Gutierrez, Benjamin T. & Plant, Nathaniel G. & Turecek, Aaron M. & Robert Thieler, E., 2014. "A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features," Ecological Modelling, Elsevier, vol. 276(C), pages 38-50.
    19. Meyer, Spencer R. & Johnson, Michelle L. & Lilieholm, Robert J. & Cronan, Christopher S., 2014. "Development of a stakeholder-driven spatial modeling framework for strategic landscape planning using Bayesian networks across two urban-rural gradients in Maine, USA," Ecological Modelling, Elsevier, vol. 291(C), pages 42-57.
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