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

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

Ecological Modelling, 2021, vol. 450, issue C

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.

Keywords: Bayesian network (BN); Fuzzy matter element model (FME); Fuzzy mathematics and Bayesian network model (FBM); Species habitat suitability; Angelica sinensis (Oliv.) Diels (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380021001307
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:450:y:2021:i:c:s0304380021001307

DOI: 10.1016/j.ecolmodel.2021.109560

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().