探索基于模糊规则的最佳建模程序,以评估森林土壤中指示性褶虫物种的栖息地适宜性

IF 2.6 3区 环境科学与生态学 Q2 ECOLOGY Ecological Modelling Pub Date : 2024-10-08 DOI:10.1016/j.ecolmodel.2024.110903
Yongeun Kim , Yun-Sik Lee , Minyoung Lee , June Wee , Jinsol Hong , Kijong Cho
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引用次数: 0

摘要

面对不断加剧的人为破碎化和栖息地破坏,利用指示物种对土壤栖息地干扰进行研究对于保护和维持森林生态系统的生态功能日益重要。栖息地适宜性建模方法是根据指示物种的生态偏好评估栖息地条件的重要工具,但其在森林土壤中对此类物种的应用仍有待探索。因此,本研究旨在根据指示物种的丰度等级,确定开发模糊模型以评估其生境适宜性的最佳程序,从而填补这一空白。根据从七座山区收集到的数据,使用三种类型的选定变量数(3变量、4变量和5变量)和两种输入变量选择方法(基于统计的变量选择,SVS;基于知识的变量选择,KVS),建立了评估四叶福寿花和八叶福寿花栖息地适宜性的模糊模型,并比较了它们的性能。结果表明,在模型训练和测试阶段,SVS-模糊模型的性能均优于 KVS-模糊模型。随着输入变量数量的增加,KVS-模糊模型的性能有所提高,但与 SVS-模糊模型相比,其性能仍然较低。同时,最优 SVS 模糊模型有效地解释了基于栖息地环境条件的两种藻类的丰度等级(F1 分数为 0.743,马修斯相关系数为 0.520)。这项研究的结果为建立有效的模型来了解土壤指示物种的栖息地适宜性奠定了坚实的基础。将模糊建模的应用范围扩大到森林土壤中的各种物种,将提高我们对生境干扰和退化的认识,有助于制定森林生态系统保护战略。
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Exploring the optimal fuzzy rule-based modeling procedure to assess habitat suitability of indicator Collembola species in forest soils
In the face of escalating anthropogenic fragmentation and habitat destruction, research on soil habitat disturbance using indicator species is increasingly critical to conserve and maintain the ecological functions of forest ecosystems. The modeling methodology for habitat suitability is a valuable tool for assessing habitat conditions based on the ecological preferences of indicator species; however, its application to such species in forest soils remains unexplored. Therefore, this study aimed to fill this gap by identifying an optimal procedure for developing a fuzzy model to evaluate the habitat suitability of indicator species based on their abundance classes. Fuzzy models were developed for assessing the habitat suitability of Folsomia quadrioculata and F. octoculata based on data collected from seven mountains using three types of selected variable numbers (3-, 4-, and 5-variable) for two input variable selection methods (statistics-based variable selection, SVS; knowledge-based variable selection, KVS), and their performance was compared. Our results indicate that the SVS-fuzzy model performed better than the KVS-fuzzy model in both the model training and testing phases. As the number of input variables increased, the performance of the KVS-fuzzy model improved; however, it still exhibited lower performance compared to the SVS-fuzzy model. Meanwhile, the optimal SVS-fuzzy model effectively explained the abundance classes of the two collembolan species based on the environmental conditions of their habitats (F1 score > 0.743, Matthews correlation coefficient > 0.520). The findings of this study provide a solid foundation for developing effective models to understand the habitat suitability of soil indicator species. Expanding the application of fuzzy modeling to diverse species in forest soils will improve our understanding of habitat disturbance and degradation, contributing to the development of conservation strategies for forest ecosystems.
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来源期刊
Ecological Modelling
Ecological Modelling 环境科学-生态学
CiteScore
5.60
自引率
6.50%
发文量
259
审稿时长
69 days
期刊介绍: The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).
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