Predicting Species Occurrence of Litsea leytensis Merr. in the Provinces of Laguna and Quezon, Philippines

IF 0.4 4区 环境科学与生态学 Q4 ENVIRONMENTAL SCIENCES Journal of Environmental Science and Management Pub Date : 2023-06-30 DOI:10.47125/jesam/2023_1/03
Kathreena Engay-Gutierrez, M. Espaldon, C. Tiburan, Jr., Jessica Villanueva-Peyraube, D. Macandog, Marisa J. Sobremisana
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Abstract

Litsea leytensis Merr. is an endemic and premium hardwood species in the Philippines used for wood carving. It is a threatened species that survival in the wild is impossible with persistent causal factors. The study estimated the species probability of occurrence in Laguna and Quezon based on local knowledge, published records of species distribution, and environmental variables using the Maximum Entropy (MaxEnt) model. Six pre-models were generated: one climatic model, four partial models of variable groups combined with climatic variables, and one full model with 31 original variables. The Final model had 19 highly correlated variables after variable selection and reduction using Jackknife and multi-collinearity tests. Analysis of variable importance revealed that L. leytensis’ occurrence was mostly determined by climatic (62.0%), edaphic (21.76%), and anthropogenic variables (9.53%), while topographic (5.15%) and vegetation-related variables (1.34%) had lesser contributions. The Area Under the Receiver Operating Characteristic Curve (AUC) and True Skill Statistics (TSS) measured model accuracy; and the Final model performed best at AUC = 0.9489 and TSS = 0.7175. Modeling species probability of occurrence could help key sectors in Laguna and Quezon to formulate appropriate conservation strategies for L. leytensis as a reforestation and industrial tree plantation species.
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枸杞子的物种发生预测。在菲律宾的拉古纳和奎松省
Litsea leytensis Merr。是菲律宾特有的优质硬木品种,用于木雕。这是一种受威胁的物种,由于持续的原因,在野外生存是不可能的。利用最大熵模型(Maximum Entropy model, MaxEnt),利用当地知识、已发表的物种分布记录和环境变量,估计了拉古纳和奎松的物种发生概率。共生成6个预模式:1个气候模式,4个结合气候变量组的部分模式,1个包含31个原始变量的完整模式。经折刀检验和多重共线性检验,最终模型有19个高度相关的变量。变量重要性分析表明,leytensis的发生主要由气候(62.0%)、土壤(21.76%)和人为因素(9.53%)决定,地形(5.15%)和植被相关变量(1.34%)的贡献较小。受试者工作特征曲线下面积(AUC)和真技能统计量(TSS)测量模型精度;最终模型在AUC = 0.9489、TSS = 0.7175时表现最佳。建立物种发生概率模型可以帮助拉古纳和奎松的重点部门制定适当的保护策略,以作为再造林和工业人工林树种。
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来源期刊
CiteScore
0.90
自引率
0.00%
发文量
10
审稿时长
2 months
期刊介绍: The Journal of Environmental Science and Management (JESAM) is an international scientific journal produced semi-annually by the University of the Philippines Los Baños (UPLB). JESAM gives particular premium to manuscript submissions that employ integrated methods resulting to analyses that provide new insights in environmental science, particularly in the areas of: environmental planning and management; protected areas development, planning, and management; community-based resources management; environmental chemistry and toxicology; environmental restoration; social theory and environment; and environmental security and management.
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