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利用基于机器学习算法的方法(最大熵模型)对南非塞胡库内区非洲艾蒿的潜在分布进行建模。

Modelling the Potential Distribution of African Wormwood () Using a Machine Learning Algorithm-Based Approach (MaxEnt) in Sekhukhune District, South Africa.

作者信息

Matsane Willem, Dhau Inos, Mothapo Mologadi Clodean, Thamaga Kgabo Humphrey

机构信息

Department of Geography and Environmental Studies University of Limpopo Sovenga South Africa.

Department of GIS and Remote Sensing University of Fort Hare Alice South Africa.

出版信息

Ecol Evol. 2025 Aug 18;15(8):e71866. doi: 10.1002/ece3.71866. eCollection 2025 Aug.

DOI:10.1002/ece3.71866
PMID:40837534
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12360960/
Abstract

Jacq. ex Willd, commonly known as African wormwood, is a native medicinal plant that has been unsustainably harvested primarily for its leaves because of their medicinal properties. The unsustainable harvesting of this plant underscores the urgent need for conservation and management practices. This study, therefore, used the MaxEnt model of the potential distribution of Sekhukhune District Municipality, South Africa. We used 105 sampled records and 27 environmental variables to model the potential spatial distribution of using the MaxEnt modeling approach. The predictions were performed using current climatic and topographic conditions. A significant portion of the area, 54.46%, is highly suitable for the distribution of , with various degrees. Precipitation contributed 33.6% to the suitability predictions, followed by NDVI, soil, and distance from rivers with 27.1%, 8.1%, and 5.7% respectively. is predicted to be persistent in mountainous areas and along riverbanks. Higher elevated areas from 1000 to 1700 m are highly suitable for the persistence of species, as it remains cool and relatively moist under the changing climate. Conservation efforts should be focused on mountainous areas and along riverbanks. Rivers such as the Ngwaritsi, Motsephiri, and Steelpoort are in areas with highly suitable predictions. On the basis of the findings, we recommend conservation and management of highly suitable areas. A stakeholder-inclusive conservation framework is proposed to guide community-based protection of habitats.

摘要

雅克(Jacq. ex Willd),通常被称为非洲苦艾,是一种本土药用植物,因其叶子的药用特性而遭到不可持续的采摘。这种植物的不可持续采摘凸显了保护和管理措施的迫切需求。因此,本研究使用了南非塞库胡内区市潜在分布的最大熵(MaxEnt)模型。我们使用105个采样记录和27个环境变量,采用最大熵建模方法对其潜在空间分布进行建模。预测是根据当前的气候和地形条件进行的。该区域很大一部分,即54.46%,非常适合其分布,程度各异。降水量对适宜性预测的贡献为33.6%,其次是归一化植被指数(NDVI)、土壤和距河流距离,分别为27.1%、8.1%和5.7%。预计它将在山区和河岸持续存在。海拔1000至1700米的较高区域非常适合该物种的持续存在,因为在气候变化下那里仍然凉爽且相对湿润。保护工作应集中在山区和河岸。恩瓦里齐河、莫特塞菲里河和斯蒂尔波特河等河流所在区域预测适宜性很高。基于这些发现,我们建议对高度适宜的区域进行保护和管理。提出了一个包含利益相关者的保护框架,以指导基于社区的栖息地保护。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a299/12360960/121277285c47/ECE3-15-e71866-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a299/12360960/fef7d4aa3bb4/ECE3-15-e71866-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a299/12360960/f5cbb6513135/ECE3-15-e71866-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a299/12360960/8273b8b5f9dd/ECE3-15-e71866-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a299/12360960/81f51ee6bca1/ECE3-15-e71866-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a299/12360960/121277285c47/ECE3-15-e71866-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a299/12360960/fef7d4aa3bb4/ECE3-15-e71866-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a299/12360960/f5cbb6513135/ECE3-15-e71866-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a299/12360960/8273b8b5f9dd/ECE3-15-e71866-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a299/12360960/81f51ee6bca1/ECE3-15-e71866-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a299/12360960/121277285c47/ECE3-15-e71866-g002.jpg

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