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Classifying habitat characteristics of wetlands using a self-organizing map
Ecological Informatics ( IF 5.1 ) Pub Date : 2023-03-04 , DOI: 10.1016/j.ecoinf.2023.102048
Seong-Hyeon Kim, Kwang-Jin Cho, Tae-Su Kim, Chang-Su Lee, Thakur Dhakal, Gab-Sue Jang

Wetlands are nutrient-rich and biodiverse ecosystems that provide habitats for various animals and plants and protect against flooding. Classification of wetlands provides information to conservation planners and resource managers for ecosystem service determination. Many ecological case studies illuminate the self-organizing map (SOM) as a robust and powerful data classification and visualization tool. In this study, we use the SOM to analyze the habitat characteristics of inland wetlands in South Korea. We surveyed the plants, benthic macroinvertebrates, and bird species inhabiting 530 nationwide wetlands for four years from 2016 to 2019. Nine environmental features, including the proportion of urban area, farmland, grassland, a forest within a 1 km buffer zone, distance from the river and nearest wetland, area, perimeter, and average slope of wetland polygons, were used to train the SOM and examine the habitat characteristics of the surveyed living components. A map size of 10 × 11 pixels was considered for SOM training, and the output data were classified into eight clusters. Based on the occurrence frequency of the surveyed species group, most species were distributed in all clusters, whereas some dominated in specific clusters. We believe that our study contributes significantly to the literature because it highlights the significance of the SOM approach to cluster wetlands with dependent habitats and provides ecological information to build sustainable wetland conservation policies.



中文翻译:

使用自组织地图对湿地栖息地特征进行分类

湿地是营养丰富且生物多样性丰富的生态系统,可为各种动植物提供栖息地并抵御洪水。湿地分类为保护规划者和资源管理者提供信息,以确定生态系统服务。许多生态案例研究阐明了自组织地图 (SOM) 作为一种强大而强大的数据分类和可视化工具。在本研究中,我们使用 SOM 分析韩国内陆湿地的生境特征。我们从 2016 年到 2019 年,连续四年对全国 530 个湿地的植物、底栖大型无脊椎动物和鸟类进行了调查。9 个环境特征,包括 1 公里缓冲区内的城市面积、农田、草地、森林的比例,与湿地的距离。河流和最近的湿地、面积、周长、和湿地多边形的平均坡度,用于训练 SOM 并检查所调查的生物成分的栖息地特征。SOM 训练考虑了 10 × 11 像素的地图大小,输出数据分为八个簇。根据被调查物种群的出现频率,大多数物种分布在所有簇中,而一些物种在特定簇中占主导地位。我们相信我们的研究对文献有重大贡献,因为它强调了 SOM 方法对具有依赖栖息地的湿地集群的重要性,并提供了生态信息以建立可持续的湿地保护政策。输出数据分为八个簇。根据被调查物种群的出现频率,大多数物种分布在所有簇中,而一些物种在特定簇中占主导地位。我们相信我们的研究对文献有重大贡献,因为它强调了 SOM 方法对具有依赖栖息地的湿地集群的重要性,并提供了生态信息以建立可持续的湿地保护政策。输出数据分为八个簇。根据被调查物种群的出现频率,大多数物种分布在所有簇中,而一些物种在特定簇中占主导地位。我们相信我们的研究对文献有重大贡献,因为它强调了 SOM 方法对具有依赖栖息地的湿地集群的重要性,并提供了生态信息以建立可持续的湿地保护政策。

更新日期:2023-03-08
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