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使用拓数据分析量化上密西西比河系统的生态系统状态和状态过渡
Danelle Marie Larson1, Wako Bungula2, Casey McKean3
1U.S. Geological Survey, Upper Midwest Environmental Sciences Center, La Crosse, Wisconsin, United States of America.
PLoS computational biology
|June 7, 2023
概括
拓数据分析确定了密西西比河上游系统的五个生态系统状态,揭示了关键的水质变量和过渡,以指导保护和恢复工作.
科学领域:
- 生态生态学 生态生态学
- 环境科学 环境科学
- 数据科学数据科学数据科学
背景情况:
- 水生生态系统可以存在于多个状态,影响管理和康复战略.
- 上密西西比河系统 (UMRS) 是一个复杂的,大规模的洪水平原河流系统,需要对其生态系统状态进行有效的描述.
研究的目的:
- 在UMRS中使用长期数据集对生态系统状态进行分类.
- 为了确定关键的状态变量,并检测生态系统状态的过渡超过三十年.
- 为UMRS的保护和恢复工作提供信息.
主要方法:
- 结合了30年的高维水质监测数据集与拓数据分析 (TDA) 技术.
- 利用TDA对生态系统状态进行分类,识别状态变量和检测状态转换.
- 分析了跨河流和季节的生态系统状态的模式.
主要成果:
- 确定了五个不同的生态系统状态:一个清水的冬季状态,一个具有广泛条件的现状状态,以及三个日益混乱的状态.
- 确定悬浮固体,叶绿素a和总作为关键状态变量,与浅湖生态系统一致.
- 检测到季节性和偶发性的短期状态转换,以及30年来长期改善水质的证据.
结论:
- TDA有效地对生态系统状态进行分类,并识别大型河流系统中的状态变量.
- 这些发现提供了定量目标,并为UMRS中的监管和恢复机构的决策提供了信息.
- TDA变化检测提供了一个新的工具,用于预测生态系统对不良状态转换的脆弱性,可转移到其他数据丰富的生态系统.
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