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在建模流的生物状况时,评估先前流量变化信息的附加值
Taylor Woods1, Ken Eng2, Daren M Carlisle3
1U.S. Geological Survey, Eastern Ecological Science Center, 11649 Leetown Road, Kearneysville, WV 25430, USA.
The Science of the total environment
|November 6, 2023
概括
短期流量数据显著改善了溪流中鱼类健康的生态模型. 包括这些信息在内,可以提高各种溪流大小和生态区域的预测,优于仅使用长期流量数据的模型.
科学领域:
- 生态生态学 生态生态学
- 水文学的水文学
- 环境科学 环境科学
背景情况:
- 大规模的生态建模通常基于流量来预测河流生物学.
- 目前的方法通常使用从流量测量结果汇总的长期流量指标.
- 这种方法有其局限性,包括空间偏差和排除短期流量变化.
研究的目的:
- 评估是否短期前期的流量变化数据改善了河流鱼的生物状况模型.
- 为了比较使用长期流量模式数据的模型的性能与包含短期数据的模型的性能.
主要方法:
- 利用了长期流量模式描述器和短期先行流量改变指标.
- 通过使用不同组合的流量数据,开发和比较溪流鱼类生物状况的生态模型.
- 使用kappa统计数据评估模型性能.
主要成果:
- 与仅使用长期数据 (kappa = 0.23) 的模型相比,结合短期先前流量数据的模型显示出更好的性能 (kappa = 0.29).
- 短期数据提高了不同大小的河流和九个生态区域中的六个生态区域的预测准确度.
- 仅使用短期数据的模型与仅使用长期数据 (kappa = 0.23) 的模型的性能类似.
结论:
- 短期前代流量指标提供了有价值的生态见解,这些见解不能完全被长期总结所捕获.
- 纳入短期流量数据可以增强流系统的宏观生态建模.
- 当长期记录不可用时,短期流量数据提供了一个可行的替代方案.
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