告知志愿者水质监测项目设计和流域规划:阿肯色州上白河流域的StreamSmart数据分析案例研究

IF 0.9 Q4 WATER RESOURCES
Erin Grantz, Brian E. Haggard, BENG 4973/5973
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引用次数: 0

摘要

流域组织H2Ozarks成立了StreamSmart公民科学项目,为阿肯色州上白河流域建立基线和长期水质数据。StreamSmart志愿者收集水样,并在土地利用-土地覆盖(LULC)梯度的bb20个地点进行栖息地和大型无脊椎动物群落评估。自2020年以来,H2Ozarks对该项目进行了适应性评估,以确保对水质数据的投资符合核心目标,特别关注规划工具,并将志愿者工作的期望与培训和支持水平保持一致。研究目标是利用StreamSmart数据,1)利用一系列方法(Spearman秩相关、非参数变化点分析、分类和回归树分析)促进对流域水质对压力源的反应的理解,2)探索方案设计和流域规划的影响。水化学- LULC关系与先前的区域研究以及全球模式一致。检测到的阈值和层次结构为管理LULC变化以保护水质提供了潜在目标,但需要进一步分析以完善这些关系。大型无脊椎动物的应激反应在敏感和不敏感的分类群以及栖息地指数成分中最容易检测到,这表明有可能简化这些规划元素。StreamSmart的研究结果也应该为其他资源有限的小规模志愿者监测项目提供信息,但这些项目积极评估能够产生最大科学投资回报的数据和项目活动类型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Informing Volunteer Water Quality Monitoring Program Design and Watershed Planning: Case Study of StreamSmart Data Analysis in the Upper White River Basin, Arkansas

Informing Volunteer Water Quality Monitoring Program Design and Watershed Planning: Case Study of StreamSmart Data Analysis in the Upper White River Basin, Arkansas

The watershed group H2Ozarks founded the StreamSmart Citizen Science Program to establish baseline and long-term water quality data for the Upper White River Basin, Arkansas. StreamSmart volunteers collect water samples and conduct habitat and macroinvertebrate community assessments at >20 sites across a land use-land cover (LULC) gradient. Since 2020, H2Ozarks has adaptively assessed the program to ensure that the investment in water quality data meets core goals, with particular interest in planning tools and aligning expectations of volunteer effort with the level of training and support. Study objectives were to use StreamSmart data to 1) facilitate understanding of water quality response to stressors in the basin using a range of methods (Spearman rank correlation, non-parametric changepoint analysis, and categorical and regression tree analysis) and 2) explore implications for program design and watershed planning. Water chemistry-LULC relationships were in-line with prior regional studies, as well as global patterns. Detected thresholds and hierarchy provide potential targets for managing LULC change to protect water quality, but further analysis is warranted to refine these relationships. Macroinvertebrate stressor-response was most detectable for sensitive and less sensitive taxa and for habitat index components, suggesting potential to streamline these programmatic elements. Study findings for StreamSmart should also be informative for other small-scale volunteer monitoring programs with limited resources, but which actively evaluate the types of data and program activities that yield a maximum scientific return on investment.

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