Estimates of Lake Nitrogen, Phosphorus, and Chlorophyll-a Concentrations to Characterize Harmful Algal Bloom Risk Across the United States

IF 7.3 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES Earths Future Pub Date : 2024-08-26 DOI:10.1029/2024EF004493
Meredith M. Brehob, Michael J. Pennino, Amalia M. Handler, Jana E. Compton, Sylvia S. Lee, Robert D. Sabo
{"title":"Estimates of Lake Nitrogen, Phosphorus, and Chlorophyll-a Concentrations to Characterize Harmful Algal Bloom Risk Across the United States","authors":"Meredith M. Brehob,&nbsp;Michael J. Pennino,&nbsp;Amalia M. Handler,&nbsp;Jana E. Compton,&nbsp;Sylvia S. Lee,&nbsp;Robert D. Sabo","doi":"10.1029/2024EF004493","DOIUrl":null,"url":null,"abstract":"<p>Excess nutrient pollution contributes to the formation of harmful algal blooms (HABs) that compromise fisheries and recreation and that can directly endanger human and animal health via cyanotoxins. Efforts to quantify the occurrence, drivers, and severity of HABs across large areas is difficult due to the resource intensive nature of field monitoring of lake nutrient and chlorophyll-<i>a</i> concentrations. To better characterize how nutrients interact with other environmental factors to produce algal blooms in freshwater systems, we used spatially explicit and temporally matched climate, landscape, in-lake characteristic, and nutrient inventory data sets to predict nutrients and chlorophyll-<i>a</i> across the conterminous US (CONUS). Using a nested modeling approach, three random forest (RF) models were trained to explain the spatiotemporal variation in total nitrogen (TN), total phosphorus (TP), and chlorophyll-<i>a</i> concentrations across US EPA's National Lakes Assessment (<i>n</i> = 2,062). Concentrations of TN and TP were the most important predictors and, with other variables, the RF model accounted for 68% of variation in chlorophyll-<i>a</i>. We then used these RF models to extrapolate lake TN and TP predictions to lakes without nutrient observations and predict chlorophyll-<i>a</i> for ∼112,000 lakes across the CONUS. Risk for high chlorophyll-<i>a</i> concentrations is highest in the agriculturally dominated Midwest, but other areas of risk emerge in nutrient pollution hot spots across the country. These catchment and lake-specific results can help managers identify potential nutrient pollution and chlorophyll-<i>a</i> hot spots that may fuel blooms, prioritize at-risk lakes for additional monitoring, and optimize management to protect human health and other environmental end goals.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"12 8","pages":""},"PeriodicalIF":7.3000,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004493","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Earths Future","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1029/2024EF004493","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Excess nutrient pollution contributes to the formation of harmful algal blooms (HABs) that compromise fisheries and recreation and that can directly endanger human and animal health via cyanotoxins. Efforts to quantify the occurrence, drivers, and severity of HABs across large areas is difficult due to the resource intensive nature of field monitoring of lake nutrient and chlorophyll-a concentrations. To better characterize how nutrients interact with other environmental factors to produce algal blooms in freshwater systems, we used spatially explicit and temporally matched climate, landscape, in-lake characteristic, and nutrient inventory data sets to predict nutrients and chlorophyll-a across the conterminous US (CONUS). Using a nested modeling approach, three random forest (RF) models were trained to explain the spatiotemporal variation in total nitrogen (TN), total phosphorus (TP), and chlorophyll-a concentrations across US EPA's National Lakes Assessment (n = 2,062). Concentrations of TN and TP were the most important predictors and, with other variables, the RF model accounted for 68% of variation in chlorophyll-a. We then used these RF models to extrapolate lake TN and TP predictions to lakes without nutrient observations and predict chlorophyll-a for ∼112,000 lakes across the CONUS. Risk for high chlorophyll-a concentrations is highest in the agriculturally dominated Midwest, but other areas of risk emerge in nutrient pollution hot spots across the country. These catchment and lake-specific results can help managers identify potential nutrient pollution and chlorophyll-a hot spots that may fuel blooms, prioritize at-risk lakes for additional monitoring, and optimize management to protect human health and other environmental end goals.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
估算全美湖泊氮、磷和叶绿素-a 浓度,确定藻类大量繁殖的风险特征
过量的营养物污染会导致有害藻华(HABs)的形成,从而损害渔业和娱乐活动,并可能通过蓝藻毒素直接危害人类和动物的健康。由于实地监测湖泊营养物和叶绿素-a 浓度需要大量资源,因此很难量化大面积有害藻华的发生、驱动因素和严重程度。为了更好地描述营养物质如何与其他环境因素相互作用,导致淡水系统中藻类大量繁殖,我们使用了空间明确、时间匹配的气候、景观、湖泊特征和营养物质清单数据集来预测整个美国大陆(CONUS)的营养物质和叶绿素-a。采用嵌套建模方法,训练了三个随机森林(RF)模型来解释美国环保署国家湖泊评估(n = 2,062)中总氮(TN)、总磷(TP)和叶绿素-a 浓度的时空变化。总氮和总磷的浓度是最重要的预测因子,加上其他变量,RF 模型可解释 68% 的叶绿素-a 变化。然后,我们利用这些 RF 模型将湖泊 TN 和 TP 预测结果外推至没有营养观测数据的湖泊,并预测了美国中部地区 11.2 万个湖泊的叶绿素-a。在以农业为主的中西部地区,叶绿素-a 浓度偏高的风险最高,但在全国各地的营养污染热点地区,也出现了其他风险区域。这些针对集水区和湖泊的研究结果可以帮助管理者识别可能助长水华的潜在营养物污染和叶绿素-a 热点,优先对有风险的湖泊进行额外监测,并优化管理以保护人类健康和其他环境终极目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Earths Future
Earths Future ENVIRONMENTAL SCIENCESGEOSCIENCES, MULTIDI-GEOSCIENCES, MULTIDISCIPLINARY
CiteScore
11.00
自引率
7.30%
发文量
260
审稿时长
16 weeks
期刊介绍: Earth’s Future: A transdisciplinary open access journal, Earth’s Future focuses on the state of the Earth and the prediction of the planet’s future. By publishing peer-reviewed articles as well as editorials, essays, reviews, and commentaries, this journal will be the preeminent scholarly resource on the Anthropocene. It will also help assess the risks and opportunities associated with environmental changes and challenges.
期刊最新文献
Effective Adaptation Options to Alleviate Nuisance Flooding in Coastal Megacities—Learning From Ho Chi Minh City, Vietnam Observations Over a Century Underscore an Increasing Likelihood of Compound Dry-Hot Events in China Response of Global Runoff Components to Rising CO2 Increased Asian Sulfate Aerosol Emissions Remarkably Enhance Sahel Summer Precipitation Consumption-Based Emissions of African Countries: An Analysis of Decoupling Dynamics and Drivers
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1