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
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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.

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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。
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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.
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