预测藻类水华:我们是否忽视了地下水?

Predicting algal blooms: Are we overlooking groundwater?

机构信息

Department of Earth and Environmental Sciences, University of Waterloo, Waterloo, ON, Canada.

Civil, Environmental & Architectural Engineering, University of Kansas, Lawrence, KS, USA.

出版信息

Sci Total Environ. 2021 May 15;769:144442. doi: 10.1016/j.scitotenv.2020.144442. Epub 2021 Jan 6.

Abstract

Significant advances in understanding and predicting freshwater algal bloom dynamics have emerged in response to both increased occurrence and financial burden of nuisance and harmful blooms. Several factors have been highlighted as key controls of bloom occurrence, including nutrient dynamics, local hydrology, climatic perturbations, watershed geomorphology, biogeochemistry, food-web control, and algal competition. However, a major research gap continues to be the degree to which groundwater inputs modulate microbial biomass production and food-web dynamics at the terrestrial-aquatic interface. We present a synthesis of groundwater related algal bloom literature, upon which we derive a foundational hypothesis: long residence times cause groundwater to be geochemically and biologically distinct from surface water, allowing groundwater inputs to modulate algal bloom dynamics (growth, decline, toxicity) through its control over in-stream water chemistry. Distinct groundwater chemistry can support or prevent algal blooms, depending on specific local conditions. We highlight three mechanisms that influence the impact of groundwater discharge on algal growth: 1) redox state of the subsurface, 2) extent of water-rock interactions, and 3) stability of groundwater discharge. We underscore that in testing hypotheses related to groundwater control over algal blooms, it is critical to understand how changes in land use, water management, and climate will influence groundwater dynamics and, thus, algal bloom probabilities. Given this challenge, we argue that advances in both modeling and data integration, including genomics data and integrated process-based models that capture groundwater dynamics, are needed to illuminate mechanistic controls and improve predictions of algal blooms.

摘要

为应对有害和滋扰性水华频繁发生及其造成的经济负担,人们对淡水藻类水华动态的理解和预测取得了重大进展。有几个因素已被强调为水华发生的关键控制因素,包括营养动态、局部水文学、气候波动、流域地貌、生物地球化学、食物网控制和藻类竞争。然而,一个主要的研究差距仍然是地下水输入在多大程度上调节陆地-水域界面的微生物生物量生产和食物网动态。我们对与地下水有关的藻类水华文献进行了综合分析,并从中得出一个基本假设:长停留时间导致地下水在地球化学和生物学上与地表水不同,从而通过控制河流中的水化学,地下水输入可以调节藻类水华动态(生长、衰退、毒性)。独特的地下水化学可以支持或阻止藻类水华的发生,具体取决于特定的局部条件。我们强调了影响地下水排放对藻类生长影响的三个机制:1)地下的氧化还原状态,2)水-岩相互作用的程度,3)地下水排放的稳定性。我们强调,在测试与地下水对藻类水华控制有关的假设时,了解土地利用、水管理和气候变化将如何影响地下水动态,从而影响藻类水华的可能性,这一点至关重要。考虑到这一挑战,我们认为需要在建模和数据集成方面取得进展,包括基因组学数据和捕获地下水动态的综合基于过程的模型,以阐明机制控制并提高对藻类水华的预测能力。

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