Predicting algal blooms: Are we overlooking groundwater?

Andrea E. Brookfield, Amy T. Hansen, Pamela L. Sullivan, Jonathan A. Czuba, Matthew F. Kirk, Li Li, Michelle E. Newcomer, Grace Wilkinson

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

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.

Original languageEnglish (US)
Article number144442
JournalScience of the Total Environment
Volume769
DOIs
StatePublished - May 15 2021

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Environmental Chemistry
  • Waste Management and Disposal
  • Pollution

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