Paul Montagna, TAMUCC
Humans have had a significant influence on estuaries through land use change and increased use of fertilizers, causing proliferation of algal blooms, hypoxia, and presence of harmful microbes. Now, acidification due to myriad processes has been identified as a potential threat to many estuaries. In Texas estuaries for example, short-term acidification as a result of episodic hypoxia is a well-documented phenomenon. Unfortunately, a longer-term trend toward chronic acidification (decreasing alkalinity, pH) has now been observed. The alkalinity decrease is likely caused by a reduction in riverine alkalinity export due to precipitation declines under drought conditions and freshwater diversions for human consumption.
Based on our existing long-term data, we hypothesize that hydrology acts as a switch, where increased river flows cause hypoxia and short-term acidification due to increased loads of organic matter, whereas prolonged low flows cause long-term acidification due to reduced loads of riverine alkalinity and calcification. In urbanized, wastewater-influenced systems, we hypothesize that reduced flows out of the watershed may lead to long-term acidification and chronic hypoxia due to reduced loads of riverine alkalinity and presence of low pH, high nutrient/organic matter wastewater.
To test our hypotheses, field and modeling studies are proposed to examine the relationships between estuarine acidification and other stressors (i.e., reduced freshwater inflow, hypoxia, and nutrient loading). Analysis of changes in ecosystem health and model calibration will be conducted based on long-term data. Mechanistic linkages between acidification, eutrophication and flow will be quantified through a field campaign. Chemical markers of organic matter sources fueling hypoxia will be determined. Future ecological states of the estuaries will be predicted using ecosystem models that account for projected changes in aforementioned parameters and ocean conditions based on IPCC estimates. The combination of prediction and consequence will be useful to multiple stakeholder groups.