Predicting anoxia in low-nutrient temperate lakes.

Area of Science:

• Limnology
• Ecology
• Environmental Science

Background:

• Hypolimnetic anoxia in lakes can harm aquatic life and release phosphorus.
• Anoxia is often caused by organic matter decomposition, worsened by nutrient loads.
• Natural anoxia, influenced by lake basin shape, is crucial for reference condition assessments.

Purpose of the Study:

• To investigate factors causing natural versus human-influenced anoxia in low-nutrient lakes.
• To develop predictive models for hypolimnetic anoxia extent based on lake characteristics.
• To assess the roles of morphometry, thermal stratification, total phosphorus (TP), and dissolved organic carbon (DOC) in anoxia.

Main Methods:

• Constructed logistic regression models to predict anoxic extent (≥10% aerial coverage).
• Tested variables including maximum lake depth, thermocline depth, epilimnetic TP, and DOC.
• Compared model performance with and without TP and for lakes with limited bathymetric data.

Main Results:

• Maximum lake depth and proportion of area under the metalimnion were key predictors (84% accuracy).
• Including TP improved model accuracy slightly (86%), but morphometric factors remained dominant.
• A model using maximum depth and thermocline depth predicted anoxia with 81% accuracy.
• DOC did not significantly improve model performance.

Conclusions:

• Lake morphometry and stratification dynamics are the primary drivers of anoxic extent in low-nutrient temperate lakes.
• Total phosphorus is a significant factor but secondary to physical lake characteristics.
• Predictive models based on morphometry and stratification aid in understanding and managing lake ecosystems and potential regime shifts.