Robust estimation of lake metabolism by coupling high frequency dissolved oxygen and chlorophyll fluorescence data in a Bayesian framework

Gross primary production (GPP) and community respiration (R) are increasingly calculated from high-frequency measurements of dissolved oxygen (DO) by fitting dynamic metabolic models to the observed DO time series. Because different combinations of metabolic components result in nearly the same DO time series, theoretical problems burden this inverse modeling approach. Bayesian parameter inference could improve identification of processes by including independent knowledge in the estimation procedure. This method, however, requires model development because parameters of existing metabolic models are too abstract to achieve a significant improvement. Because algal biomass is a key determinant of GPP and R, and high-frequency data on phytoplankton biomass are increasingly available, coupling DO and biomass time series within a Bayesian framework has a high potential to support identification of individual metabolic components. We demonstrate this potential in 3 lakes. Phytoplankton data were simulated via a sequential Bayesian learning procedure coupled with an error model that accounted for systematic errors caused by structural deficiencies of the metabolic model. This method provided ecologically coherent, and therefore presumably robust, estimates for biomass-specific metabolic rates and contributes to a better understanding of metabolic responses to natural and anthropogenic disturbances

The role of biota in shaping the phosphorus cycle in lakes

Although phosphorus is an abundant element on Earth, its low availability often constrains the growth and/or biomass of aquatic biota.  Introducing large quantities of available P into the biosphere, humans have opened up the relatively closed biogeochemical cycle of P, resulting in the eutrophication of many types of aquatic ecosystems worldwide.  A thorough understanding of the P cycle is needed, therefore, to both understand the structure and functioning of aquatic ecosystems and to preserve the quality of our aquatic resources. In this review, we deal first with the often misused concept of ‘nutrient limitation’.  The rather general use of P uptake kinetics as an indicator of nutrient deficiency requires a discussion on methodology.  Since metabolic rates and nutrient demands scale with the size of organisms, coexistence of aquatic osmotrophs relies on unique adaptations and is controlled by the whole network of ecological interactions.  Some of these adaptations and interactions are reviewed, with a focus on P cycling.  Finally, a case study demonstrates that the complicated P cycle must be simplified to extremes to predict eutrophication-related changes in a shallow lake

Automatic High Frequency Monitoring for Improved Lake and Reservoir Management

Recent technological developments have increased the number of variables being monitored in lakes and reservoirs using automatic high frequency monitoring (AHFM). However, design of AHFM systems and posterior data handling and interpretation are currently being developed on a site-by-site and issue-by-issue basis with minimal standardization of protocols or knowledge sharing. As a result, many deployments become short-lived or underutilized, and many new scientific developments that are potentially useful for water management and environmental legislation remain underexplored. This Critical Review bridges scientific uses of AHFM with their applications by providing an overview of the current AHFM capabilities, together with examples of successful applications. We review the use of AHFM for maximizing the provision of ecosystem services supplied by lakes and reservoirs (consumptive and non consumptive uses, food production, and recreation), and for reporting lake status in the EU Water Framework Directive. We also highlight critical issues to enhance the application of AHFM, and suggest the establishment of appropriate networks to facilitate knowledge sharing and technological transfer between potential users. Finally, we give advice on how modern sensor technology can successfully be applied on a larger scale to the management of lakes and reservoirs and maximize the ecosystem services they provide