Droevendaalsesteeg 10
6708 PB Wageningen
The Netherlands
During my PhD project at NIOO-KNAW and Wageningen University I will explore the potential of the new concept of Smart Nutrient Retention Networks to improve water quality and sustainable nutrient use.
The underlying societal problem that I aim to address in this project is that nutrients end up in surface waters, where they cause water quality problems (e.g. harmful algal blooms) and eventually are lost into the ocean where they become unavailable to humanity. The idea is that positive feedback mechanisms between water plants and nutrient retention in individual waterbodies can affect water quality of larger hydrological networks. In my project, I will develop a model to test and demonstrate smart management strategies to retain and recycle nutrients locally, whilst improving water quality at a larger scale.
Worldwide, water quality managers target a clear, macrophyte-dominated state over a turbid, phytoplankton-dominated state in shallow lakes. The competition mechanisms underlying these ecological states were explored in the 1990s, but the concept of critical turbidity seems neglected in contemporary water quality models. In particular, a simple mechanistic model of alternative stable states in shallow lakes accounting for resource competition mechanisms and critical turbidity is lacking. To this end, we combined Scheffer's theory on critical turbidity with insights from nutrient and light competition theory founded by Tilman, Huisman and Weissing. This resulted in a novel graphical and mathematical model, GPLake-M, that is relatively simple and mechanistically understandable and yet captures the essential mechanisms leading to alternative stable states in shallow lakes. The process-based PCLake model was used to parameterize the model parameters and to test GPLake-M using a pattern-oriented strategy. GPLake-M's application range and position in the model spectrum are discussed. We believe that our results support the fundamental understanding of regime shifts in shallow lakes and provide a starting point for further mechanistic and management-focused explorations and model development. Furthermore, the concept of critical turbidity and the relation between light-limited submerged macrophytes and nutrient-limited phytoplankton might provide a new focus for empirical aquatic ecological research and water quality monitoring programs.
Water quality improvement to avoid excessive phytoplankton blooms often requires eutrophication management where both phosphorus (P) and nitrogen (N) play a role. While empirical eutrophication studies and ecological resource competition theory both provide insight into phytoplankton abundance in response to nutrient loading, they are not seamlessly linked in the current state of eutrophication research. We argue that understanding species competition for multiple nutrients and light in natural phytoplankton communities is key to assessing phytoplankton abundance under changing nutrient supply. Here we present GPLake-S, a mechanistic model rooted in ecological resource competition theory, which has only eight parameters and can predict chlorophyll-a to nutrient relationships for phytoplankton communities under N, P, N+P colimitation and light limitation. GPLake-S offers a simple mechanistic tool to make first estimates of chlorophyll-a levels and nutrient thresholds for generic lake properties, accounting for variation in N:P ratio preferences of phytoplankton species. This makes the model supportive of water management and policy.