Droevendaalsesteeg 10
6708 PB Wageningen
The Netherlands
I have a background in environmental sciences and aquatic ecology. After my PhD-research on the retention and removal of nutrients in networks of aquatic ecosystems, I am now working as postdoc at NIOO-KNAW. I have a strong interest in nature-based solutions and ecosystem-based approaches at local to global scales. My professional ambition is to integrate scientific knowledge and to use it to contribute to a sustainable future.
Eutrophication is an ecological process showing the state shift of a lake. This shift could be triggered when the external nitrogen (N) loads exceed N thresholds. Meanwhile, external water inputs and the resulting changes in lake water depth could affect N thresholds. Thus, the shift towards eutrophication may occur more quickly when the N thresholds decrease. Lake Baiyangdian is located in the North China Plain and plays an essential role in ecosystem service provision. However, this lake may have seen a decrease in the N threshold decrease due to frequent water replenishment since 2015. In this study, we compared the external N loads to Lake Baiyangdian with the N thresholds from 2012 to 2017. For this, we considered the effects of water replenishment by linking the MARINA-Lakes and the PCLake + models. Then, we assessed how N thresholds could be met by external N loads from sub-basins of Lake Baiyangdian under 2017 and different N management cases, including improved crop yield and efficiency (S1), improved sewage treatment (S2), improved manure management (S3), and combined options (S4). Results indicate that a 45% reduction in river export of N to Lake Baiyangdian was found from 2012 to 2017. Agricultural sources (fertilizer and manure) accounted for 59% of river exports of N in 2017. River N exports to the lake are projected to be reduced by 13–67% under the four cases. In 2017, the N-load response curve exhibited hysteresis with a 56–87% decrease in N thresholds compared to 2012. Measures in S4 can help to reduce external N exports to Lake Baiyangdian below the N thresholds. Our study emphasizes the importance of combined N management strategies to mitigate the eutrophication risk of the lake. These results offer valuable insights for N management in lake basins experiencing increasing water depth resulting from water replenishment.
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.