How nutrient retention and TN:TP ratios depend on ecosystem state in thousands of Chinese lakes.

Worldwide, anthropogenic activities threaten surface water quality by aggravating eutrophication and increasing total nitrogen to total phosphorus (TN:TP) ratios. In hydrologically connected systems, water quality management may benefit from in-ecosystem nutrient retention by preventing nutrient transport to downstream systems. However, nutrient retention may also alter TN:TP ratios with unforeseen consequences for downstream water quality. Here, we aim to increase understanding of how nutrient retention may influence nutrient transport to downstream systems to improve long-term water quality management. We analyzed lake ecosystem state, in-lake nutrient retention, and nutrient transport (ratios) for 3482 Chinese lakes using the lake process-based ecosystem model PCLake+. We compared a low climate change and sustainability-, and a high climate change and economy-focused scenario for 2050 against 2012. In both scenarios, the effect of nutrient input reduction outweighs that of temperature rise, resulting in more lakes with good ecological water quality (i.e., macrophyte-dominated) than in 2012. Generally, the sustainability-focused scenario shows a more promising future for water quality than the economy-focused scenario. Nevertheless, most lakes remain phytoplankton-dominated. The shift to more macrophyte-dominated lakes in 2050 is accompanied by higher nutrient retention fractions and less nutrient transport to downstream waterbodies. In-lake nutrient retention also alters the water's TN:TP ratio, depending on the inflow TN:TP ratio and the ecosystem state. In 2050 higher TN:TP ratios are expected in the outflows of lakes than in 2012, especially for the sustainability-focused scenario with strong TP loading reduction. However, the downstream impact of increased TN:TP ratios depends on actual nutrient loadings and the limiting nutrient in the receiving system. We conclude that nutrient input reductions, improved water quality, higher in-lake nutrient retention fractions, and lower nutrient transport to downstream waterbodies go hand in hand. Therefore, water quality management could benefit even more from nutrient pollution reduction than one would expect at first sight.

Regime shifts in shallow lakes explained by critical turbidity.

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.

A Generically Parameterized model of Lake eutrophication (GPLake) that links field-, lab- and model-based knowledge.

Worldwide, eutrophication is threatening lake ecosystems. To support lake management numerous eutrophication models have been developed. Diverse research questions in a wide range of lake ecosystems are addressed by these models. The established models are based on three key approaches: the empirical approach that employs field surveys, the theoretical approach in which models based on first principles are tested against lab experiments, and the process-based approach that uses parameters and functions representing detailed biogeochemical processes. These approaches have led to an accumulation of field-, lab- and model-based knowledge, respectively. Linking these sources of knowledge would benefit lake management by exploiting complementary information; however, the development of a simple tool that links these approaches was hampered by their large differences in scale and complexity. Here we propose a Generically Parameterized Lake eutrophication model (GPLake) that links field-, lab- and model-based knowledge and can be used to make a first diagnosis of lake water quality. We derived GPLake from consumer-resource theory by the principle that lacustrine phytoplankton is typically limited by two resources: nutrients and light. These limitations are captured in two generic parameters that shape the nutrient to chlorophyll-a relations. Next, we parameterized GPLake, using knowledge from empirical, theoretical, and process-based approaches. GPLake generic parameters were found to scale in a comparable manner across data sources. Finally, we show that GPLake can be applied as a simple tool that provides lake managers with a first diagnosis of the limiting factor and lake water quality, using only the parameters for lake depth, residence time and current nutrient loading. With this first-order assessment, lake managers can easily assess measures such as reducing nutrient load, decreasing residence time or changing depth before spending money on field-, lab- or model- experiments to support lake management.

Success of lake restoration depends on spatial aspects of nutrient loading and hydrology.

Many aquatic ecosystems have deteriorated due to human activities and their restoration is often troublesome. It is proposed here that the restoration success of deteriorated lakes critically depends on hitherto largely neglected spatial heterogeneity in nutrient loading and hydrology. A modelling approach is used to study this hypothesis by considering four lake types with contrasting nutrient loading (point versus diffuse) and hydrology (seepage versus drainage). By comparing the longterm effect of common restoration measures (nutrient load reduction, lake flushing or biomanipulation) in these four lake types, we found that restoration through reduction of nutrient loading is effective in all cases. In contrast, biomanipulation only works in seepage lakes with diffuse nutrient inputs, while lake flushing will even be counterproductive in lakes with nutrient point sources. The main conclusion of the presented analysis is that a priori assessment of spatial heterogeneity caused by nutrient loading and hydrology is essential for successful restoration of lake ecosystems.