Abstract

Ongoing eutrophication frequently causes toxic phytoplankton blooms. This induces huge worldwide challenges for drinking water quality, food security and public health. Of crucial importance in avoiding and reducing blooms is to determine the maximum nutrient load ecosystems can absorb, while remaining in a good ecological state. These so called critical nutrient loads for lakes depend on the shape of the load-response curve. Due to spatial variation within lakes, load-response curves and therefore critical nutrient loads could vary throughout the lake. In this study we determine spatial patterns in critical nutrient loads for Lake Taihu (China) with a novel modelling approach called Spatial Ecosystem Bifurcation Analysis (SEBA). SEBA evaluates the impact of the lake's total external nutrient load on the local lake dynamics, resulting in a map of critical nutrient loads for different locations throughout the lake. Our analysis shows that the largest part of Lake Taihu follows a nonlinear load-response curve without hysteresis. The corresponding critical nutrient loads vary within the lake and depend on management goals, i.e. the maximum allowable chlorophyll concentration. According to our model, total nutrient loads need to be more than halved to reach chlorophyll-a concentrations of 30–40 μg L−1 in most sections of the lake. To prevent phytoplankton blooms with 20 μg L−1 chlorophyll-a throughout Lake Taihu, both phosphorus and nitrogen loads need a nearly 90% reduction. We conclude that our approach is of great value to determine critical nutrient loads of lake ecosystems such as Taihu and likely of spatially heterogeneous ecosystems in general.

Highlights

  • Extensive eutrophication threatens numerous lakes worldwide, leading to major challenges for drinking water supply, food security and public health (Brooks et al, 2016)

  • To determine the different load-response curves and the corresponding critical nutrient loads for different locations throughout Lake Taihu we developed Spatial Ecosystem Bifurcation Analysis (SEBA) using model simulations

  • We found that the indicator for linearity, R2adj, keeps largely below 0.4, suggesting that largest parts of Lake Taihu react nonlinearly to eutrophication and oligotrophication (Fig. 5, histogram and load-response curves for location 3 and 4)

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Summary

Introduction

Extensive eutrophication threatens numerous lakes worldwide, leading to major challenges for drinking water supply, food security and public health (Brooks et al, 2016). Water quality managers look for successful and efficient measures In this process, they need to carefully walk on the thin line between the desired water quality and the available financial resources (Groffman et al, 2006). Success of management actions depends on the identification of ecological thresholds (Kelly et al, 2015). These thresholds set limits to sustainable use of resources within the safe operating space (Rockstro€m et al, 2009) and exceedance leads to undesired ecological consequences such as toxic phytoplankton blooms (Groffman et al, 2006). A common threshold used in limnology is the concept of critical nutrient loads

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