Probabilistic Estimate of a Threshold for Eutrophication

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Abstract

Regime shifts, or massive changes in ecosystems, are often associated with thresholds in drivers such as climate, land-use change, nutrient fluxes, or other factors. A frequently studied example is eutrophication, which is a serious environmental problem of lakes and reservoirs associated with phosphorus (P) enrichment above a threshold. We estimated probability distributions of thresholds for eutrophication of Lake Mendota, Wisconsin, USA using 30 years of annual P budgets. Although thresholds were likely to influence eutrophication of the lake (probability 96.6%), the probability distributions of thresholds spanned a wide range of P loading rates. Management recommendations are consistent with simpler models that recommend P load targets near or below the lowest P loads observed in the past 30 years. If loads increase, there is considerable risk of crossing a threshold to sustained eutrophication with high in-lake P concentrations and poor water quality. On the other hand, if loads decrease there is a chance of crossing a mitigation threshold, causing substantial reductions in P concentrations and improvements in water quality. Consideration of these risks will increase estimates of the net economic benefits of lower P loading. Our analysis illustrates a process for estimating probability distributions for thresholds of ecosystem regime shifts. Even though threshold probability distributions may be wide with thick tails, they provide crucial information about potential consequences of alternative policy choices.

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