@article { ISI:000424187200035,
	title = {A probabilistic method to enhance understanding of nutrient limitation dynamics of phytoplankton},
	journal = {ECOLOGICAL MODELLING},
	volume = {368},
	year = {2018},
	month = {JAN 24},
	pages = {404-410},
	abstract = {Determination of the limiting nutrient of phytoplankton is critical to the lake eutrophication management. The average value of total nitrogen/total phosphorus (TN/TP) ratio is widely used to determine the limiting nutrient; while it suffers from the risk of the incorrect description of data and neglecting dynamics of the nutrient limitation. A probabilistic method was thereby proposed in this study to explore dynamics of nutrient limitation, including (a) indicator definition as the probability of TN/TP ratio failing in Redfield ratio line (PFR), indicating the possibility of TN limitation, to improve a probabilistic measure for the nutrient limitation; (b) Bayesian ANOVA analysis for posterior distributions of different treatments; and (c) dynamics determination as PFRs to show dynamics of nutrient limitation. Lake Xingyun in Southwestern China was taken as a case to explore the interannual and seasonal dynamics of the nutrient limitation. According to modeling results, we deducted that (a) for the interannual dynamics, the limiting nutrient shifted from TP to TN; and (b) for the seasonal dynamics, TN and TP were co-limiting. Deductions were further confirmed by the observed data. With the proposed probabilistic method, the co-limitation of TN and TP was identified for the seasonal dynamics; while using the average ratio solely denied the possibility of co-limitation. The current study also revealed that, due to neglecting the interannual and seasonal dynamics of nutrient limitation, the average ratio might mislead the eutrophication management strategy by recommending reducing TN and TP concentration together. The proposed probabilistic method demonstrated that TN was the limiting nutrient during the growing season of the phytoplankton in recent years and actions should focus on the TN concentration reduction. (C) 2017 Elsevier B.V. All rights reserved.},
	issn = {0304-3800},
	doi = {10.1016/j.ecolmodel.2017.11.004},
	author = {Liang, Zhongyao and Wu, Sifeng and Chen, Huili and Yu, Yanhong and Yong Liu}
}
