Next Article in Journal
Protecting Coastlines from Flooding in a Changing Climate: A Preliminary Experimental Study to Investigate a Sustainable Approach
Next Article in Special Issue
Urea Inputs Drive Picoplankton Blooms in Sarasota Bay, Florida, U.S.A.
Previous Article in Journal
Sea-Level Variability in the Gulf of Naples and the “Acqua Alta” Episodes in Ischia from Tide-Gauge Observations in the Period 2002–2019
Previous Article in Special Issue
Interannual and Seasonal Shift between Microcystis and Dolichospermum: A 7-Year Investigation in Lake Chaohu, China
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Exploring How Cyanobacterial Traits Affect Nutrient Loading Thresholds in Shallow Lakes: A Modelling Approach

1
Department of Aquatic Ecology, Netherlands Institute of Ecology (NIOO-KNAW), P.O. Box 50, 6700 AB Wageningen, The Netherlands
2
Department of Aquatic Ecology and Water Quality Management, Wageningen University & Research, P.O. Box 47, 6700 AA Wageningen, The Netherlands
3
PBL, Netherlands Environmental Assessment Agency, P.O. Box 30314, 2500 GH The Hague, The Netherlands
4
Institute of Marine Sciences, The University of North Carolina at Chapel Hill, Morehead City, NC 28557, USA
5
Water Systems and Global Change Group, Wageningen University & Research, P.O. Box 47, 6700 AA Wageningen, The Netherlands
*
Author to whom correspondence should be addressed.
Water 2020, 12(9), 2467; https://doi.org/10.3390/w12092467
Submission received: 10 July 2020 / Revised: 26 August 2020 / Accepted: 28 August 2020 / Published: 2 September 2020

Abstract

Globally, many shallow lakes have shifted from a clear macrophyte-dominated state to a turbid phytoplankton-dominated state due to eutrophication. Such shifts are often accompanied by toxic cyanobacterial blooms, with specialized traits including buoyancy regulation and nitrogen fixation. Previous work has focused on how these traits contribute to cyanobacterial competitiveness. Yet, little is known on how these traits affect the value of nutrient loading thresholds of shallow lakes. These thresholds are defined as the nutrient loading at which lakes shift water quality state. Here, we used a modelling approach to estimate the effects of traits on nutrient loading thresholds. We incorporated cyanobacterial traits in the process-based ecosystem model PCLake+, known for its ability to determine nutrient loading thresholds. Four scenarios were simulated, including cyanobacteria without traits, with buoyancy regulation, with nitrogen fixation, and with both traits. Nutrient loading thresholds were obtained under N-limited, P-limited, and colimited conditions. Results show that cyanobacterial traits can impede lake restoration actions aimed at removing cyanobacterial blooms via nutrient loading reduction. However, these traits hardly affect the nutrient loading thresholds for clear lakes experiencing eutrophication. Our results provide references for nutrient loading thresholds and draw attention to cyanobacterial traits during the remediation of eutrophic water bodies.
Keywords: harmful algal blooms; regime shift; alternative stable state; resilience; hysteresis; light limitation; nutrient limitation; critical nutrient loading harmful algal blooms; regime shift; alternative stable state; resilience; hysteresis; light limitation; nutrient limitation; critical nutrient loading

Share and Cite

MDPI and ACS Style

Chang, M.; Teurlincx, S.; Janse, J.H.; Paerl, H.W.; Mooij, W.M.; Janssen, A.B.G. Exploring How Cyanobacterial Traits Affect Nutrient Loading Thresholds in Shallow Lakes: A Modelling Approach. Water 2020, 12, 2467. https://doi.org/10.3390/w12092467

AMA Style

Chang M, Teurlincx S, Janse JH, Paerl HW, Mooij WM, Janssen ABG. Exploring How Cyanobacterial Traits Affect Nutrient Loading Thresholds in Shallow Lakes: A Modelling Approach. Water. 2020; 12(9):2467. https://doi.org/10.3390/w12092467

Chicago/Turabian Style

Chang, Manqi, Sven Teurlincx, Jan H. Janse, Hans W. Paerl, Wolf M. Mooij, and Annette B. G. Janssen. 2020. "Exploring How Cyanobacterial Traits Affect Nutrient Loading Thresholds in Shallow Lakes: A Modelling Approach" Water 12, no. 9: 2467. https://doi.org/10.3390/w12092467

APA Style

Chang, M., Teurlincx, S., Janse, J. H., Paerl, H. W., Mooij, W. M., & Janssen, A. B. G. (2020). Exploring How Cyanobacterial Traits Affect Nutrient Loading Thresholds in Shallow Lakes: A Modelling Approach. Water, 12(9), 2467. https://doi.org/10.3390/w12092467

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop