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. 2018 Oct 5;13(10):e0205260.
doi: 10.1371/journal.pone.0205260. eCollection 2018.

Effects of climatically-modulated changes in solar radiation and wind speed on spring phytoplankton community dynamics in Lake Taihu, China

Jianming Deng  1 , Wei Zhang  2 , Boqiang Qin  1 , Yunlin Zhang  1 , Hans W Paerl  3   4 , Nico Salmaso  5
Affiliations

Effects of climatically-modulated changes in solar radiation and wind speed on spring phytoplankton community dynamics in Lake Taihu, China

Jianming Deng et al. PLoS One. .

Abstract

Many studies have focused on the interactive effects of temperature increases due to global warming and nutrient enrichment on phytoplankton communities. Recently, non-temperature effects of climate change (e.g., decreases in wind speed and increases in solar radiation) on large lakes have received increasing attention. To evaluate the relative contributions of both temperature and non-temperature effects on phytoplankton communities in a large eutrophic subtropical shallow lake, we analyzed long-term monitoring data from Lake Taihu, China from 1997 to 2016. Results showed that Lake Taihu's spring phytoplankton biovolume and composition changed dramatically over this time frame, with a change in dominant species. Stepwise multiple linear regression models indicated that spring phytoplankton biovolume was strongly influenced by total phosphorus (TP), light condition, wind speed and total nitrogen (TN) (radj2 = 0.8, p < 0.01). Partial redundancy analysis (pRDA) showed that light condition accounted for the greatest variation of phytoplankton community composition, followed by TP and wind speed, as well as the interactions between TP and wind speed. Our study points to the additional importance of non-temperature effects of climate change on phytoplankton community dynamics in Lake Taihu.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Weather stations and water quality sampling sites in Lake Taihu.
Weight factors were calculated based on the relative polygon size to the total area of Lake Taihu. Monthly sampling sites with red dots indicating locations included in the present study. The figure is for illustrative purposes only.
Fig 2
Fig 2. Long-term trends in water quality and meteorological variables Lake Taihu from 1997 to 2016.
The trends evaluated by GAMs were shown as blue solid lines. The 95% confidences were shown by blue shade. Adjusted r2 values were shown. The data were presented as mean ± standard error. * p < 0.05; ** p < 0.01.
Fig 3
Fig 3. Long-term variation of mean spring phytoplankton biovolume in Lake Taihu from 1997 to 2016.
The trends evaluated by GAMs were shown in blue solid line. The 95% confidences were shown by blue shade. The data were presented as mean ± standard error.
Fig 4
Fig 4. Ordination results.
(a) RDA ordination of phytoplankton samples from 1997 to 2016. (b) Environment variables (p < 0.05) and MFGs in the first two axes RDA.
Fig 5
Fig 5. Venn diagram representing the result of the pRDA analyses.
Amount of variation in phytoplankton groups biovolume explained by light condition, wind speed, TP and their interactions. Each area is proportional to the share of the inertia explained by the single factor or its interactions with other corresponding factors. Numbers correspond to the percentage of the explained variation associated with each variable type. Negative values are not shown.
See this image and copyright information in PMC

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References

    1. Barton AD, Irwin AJ, Finkel ZV, Stock CA. Anthropogenic climate change drives shift and shuffle in North Atlantic phytoplankton communities. Proceedings of the National Academy of Sciences. 2016; 113(11):2964–9. - PMC - PubMed
    1. Bopp L, Resplandy L, Orr JC, Doney SC, Dunne JP, Gehlen M, et al. Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models. Biogeosciences. 2013; 10:6225–45.
    1. Elliott JA. The seasonal sensitivity of cyanobacteria and other phytoplankton to changes in flushing rate and water temperature. Glob Change Biol. 2010; 16(2):864–76.
    1. Sommer U, Lengfellner K. Climate change and the timing, magnitude, and composition of the phytoplankton spring bloom. Glob Change Biol. 2008; 14(6):1199–208.
    1. O’Neil J, Davis T, Burford M, Gobler C. The rise of harmful cyanobacteria blooms: the potential roles of eutrophication and climate change. Harmful Algae. 2012; 14:313–34.

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