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Community rescue in experimental phytoplankton communities facing severe herbicide pollution

Nature Ecology & Evolution volume 4, pages 578–588 (2020)Cite this article

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Abstract

Community rescue occurs when ecological or evolutionary processes restore positive growth in a highly stressful environment that was lethal to the community in its ancestral form, thus averting biomass collapse in a deteriorating environment. Laboratory evidence suggests that community rescue is most likely in high-biomass communities that have previously experienced moderate doses of sublethal stress. We assessed this result under more natural conditions, in a mesocosm experiment with phytoplankton communities exposed to the ubiquitous herbicide glyphosate. We tested whether community biomass and prior herbicide exposure would facilitate community rescue after severe contamination. We found that prior exposure to glyphosate was a very strong predictor of the rescue outcome, while high community biomass was not. Furthermore, although glyphosate had negative effects on diversity, it did not influence community composition significantly, suggesting a modest role for genus sorting in this rescue process. Our results expand the scope of community rescue theory to complex ecosystems and confirm that prior stress exposure is a key predictor of rescue.

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Fig. 1: Experimental site, design and timeline.
Fig. 2: Phytoplankton biomass dynamics during the experiment.
Fig. 3: Effect of glyphosate on phytoplankton biodiversity.
Fig. 4: Effect of glyphosate on phytoplankton community composition.
Fig. 5: Predictors of final phytoplankton biomass.

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Data availability

The data necessary to reproduce figures and results in this study are publicly archived in Figshare: https://doi.org/10.6084/m9.figshare.11717361.v2.

Code availability

The R code necessary to reproduce figures and results in this study is available on GitHub: https://github.com/VFugere/LEAP2016_NEE.

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Acknowledgements

The Canadian Foundation for Innovation and the Liber Ero Chair in Biodiversity Conservation provided funding to A.G. to construct and operate the LEAP mesocosm facility. We acknowledge support and operating funds from the Natural Sciences and Engineering Research Council of Canada, the Fonds de Recherche du Québec—Nature et Technologies, the Canada Research Chair Program (R.D.H.B., A.G. and B.J.S.), the Quebec Centre for Biodiversity Science and the Groupe de Recherche Interuniversitaire en Limnologie et environnements aquatiques. We thank D. Maneli, C. Normandin, A. Arkilanian and T. Jagadeesh for assistance in the field, K. Velghe for nutrient analyses, P. Carrier-Corbeil and M. Rautio for phytoplankton identification and M. A. P. Castro for developing the LC–MS method for glyphosate measurements and for conducting chemical analyses.

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Authors and Affiliations

  1. Department of Biology, McGill University, Montreal, Québec, Canada

    Vincent Fugère, Marie-Pier Hébert, Charles C. Y. Xu, Rowan D. H. Barrett, Graham Bell, Gregor F. Fussmann & Andrew Gonzalez

  2. Department of Biological Sciences, University of Québec at Montréal, Montreal, Québec, Canada

    Vincent Fugère, Marie-Pier Hébert & Beatrix E. Beisner

  3. Département des Sciences Biologiques, Université de Montréal, Montreal, Québec, Canada

    Naíla Barbosa da Costa & B. Jesse Shapiro

  4. Redpath Museum, McGill University, Montreal, Québec, Canada

    Charles C. Y. Xu & Rowan D. H. Barrett

  5. Department of Chemical Engineering, McGill University, Montreal, Québec, Canada

    Viviane Yargeau

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Contributions

V.F., M.-P.H., R.D.H.B., B.E.B., G.B., G.F.F., B.J.S. and A.G. designed the study. V.F., M.-P.H. and N.B.C. collected the data. C.C.Y.X. and V.Y. contributed to the development of laboratory methods. B.E.B. provided a phytoplankton trait database for biovolume estimation. V.F. analysed data, made the figures and drafted the manuscript. All authors contributed significantly to data interpretation and commented on manuscript drafts.

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Correspondence to Vincent Fugère or Andrew Gonzalez.

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Extended data

Extended Data Fig. 1 Glyphosate and nutrient concentrations.

Time series of glyphosate concentration (a), total nitrogen (TN; b), and total phosphorus (TP; c) during the experiment. Lines are colour-coded by glyphosate treatment while symbols indicate nutrient treatment (a small offset on x axis values was introduced to better distinguish low and high nutrient ponds). In (a), low glyphosate concentrations in some control ponds in early Phase I are most likely the product of field contamination.

Extended Data Fig. 2 Other physicochemical parameters.

Time series of water depth (a), temperature (b), specific conductance (SPC; c), dissolved oxygen (DO; d), and pH (e) during the experiment. Lines are colour-coded by glyphosate treatment while symbols indicate nutrient treatment, as in Extended Data 1. (a,b) Depth and temperature varied over time but not across mesocosms. (c) Mean specific conductance increased slightly over Phase I (from 91 to 116 µS/cm), indicative of solute accumulation in the mesocosms due to evaporation. (d) Dissolved oxygen concentration tracked changes in phytoplankton biomass and was negatively affected by the first glyphosate pulse in the ponds exposed to the highest dose. (e) pH was mostly stable over time, although the highest glyphosate doses temporarily lowered pH by < 1 unit. In Phase II, biomass collapse in most communities decreased dissolved oxygen concentration (d), while specific conductance and pH respectively increased and decreased in all ponds that received the lethal dose irrespective of the response of their phytoplankton community (c,e).

Extended Data Fig. 3 Drivers of Phase I biomass dynamics.

Regression tree model of phytoplankton biomass over the course of Phase I as a function of date, nutrient treatment, and glyphosate and imidacloprid concentrations. Boxplots show the distribution of log-transformed chlorophyll a values in each group. Results (p value) of permutation tests of a correlation between the response and significant predictors are indicated. The tree demonstrates that at dates < 15 days, biomass is negatively affected only in ponds receiving more than 3 mg/L of glyphosate, while after day 15, biomass increases with glyphosate treatment but only in ponds receiving doses > 4 mg/L. This regression tree also shows that the positive effect of the nutrient treatment on biomass is only significant in low-glyphosate ponds, and it confirms that imidacloprid had no discernible effect on phytoplankton biomass.

Extended Data Fig. 4 Phosphorus data.

Relationship between total phosphorus (TP) and soluble reactive phosphorus (SRP) in 16 ponds on day 35 of the experiment, shortly after the second glyphosate dose was applied. Symbols indicate nutrient treatment while colours indicate glyphosate treatment. Note that ponds receiving the highest glyphosate dose also show the highest concentration of SRP. However, given that SRP was measured immediately after a glyphosate application but several weeks after the onset of the nutrient treatment, and given that SRP is often assimilated very quickly by phytoplankton, these measurements likely under-estimate the effect of the nutrient treatment on SRP. ppb = parts per billion (µg/L).

Extended Data Fig. 5 Final biomass vs. final glyphosate concentration.

Phytoplankton biomass at the end of Phase II as a function of Phase II glyphosate concentration. Although all ponds had a target in-pond concentration of 40 mg/L for the lethal dose in Phase II, residual glyphosate from past exposure, and/or potential error associated with glyphosate measurements for some ponds, led to unintended variance in measured concentrations at the beginning of Phase II. The effect of glyphosate concentration on phytoplankton biomass (log 1+x transformed) was statistically significant in a GAM (p = 0.007). However, the modelled relationship was positive (thus excluding the possibility that high-biomass ponds received less glyphosate in Phase II), driven by the high biomass of high-glyphosate ponds, and failed to capture the response of the two high-nutrient ponds that received the highest glyphosate dose in Phase I. Symbols indicate nutrient and glyphosate treatment as in Extended Data 4. chl. = chlorophyll.

Extended Data Fig. 6 Final biomass vs. zooplankton density.

Phytoplankton biomass at the end of Phase II as a function of crustacean zooplankton density at the end of Phase II. Symbol shape indicates nutrient treatment while symbol colour indicates Phase I glyphosate treatment, following the same nomenclature as all other figures. Note that the GAM testing for an effect of zooplankton density (log 1+x transformed) on phytoplankton biomass (log transformed) described in the main text (Fig. 5b) excluded the two control ponds (black symbols in this figure), as for all other predictor variables–hence the low explanatory power of the zooplankton GAM in Fig. 5b.

Extended Data Fig. 7 Correspondence between biomass and biovolume.

Relationship between community biovolume and biomass measured as chlorophyll a concentration. Each symbol represents a pond for which biovolume and biomass data were averaged across time points. The line and polygon indicate fitted values with confidence intervals from a GAM with biomass as the response and biovolume as the predictor. Biovolume was a significant predictor of biomass (p = 0.0004), and the adjusted R2 of this GAM was 0.54. The Pearson correlation coefficient between the two variables was 0.75 for the time-averaged data and 0.56 for the raw (unaveraged) data considering all pond by sampling occasion combinations as independent data points.

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Fugère, V., Hébert, MP., da Costa, N.B. et al. Community rescue in experimental phytoplankton communities facing severe herbicide pollution. Nat Ecol Evol 4, 578–588 (2020). https://doi.org/10.1038/s41559-020-1134-5

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