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Species multidimensional effects explain idiosyncratic responses of communities to environmental change

Nature Ecology & Evolution volume 4, pages 1036–1043 (2020)Cite this article

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Abstract

Environmental change can alter species’ abundances within communities consistently; for example, increasing all abundances by the same percentage, or more idiosyncratically. Here, we show how comparing effects of temperature on species grown in isolation and when grown together helps our understanding of how ecological communities more generally respond to environmental change. In particular, we find that the shape of the feasibility domain (the parameter space of carrying capacities compatible with positive species’ abundances) helps to explain the composition of experimental microbial communities under changing environmental conditions. First, we introduce a measure to quantify the asymmetry of a community’s feasibility domain using the column vectors of the corresponding interaction matrix. These column vectors describe the effects each species has on all other species in the community (hereafter referred to as species’ multidimensional effects). We show that as the asymmetry of the feasibility domain increases the relationship between species’ abundance when grown together and when grown in isolation weakens. We then show that microbial communities experiencing different temperature environments exhibit patterns consistent with this theory. Specifically, communities at warmer temperatures show relatively more asymmetry; thus, the idiosyncrasy of responses is higher compared with that in communities at cooler temperatures. These results suggest that while species’ interactions are typically defined at the pairwise level, multispecies dynamics can be better understood by focusing on the effects of these interactions at the community level.

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Fig. 1: Theory relating differences in species’ performances in isolation and species evenness when grown together.
Fig. 2: Theoretical results.
Fig. 3: Theoretical distribution of structural measures.
Fig. 4: Empirical results.
Fig. 5: Empirical distribution of structural measures across temperatures.

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Data availability

The experimental data used in this study are available as indicated in ref. 39.

Code availability

Codes for Figs. 2 and 3 are available at https://github.com/MITEcology/NEE_Tabi_et_al_2020.

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Acknowledgements

The University of Zurich Research Priority Programme on Global Change and Biodiversity supported this research. Furthermore, funding came from the Swiss National Science Foundation (grant 31003A_159498 to O.L.P.). Funding was also provided by the Mitsui Chair (S.S.). This is also publication ISEM-2020-075 of the Institut des Sciences de l’Evolution de Montpellier (E.A.F.). We thank Y. Choffat, P. Ganesanandamoorthy, A. Garnier, J. I. Griffiths, S. Greene, T. M. Massie, G. M. Palamara and M. Seymour for help with the data collection. We also thank M. AlAdwani, S. Cenci and C. Song for insightful discussions about this study.

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Authors and Affiliations

  1. Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland

    Andrea Tabi, Frank Pennekamp, Florian Altermatt, Roman Alther, Emanuel A. Fronhofer, Katherine Horgan, Elvira Mächler, Mikael Pontarp & Owen L. Petchey

  2. Department of Aquatic Ecology, Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland

    Florian Altermatt, Roman Alther, Emanuel A. Fronhofer & Elvira Mächler

  3. ISEM, Université de Montpellier, CNRS, IRD, EPHE, Montpellier, France

    Emanuel A. Fronhofer

  4. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Serguei Saavedra

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Contributions

A.T. and S.S. conceived of and wrote the study, and analysed and interpreted the data. O.L.P. took part in the reviewing and editing process. F.P., F.A., R.A., E.A.F., K.H., E.M., M.P. and O.L.P. contributed to the experiment from which data were used as stated in ref. 39.

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Correspondence to Andrea Tabi.

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Extended data

Extended Data Fig. 1 Example of fitting 2-species LV model across temperature.

Illustration using time series of interacting Colpidium (blue) and Dexiostoma (red) as an example. Each panel shows a different temperature-replicate combination. Dots are the observations and the corresponding lines indicate the prediction of the best fitting model. The mean absolute error (MAE), partial correlation (R) and the tuning parameter (β) of the best fit are also plotted in each graph.

Extended Data Fig. 2 The effect of connectance, niche overlap and asymmetry on the relationship between species evenness and relative performance in isolation in 10-species communities.

Panel (A) shows a strong interaction between asymmetry and connectance, that is high asymmetry and connectance leads to the weaker negative relationship (measured as the Spearman’s rank correlation) between species evenness and the relative performance in isolation. Connectance is measured as the fraction of non-zero coefficients and modeled following Ref. 34. Note that the value of asymmetry corresponds to the tuning parameter P used in the sampling of the interaction matrix (see Methods). In panel (B), we generated the interaction matrices based on a niche framework27, where all interaction coefficients are negative (competitive). Here, similarly to panel (A) high asymmetry and niche overlap lead to the weakest correlation.

Extended Data Fig. 3 The relationship between species evenness and temperature empirically measured in 2- and 3-species microbial communities.

Species evenness was measured as the median evenness of the time series for each community. There was no statistical relationship found between species evenness and temperature.

Extended Data Fig. 4 The relationship between average productivity and temperature empirically measured in 2- and 3-species microbial communities.

Average productivity was measured as the median of the time series of total biomass for each community. Average productivity declined with increasing temperature in 2- and 3-species communities as well.

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Tabi, A., Pennekamp, F., Altermatt, F. et al. Species multidimensional effects explain idiosyncratic responses of communities to environmental change. Nat Ecol Evol 4, 1036–1043 (2020). https://doi.org/10.1038/s41559-020-1206-6

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