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Low investment in sexual reproduction threatens plants adapted to phosphorus limitation

Nature volume 505, pages 82–86 (2014)Cite this article

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Abstract

Plant species diversity in Eurasian wetlands and grasslands depends not only on productivity but also on the relative availability of nutrients, particularly of nitrogen and phosphorus1,2,3,4. Here we show that the impacts of nitrogen:phosphorus stoichiometry on plant species richness can be explained by selected plant life-history traits, notably by plant investments in growth versus reproduction. In 599 Eurasian sites with herbaceous vegetation we examined the relationship between the local nutrient conditions and community-mean life-history traits. We found that compared with plants in nitrogen-limited communities, plants in phosphorus-limited communities invest little in sexual reproduction (for example, less investment in seed, shorter flowering period, longer lifespan) and have conservative leaf economy traits (that is, a low specific leaf area and a high leaf dry-matter content). Endangered species were more frequent in phosphorus-limited ecosystems and they too invested little in sexual reproduction. The results provide new insight into how plant adaptations to nutrient conditions can drive the distribution of plant species in natural ecosystems and can account for the vulnerability of endangered species.

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Figure 1: Relationship between biodiversity indices of vascular plants and N:P ratio corrected for productivity effects.
Figure 2: Relationship between N:P ratios and community-mean trait values of herbaceous vascular plant species, after removing confounding effects of productivity.
Figure 3: Relationship between N:P ratios and community-mean values for C, S and R scores of CSR strategy after removing confounding effects of productivity.
Figure 4: Difference in trait values between endangered and non-endangered herbaceous vascular plant species.

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Acknowledgements

We would like to thank N. A. Soudzilovskaia for obtaining the Russian Red List of plant species, M. Soons, D. Ertsen and D. van der Goes for permission to use their vegetation records, T. Markus and M. Stoete for drawing figures and J. Burrough for editing the near-final draft. Y.F. was funded by the Utrecht Centre of Geosciences, and the research in the Rospuda river valley was financed by the Polish Ministry of Science and Higher Education Grant no. N304 010 31/0414.

Author information

Authors and Affiliations

  1. KWR Watercycle Research Institute, PO Box 1072, 3430 BB Nieuwegein, The Netherlands ,

    Yuki Fujita

  2. Plant Biology and Nature Management, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium ,

    Harry Olde Venterink

  3. Department of Ecological Science, VU University Amsterdam, de Boelelaan 1085, 1081 HV Amsterdam, The Netherlands,

    Peter M. van Bodegom

  4. Centre for Crop Systems Analysis, Wageningen University, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands ,

    Jacob C. Douma

  5. Faculty of Science, Utrecht University, Princetonplein 5, 3584 CC Utrecht, The Netherlands ,

    Gerrit W. Heil

  6. Institute of Landscape Ecology, Faculty of Geosciences, University of Münster, Robert-Koch-Strasse 28, 48149 Münster, Germany ,

    Norbert Hölzel

  7. Department of Plant Ecology and Environmental Conservation, Institute of Botany, University of Warsaw, Al. Ujazdowskie 4, Warsaw, Poland,

    Ewa Jabłońska, Wiktor Kotowski & Paweł Pawlikowski

  8. Warsaw University of Life Sciences, Faculty of Civil and Environmental Engineering, 02-722 Warsaw, Nowoursynowska 166, Poland ,

    Tomasz Okruszko

  9. Biometris, Wageningen University, PO Box 100, 6700 AC Wageningen, The Netherlands ,

    Peter C. de Ruiter

  10. Environmental Sciences, Copernicus Institute of Sustainable Development, Faculty of Geosciences, Utrecht University, PO Box 80115, 3508 TC Utrecht, The Netherlands ,

    Martin J. Wassen

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  1. Yuki Fujita
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Contributions

Y.F., H.O.V., N.H., E.J., W.K., P.P., T.O. and M.J.W. collected data; Y.F., H.O.V., P.M.v.B., J.C.D. and M.J.W analysed data; Y.F., H.O.V., P.M.v.B., P.C.d.R. and M.J.W. wrote the manuscript; J.C.D., G.W.H., N.H., E.J., W.K., P.P. and T.O. commented on the manuscript; P.C.d.R., G.W.H. and M.J.W. were project leaders.

Corresponding author

Correspondence to Martin J. Wassen.

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Extended data figures and tables

Extended Data Figure 1 Data analysis approach.

a, b, Schematic proposed relationships between site productivity (that is, aboveground biomass of vascular plants; X2), N:P ratio in aboveground plant biomass (X1), and species diversity (a; X3) or community-mean traits (b; X4). Solid arrows are relationships in which the explanatory variable is constrained by the response variable (direct causality); dashed arrows are relationships in which upper bound of the explanatory variable is constrained by the response variable (limitation). Arrow a represents the pattern predicted by the growth rate hypothesis (see Supplementary Discussion 1 for details). The effect of N:P ratio on species diversity (arrow b) was tested by quantile regression analysis (thus treating arrow c as another limiting factor) with the residual values of X1 versus X2 as an explanatory variable (thus removing the effect illustrated by arrow a). The effect of N:P ratio on a community-mean trait (arrow d) was tested by comparing the residual values of X1 versus X2 (thus removing the effect illustrated by arrow a) with the residual values of X4 versus X2 (thus removing the effect illustrated by arrow e), using concepts of path analysis.

Extended Data Figure 2 Ninety-five per cent confidence intervals of the quantile regression coefficients.

a–c, Estimates (dots) and 95% confidence intervals (bars) of quadratic and linear coefficients (b2 and b1, respectively) of quantile regression models are shown for the number of vascular plant species (a), the number of endangered species (b), and the percentage of endangered species (c) regressed by N:P ratio corrected for productivity effects. The fitted models were (y1): ln(y1)  = b0 + b1x + b2x2 for number of species; (y2): ln(y2 + 1) = b0 + b1x + b2x2for number of endangered species; and (y3 = 100*y2/y1): ln((y2 + 0.5)/(y1 − y2 + 0.5)) = b0 + b1x for percentage of endangered species, where x is the residuals of plant N:P ratio regressed by productivity. Models were examined for 50% (τ = 0.50) to 95% (τ = 0.95) quantiles. See Fig. 1 for the shape of the quantile regression models for τ = 0.50, 0.75, 0.90, 0.95.

Extended Data Figure 3 Effects of habitat types on relationships between residual N:P ratio and biodiversity indices.

Relationships between N:P ratio corrected for productivity effects and the number of endangered species (a) and percentage of endangered species (b) are shown for different habitat types (left, 187 fens; middle, 56 bogs; and right, 296 other habitat types). Linear, rather than quadratic, quantile regression models were applied because for most quantiles the quadratic coefficients did not differ significantly from zero. τth linear quantile regression models (τ = 0.50, 0.75, 0.90, 0.95) are shown only when the 95% confidence intervals of the linear coefficients of the regression models were above or below zero for the majority of the quantiles. Number and percentage of endangered species increased concomitantly with increasing N:P ratio (corrected for productivity) even in plots that are not fens and bogs, indicating that our findings on the relationship between N:P ratio and endangered species were not an artefact resulting from the stratified sampling of habitat types.

Extended Data Figure 4 Relationships between community-mean trait values and plant N:P ratio.

a–r, The tested traits are canopy height (a, number of sites (n) = 530), leaf mass (b, n = 525), specific leaf area (c, n = 529), leaf dry-matter content (d, n = 525), seed mass (e, n = 533), seed number per shoot (f, n = 524), seed investment (g, n = 523), starting month of flowering (h, n = 528), flowering period (i, n = 528), lateral spread (j, n = 526), reproduction by seeds (k, n = 528), vegetative reproduction (l, n = 528), life span (m, n = 531), plant architecture (n, n = 533), N fixation (o, n = 502), C score (p, n = 528), S score (q, n = 528) and R score (r, n = 528). See Extended Data Table 1 for abbreviations and units of the traits. Canopy height, leaf mass, specific leaf area, seed mass, number of seeds, seed investment, and flowering period were log-transformed before the calculation of community-mean values. For binary traits, plot mean values were shown as a fraction of species with 1s over total species (that is, sum of 1s and 0s) to allow graphical presentation. Standardized regression coefficients (β) of community-mean trait regressed by N:P ratio using GLM and their two-tailed p-values (***P < 0.001, **P < 0.01, *P < 0.05) are shown.

Extended Data Table 1 List of functional traits of herbaceous vascular plant species.
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Supplementary information

Supplementary Information

This file contains Supplementary Discussions 1-5. Discussion 1 justifies the use of plant N:P ratio as a proxy for N:P stoichiometry of a site. We summarize the regulation mechanisms of plant N:P ratio and explain how our analysis took into account the confounding effects of productivity on plant N:P ratio. Discussion 2 shows the results of a Principal Component Analysis of plant functional traits. The relationships between community-mean PCA axis scores and N:P ratio are shown, as well as the difference between the PCA axis scores of endangered and non-endangered species. In discussion 3 we discuss the potential consequences of the different plot sizes in our dataset on the observed pattern of species diversity. Furthermore, we explain how we tested if the observed relationship between P limitation and endangered species holds when we use a subset of data from the most common plot size (10 m2). Discussion 4 tests if the relationship between seed investment and N:P ratio still holds after correcting seed investment for plant size and Finally in Discussion 5 we summarize the existing knowledge about environmental factors potentially related to P limitation. Furthermore, we examine the potential confounding effects of several environmental factors on the relationship between P limitation and richness of endangered species. (PDF 583 kb)

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Fujita, Y., Venterink, H., van Bodegom, P. et al. Low investment in sexual reproduction threatens plants adapted to phosphorus limitation. Nature 505, 82–86 (2014). https://doi.org/10.1038/nature12733

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