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Root traits explain plant species distributions along climatic gradients yet challenge the nature of ecological trade-offs


Ecological theory is built on trade-offs, where trait differences among species evolved as adaptations to different environments. Trade-offs are often assumed to be bidirectional, where opposite ends of a gradient in trait values confer advantages in different environments. However, unidirectional benefits could be widespread if extreme trait values confer advantages at one end of an environmental gradient, whereas a wide range of trait values are equally beneficial at the other end. Here, we show that root traits explain species occurrences along broad gradients of temperature and water availability, but model predictions only resembled trade-offs in two out of 24 models. Forest species with low specific root length and high root tissue density (RTD) were more likely to occur in warm climates but species with high specific root length and low RTD were more likely to occur in cold climates. Unidirectional benefits were more prevalent than trade-offs: for example, species with large-diameter roots and high RTD were more commonly associated with dry climates, but species with the opposite trait values were not associated with wet climates. Directional selection for traits consistently occurred in cold or dry climates, whereas a diversity of root trait values were equally viable in warm or wet climates. Explicit integration of unidirectional benefits into ecological theory is needed to advance our understanding of the consequences of trait variation on species responses to environmental change.

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Fig. 1: The ecological consequences of trait variation on species distributions along climatic gradients.
Fig. 2: Specific root length and root diameter are related to species occurrences along climatic gradients.
Fig. 3: RTD and root N are related to species occurrences along climatic gradients.

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We thank the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig for supporting the sRoot and sPlot working groups and the University of Wyoming Advanced Research Computing Center for technical support. sPlot was initiated by sDiv and funded by the German Research Foundation (FZT 118) and is now a platform of iDiv. The sRoot workshops and L.M. were also supported by NWO-Vidi grant 864.14.006. C.M.I. and the Fine-Root Ecology Database were supported by the Biological and Environmental Research program in the US Department of Energy’s Office of Science. J.B. was supported by Deutsche Forschungsgemeinschaft (DFG) project 432975993. N.R.G.-R. thanks the Dorothea Schlözer Postdoctoral Programme of the Georg-August-Universität.

Author information




A.W., L.M., H.B. and D.C.L. conceived of the idea for the project. All authors were involved with collecting datasets, developing the conceptual framework and interpreting the results. D.C.L., F.M.S. and H.B. performed the statistical analyses. D.C.L. wrote the first draft of the manuscript. All authors commented on and agreed with the final version of the manuscript.

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Correspondence to Daniel C. Laughlin.

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Peer review information Nature Ecology & Evolution thanks Benjamin Delory and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Geographic and climatic distribution of vegetation plots.

Distribution of vegetation plots (A) across the globe, and (B) in climate space represented by mean annual temperature (MAT) and mean annual precipitation (MAT) superimposed onto Whittaker biomes78. The legend for color codes of vegetation types (black=forest, gold=grassland, blue=wetland) can be seen in panels C and D. Note the heavy bias toward North America, Europe, and Asia. Plots are located in all major biomes except tropical rainforest, but the majority of plots are found in temperate grasslands, temperate forests and woodlands, and boreal forest biomes. Note that we do not use the Whittaker biomes in our classification of plots into forest, grassland, and wetlands but rather use the composition data to do so (see Methods). These three vegetation types span a broad range of climate space and it is common to find grassland plots in a forest biome and forest plots within a grassland biome. (C) Plots in climate space using the climate variables that were used in the models (minimum temperature of the coldest month, and the precipitation-to-potential evapotranspiration ratio). (D) Principal coordinates analysis (PCoA) of vegetation composition using Bray-Curtis distances. The first axis explains 12% of the variation and the second axis explains 5%. Plots are color-coded according to how they were classified (that is, forest, grassland, wetland) and we illustrate 80% confidence ellipses for each vegetation type. This plot illustrates a random sample of 15,461 plots because analysis of >100,000 observations with >600 species was not computationally feasible within the time limits imposed by high-performance computer clusters.

Extended Data Fig. 2 Species distributions along climatic gradients in relation to their specific root length (SRL) and root tissue density (RTD) in forests and grasslands combined.

The left-column illustrates the modelled distributions of species using quadratic polynomials in the random effects. The y-axis of modeled probabilities of occurrence were square root transformed to amplify distributions of less common species to make them more visible. The right-column illustrates the relationship between optimum climatic conditions and root functional traits for each species, where the dark line illustrates the fitted regression line and the dotted lines represent 95% confidence intervals. Trait values for each species are color-coded using two different color ramps for each trait where dark colors are low trait values and light colors are high trait values. Size of the species symbols is proportional to their occurrence in the dataset. See Supplementary Table 1 for numbers of species in each model.

Extended Data Fig. 3 The occurrences of species-level average trait values of specific root length and root tissue density along two climatic gradients.

Illustration of occurrences of specific root length and root tissue density along the gradients of minimum temperature in the coldest month and the precipitation-to-potential evapotranspiration ratio. The climate gradients are scaled to unit variance below and plotted in their native scale above. The traits are scaled to unit variance on the left and plotted in their native scale to the right.

Extended Data Fig. 4 The occurrences of species-level average trait values of root diameter and root nitrogen along two climatic gradients.

Illustration of occurrences of root diameter and root nitrogen along the gradients of minimum temperature in the coldest month and the precipitation-to-potential evapotranspiration ratio. The climate gradients are scaled to unit variance below and plotted in their native scale above. The traits are scaled to unit variance on the left and plotted in their native scale to the right.

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Laughlin, D.C., Mommer, L., Sabatini, F.M. et al. Root traits explain plant species distributions along climatic gradients yet challenge the nature of ecological trade-offs. Nat Ecol Evol (2021).

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