Implications for biodiversity-ecosystem functioning relationships

Our study suggests that the presence of deep-rooting species is important for increased biomass production in diverse communities. This is consistent with previous studies showing positive effects of deep-rooting legumes (Mueller et al., 2013, Hernandez and Picon-Cochard, 2016), and deep-rooting forbs (Reich et al., 2004, Skinner et

al., 2004) on biodiversity effects. In our study, on average forbs rooted deeper than

grasses and showed greater performance in mixtures (see chapter 3). However, we also found that within these two groups, there is considerable variation in rooting depth and performance in mixtures. This shows that investigating the effects of trait differences at the species level can provide more insights than focusing on functional groups. This is in line with Mueller et al. (2013), who concluded that the actual rooting

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Does the root distribution of neighbours affect performance of individual plants? depth of the community better explained increased community biomass production in mixtures than the presence of deep-rooting legumes. Similarly, Oram et al. (2018) found a positive relationship between rooting depth and biodiversity effects, while the two main functional groups (grasses and forbs) did not differ in rooting depth. More importantly, our study shows that overyielding of deep-rooting species predominantly occurs in the presence of shallow neighbours. Since this benefit for deep rooting did not lead to a decline of the shallow species, this will probably lead to positive effects on biomass production at the community level. A few studies at the community level have tried to link differences in rooting depth among species (measured as functional diversity) to community biomass or complementarity effects, but found no relationships (Roscher et al., 2012, Barkaoui et al., 2016, Wagg et al., 2017a, Oram et al., 2018, chapter 2 and 3). An important reason for the discrepancy between these findings and our results may be the difference in resolution between the studies. At the level of communities, effects on individual plants and species in local neighbourhoods are averaged, potentially concealing differential responses within and among species. By investigating the effects of rooting depth on individual plants in local neighbourhoods, i.e. surrounding neighbouring plants, the spatial resolution was increased. Assuming individual plants mainly interact with directly surrounding plants, then species or functional trait composition of the direct neighbours will explain shifts in performance much better than species richness or composition at the plot level (Fichtner et al., 2017). Further, the fact that we found a significant relationship may also be due to the large number of data points. We were able to include almost 1700 individuals in a range of local neighbourhoods, while biodiversity studies focusing at the community level are typically restricted to a limited number of plots (e.g. 82 plots in Jena main biodiversity experiment (Roscher

et al., 2012), 138 plots in the Jena Trait Based Experiment (Oram et al., 2018), and

152 plots in Mueller et al., 2013), and a single species composition (measurement) per plot. Thus, research at the species level, using local neighbourhoods, i.e. traits of directly surrounding plants, instead of plot averages, can enhance our understanding of the importance of trait differences between species for ecosystem functioning at the community level.

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4.5.4 Conclusions

Our results show that both the rooting depth of a species and rooting depth of the neighbours can explain aboveground performance of plant species in grassland communities. Particularly deep-rooting individuals surrounded by shallow-rooting neighbours showed increased performance in mixtures. Shallow species showed no response to neighbour rooting depth and did not show increased performance in mixtures. These results suggest that spatial resource partitioning via rooting depth contributes – at least partially – to the positive effects of plant species richness on plant productivity. We see two directions for future research: 1) strengthening the link between rooting depth and resource uptake, for example by incorporating other root traits, and 2) establishing relationships between trait differences between species and performance in local neighbourhoods across resource gradients. Combining these may further enhance our understanding of the mechanisms underlying the positive effects of biodiversity on ecosystem functioning.

4.6 Acknowledgements

We would like to thank everyone that helped with planting, harvesting and collecting the data. Special thanks to Jan van Walsem, Frans Moller and Jan-Willem van der Paauw, Natalie Oram and Anne Jansma for their help in the common garden experi- ment. L.M.B. was supported by the Research School for Socio-Economic and Natural Sciences of the Environment (SENSE), the Netherlands. L.M. was supported by a NWO VIDI grant 864.14.006.

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Does the root distribution of neighbours affect performance of individual plants?

Figure S4.1 Species planting position schemes of the monocultures, 4-species mixtures and 16-species mixtures. Species were randomly assigned to a planting position (a letter) for each different species composition. As an example, the green square represents a measured individual that we harvested, of which its own rooting depth (DRF_own) was estimated using the rooting depth (deep root fraction) found in monocultures. Neighbour rooting depth (DRF_neighb) was calculated based on the heterospe- cific neighbours that directly surrounded the measured individual (shown in orange), excluding the conspecific neighbours (shown in yellow). We only measured individuals that were planted in the inner 6 x 6 rows.

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P. pratense P. vulgaris S. officinalis T. flavescens

G. mollugo L. autumnalis L. hispidus L. vulgare

B. media C. jacea F. pratensis F. rubra

A. millefolium A. stolonifera A. odoratum A. elatius

1 4 16 1 4 16 1 4 16 1 4 16 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100

Planted species richness

% sur viv al 2014 2015 2016

Figure S4.2 Average survival of the selected individuals per species in monocultures, 4-species mixtu- res and 16-species mixtures in three subsequent years (2014 - 2016).

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Does the root distribution of neighbours affect performance of individual plants?

Table S4.1 Competing models explaining individual performance in mixtures (dY), using the esti- mated rooting depth of the individuals (DRF_own), average rooting depth of the neighbouring plants (DRF_neigh), species richness (sr), year (yr) and all their interactions as explaining factors. The models with weight sum up to 0.96 are shown. The model with only DRF_own and the intercept-only model are shown as well for comparison. The last row shows the relative importance of the variables (w + (j)) (Burnham, 2002). The best model (model 1) is further used for statistical analyses.

4.8 Supplementary tables

Model Intercept DRF_own DRF_neigh sr year DRF_own

*DRF_neigh DRF*sr own DRF*yearown DRF*sr neigh

1 -0.31 2.62 0.43 + + -6.78 + + 2 -0.30 2.61 0.41 + + -6.76 + + + 3 -0.27 2.62 0.29 + + -6.78 + + 4 -0.27 2.49 0.29 + + -6.20 + + + 5 -0.27 2.62 0.27 + + -6.76 + + + 6 0.03 1.13 -1.09 + + + + 7 -0.24 2.50 0.14 + + -6.21 + + + 8 -0.32 2.70 0.43 + + -6.79 + 9 -0.24 2.46 0.12 + + -6.02 + + 10 0.03 1.13 -1.12 + +   + + + 11 -0.22 2.42 0.04 + + -5.85 + + + 12 -0.32 1.54       13 0.03       w+(j)   1.00 1.00 1.00 1.00 0.95 0.98 1.00 0.34      

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*year sr *year DRF*DRFown_neigh *sr DRF_own *DRF_neigh *year DRF_own *sr *year DRF_neigh *sr *year DRF_own *DRF_neigh *sr *year df ΔAIC weight + +   18 0.000 0.493 + +   19 2.008 0.181 + + +   20 3.327 0.093 + + +   20 3.743 0.076 + + +   21 5.337 0.034 + +   17 5.838 0.027 + + + +   22 7.076 0.014 +   15 7.220 0.013 + + + +   22 7.226 0.013   +     +     18 7.774 0.010 + + + + + + + 28 17.955 0.000       6 121.329 0.000       5 271.623 0.000 0.19 1.00 0.10 0.02 0.97 0.01 0.00      

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