Biodiversity effects on plant stoichiometry

Abstract

In the course of the biodiversity-ecosystem functioning debate, the issue of multifunctionality of species communities has recently become a major focus. Elemental stoichiometry is related to a variety of processes reflecting multiple plant responses to the biotic and abiotic environment. It can thus be expected that the diversity of a plant assemblage alters community level plant tissue chemistry. We explored elemental stoichiometry in aboveground plant tissue (ratios of carbon, nitrogen, phosphorus, and potassium) and its relationship to plant diversity in a 5-year study in a large grassland biodiversity experiment (Jena Experiment). Species richness and functional group richness affected community stoichiometry, especially by increasing C:P and N:P ratios. The primacy of either species or functional group richness effects depended on the sequence of testing these terms, indicating that both aspects of richness were congruent and complementary to expected strong effects of legume presence and grass presence on plant chemical composition. Legumes and grasses had antagonistic effects on C:N (-27.7% in the presence of legumes, +32.7% in the presence of grasses). In addition to diversity effects on mean ratios, higher species richness consistently decreased the variance of chemical composition for all elemental ratios. The diversity effects on plant stoichiometry has several non-exclusive explanations: The reduction in variance can reflect a statistical averaging effect of species with different chemical composition or a optimization of nutrient uptake at high diversity, leading to converging ratios at high diversity. The shifts in mean ratios potentially reflect higher allocation to stem tissue as plants grew taller at higher richness. By showing a first link between plant diversity and stoichiometry in a multiyear experiment, our results indicate that losing plant species from grassland ecosystems will lead to less reliable chemical composition of forage for herbivorous consumers and belowground litter input.

Figure 1. C:N ratio versus plant species richness.

GAMLSS (generalized additive model for location scale and shape) model of the molar C:N ratio versus species richness (natural logarithm) of the years 2003–2007. Black line stands for the mean. For better illustration of the variance, percentiles of the standard deviation are given as grey lines. Sown div. = sown diversity, leg = legume.

Figure 2. C:P ratio versus plant species richness.

GAMLSS (generalized additive model for location scale and shape) model of the molar C:P ratio versus species richness of the years 2003–2007. Black line stands for the mean. For better illustration of the variance, percentiles of the standard deviation are given as grey lines. Sown div. = sown diversity, leg = legume.

Figure 3. P:K ratio versus plant species richness.

GAMLSS (generalized additive model for location scale and shape) model of the molar P:K ratio versus species richness of the years 2003–2007. Black line stands for the mean. For better illustration of the variance, percentiles of the standard deviation are given as grey lines. Sown div. = sown diversity, leg = legume.

Figure 4. Observed C:N versus predicted C:N ratios.

For every measured C:N ratio (2, 4, 8 and 16 species mixtures) the corresponding calculated C:N ratio is shown across years (2003–2006). The green line gives the fit of an orthogonal regression (intercept 1.03 (SD 0.423); estimated C:N 0.999 (SD 0.043). The blue line gives a linear regression (Intercept 8.1448 (SD 1.434); estimated C:N 0.756 (SD 0.046)). For comparison, identity is given by a black line.

Figure 5. Comparison of the coefficient of variance of observed C:N and predicted C:N ratios.

The Coefficient of Variation (CV) of measured (oCN) and calculated C:N (pCN) ratios is shown for different diversity levels (2, 4, 8, and 16 species mixtures) separated by years (2003–2006).

Figure 6. Multielemental stoichiometric distance (SDist) from the origin of the PCA versus sown diversity (log transformed).

Error bars are ±1 SD. Axis 1 reflects plant C concentration and opposingly P and K concentration, whereas Axis 2 reflects N alone. The distance from the origin of the PCA (0,0) was used as a measure of stoichiometric imbalance (see methods).