Ecological Archives E088-073-A3

Spencer R. Hall, Mathew A. Leibold, David A. Lytle, and V. H. Smith. 2007. Grazers, producer stoichiometry, and the light : nutrient hypothesis revisited. Ecology 88:1142–1152.

Appendix C. Depth and the light : nutrient hypothesis.

In this Appendix, we consider mixing depth as a major determinant of light supply to ecosystems. While this factor is not particularly germane to our pond survey and certainly not to the mesocosm experiment, it featured prominently in the original light:nutrient hypothesis study based on data from lakes (Sterner et al. 1997) and in highly relevant mesocosm experiments (Diehl et al. 2002, 2005). These latter experiments varied mixing depth in enclosures where abundance of crustacean grazers (at least) were greatly reduced. When we pooled all of Diehl et al.’s (2002, 2005) data, we found a positive relationship between light:total phosphorus supply (molar) and algal seston carbon:phosphorus ratio (molar; R2 = 0.76, P < 0.0001, N = 36; Fig. C1), as predicted by the light:nutrient hypothesis. This relationship emerged despite low levels of grazing by crustaceans and was driven by self-shading of algae over depth gradients (as also predicted by our model: Fig. C2.A).

However, this resource supply-seston stoichiometry relationship in low-grazing enclosures (Diehl et al.) differed from those derived from lakes (Sterner et al.) in two key ways. First, the slope of the resource-seston regression from Diehl et al.’s experiments (59.4; lower and upper 95% CIs are 48.7 and 70.4) is much more shallow than the slope derived from Sterner et al.’s (1997) large dataset in July (156) and August (256), and still less than that derived from their “small” dataset (71 – but the upper confidence interval on the Diehl slope almost includes this slope; Fig. C1). The model shows that the resource supply-producer stoichiometry relationship should indeed be less steep for ungrazed systems until nutrient supply becomes very high (i.e., over 150 mg P/m3, much higher than that supplied to the lakes considered by Sterner et al.’s and Diehl et al.’s studies). However, the intercept for data from the low-grazed mesocosms (113.4; 95% CIs 95.2, 130.4) was smaller than that for the July (132), August (170), and smaller (252) data sets of Sterner et al. (1997). This result contradicts behavior of the model, which all else being equal, would predict a higher, not lower intercept for ungrazed systems. Apparently, more must differ between these datasets – and ecosystems – than just grazing by crustaceans.

FigC1
 
   FIG. C1. Resource ratio:seston stoichiometry correlation among low-grazing enclosures of varying mixing depth (Diehl et al. 2002, 2005; data from all three experiments were pooled) and regression relationships derived from the original light:nutrient hypothesis study (Sterner et al. 1997). In that earlier study, the Sterner et al. derived three relationships: for a broad lake set in August, one for the same set in July (both on their Figure 2), and a smaller lake set (their Figure 3). Note that for consistency with Sterner et al. (1997), phosphorus units are molar and axes are arithmetic.

 

FigC2
 
   FIG. C2. Predictions from the stoichiometrically explicit food chain model in which incident light supply is high (L = 1500) but mixing depth varies widely, as for the lakes of Sterner et al. and the enclosures of Diehl et al. (2002, 2005). Here we show results from the model (A) without grazers and (B) with grazers. Curves connect a gradient of nutrient supply, from low (5 mg P/m3, right) to high (150 mg P/m3, left).

 

LITERATURE CITED

Diehl, S, S. A. Berger, R. Ptacnik, and A. Wild. 2002. Phytoplankton, light, and nutrients in a gradient of mixing depths: field experiments. Ecology 83:399–411.

Diehl, S., S. A. Berger, and R. Wöhrl. 2005. Flexible nutrient stoichiometry mediates environmental influences on phytoplankton and its abiotic resources. Ecology 86:2931–2945.

Sterner, R. W., J. J. Elser, E. J. Fee, S .J. Guilford, and T. H. Chrzanowski. 1997. The light:nutrient relation in lakes: the balance of energy and materials affects ecosystem structure and process. American Naturalist 150:663–684.



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