Graphs that don't exist: state factors and shade

Shade, drought, and nutrient scarcity are three resource stresses that constrain vegetation globally. Each of these are influenced by state factors as well as other more proximal controls on ecosystem function.

At least theoretically. We've actually never tested these ideas, which constrains our ability to explain and predict a lot about how ecosystems work.

Take shade. Plants produce leaves, which creates shade beneath them. Yet, the amount of shade in different stands varies tremendously. Theoretically, sites that are more limited by water should be able to produce less leaf area, leaving more light to the understory and removing a constraint on the growth of understory vegetation.

Despite decades of light measurements and hemispherical photographs of canopies, the data has never been synthesized to generate a global map of shade that can be analyzed in terms of determinants. Do dry ecosystems have a lower potential for producing shade than wet ecosystems? And how does that vary with temperature? Do forests in colder regions cast less shade, all other things equal?

Part of this echoes Peter Grubb's assertion that higher fertility sites should generate more shade and have more slow-growing shade-tolerant species, which still hasn't been tested directly as far as I can tell.

What holds for shade also holds for nutrient availability and water potentials. We just don't know the basic drivers of resource availability and hence don't know how global change factors like warming will affect the availability of the most limiting resources.

Drought vs. shade tolerance

The leaf economics spectrum is the modern incarnation of Grime's C-S axis. Without the overarching evolutionary strategies attached, it describes a broad set of correlations that cover species with leaves that have low activity rates, are built tough and live a long time, to those that have high activity rates, are built wimpy, and live a short time.

The evolutionary underpinning of the broad correlations--what ecological forces would select for the correlations--has remained opaque.

Ülo Niinemets has been publishing on this question for a few years. For example, in 2006, he and Valladares compiled rankings of shade and drought tolerance for woody species in the northern continents. The correlation was somewhat weak, but was negative. More importantly it showed that although there were species that had low shade and drought tolerances (x-axis), there were no species with high shade and drought tolerances.

In a follow-up paper, they examined the associations between stress tolerances and functional traits. They concluded that the traits associated with shade tolerance did not consistently have traits associated with stress-tolerance, while drought tolerant species did.

The evidence for drought tolerance being associated with traits that are low on the leaf economics spectrum, though, seemed a lot more mixed when examined individually. For example, across all species the pairwise correlation coefficient was just 0.18 (P <  0.001), which translates to an r2 of 0.04. Plus the relationship was negative for conifers (EC). LMA relationships were all positive and r = 0.3 overall (r2 = 0.09).

What you can see, though, is that most of the leaf economics spectrum are differences between broadleaf deciduous species and evergreen conifers. And these two groups do not differ primarily in terms of drought (or shade) tolerance. Hence, the trait relationships are pretty weak.

They ran a PCA of 4 main leaf economic traits (leaf longevity, %N, LMA, and photosynthetic rate). Overall and within each group, drought tolerant species ranked lower on the leaf economics spectrum. Overall r = 0.29 (P < 0.01).

I'm still working to rectify these results with what we've found for grasses. A few points are important here.

•Drought tolerance scores were rankings derived from observations, and do not necessarily represent physiological drought tolerance.

•The majority of the leaf economics spectrum for trees is associated with broad functional groups, which do not correspond to differences in shade or drought tolerance.

•Shade tolerance was not associated with the LES, mostly because of shade species having low LMA. But this is because shade tolerant species have thin leaves, not because they have low density (a different paper shows this). This also brings up the question whether LMA should be part of the LES [Answer: SLA (and LMA) should R.I.P.--leaf tissue density is much better.]

•If shade tolerance is not associated with the leaf economics spectrum, is drought tolerance? The glass is 10% full here at best.

•For grasses, we just don't see the same results. Drought tolerance is associated with high rates or gas exchange and no difference in leaf tissue density.

Research like this is going to be important for the interpretation of the leaf economic spectrum. Species high on the spectrum probably can be considered modern C species. But what about low? Is there one general stress-tolerant syndrome with variants that correspond to shade-, drought-, and nutrient-stress tolerance? Or are these largely independent of one another, but just never have the traits of high-resource species?

The endpoints definitely form a pyramid. The question is how tall is the pyramid? How different are high resource species from low-water species, compared to low-water to low-nutrient? We'll probably need more than 4 leaf traits to find this out.

Niinemets, U. and F. Valladares. 2006. Tolerance to shade, drought, and waterlogging of temperate Northern Hemisphere trees and shrubs. Ecological Monographs 76:521-547.

Hallik, L., U. Niinemets, and I. J. Wright. 2009. Are species shade and drought tolerance reflected in leaf-level structural and functional differentiation in Northern Hemisphere temperate woody flora? New Phytologist 184:257-274.

New review on shade tolerance

Another good review out. This time on shade tolerance. Valladares and Niinemets reviewed competing hypotheses underlying shade tolerance, focusing mainly on carbon gain and stress-tolerance hypotheses, as well as sections on acclimation to variation in light and ontogenetic changes. The authors do a good job of capturing the two major contrasting aspects of performance (carbon gain vs. loss) and it is important to incorporate ontogeny explicitly. Their figure demonstrating inverse relationships between drought and shade tolerance is an important one.

Comparing their work with RSWP, it is important to emphasize potential carbon losses that can come from disturbance as well as stress. Also, it seems like understanding of the ontogeny of shade tolerance is better served by beginning to understand how large plants can grow at a given light level, rather than comparing RGR’s at a given light level.

In all, a good, well-timed review.