Relationship between leaf tissue density (RhoL) and leaf dry matter content (DMC) across 42 Konza grassland species.
There has been some debate on how best to represent plant investment into leaves. Specific leaf area, the ratio of area to mass, is at best an imperfect measure. Plants with high SLA certainly produce a lot of leaf area for minimum investment. Yet, high SLA can come as a result of being thin or low density. And it seems that many of the ecological conditions associated with high SLA are really associated with low tissue density rather than thin leaves.
How to measure tissue density is one of the current debates. On the one hand, tissue density (mass per unit volume) can be derived by measuring the thickness of leaves in addition to SLA. Deriving leaf tissue density (LTD) from thickness measurements provide a direct covariate (thickness) and are relatively simple to do. Yet, for some leaves, measuring the average thickness can be problematic. On the other hand, an approximation of tissue density can be derived from the leaf dry matter content (LDMC). Leaves are weighed in a hydrated state and then again dry. The ratio of dry mass to wet mass is LDMC. There are a number of assumptions to equate this ratio to leaf tissue density, but it has been favored.
Across 40+ species at Konza, I measured LTD and LDMC. The two metrics correlated pretty well (r = ~0.8). Some species seemed to have higher LTD than one would expect based on LDMC. In species with a high proportion of veins, thickness is probably underestimated, since it is generally measured between major veins. The artemisiifolia I selected was deeply lobed and did not have much lamina relative to veins. Its LTD was probably too high. On the other hand, both Bothriochloa and Schizachyrium species had higher LTD than expected from LDMC, but this likely would not have been caused by underestimating thickness or area. Instead, these species likely have high silica concentrations that add more mass per unit volume than other species. This is something I still need to confirm.
As to whether LTD or LDMC does a better job of predicting abundance, they both were about the same. Using long-term abundance data, they both had equal predictive power on average.
Whether one metric is better than another is likely equivocal. It depends on the situations as both have their limitations. I’d probably use both for awhile until better consensus can be reached.
I’m not sure I’ll get around to publishing these data, so I thought I’d put so of the results up here.