Quantitative descriptions of leaf shape used as diagnostics are hard to come by. There are numerous qualitative descriptions (lyrate, cordate, acicular, etc.), and I think this fits within the example you give that "the laminar shape for this species is mainly ovate." But actual quantitative ranges as you mention (e.g., that the L:W ratio of Acer lies within a certain range) are much more difficult to come by. Also, there are ways of quantifying leaves using all the shape variance present in their outlines, and I describe some of these methods below. By using quantitative methods such as these, you can avoid the trap of a subjective criteria that arbitrarily distinguishes leaf morphs by a particular feature. Plus, you won't be biased by using a particular shape attribute, as you will be measuring the entirety of shape. Use of these various methods though depends on the species you are studying.
Oreotrephes I think is on track saying that, if possible, you should build your own diagnostic criteria for whatever system you are working in. You mentioned certain "ranges" that can diagnose a species ... this is a critical question. Measuring intra-genotype/individual variance in shape for your system is critical. Which leaf to measure for a species? ... i.e., shoot position, developmental age of the leaf, if working with compound leaves, the placement of the leaflet along the proximal distal axis of the leaf, what about heteroblasty (changes in leaf form at different nodes), leaves from lateral vs. main branches, environmental effects on leaves (e.g. sun vs. shade leaves)?
For tomato, I measure shape quantitatively using Elliptical Fourier Descriptors, which reduces the shape of an object to a series approximation and explains variance with a Principal Component Analysis. I use the resulting Principal Component values of leaves as a trait and explain shape quantitatively that way. A very useful program to perform Elliptical Fourier Descriptors is described in Iwata & Ukai 2002 and can be downloaded here. In Chitwood et al 2012, I describe how to perform shape analysis on tomato leaves, separating components of shape based on genotype (e.g., by species), by position in the leaf series (heteroblasty), the ontogentic age of the leaf, and placement of leaflets along the proximal-distal axis.
Other easy ways to measure shape: Circularity, solidity, L:W ratio (or aspect ratio) as you mentioned. All very easy to measure in ImageJ!
You mentioned Acer leaves, which piqued my interest because I study differences in the shape of grape leaves. But like grape, many Acer leaves are palmately lobed. If every one of your samples has certain features (e.g. 5 lobes and 5 sinuses as in Acer, including petiolar sinus) then you can perform a landmark analysis using a Generalized Procrustes Analysis (The "Shapes" package in R is useful for this analysis).
Using global methods to describe shape, that is, methods to quantify the totality of shape variance, are critical to distinguish leaves. It may very well be that two leaves are so similar from different species that they are not statistically separable by shape! Be creative in the ways you measure shape, and if need be, create your own system for doing so!