Biodiversity measurements

Steinmann, Linder, and Zimmermann. 2009. Modelling plant species richness using functional groups. Ecological Modelling

In the ever-elusive goal of better plant richness modelling, these folk take on the challenge by using various higher order divisions in their models, to see what shakes out best for modelling plant species richness across Switzerland. They mainly attempted a middle-path sort of route- not a bottom-up, model the individual plant responses to environmental gradients and then overlay all those maps together (a common approach which completely disregards community interactions), and not a top-down, community model which doesn't model individual species responses (an obvious deficiency).

They found little benefit to their approach, which was sort of a let-down- but, in another way, refreshing. Non-results are rarely published, which is a shame. There was an interesting facet in that some functional groups were modeled far better than others, indicating some interesting differences (but, one of the best were trees, which usually model well because of their longevity and, therefore, sensitivity to environmental factors/relative immunity from stochastic events).

Rocchini, Chiarucci, and Loiselle. 2004. Testing the spectral variability hypothesis by using satellite multispectral imagery. Acta Oecologica

My interest in the spectral variability hypotheses (also described in an earlier post about Palmer, et al 2002) stems mainly from my dislike of classified imagery as such. It eliminates so much information from the image, and locks you into whatever errors are present at the time of the classification. The SVH is a way around it, but relatively unexplored. Rocchini and others seem to be the only group working on the idea, and they always use high spatial resolution stuff (they also have a kicking dataset, like Steinmann et al, which apparently they get mostly from other people. Lucky.). They've published a few more papers on the idea, but this 2004 is the first, so... start at the beginning.

They explain ~50% of the species richness at a 1 ha scale (over landscapes, of course), which is pretty impressive, since it's all done without looking at the individual spectral responses of the plants. The image is ground-truthed, of course, but only by count; i.e. anybody can do that, without any special tools. Plus, this is with Quickbird, so it's only four bands, and I'd bet good money you can improve on that 50% really easily with some higher spectral resolution stuff. At 30 m Landsat? That's a good question, and I'm sure it really depends on the scale of vegetiation present. People have used NDVI for this sort of thing via Landsat (Gould 2000), but I'm unaware of any attempts at full-on variability style methodologies.