Climate change and range shifts

Predicting climate-induced range shifts: Model differences and model reliability. Lawler et al, 2006

Modeling! Modeling in R, which is more impressive. This is a great paper- not in terms of being particularly interesting, or revolutionary, but in terms of usefulness. There needs to be more papers like this, a straightforward comparison between modeling approaches using the same data, so relative errors, types of errors, etc can all be directly seen. The researchers take 100 different mammal species present in and around Brazil, and model their current distribution based on nine climate variables and one land cover variable- basically the inputs for most climate change scenarios. Then, they compare the results to actual distributions. Fun.

There are some interesting results. Random forest models were far and away the best. Genetic algorithms were second place, although they had problems with errors of commisson. Other models, like classification trees, GAMs, etc did relatively worse. I'd hypothesize that random forests did better specifically because they sampled from the 10 inputs with replacement, meaning they randomlly added weights to the various factors, so there was an added feature that neural networks and the other machine learning algorithms didn't have.

But, like all models, they have their problems, which follow.....

Prediction of plant species distributions across six millenia. Pearman et al, 2008.

This is a more applied study, where Pearman and friends attempt to model tree species in Europe. For a twist, they model from 6000 BP to now, 6000 BP only, and now only, in an attempt validate future predictions (using past climate records and pollen finds). Their main finding was that some species are modeled quite well, and others not so well- the ones which came out winners are dominant competitors for light. This makes perfect sense, and highlights the main limitation of this study, Lawler's, and most other species distribution models I've seen (and they readily admit to this limitation as well). Light competition is the only way in which most plants experience biotic constraints on their distribution. Most plants don't interact directly, especially these trees, beyond the race for good spots in the canopy. Thus, species which are competitively dominant won't really experience biotic controls on their distribution, because wherever they live, they win. Species which are not competitively dominant will experience this biotic limit to their range, and therefore models which don't take biotic factors into account won't be as accurate.

A second limition is both assume that species are at current equilibria with respect to their distribution. But the Johnstone article (reviewed earlier) indicates that some species are still expanding their range, invalidating this assumption.

Pearman also mentionsthe possibility of rapid niche shifts, which I don't know much about, but which would also invalidate predictions into the future.