Bayesian SDM - more things we can touch

Fine-scale environmental variation in species distribution modelling: regression dilution, latent variables and neighbourly advice

http://onlinelibrary.wiley.com/doi/10.1111/j.2041-210X.2010.00077.x/full

Conclusion:

We then show how applying our correction to multiple co-occurring species simultaneously increases the accuracy of parameter estimates for each species, as well as estimates for the true environment at each survey plot – a phenomenon we call ‘neighbourly advice’. With a sufficient number of species, the estimates of the true environment at each plot can become extremely accurate.

Our correction for regression dilution could be integrated with models addressing other issues in SDM, e.g. biotic interactions and/or spatial dynamics. We suggest that Bayesian analysis, as employed here to address uncertainty in predictor variables, might offer a flexible toolbox for developing such next-generation species distribution models.