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This topic has been one of my interests in the last four years...I have make some analysis, unfortunately none has been published, I hope for this summer I've submitted something. One of these analysis was focused in testing some hypothesis used as explanation of species diversity along altitudinal gradients. I used a databased with Pristimantis spp. (formerly known as Eleutherodactylus) and I tested three hypothesis: mid-domain effect, area, and Rapoport's rule. None of these it was an 
explanation of patterns of species diversity along three mountain systems in Colombia. So, I think historial and climatic factors are correlated with species richness, but this require additional analysis. Thinking a little in this, I made an analysis for all amphibian species in Colombia, and I used several factors as predictors: climatic, topographic, area. Because I enjoy a little with spatial statistics and put to test methods, I tested effects of spatial scale in the predictability of species richness. Using three grid size cell (1º, 0.5º, 0.25º cell) and three spatial methods (OLS: ordinary least squares, GLS: generalized least squares, SAR: spatial autorregresive regression) I want to see what method is better and what scales is appropiated (not extension only grain size). I'm working in it but slowly...
This topic has been one of my interests in the last four years...I have make some analysis, unfortunately none has been published, I hope for this summer I've submitted something. One of these analysis was focused in testing some hypothesis used as explanation of species diversity along altitudinal gradients. I used a databased with Pristimantis spp. (formerly known as Eleutherodactylus) and I tested three hypothesis: mid-domain effect, area, and Rapoport's rule. None of these it was an 
explanation of patterns of species diversity along three mountain systems in Colombia. So, I think historial and climatic factors are correlated with species richness, but this require additional analysis. Thinking a little in this, I made an analysis for all amphibian species in Colombia, and I used several factors as predictors: climatic, topographic, area. Because I enjoy a little with spatial statistics and put to test methods, I tested effects of spatial scale in the predictability of species richness. Using three grid size cell (1º, 0.5º, 0.25º cell) and three spatial methods (OLS: ordinary least squares, GLS: generalized least squares, SAR: spatial autorregresive regression) I want to see what method is better and what scales is appropiated (not extension only grain size). I'm working in it but slowly...
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