John Alroy

@johnalroy.bsky.social

Biodiversity and extinction researcher

The Ecological Register now features an interactive mapping tool that lets you find ecological and palaeontological survey data. You can search using Latin names, English names, and time interval names. Click on a link and you can download all the surveys. The home page lists major data sets.

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Extinct Pleistocene carnivores were diurnal and highly active - fresh off the press 🐯 Only BMR and diurnality are robust predictors of extinction and this also stands for extant species 🦨🐅🦝 With @johnalroy.bsky.social we use an exhaustive sample and account for phylogenetic and trait uncertainty.

https://nsojournals.onlinelibrary.wiley.com/doi/10.1002/ecog.08061https://nsojournals.onlinelibrary.wiley.com/doi/10.1002/ecog.08061

Fisher's alpha goes down, not up, as more stems are randomly drawn from across the BCI plot (upper green line). But it goes up if stems are drawn in order going SW-to-NE across the plot (lower). Chao 1 rises steeply (red). CEGS doesn't (upper blue) while capturing the area signal (lower blue).

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Methods matter! BCI tree diversity partitioned by size class (5 cm DBH running window). CEGS (blue): flat, then a sudden drop ~40 cm. Chao 1: lower, different, and higher variance. CBR/alpha/theta (orange/purple/pink): ~50% increase on the way up to ~25 cm. But diversity should always decline.

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Likelihood differencing is here: the new release of the richness R package for diversity analysis includes an LD version of the CEGS function, which fits species abundance distributions and estimates richness. Check this out if you found my recent preprints interesting. github.com/johnalroy/ri...

Release Version 3.1 · johnalroy/richness

Version 3.1 of the richness package introduces likelihood differencing with the new cegsLD function. The existing Bayesian and maximum likelihood versions of CEGS (cegsB and cegsML) have been subst...

github.com

The BCI manuscript is now done. The log series and ZSM fit the overall 50 ha data poorly. They predict the 1 ha subplot data just as poorly (last post) and underestimate beta diversity (new graph). CEGS is of course best. Manuscript available upon request: comments would be very much appreciated.

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CEGS wins again. Predictive test based on the 50 ha BCI tree plot dataset of Hubbell/Foster/Condit (thanks). CEGS fits to species counts in 1 ha plots better predict counts in 9 plots to the east (blue). PLN wins once (red). Log series loses every time. Likelihood ratio cutoff is 10:1.

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Rarefaction is also dead – and CEGS gets the job done again. It recovers richness when common species are set aside or when samples are drawn from composite ecological communities. Rarefaction, Shannon's H, and Simpson's D are way off in both cases. www.authorea.com/users/363764...

Coverage-based rarefaction does not quantify species richness

Coverage-based rarefaction (CBR) is a high-profile tool for assessing biodiversity that provides relative species richness estimates. It leverages the Good-Turing index u to interpolate expected richn...

authorea.com

I have just submitted a short paper about the compound exponential-geometric series (CEGS). CEGS predicts count distributions and species richness with high accuracy. A preprint is available upon request.