I often grimace/sigh when someone says "I'm having trouble with fitting this model by frequentist optimization, maybe MCMC sampling will work better" ... most of the geometry problems (multimodality, scaling, numerical instability) that plague hill-climbing algos also cause problems for samplers ...

McMaster research team digitizes more than 100 years of Canadian infectious disease data The new, publicly accessible database contains more than a million infectious disease incidence counts dating back to 1903.

This is a really cool project, I was lucky to have the opportunity to participate.

news.mcmaster.ca/mcmaster-res...

Pest host expansion as a scale-free stepwise process across the host phylogeny Abstract. The present and future host ranges of pests have important implications for ecology, economics and health. Most multi-host pests have phylogeneti

Haven't seen it posted yet, so I'm giving this paper led by @phyloecology.bsky.social a boost.

It models pest expansion onto hosts as a biased random walk on a graph (here, a phylogenetic tree). There's lots of way this approach could be expanded - hopefully it inspires
doi.org/10.1098/rspb...

Robustness is better assessed with a few thoughtful models than with billions of regressions | PNAS Robustness is better assessed with a few thoughtful models than with billions of regressions

Great piece on the absurdity of brute force multiverse analyses.

www.pnas.org/doi/10.1073/...

> CEGS fit to the Barro Colorado Island tree inventory is near-perfect, so nothing more needs to be assumed

...for Barro Colorado Island trees, maybe. How does it perform for other communities?

Presumably you are not arguing that we only need 2 parameters to usefully describe any kind of assembly.

Thanks for the interesting paper!

It seems like one of your arguments is that the parameters of abundance distributions are more useful descriptions of community assembly than H/D/J.

OK. ✅

But are ~2 parameters enough to capture complex assembly processes? Why not fit population models instead?

Ecologists’ endless quest for automatic inference
statmodeling.stat.columbia.edu/2025/05/28/e...

Excited to attend the ESJ (Ecological Society of Japan) meeting in Sapporo! Our lab has six presentations there:
esj.ne.jp/meeting/abst...
esj.ne.jp/meeting/abst...
esj.ne.jp/meeting/abst...
esj.ne.jp/meeting/abst...
esj.ne.jp/meeting/abst...
esj.ne.jp/meeting/abst...

amnat.org/an/newpapers...

Nice to see Tahirah Williams' fantastic layperson summary of our ( @vishuguttal.bsky.social and I) Synthesis work on demographic stochasticity and eco-evolutionary dynamics out on the @asn-amnat.bsky.social webpage!

#evolsky #evolution #mathsky #physky #philbio 🧪🧬🌏

ESIIL synthesis center's Innovation Summit for 2025 is focusing on "Environmental Tipping Points and Transformation, an immersive, hands-on event where innovation meets collaboration." Come join us in Boulder! cu-esiil.github.io/Innovation-S... Apps due Jan 31.

Do I use hierarchical modeling?

Bro my models have so many hierarchies they could form the basis of an unjust society.

Would vine copulas be relevant here? I might be misunderstanding the question

sbi reloaded: a toolkit for simulation-based inference workflows Scientists and engineers use simulators to model empirically observed phenomena. However, tuning the parameters of a simulator to ensure its outputs match observed data presents a significant challeng...

For those interested in applying simulation-based inference for their ecology/evolution problems, this is a nice and brief overview of the Python package "sbi", a great toolkit for such purposes. arxiv.org/abs/2411.17337

What about running some simulations? Start with known h^2, generate a range of sample sizes, then see how well your estimation approach returns the known h^2 for different sample sizes.

Like the authors, I think these tools are becoming increasingly important to the field as models become more realistic, and therefore more complex. With recent advances in simulation-based inference, we might even be able to use them to parameterize previously intractable models.

Recent advances in stochastic simulation algorithms create opportunities to study new ecological and eco‐evolutionary problems Incorporating stochasticity into ecological modeling is vital for understanding the structure and function of ecological systems, but stochasticity has been challenging to consistently introduce into...

This new paper by Misha Kummel and David Vasseur on stochastic simulation algorithms in @oikosjournal.bsky.social is absolutely fantastic. Clear, precise, and insightful. A real treat to read. Check it out if you can: nsojournals.onlinelibrary.wiley.com/doi/full/10....