A guest post by Carsten F. Dormann, University of Freiburg In “biodiversity science”, species richness takes a very prominent role. It is the most analysed response, and an extremely common predictor, too. Of course everyone in the field (and lab) knows that “species richness” is a somewhat weird variable. When Cedar Creek and Jena experiment…
A guest post by Carsten Dormann. A recent talk in the colloquium of the Freiburg Centre for Data and Modelling (FDM) on a “Mystery in Machine Learning” (by Lena Kulla) brought a 2019 paper by Belkin et al. to my attention. In it, they showed a graph of a model’s error (squared loss) over model…
This is a guest post by Carsten Dormann. It is his invited keynote lecture at the 2021 Annual Meeting of the Gesellschaft für Ökologie in Braunschweig (specifically on 1 Sept 2021 at 8:15). The topic of the conference was “From Science to Policy”, and he deemed it necessary to question whether thus step is not…
A guest post by Carsten F. Dormann. In October 2021, Paul Ehrlich wrote a “Correspondence” in Nature with which I seemed to sympathise to a surprisingly large part. But the last sentence wiped out all agreement, as it revealed a fundamentally different view of the role and “duty” of “scientists”. I wrote this blog at…
The latest update of the DHARMa R package (0.4.6) includes an option to perform simulated likelihood ratio tests (LRTs) for GLMMs based on a parametric bootstrap. I wanted to shortly comment on how this works and why this is useful. Why is this useful? A well-known issue with mixed models is that the df lost…
Note also the blog post by Daniel Lakens on the same topic here. Update March 23, 2022: a more concise / slightly modified version of these thoughts was published as a letter in TREE, co-authored together with Fred Barraquand. Background Criticism of p-values has been rampant in recent years, as were predictions of their imminent…
In regression analysis, a common problem is to decide on the right functional form of the fitted model. On the one hand, we would like to make the model as flexible as possible so that it can adjust itself bias-free to the true data-generating process. On the other hand, the more freedom we give the…
A guest post by Oskar Hagen (iDiv) | www.hagen.bio | @hagen_oskar What is the cause and what are the processes that gave rise to Earth’s biodiversity patterns through space and time? Much research has been devoted to describing these patterns, and over the years, the fields of macroecology and macroevolution have slowly transitioned from a mainly correlational…
Do you remember the notorious hurricane / himmicane study (Jung et al., PNAS, 2014)? At the time, there was a heavy backlash against the study, and probably rightly so, as the statistical analysis turns out to be highly unstable against a change of the regression formula. You can find some links here. Over the years,…
tl;dr: DHARMa tests will pick up on overdispersion before you see a rise of Type I error. Overdispersion is a common problem in GL(M)Ms with fixed dispersion, such as Poisson or binomial GLMs. Here an explanation from the DHARMa vignette: GL(M)Ms often display over/underdispersion, which means that residual variance is larger/smaller than expected under the…
A colleague forwarded me a preprint (Louca and Pennell, 2019), which questions if time-varying extinction / speciation rates can be simultaneously inferred from extant phylogenies. I’d like to preface this by saying that this is not really my core expertise, so take my points with a grain of salt. Anyway, I was interested in the…
A guest post by Carsten Dormann (Uni Freiburg) / @CarstenDormann. Cover picture by Takver via Wikimedia Commons. BioScience has just published the latest installment of “Scientists’ Warnings“. There have been two previous such Warnings, the latest organised by the same authors in 2017. Quite a few scientists have signed this Warning. I chose not to,…
Although one would think that the basic concepts of statistics should be the same across all sciences, there is an amazing heterogeneity between fields in how statistics is taught and practiced. One example are the validity concepts (e.g. construct validity, internal validity, external validity) that are heavily taught in the social sciences and economics (see…
Guest post by Carsten Dormann (Uni Freiburg) / @CarstenDormann The relationship between species richness and ecosystem function is a field of ecology that has always puzzled me. I learned the scientific rope in a department of vegetation ecologists: vegetation was the result of environmental conditions, and indeed a substantial part of their research was to…
A guest post by @MaxMaPichler, MSc student in the Group for Theoretical Ecology / UR Artificial neural networks, especially deep neural networks and (deep) convolutions neural networks, have become increasingly popular in recent years, dominating most machine learning competitions since the early 2010’s (for reviews about DNN and (D)CNNs see LeCun, Bengio, & Hinton, 2015). In ecology,…
By Lisa Hülsmann and Florian Hartig (U Regensburg), with short comments by Ryan Chisholm (NUS) and Matteo Detto (Princeton). By Betteridge’s law, the answer to this question is of course no. Or better: we don’t know. But let’s back up a bit: Global gradients in CNDD Almost a year ago, LaManna and coauthors published a paper in Science…
This (co-)guest post by Carsten F. Dormann & Florian Hartig summarizes a comprehensive review on model averaging for predictive inference, just published in Ecological Monographs.
Over at dynamic ecology, Jeremy Fox argues that Technical statistical mistakes are overrated; ecologists (especially students) worry too much about them. Individually and collectively, technical statistical mistakes hardly ever appreciably slow the progress of entire subfields or sub-subfields. And fixing them rarely meaningfully accelerates progress. continuing with Don’t agree? Try this exercise: name the most…
Originally posted on AK Computational Ecology:
This guest post by Carsten F. Dormann, with inputs from Casper Kraan and the panel (see below) summarises the results from the short workshop “Biotic interactions and joint species distribution models” at the Ecology Across Borders BES/GfÖ/NEVECOL/EEF-meeting 2017 in Ghent, Belgium. The purpose of this event was to exchange thoughts and…
This is a somewhat belated introduction of a package that we published on CRAN at the beginning of the year already, but I hadn’t found the time to blog about this earlier. In the R environment and beyond, a large number of packages exist that estimate posterior distributions via MCMC sampling, either for specific statistical models (e.g.…
In good old tradition, including being too late, I provide here the JCR 2016 data for the top 40 journals indexed by what is now Clarivate Analytics’ Web of Science in the subject area “Ecology”, released in June 2017 (see footnote 1). For comparison, see my old posts, summarizing the JCR 2015, JCR 2014, JCR 2013, JCR 2012, JCR…
As I said before, I firmly side with Andrew Gelman (see e.g. here) in that model checking is dangerously neglected in Bayesian practice. The philosophical criticism against “rejecting” models (double-using data etc. etc.) is all well, but when using Bayesian methods in practice, I see few sensible alternatives to residual checks (both guessing a model and…
We are pleased to announce our 7th international summer school on Bayesian Modelling in the ecological and environmental sciences (see past courses here). This year the course will take place at the Heathland Centre on the beautiful island of Lygra in western Norway. Motivation Bayesian inference is an increasingly used statistical framework in ecology and…
A guest post by Carsten F. Dormann Over the last years, I have been using null models more often than I liked. I had to, when there was no other way to figure out if an ecological pattern was unexpected, or trivial. Inspired by some recent (and also some older) posts, I thought I might throw around…
I just released a small R package that I have been working on for a while. The motivation for this package came from the observation that I kept on receiving questions about residual checks for GLMMs. The problem that people have is that they have fitted their GLMM, maybe they tested it for overdispersion and…
theoretical ecology 