Our new article “Advancing general ecosystem models (GEMs): Towards a mechanistic understanding of the biosphere in the light of the Anthropocene” let by Joachim Paul Töpper just out at Ecological Solutions and Evidence https://t.co/Apl5FrGiAp

All details in

But why does the effect appear in the first place? We believe the reason is that as mutualism rates are predicted by latitude, mutualism and latitude are perfectly nonlinear confounded. Using only a linear model, nonlinear effects of latitude create spurious effects of mutualism.

The main issue we see is that the mutualism covariate is not measured, but predicted by a very simple model that only depends on latitude (R2 = 0.14). Predicting mutualism rates with a more precise model (R=0.39) removes any effect of this covariate in the main regression.

In @nature, Delavaux et al., 2024 suggest that species richness on oceanic islands is reduced by mutualism rates on the mainland. In https://t.co/0AFd2FXGFZ, @_Max_Pichler and I had another look at this question and conclude that this effect is likely a statistical artefact.

Our study "Analyzing longitudinal trait trajectories using GWAS identifies genetic variants for kidney function decline" led by Simon Wiegrebe and Iris Heid just out in @NatureComms https://t.co/vYf1BpchED

On my way back from a short visit at Uni Birmingham! Thanks @cabral_sarmento for inviting me!

Given the general exodus around me, I want to say that while I will stay here for the moment, you can also find me at #Bluesky under @florianhartig

sensitivity analysis, uncertainty analysis and model inversion for complex (ecological) models. Comments welcome!

Our preprint "Calibration, sensitivity and uncertainty analysis of ecological models -- a review" with Anne Malchow now available at https://t.co/i5KvFbsAkc This is our attempt at giving a broad overview about methods and issues surrounding

As every year in fall, I teach our intro stats class for biologists. As I was discussing NHST and p-values, I observed the students' faces digesting that you can have 5% type I error and still an FDR of > 50%, as visualised so nicely by @ReginaNuzzo https://t.co/NtjvzTgnXF

Had a wonderful time this week at the @SFE2_2024 conference in #Lyon. Thanks to Stéphane Dray for inviting me to the symposium "Advances in Statistical Ecology", and great catching up with @efronhofer @guiblanchet3 @FredBarraquand and many more #SFE2

To find out more about DHARMa, visit

persons, we now have an option to switch the signal color used to highlight residual problems. See NEWS for further updates (above, you see a plot with options(DHARMaSignalColor = "blue") )Welcome also to @melina_sleite , who joined the DHARMa development team.

DHARMa v0.4.7 #rstats package for #glmm residual diagnostics now available on #CRAN. Among other things, this version includes a new residual test for #phylogenetic correlation, as well as support for the #phylolm package. Moreover, to make DHARMa more accessible for color-blind

Doing some Bayesian statistics and confused about which test to apply in which situation? Just consult this handy flowchart!

Fantastic chance to present much of our recent work on the connection of ML and #DeepLearning with statistics, including the cito #Rstats package for building neural works with R as well as our recent work on inductive biases in different ML algorithms https://t.co/lFWz0APvb8

It was a pleasure to talk today (remotely) on "Can predictive #MachineLearning models be used for statistical #inference?" at the XXVIII Reunión Científica Grupo Argentino de Bioestadística, held at Ciudad Universitaria, Buenos Aires, Argentina.

Great to see our article "Consequences of Local Conspecific Density Effects for Plant Diversity and Community Dynamics" lead by Joe LaManna and Camille Delavaux now out and available in @Ecology_Letters https://t.co/NYhyAKTHpX

Our article "The road to integrate climate change projections with regional land‐use–biodiversity models" led by @cabral_sarmento with many others including now published in @PaN_BES https://t.co/6Mrjga4lS7