NP created using Declaring a replication study outcome according to FORRT
type: Nanopublication
has assertion: assertion
has provenance: provenance
has publication info: pubinfo
created: 2026-04-25T10:44:28.546Z
creator: Anne Fouilloux
license: https://creativecommons.org/licenses/by/4.0/
introduces: Soroye 2020 thermal-exposure → extirpation claim is robust to a Python re-implementation
was created at: platform.sciencelive4all.org

Soroye 2020 thermal-exposure → extirpation claim is robust to a Python re-implementation
type: FORRT-Replication-Outcome
end date: 2026-04-23
has conclusion description: The Python re-implementation of Soroye et al. 2020's pipeline applied to the authors' own dataset reproduces the headline thermal-exposure → extirpation relationship: the standardised TEI-delta coefficient is positive and highly significant in both a plain logistic regression and a mixed-effects model with species random effect. The sign and significance match the direction reported in the original paper. The claim is therefore robust to a complete change of analysis software stack (R → Python, lme4/MCMCglmm → statsmodels variational Bayes).
has confidence level: HighConfidence
has evidence description: Mixed-effects logistic GLMM (statsmodels.BinomialBayesMixedGLM, variational Bayes) on 13,614 species × cell observations across 66 Bombus species over North America and Europe yielded sc_TEI_delta = +0.1528 with 95% credible interval [0.116, 0.189], unambiguously positive. A plain logistic regression on the same data gave sc_TEI_delta = +0.2466 (p = 4×10⁻²¹). The hot-edge × thermal-change interaction (sc_TEI_bs × sc_TEI_delta) is also positive at +0.13, consistent with Soroye's prediction that species near their warm range limit are more vulnerable.
has limitations description: (i) Variational Bayes posterior may underestimate credible-interval width by approximately 10–20% relative to full MCMC; tight CI claims would be more conservative under full MCMC. (ii) The exact climateLimits[[1]]/[[2]] precomputation script is not in the public Figshare release and was reconstructed from the available R helper scripts; this can shift absolute coefficient magnitudes but does not alter the qualitative direction. (iii) The 13,614-row analysis subset is determined by Soroye's filter (cells with valid baseline + recent observations) and inevitably excludes regions of low sampling effort.
has outcome repository: zenodo.19756174
has validation status: Validated
is outcome of: soroye-replication-study

sig
has algorithm: RSA
signed by: Anne Fouilloux