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" } ], "https://w3id.org/sciencelive/o/terms/hasDiscipline": [ { "@id": "http://www.wikidata.org/entity/Q7150" } ], "https://w3id.org/sciencelive/o/terms/hasMethodologyDescription": [ { "@value": "All five preprocessing and modelling steps in the original R pipeline (Cleandata_and_makeMCPs.R, CalcSpeciesPr_Rich.R, CalcSamplingEffort_Cont.R, the climate-position computation, and binomialGLMM4Presence.R) were re-implemented in Python 3.12 using xarray, pandas, statsmodels, and scipy. The mixed-effects logistic GLMM was fit with the species random effect and the same fixed-effect interactions as the original (thermal-position baseline + delta + their interaction, precipitation analogues, baseline × baseline interaction, delta × delta interaction). The datasets are the authors' bundled Bombus + CRU TS 3.24.01 monthly climate data (Figshare 10.6084/m9.figshare.9956471) on a 100 km cylindrical equal-area grid for the 1901–1974 baseline and 2000–2014 recent periods." } ], "https://w3id.org/sciencelive/o/terms/hasScopeDescription": [ { "@value": "The complete claim — that local extirpation rate in bumble bee species rises with the frequency at which local temperatures exceed species-specific historically observed thermal tolerances — is tested on the authors' original dataset across all 66 bumble bee species and the entire North America + Europe study area. Both the regression specification (mixed-effects logistic with thermal-position baseline + delta + their interaction, precipitation analogues, and species random effect) and the response variable (binary local extirpation between the 1901–1974 baseline and 2000–2014 recent\n period) match the original. 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