. . . . . . "TEI mechanism — HEALPix nside=128 substrate extension on Iberian Bombus (full GLMM refit at native DestinE Climate DT pixelisation)" . . . . "1. Pixelisation. Soroye 2020 fit at the CEA grid (~100 km, equal-area cylindrical). This Study fits at HEALPix-NESTED nside=128 on the WGS84 ellipsoid (~46 km). Cell area is ~4× smaller than Soroye's; cell shape and topology differ. This is the SAME deviation kind as the canonical nside=64 sibling, just at a finer resolution.\n\n2. Region. Iberian peninsula only — same as the canonical sibling.\n\n3. Inference engine. Two independent Python implementations (statsmodels VB, bambi/PyMC NUTS) — same as the canonical sibling.\n\n4. Prior choices. Bambi defaults (Half-StudentT on group SDs) rather than Soroye's MCMCglmm informative inverse-Wishart — same deviation as the canonical sibling.\n\n5. Climate inputs. Soroye's bundled CRU TS 3.24.01 from his Figshare deposit, used unchanged — NOT a deviation.\n\n6. Tier 2 projection grid alignment. Unlike the canonical nside=64 sibling, this Study fits AND projects at the same native HEALPix nside=128 substrate — no parent-cell aggregation between fit and projection grids. This eliminates one source of cross-substrate aggregation noise but introduces a finer-grained per-cell extrapolation tail (more cells lie far outside the training distribution per species)." . . "METHOD\n\nThe methodology mirrors the canonical nside=64 sibling exactly except for the spatial substrate. Cell coverage and per-species niche limits are computed on HEALPix-NESTED nside=128 cells of the WGS84 ellipsoid (using the healpix-geo Python library); per-species niche limits and the GLMM are refit at this substrate.\n\nGLMM specification (identical to Soroye 2020 and to the canonical sibling):\n extinction ~ continent + sc_sampling + sc_TEI_bs + sc_TEI_delta + sc_TEI_bs:sc_TEI_delta + sc_PEI_bs + sc_PEI_delta + sc_PEI_bs:sc_PEI_delta + sc_TEI_bs:sc_PEI_bs + sc_TEI_delta:sc_PEI_delta + (1|species)\n\nInference: variational-Bayes via statsmodels.BinomialBayesMixedGLM (fast first pass) and full-posterior NUTS via bambi/PyMC, 4 chains × 2000 samples (authoritative HDIs).\n\nTier 2 — SSP3-7.0 future projection. DestinE Climate DT IFS-NEMO standard SSP3-7.0 GRIB files retrieved via polytope on LUMI for the 2020–2029 and 2030–2039 horizons, decoded with eccodes (Python API, NESTED-aware), subset to pre-computed Iberian HEALPix nside=128 cells. The future-period TEI_delta and PEI_delta are computed on the SAME substrate the GLMM was fit on (no cross-substrate aggregation step). Per-species ranking is reported following the protocol established in the methodological sibling chain (n_cells ≥ 10, main-effects-only η at projection time)." . "SCOPE: the GLMM coefficient on standardised TEI_delta at HEALPix nside=128 (the native pixelisation of DestinE Climate DT IFS-NEMO standard), Iberian Bombus only.\n\nIN SCOPE\n - Soroye 2020's GLMM specification (identical to the canonical nside=64 sibling).\n - Soroye 2020's CRU TS 3.24.01 climate inputs (identical, kept unchanged).\n - HEALPix-NESTED nside=128 on the WGS84 ellipsoid (~46 km cells; the native DestinE Climate DT pixelisation).\n - Tier 1 historical fit on the 1901–1974 baseline period and 2000–2014 recent period.\n - Tier 2 SSP3-7.0 future projection at substrate-matched nside=128 (no parent-aggregation deviation between fit and projection grids).\n\nOUT OF SCOPE for this Replication Study (handled by separate chains)\n - The canonical CEA + nside=64 substrate-comparison at coarser resolution — see weatherxbiodiversity-projection.\n - Cross-substrate methodological diagnostic — see weatherxbiodiversity-substrate-sensitivity.\n - Bombus species outside the Iberian peninsula." . . . "Anne Fouilloux" . "2026-05-11T19:28:01.754Z"^^ . . . . . "TEI mechanism — HEALPix nside=128 substrate extension on Iberian Bombus (full GLMM refit at native DestinE Climate DT pixelisation)" . . "RSA" . "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" . 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