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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\303\227 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 \342\200\224 same as the canonical sibling.\n\n3. Inference engine. Two independent Python implementations (statsmodels VB, bambi/PyMC NUTS) \342\200\224 same as the canonical sibling.\n\n4. Prior choices. Bambi defaults (Half-StudentT on group SDs) rather than Soroye\'s MCMCglmm informative inverse-Wishart \342\200\224 same deviation as the canonical sibling.\n\n5. Climate inputs. Soroye\'s bundled CRU TS 3.24.01 from his Figshare deposit, used unchanged \342\200\224 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 \342\200\224 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)." } } } rows { name { value: "hasDiscipline" } } rows { name { value: "Q1886501" } } rows { quad { p_iri { } o_iri { prefix_id: 12 } } } rows { name { value: "hasMethodologyDescription" } } rows { quad { p_iri { prefix_id: 9 } o_literal { lex: "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 \303\227 2000 samples (authoritative HDIs).\n\nTier 2 \342\200\224 SSP3-7.0 future projection. DestinE Climate DT IFS-NEMO standard SSP3-7.0 GRIB files retrieved via polytope on LUMI for the 2020\342\200\2232029 and 2030\342\200\2232039 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 \342\211\245 10, main-effects-only \316\267 at projection time)." } } } rows { name { value: "hasScopeDescription" } } rows { quad { p_iri { } o_literal { lex: "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\342\200\2231974 baseline period and 2000\342\200\2232014 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 - 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