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The validation rests on six fitness criteria, evaluated end-to-end across nine grid systems on synthetic uniform sphere data and on real GBIF Quercus suber occurrences. (1) Equal-area correctness: HEALPix-on-sphere has a small but systematic ~0.7% area bias at boreal latitudes vs WGS84; HEALPix-on-WGS84 via authalic-sphere mapping (healpix-geo / GRID4EARTH) and rHEALPix resolve it. (2) Cell-shape preservation: all DGGS family members preserve compact cells across latitudes; the projection family does not. (3) Hierarchical refinement: HEALPix NESTED bit-shift makes parent-child operations O(1) integer arithmetic, faster than alternative lookup-based hierarchies. (4) Ellipsoidal correctness: healpix-geo and rHEALPix provide it; HEALPix-on-sphere does not. (5) Iso-latitude pixelization: HEALPix-only among the family; makes zonal climate-zone analyses essentially free. (6) ML-ecosystem compatibility: HEALPix is the substrate for spherical-CNN architectures (DeepSphere), scattering networks (foscat / FIESTA stack), and native sphere-harmonic transforms (healpy.map2alm); alternative DGGS lack this depth. " } } } rows { name { value: "hasConfidenceLevel" } } rows { name { value: "HighConfidence" } } rows { quad { p_iri { } o_iri { } } } rows { name { value: "hasEvidenceDescription" } } rows { quad { p_iri { } o_literal { lex: "Notebook 01: 1,000,000 uniform random points on the sphere binned on 5\302\260 lat-lon vs HEALPix nside=16 NESTED produce a 23\303\227 count bias at the equator vs 85\302\260N from cell-area geometry alone, matching the analytical prediction. Notebook 02 + 07: 20,100 Quercus suber GBIF occurrences aggregated onto eight equal-area grids (HEALPix-sphere, HEALPix-geo-WGS84, H3 res 3, rHEALPix res 4, Mollweide 100 km, EEA reference grid 100 km, ISEA3H res 8) plus the lat-lon cautionary baseline produce visually identical density patterns over the species\' Mediterranean range, while lat-lon distorts. Notebook 03: aspect-ratio chart from 0\302\260 to 70\302\260N for nine grids \342\200\224 DGGS family stays near aspect 1.0\342\200\2231.3, projection family diverges (Behrmann 5.0 at 65\302\260N). Notebook 04: 3\303\2273 ML kernel at 65\302\260N, 15\302\260E shows Behrmann aspect 5.0 (long N\342\200\223S strip), Mollweide 1.3, lat-lon 1.2, EEA reference grid 1.0 (azimuthal preserves shape near 52\302\260N centre), HEALPix-sphere 1.3, HEALPix-geo 1.3, rHEALPix 1.2, H3 res 3 1.0, ISEA3H res 8 1.2. Notebook 06: HEALPix NESTED parent\342\200\223child relation verified as integer bit-shift (parent = pix >> 2, children = pix << 2 | k) against healpy.pix2ang/ang2pix. Notebook 08 Section A: pyproj.Geod-exact ellipsoidal area vs HEALPix-on-sphere area shows +0.45% at the equator, \342\210\2220.65% at 65\302\260N, \342\210\2220.88% at 85\302\260N \342\200\224 total 1.3 percentage-point swing across populated latitudes. Notebook 08 Section C: 12 pixels in a HEALPix nside=16 ring confirmed at identical colatitude to 1e-10 precision, vs H3 hex tessellation which breaks iso-latitude alignment.\n\nRepository: https://github.com/annefou/dggs-biodiversity-bias\n" } } } rows { name { value: "hasLimitationsDescription" } } rows { quad { p_iri { } o_literal { lex: "The validation is a multi-criteria fitness-for-purpose evaluation, not a single-metric benchmark; the relative importance of the six criteria depends on the use case. For biodiversity counts in isolation at coarse resolution, any equal-area DGGS satisfies the count-correctness criterion; the HEALPix-specific advantages (NESTED bit-shift, iso-latitude, ML-ecosystem compatibility, ellipsoidal-correctness path) become decisive in the integrated regime where biodiversity is stacked at high resolution with Copernicus EO and Destination Earth climate-model output, less so in standalone biodiversity workflows. The ~0.7% sphere-vs-WGS84 area bias is small per-cell; the case that it compounds materially across millions of cells \303\227 decades into climate-attribution errors is sketched (notebook 08 Section A) but not fully quantified by a stacked-product end-to-end demonstration. The real-data demonstration uses a single species (Q. suber, 20,100 occurrences); broader cross-taxon and global-coverage tests are out of scope. 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