19-range-shift-lag-velocity
Supplied working report; original verdicts not validated.
Review status: Needs review. This is an archival source note, not a passed proof.
REPORT.md
# 19 — Ranges Lag Velocity (`range-shift-lag-velocity`) - Source: Incoprea Theory, Volume XXIX (`range-shift-lag-velocity`) - Claim: Observed range shifts lag climate velocity by a fraction set by dispersal rate rather than by the magnitude of warming. - Prediction: Lag should scale with dispersal, not with warming. - Refutation: Lag tracking warming would remove the dispersal term. ## Test performed Literature-led assessment (evidence class b), against the key datasets named in the notebook, plus a transcription of their published numbers into a small CSV and figure ([data/range_shift_evidence.csv](data/range_shift_evidence.csv), [figures/lag_drivers.png](figures/lag_drivers.png), [code/01_shift_figure.py](code/01_shift_figure.py)). Two legs were tested separately: (1) does observed lag/shift scale with **warming magnitude** (which the hypothesis says it should not), and (2) does it scale with **dispersal** (which the hypothesis says it should)? A full re-analysis of the Chen et al. 2011 supplementary database was attempted but the supplementary file is behind the Science paywall (HTTP 403), so the check uses the published results and tables/abstracts of the primary papers. ## Data (sources, URLs, sample sizes) - Chen et al. 2011, *Science* 333:1024–1026 — meta-analysis, up to 1,367 species in 31 taxonomic groups (Europe, N. America, Chile, Malaysia, Marion Island). https://pubmed.ncbi.nlm.nih.gov/21852500/ (full text: https://www.science.org/doi/10.1126/science.1206432) - Devictor et al. 2012, *Nat Clim Change* 2:121–124 — 9,490 bird + 2,130 butterfly communities, Europe, 1990–2008. https://nora.nerc.ac.uk/id/eprint/16379/ (DOI: 10.1038/nclimate1347) - Pinsky et al. 2013, *Science* 341:1239–1242 — 360 marine taxa, 128 million individuals, N. American coastal surveys 1968–2011. https://doi.org/10.1126/science.1239352 - MacLean & Beissinger 2017, *Glob Change Biol* 23:4094–4105 — review/meta-analysis of 51 studies, >11,000 species responses in 54 assemblages; formal meta-analysis on 21 studies/26 assemblages. https://onlinelibrary.wiley.com/doi/10.1111/gcb.13736 (note: the notebook cites this as PNAS; the traits meta-analysis is the GCB paper) - Loarie et al. 2009, *Nature* 462:1052–1055 — climate velocity index (A1B). https://doi.org/10.1038/nature08649 ## Result (key numbers; reference figure files) **Leg 1 — does lag/shift scale with warming? Yes, strongly.** Chen et al. 2011 found median shifts of 16.9 km/decade poleward and 11.0 m/decade uphill (~2–3× faster than the previous meta-analysis) and — directly against the hypothesis's "not with warming" — "the distances moved by species are greatest in studies showing the highest levels of warming, with average latitudinal shifts being generally sufficient to track temperature changes"; the observed shifts strongly correlated with the distances needed to keep pace with temperature. Pinsky et al. 2013: across 360 marine taxa, "climate velocity explained the magnitude and direction of shifts in latitude and depth much more effectively than did species characteristics." So the amount of movement (and hence the realized lag) tracks the warming/velocity term, which the hypothesis assigns to the wrong side of the prediction. **Leg 2 — does lag scale with dispersal? Weakly at best, and sometimes in the wrong direction.** MacLean & Beissinger 2017: across the largest trait meta-analysis to date, body size, fecundity and diet breadth had no significant study-level effect, and "multiple studies reported significant relationships that contradicted predictions"; only habitat breadth and historic range limit behaved as predicted. Devictor et al. 2012: bird communities shifted only 37 km over 1990–2008 while butterfly communities shifted 114 km, so the *better-dispersing* group accumulated the *larger* climatic debt (birds 212 km vs butterflies 135 km) — the opposite sign from "lag set by dispersal rate" ([figures/lag_drivers.png](figures/lag_drivers.png), panel 1). Dispersal is not irrelevant — Chen et al. 2011 note nearly a quarter of species moved opposite to expectation, with delays "among immobile species or those that are not good at colonizing new locations" — but it is not the dominant, consistent driver the hypothesis requires. **Synthesis.** The two candidate drivers have opposite weights from those posted: warming/climate velocity shows consistent, strong support in the two largest datasets (Chen 2011; Pinsky 2013), while dispersal-type traits show weak or sign-reversed effects in the two trait-focused analyses (MacLean & Beissinger 2017; Devictor 2012) ([figures/lag_drivers.png](figures/lag_drivers.png), panel 2). The hypothesis's own refutation criterion is therefore met on the warming side: lag does track warming. ## Verdict **Not supported** — the prediction that lag scales with dispersal rather than warming fails on the data we could reach: shift magnitude and direction track warming/climate velocity strongly (Chen et al. 2011, median 16.9 km/decade; Pinsky et al. 2013, velocity beats species traits), while dispersal-type traits show weak, inconsistent effects (MacLean & Beissinger 2017) and the higher-dispersal taxon showed the larger climatic debt (Devictor et al. 2012, birds 212 km vs butterflies 135 km). Some dispersal dependence exists, but warming magnitude is the dominant consistent driver — the opposite of the posted weighting. ## Limitations - Literature-based; Chen et al.'s supplementary species-level database could not be downloaded (paywalled, HTTP 403), so no new regression of shift vs warming/dispersal was run; numbers come from the papers' own published analyses. - Dispersal ability is rarely measured directly; studies proxy it via mobility class or body size, so the "dispersal leg" is tested only through weak proxies. - Community-level shifts (Devictor's community temperature index) measure composition turnover, not range edges; they are informative about lag but not identical to the claim's "range shifts." - Chen et al. 2011 "tracking" results are study-level means; individual species vary widely, and average tracking hides heterogeneous lags. - The rival entry `range-lag-vs-detection` is a serious confound: detection/sampling bias (e.g., resurvey effort, range-edge censoring) can inflate or hide lags, and MacLean & Beissinger's habitat-breadth/historic-range-limit effects may partly reflect detection and range-estimation issues rather than biology. It was not tested here. - Association ≠ causation at the study level (warming also correlates with study duration and location). ## References - Chen et al. 2011, *Science* 333:1024–1026. https://pubmed.ncbi.nlm.nih.gov/21852500/ - Devictor et al. 2012, *Nat Clim Change* 2:121–124. https://doi.org/10.1038/nclimate1347 (abstract: https://nora.nerc.ac.uk/id/eprint/16379/) - Pinsky et al. 2013, *Science* 341:1239–1242. https://doi.org/10.1126/science.1239352 - MacLean & Beissinger 2017, *Glob Change Biol* 23:4094–4105. https://onlinelibrary.wiley.com/doi/10.1111/gcb.13736 - Loarie et al. 2009, *Nature* 462:1052–1055. https://doi.org/10.1038/nature08649 All URLs accessed 30 October 2026.