Simple parametric tests for trait–environment association
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Bibliographic record
Abstract
Abstract Question The CWM approach is an easy way of analysing trait–environment association by regressing (or correlating) the mean trait per plot against an environmental variable and assessing the statistical significance of the slope or the associated correlation coefficient. However, the CWM approach does not yield valid tests, as random traits (or random indicator values) are far too often judged significantly related to the environmental variable, even when the trait and environmental variable are extrinsic to (not derived from) the community data. Existing solutions are the ZS ‐modified test (Zelený & Schaffers,) and the max (or sequential) test based on the fourth‐corner correlation. Both tests are based on permutations which become cumbersome when many tests need to be carried out and many permutations are required, as in methods that correct for multiple testing. The main goal of this study was to compare these existing permutation‐based solutions and to develop a quick and easy parametric test that can replace them. Methods This study decomposes the fourth‐corner correlation in two ways, which suggests a simple parametric approach consisting of assessing the significances of two linear regressions, one plot‐level test as in the CWM approach and one species‐level test, the reverse of the CWM approach, that regresses the environmental mean per species (i.e. the species niche centroid) on to the trait. The tests are combined by taking the maximum p ‐value. The type I error rates and power of this parametric max test are examined by simulation of one‐ and two‐dimensional Gaussian models and log‐linear models. Results The ZS ‐modified test and the fourth‐corner max test are conservative in different scenarios, the ZS ‐modified test being even more conservative than the fourth‐corner. The new parametric max test is shown to control the type I error and has equal or even higher power than permutation tests based on the fourth‐corner, the ZS ‐modified test and variants thereof. A weighted version of the new test showed inflated type I error. Conclusion The combination of two simple regressions is a good alternative to the fourth‐corner and the ZS ‐modified test. This combination is also applicable when multiple trait measurements are made per plot.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it