The strength of cross‐taxon congruence in species composition varies with the size of regional species pools and the intensity of human disturbance
Bibliographic record
Abstract
Abstract Aim Our aims were to determine whether cross‐taxon congruence of species composition patterns varies across regions and human disturbance levels and to infer whether these patterns relate to the size of the regional species pool and the sorting of species along a gradient of human disturbance. Location Alberta's Boreal and Grassland Natural Regions, Canada. Method We compiled presence–absence data of four biological groups (birds, vascular plants, bryophytes and mites) from low and high disturbance sites in upland habitat. The cross‐taxon congruence across ecoregion and disturbance levels was analysed using Mantel and Procrustes tests. We applied resampling without replacement to generate confidence intervals to test for significant differences in strength of congruency between disturbance levels and ecoregions. We performed indicator species analysis to highlight how the species‐level response to high and low disturbance influences the pattern in community‐level cross‐taxon congruence. Results Cross‐taxon congruence was stronger when all sites were considered than when high and low disturbance sites were considered separately. Congruency was relatively stronger in high than low disturbance sites in the Boreal ecoregion, but the pattern was reversed in the Grassland ecoregion. More species were indicators of undisturbed habitat than of highly disturbed habitats for all biological groups except for birds. Overall, biological groups that were poorly represented in a region and/or with few characteristic indicator species showed weak congruence in those sites. Main conclusions We conclude that a longer disturbance gradient can promote cross‐taxon congruence by increasing the species pool characteristic of low or high disturbance levels. Moreover, regional context can influence (or even reverse) the relative strength of cross‐taxon congruence in high and low disturbance sites, which may explain the inconsistent strength of cross‐taxon congruence along the disturbance gradient. To use biodiversity surrogates across biogeographical regions, it is therefore important to account for the regional and disturbance‐level dependence of cross‐taxon congruence.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.006 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".