Spatial Scale Affects Community Concordance Among Fishes, Benthic Macroinvertebrates, And Bryophytes In Streams
Bibliographic record
Abstract
Owing to the lack of information about the distribution patterns of many taxonomic groups, biodiversity conservation strategies commonly rely on a surrogate taxa approach for identifying areas of maximum conservation potential. Macroinvertebrates or fish are the most likely candidates for such a role in many freshwater systems. The usefulness of the surrogate taxa depends largely on community concordance, i.e., the degree of similarity in community patterns among taxonomic groups across a set of sites. We examined the effect of the spatial scale of a. study on the strength of community concordance among macroinvertebrates, bryophytes, and fish by comparing the concordance between ordinations of these groups in 101 boreal stream sites. We specifically asked if communities spanning several drainages are more concordant than those originating from a single drainage system. Our results indicate that community concordance is affected by spatial extent, being variable and generally weak at the scale of individual drainages, but strong across multiple drainage systems and ecoregions. We attribute this finding to different taxonomic groups responding to similar environmental factors and sharing a similar latitudinal gradient of community structure when viewed across large spatial scales. We also identified a "gradient of concordance," with sites contributing disproportionately to community concordance being in relatively large streams with high microhabitat variability. Overall, our results suggest that the degree of community concordance among freshwater organism groups depends critically on the spatial extent of the study, and surrogate groups at the scale of single river systems should be used with caution.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".