Legacy of salmon-derived nutrients on riparian soil chemistry and soil fertility on the Central Coast of British Columbia, Canada
Bibliographic record
Abstract
Every year, salmon return to their natal streams to spawn. Their return represents an ecosystem subsidy of nutrients and energy from the sea to the land; these materials feed into terrestrial food webs, plant communities, and forest soils. Here we test the long term effects of salmon inputs on soil fertility by sampling soils from Haíɫzaqv (Heiltsuk) Nation territory on the Central Coast of British Columbia, Canada. A total of 20 soil chemical properties were assessed via two sampling methodologies: first, across 23 watersheds representing a regional gradient of salmon density (kg of salmon per meter of stream reach per year); and second, at four sites above and below waterfalls that blocked salmon migration. At each sampling point, soil material at two depths was collected. Multivariate analysis regional gradient showed salmon density, the moss community, and the shrub community to be significant factors related to soil chemistry. Similarly, being above or below the waterfall, the moss community, and the tree community were significant in the waterfall comparison. Generalized linear mixed models along regional salmon density gradient showed an increase in nitrate (NO3−) correlated with salmon inputs (p < 0.05), and moderately significant (p < 0.1) increases in ammonium (NH4+), phosphorus (P), aluminum (Al), and copper (Cu). Net cation exchange capacity (CEC) did not change; however, magnesium (Mg) significantly decreased along these gradients (p < 0.05), while sodium (Na) had a declining tendency and calcium (Ca) had an increasing tendency. Being below salmon-blocking waterfalls or the salmon density below falls was a factor in higher total nitrogen, nitrate, ammonium, phosphorus, total sulfur (S), magnesium, and sodium concentrations; below falls sites also had lower pH and aluminum. Exploratory analysis of the regional gradient data using a random forest model apportioned high importance to soil depth, the moss community, the shrub community, salmon density and distance from the stream. These results show that salmon inputs are correlated with a number of changes in recipient soils, and these are consistent with an interpretation of improved fertility at these sites.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".