Shorebird Abundance is Associated with Nutritional Quality of Intertidal Biofilm on the Fraser River Estuary
Bibliographic record
Abstract
Abstract Dense congregations of shorebirds forage on tidal flats during long-distance migration, and their abundance is presumed to mirror the underlying ecological conditions. We quantified the nutritional content of intertidal biofilm (a thin layer of microalgae, bacteria, and other microorganisms embedded in a mucilaginous matrix that sits on the surface of tidal flats) to assess whether biofilm biomass, macronutrient content (lipid, protein, and carbohydrate), or both, provide a measure of habitat quality for migrating shorebirds. We compared shorebird use, biofilm biomass, macronutrient content, and stable isotope signatures at two mudflats on the Fraser River estuary, British Columbia, Canada, during summer 2020 (southward migration) and spring 2021 (northward migration). The abundances of Western Sandpiper ( Calidris mauri ) and Dunlin ( Calidris alpina ) were consistently higher (6–100×) at Brunswick Point relative to the Iona Foreshore site during both migration periods. Biofilm biomass (chlorophyll a ) was 2× higher at Brunswick Point than Iona Foreshore during southward migration, and was similar between sites during northward migration, suggesting biofilm biomass alone was not a main determinant of shorebird use of these sites. Macronutrient content (lipid, protein, and carbohydrate) in intertidal biofilm was 1.4× to 3.8× higher at Brunswick Point than Iona Foreshore during both migration periods, indicating an association between macronutrient content and shorebird use. Carbohydrate content was higher during southward migration at both tidal flats, whereas protein and lipid content at Iona Foreshore did not show significant differences between years or migration periods. Carbon and nitrogen stable isotope signatures during spring 2021 did not differ between the two sites, suggesting that nutrients had similar relative inputs from marine and freshwater sources. While our comparative study does not eliminate alternative explanations that might act concomitantly (e.g., invertebrate abundance, predation risk, and disturbance), our results are consistent with the hypothesis that small-bodied shorebirds are more abundant at sites where intertidal biofilm has high macronutrient content. The latter can vary in complex ways depending on the taxonomic composition and physiological state of the microphytobenthos. Thus, the nutritional “quality” of intertidal biofilm can serve as a useful measure for determining restoration goals for tidal flats or assessing coastal areas for development projects.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".