Seasonally and Spatially Variable Organic Matter Contributions From Watershed, Marine Macrophyte, and Pelagic Sources to the Northeast Pacific Coastal Ocean Margin
Bibliographic record
Abstract
Globally, coastal waters are considered biogeochemical hotspots because they receive, transform, and integrate materials and waters from both land and the open ocean. Extending from northern California to southeast Alaska, the Northeast Pacific Coastal Temperate Rainforest (NPCTR) region is no exception to this, and hosts a diversity of watershed types (old-growth rainforest, bog forest, glaciers), and tidal (sheltered, exposed) and pelagic marine (deep fjord, shallow estuary, well-mixed channel) environments. With large freshwater fluxes to the coastal ocean, cross-ecosystem connectivity in the NPCTR is expected to be high, but seasonally variable, with pulses in runoff from rainfall, snowmelt and glacial melt, and primary production associated with changes in ocean upwelling and incident light. However, the relative contribution of each ecosystem to surface ocean organic matter pools over time and space remains poorly constrained, despite their importance for the structure and function of coastal marine ecosystems. Here, we use a four-year dataset of particulate organic matter (POM) chemical composition ( δ 13 C, δ 15 N, C:N ratio) to quantify the relative contributions of watershed materials via riverine inputs, marine phytoplankton, and macrophytes (macroalgae and seagrass) to surface waters (0-10 m) at 11 stations representing fjord, shallow non-fjord estuary, sheltered channel and well-mixed coastal environments at the heart of the NPCTR in British Columbia, Canada. Watershed, marine phytoplankton, and macrophyte contributions to surficial POM ranged between 5-78%, 22-88%, and 0.1-18%, respectively, and varied by season and station. Watershed inputs were the primary source of POM across all stations in winter and were important throughout the year within the fjord. Marine phytoplankton were the principal source of POM in spring and at all stations outside of the fjord through summer and autumn, while macrophyte contributions were greatest in summer. These results demonstrated high, but seasonally and spatially variable, connectivity between ecosystems that are often considered in isolation of one another and highlight the need to consider coastal waters as integrated land-ocean meta-ecosystems. Future work should investigate how heterogeneity in POM sources determines its fate in coastal ecosystems,and the relative importance of different basal organic matter sources for the marine food web.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".