Avian-Driven Modification of Seasonal Carbon Cycling at a Tundra Pond in the Hudson Bay Lowlands (Northern Manitoba, Canada)
Bibliographic record
Abstract
The past ∼40 years have seen a geometric increase (5–7% per year) in the size of the lesser snow goose (LSG; Chen caerulescens caerulescens) population and marked spatial expansion of the area they inhabit within the coastal fen ecotype of Wapusk National Park (Hudson Bay Lowlands, northern Canada), raising concerns and uncertainty about the environmental effects of their activities (grubbing of vegetation, soil disturbance, deposition of feces) on the abundant shallow tundra ponds. In this study, we use conventional limnological measurements as well as water and carbon (C) isotope tracers to explore similarities and differences in seasonal patterns of hydrological, limnological, and biogeochemical conditions of 15 shallow coastal fen ponds that currently have minimal (if any) disturbance from the LSG population with one pond (WAP 20) that is subject to substantial LSG activity. Carbon isotope measurements reveal that C cycling at WAP 20 (LSG-disturbed site) is markedly different compared to the other ponds, whereas only small differences were observed in hydrological conditions and concentrations of major nutrients and chlorophyll a of pond water. A mid-summer decrease in C isotope composition of dissolved inorganic carbon (DIC) occurred at WAP 20, likely as a consequence of high pond-water pH and intense C demand by aquatic productivity. These conditions appear to have promoted “chemically enhanced CO2 invasion,” which causes strong kinetic C isotope fractionation. High C demand at WAP 20 is also suggested by mid-summer 13C enrichment in particulate organic matter. In contrast, the ponds with little to no LSG activity exhibited expected seasonal C isotope behavior (i.e., 13C enrichment of DIC) under conditions of increasing productivity when C is in relatively low demand. Small differences in nutrient concentrations may be due to rapid uptake by the benthic mat at WAP 20. Data from the low disturbance ponds also provide baseline information for future studies assessing potential effects of LSG.
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".