The Effect of Drying Boreal Lakes on Plants, Soils, and Microbial Communities in Lake Margin Habitats
Bibliographic record
Abstract
Abstract Decadal scale lake drying in interior Alaska results in lake margin colonization by willow shrub and graminoid vegetation, but the effects of these changes on plant production, biodiversity, soil properties, and soil microbial communities are not well known. We studied changes in soil organic carbon (SOC) and nitrogen (N) storage, plant and microbial community composition, and soil microbial activities in drying and non‐drying lakes in the Yukon Flats National Wildlife Refuge. Historic changes in lake area were determined using Landsat imagery. Results showed that SOC storage in drying lake margins declined by 0.13 kg C m−2 yr−1 over 30 years of exposure of lake sediments, with no significant change in soil N. Lake drying resulted in an increase in graminoid and shrub aboveground net primary production (ANPP, +3% yr−1) with little change in plant functional composition. Increases in ANPP were similar in magnitude (but opposite in sign) to losses in SOC over a 30‐year drying trend. Potential decomposition rates and soil enzyme activities were lower in drying lake margins compared to stable lake margins, possibly due to high salinities in drying lake margin soils. Microbial communities shifted in response to changing plant communities, although they still retained a legacy of the previous plant community. Understanding how changing lake hydrology impacts the ecology and biogeochemistry of lake margin terrestrial ecosystems is an underexamined phenomenon with large impacts to landscape processes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".