Quantifying Recent Ecological Changes in Remote Lakes of North America and Greenland Using Sediment Diatom Assemblages
Bibliographic record
Abstract
BACKGROUND: Although arctic lakes have responded sensitively to 20(th)-century climate change, it remains uncertain how these ecological transformations compare with alpine and montane-boreal counterparts over the same interval. Furthermore, it is unclear to what degree other forcings, including atmospheric deposition of anthropogenic reactive nitrogen (Nr), have participated in recent regime shifts. Diatom-based paleolimnological syntheses offer an effective tool for retrospective assessments of past and ongoing changes in remote lake ecosystems. METHODOLOGY/PRINCIPAL FINDINGS: We synthesized 52 dated sediment diatom records from lakes in western North America and west Greenland, spanning broad latitudinal and altitudinal gradients, and representing alpine (n = 15), arctic (n = 20), and forested boreal-montane (n = 17) ecosystems. Diatom compositional turnover (beta-diversity) during the 20(th) century was estimated using Detrended Canonical Correspondence Analysis (DCCA) for each site and compared, for cores with sufficiently robust chronologies, to both the 19(th) century and the prior approximately 250 years (Little Ice Age). For both arctic and alpine lakes, beta-diversity during the 20(th) century is significantly greater than the previous 350 years, and increases with both latitude and altitude. Because no correlation is apparent between 20(th)-century diatom beta-diversity and any single physical or limnological parameter (including lake and catchment area, maximum depth, pH, conductivity, [NO(3)(-)], modeled Nr deposition, ambient summer and winter air temperatures, and modeled temperature trends 1948-2008), we used Principal Components Analysis (PCA) to summarize the amplitude of recent changes in relationship to lake pH, lake:catchment area ratio, modeled Nr deposition, and recent temperature trends. CONCLUSIONS/SIGNIFICANCE: The ecological responses of remote lakes to post-industrial environmental changes are complex. However, two regions reveal concentrations of sites with elevated 20(th)-century diatom beta-diversity: the Arctic where temperatures are increasing most rapidly, and mid-latitude alpine lakes impacted by high Nr deposition rates. We predict that remote lakes will continue to shift towards new ecological states in the Anthropocene, particularly in regions where these two forcings begin to intersect geographically.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".