CENTURY-LONG SYNCHRONY OF FOSSIL ALGAE IN A CHAIN OF CANADIAN PRAIRIE LAKES
Bibliographic record
Abstract
Synchronous fluctuations in limnological variables among lakes may signal that large-scale environmental factors regulate lake ecosystem structure, yet most estimates of temporal coherence are based on short (<25 yr) time series, and little is known of how synchrony varies among biological taxa or of the causes of temporal coherence. Here we used time series of 13 fossil pigments from diverse algal groups in seven lakes of the climatically sensitive Northern Great Plains to demonstrate that algal synchrony (S) during the 20th century arose mainly from interdecadal increases in algal abundance rather than from interannual coherence. Synchrony of time series differed greatly among algal taxonomic groups (S = 0.0-0.75) and was not usually spatially structured, but decreased 83% following removal of long-term trends using exponential models or first-difference calculations. Overall, coherence was greatest for labile compounds chl a (S = 0.53) and fucoxanthin (S = 0.75), possibly reflecting the influence of postdepositional degradation processes on fossil time series. However, analysis of chemically stable pigments also indicated that synchrony was great for cryptophytes (as alloxanthin, S = 0.42) and diatoms (diatoxanthin, S = 0.37), taxa that bloom in spring. In contrast, synchrony of total algal abundance was low (beta-carotene, pheophytin a, S < 0.10), reflecting low interannual coherence of summer taxa including colonial cyanobacteria and chlorophytes. Unexpectedly, past variations in climate, resource use, and urbanization explained >85% of algal variation in individual lakes, but only 35% of synchronous algal fluctuations, suggesting that the factors controlling algal synchrony differ from those regulating algal abundance.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".