Ecological resilience in tropical Andean lakes: A paleolimnological perspective
Bibliographic record
Abstract
Abstract Little is known about whether changes in lake ecosystem structure over the past 150 years are unprecedented when considering longer timescales. Similarly, research linking environmental stressors to lake ecological resilience has traditionally focused on a few sentinel sites, hindering the study of spatially synchronous changes across large areas. Here, we studied signatures of paleolimnological resilience by tracking change in diatom community composition over the last 2000 years in four Ecuadorian Andean lakes with contrasting ecoregions. We focused on climate and anthropogenic change, and the type of biological responses that these changes induced: gradual, elastic, or threshold. We combined multivariate ordination techniques with nonlinear time‐series methods (hierarchical generalized additive models) to characterize trajectories of community responses in each lake, and coherence in such trajectories across lakes. We hypothesized that remote, high‐elevation lakes would exhibit synchronous trends due to their shared climatic constraints, whereas lower elevation lakes would show less synchronous trends as a consequence of human density and land‐cover alteration. We found that gradual and elastic responses dominated. Threshold‐type responses, or regime shifts, were only detected in the less remote lake, after a long period of gradual and elastic changes. Unexpected synchrony was observed in diatom assemblages from geographically distant and human‐impacted lakes, whereas lakes under similar broad‐scale environmental factors (climate and ecoregion) showed asynchronous community trajectories over time. Our results reveal a complex ecological history and indicate that Andean lakes in Ecuador can gradually adapt and recover from a myriad of disturbances, exhibiting resilience over century to millennial timescales.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".