Trajectories Of Zooplankton Recovery In The Little Rock Lake Whole-Lake Acidification Experiment
Bibliographic record
Abstract
Understanding the factors that affect biological recovery from environmental stressors such as acidification is an important challenge in ecology. Here we report on zooplankton community recovery following the experimental acidification of Little Rock Lake, Wisconsin, USA. One decade following cessation of acid additions to the northern basin of Little Rock Lake (LRL), recovery of the zooplankton community was complete. Approximately 40% of zooplankton species in the lake exhibited a recovery lag in which biological recovery to reference basin levels was delayed by 1-6 yr after pH recovered to the level at which the species originally responded. Delays in recovery such as those we observed in LRL may be attributable to "biological resistance" wherein establishment of viable populations of key acid-sensitive species following water quality improvements is prevented by other components of the community that thrived during acidification. Indeed, we observed that the recovery of species that thrived during acidification tended to precede recovery of species that declined during acidification. In addition, correspondence analysis indicated that the zooplankton community followed different pathways during acidification and recovery, suggesting that there is substantial hysteresis in zooplankton recovery from acidification. By providing an example of a relatively rapid recovery from short-term acidification, zooplankton community recovery from experimental acidification in LRL generally reinforces the positive outlook for recovery reported for other acidified lakes.
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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) | 0.001 | 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".