Contrasting resistance and resilience trajectories of zooplankton communities in restored fishless alpine lakes
Bibliographic record
Abstract
Abstract Catastrophic state changes often occur in ecosystems as consequences of shifts in the dominant life forms, such as in the case of sportfish introduction into naturally fishless mountain lakes. While the pronounced ecological displacement of native communities by these novel predators (i.e., weak resistance) is well documented, few studies have also examined the dynamics of their recovery rates (i.e., “engineering resilience”) following stressor removal. We addressed this knowledge gap by quantifying the taxonomic and species trait‐based ordination trajectories of crustacean zooplankton communities in stocked alpine lakes, which differed in how they were restored to a natural fishless state over a period of six decades. Resilience and resistance trajectories differed in each lake as the ecological importance of trait‐based species recolonization potential (e.g., asexual vs. sexual reproduction) replaced that of tolerance of size‐selective predation by fish (e.g., body size, pigmentation, motility). As a result, re‐establishment of large‐bodied zooplankton following the elimination of fish restored annual secondary production. In contrast, a more gradual unidirectional ordination trajectory toward smaller zooplankton body size and a decline in total zooplankton biomass occurred in a nearby alpine lake containing a protected native bull trout population. Although recovery trajectories returned via routes that differed from those of earlier resistance trajectories (i.e., hysteresis), we discovered that full taxonomic and functional recovery was realized in all the restored fishless lakes within three decades, regardless of the approach used to achieve ecosystem restoration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".