Diverse stability responses of a sub-Antarctic invertebrate understorey community to experimental giant kelp removal
Bibliographic record
Abstract
Ecological stability is crucial for understanding anthropogenic biodiversity loss and its consequences, especially when disturbances affect species that influence numerous others. The giant kelp Macrocystis pyrifera, an iconic foundation species, supports diverse communities on temperate and subpolar coasts. While giant kelp communities in temperate regions have been extensively studied, field-based manipulative research in subpolar latitudes is still limited. We investigated the resistance, resilience, and recovery of a community subjected to experimental giant kelp removal in a sub-Antarctic ecosystem. We simulated pulsed kelp loss caused by destructive storms and monitored the macrobenthic invertebrate understorey for 12 mo. The experimental disturbance elicited varying stability responses of the understorey. Understorey community biomass was strongly resistant to the disturbance but declined gradually (i.e. low resilience), showing incomplete recovery compared to undisturbed communities. Community density (total number of individuals per sample) increased notably following the removal (i.e. weak resistance) but ultimately returned to undisturbed levels (i.e. high resilience and complete recovery). Species composition exhibited low resistance and resilience, and no recovery from the disturbance. Secondary coextinctions of several understorey species accounted for the observed low compositional stability. In contrast to giant kelp communities in temperate latitudes, the slower recovery rates of kelp and the loss of key positive interactions likely contributed to the observed stability responses in this subpolar ecosystem’s invertebrate understorey. By examining the response of a sub-Antarctic understorey community to giant kelp removal, our study enhances our understanding of how foundation species sustain local biodiversity.
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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".