Taxonomic and functional-trait metrics track recovery of demersal fish and shrimp communities following system collapse
Bibliographic record
Abstract
Monitoring programs that integrate both structural and functional ecosystem components play integral roles in ecosystem management and conservation planning. In the early 1990’s, the marine ecosystem of the waters surrounding Newfoundland and Labrador (NL) underwent a regime shift. Several demersal and pelagic fish stocks collapsed simultaneously, and this had significant ecological and socioeconomic consequences. As this regime shift impacted numerous commercial and non-commercial species, assessments based on individual species would be insufficient. We explored a variety of metrics that capture different facets of diversity across multiple species to provide a more robust ecosystem assessment. These were species richness, evenness, community-weighted means of maximum body length and trophic level (i.e., the mean maximum body size or trophic level of the species present in a community), and functional dispersion (FDis). The objectives of this study were 1) to assess trends in community structure of the NL demersal community during the post-collapse period (1995-2018), 2) explore how the various community-level metrics differ or are redundant, and 3) investigate how these metrics are associated with important covariates. Several metrics were redundant and displayed strongly positive, temporal trends being consistent with expectations for a recovery encompassing the entire demersal community. In particular, unweighted community-weighted means of body length and trophic level displayed nearly equal temporal patterns, showing increasing trends throughout the study period which were most prominent in the northern study area and within a limited depth range at the upper shelf break. Corresponding biomass-weighted metrics were also correlated with each other but only showed similar increasing tendencies after the first decade. In contrast, species richness did not show any temporal increase. Evenness and biomass-weighted FDis showed similar temporal patterns, decreasing during the first decade followed by strong increases during subsequent years, patterns that were directly linked to variation in Northern shrimp and Atlantic cod biomass. This study demonstrates how a variety of community metrics can provide insight into different aspects of the post-collapse recovery of the demersal community and help us better understand the complexity of the changes the ecosystem is undergoing.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".