Environmental Filtering Drives Widespread Trait Convergence in Marine Demersal Ray‐Finned Fishes
Bibliographic record
Abstract
ABSTRACT Aim Understanding the processes that shape the distribution of biodiversity in the oceans is central for predicting and conserving ecosystems under global change. Although a vast literature exists on drivers of species diversity, the geographical patterns and drivers of ecosystem functioning, and in particular the traits that shape this functioning, remain relatively unexplored. We address this gap by testing the effects of environment, fishing pressure and evolutionary history on fish trait compositions across continental shelf seas using scientific trawl surveys. Location Northern Hemisphere shelf seas. Time Period 1999–2021. Major Taxa Studied Marine demersal ray‐finned fishes. Methods Here, we aggregate trawl and trait information (body size, habitat, reproduction, trophic ecology and growth) for 1164 demersal ray‐finned fishes on continental shelf seas throughout the Northern Hemisphere to test the relative importance of environmental, evolutionary and anthropogenic drivers in shaping trait compositions. These patterns are tested across three different spatial scales (100 km 2 to marine Ecoregions) using linear and non‐linear models. We also compare trait compositions to expectations under null and neutral models. Results Trait compositions throughout shelf seas are always positively related to environmental conditions but appear strongly associated with evolutionary history on the northeast Pacific shelves. Although fishing can alter individual traits and deplete populations, it shows no explanatory power in describing trait compositions. The majority (81%) of trait compositions are more similar than expected under neutral drift. Main Conclusions We find that environmental filtering has strongly shaped the functional convergence of fish communities while, in contrast to expectations, phylogenetic conservatism across evolutionary lineages appears uniquely strong in the Pacific Ocean but less important in the Atlantic. The widespread role of environmental conditions in shaping fish traits highlights the potential sensitivity of community functioning to environmental and climate change and sheds new light on the potential for trait‐based conservation strategies.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".