Eelgrass Meadow Edge Habitat Heterogeneity Enhances Fish Diversity on the Pacific Coast of Canada
Bibliographic record
Abstract
Abstract Eelgrass ( Zostera marina ) meadows are important fish habitats in temperate coastal areas. Understanding the relationships between seascape patterns—the spatial and temporal variability of biological and physiochemical drivers—and fish diversity in eelgrass meadows is crucial to conserving and managing these important habitats. The main objective of this study was to determine the environmental variables that influence the diversity of fish in eelgrass meadows in British Columbia, and whether a rich mosaic of edge habitats is positively associated with species richness and diversity, owing to the increased niche dimensionality and foraging opportunities provided by heterogeneous adjacent habitats. Using a spatiotemporal multispecies model based on long-term eelgrass fish diversity monitoring program data (2004–2020), we found that seascape variables, particularly those derived from unmanned aerial vehicles (meadow area, edge habitat heterogeneity), explained the most variation in species occurrence and abundance. We also found a positive effect of edge habitat heterogeneity on species richness in small and medium-sized meadows, with higher species richness and diversity in small and medium-sized meadows with high edge habitat heterogeneity. The relationship between edge habitat heterogeneity and species richness and diversity in large meadows was less clear. We also found that species richness has declined through time while diversity has been variable through time, remaining relatively stable in one region and generally decreasing in the other region. This analysis provides key insights into how seascape variables influence the distribution of species and the diversity of fish assemblages in nearshore eelgrass habitats in British Columbia.
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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) | 0.000 | 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".