Northeast Pacific eelgrass dynamics: interannual expansion distances and meadow area variation over time
Bibliographic record
Abstract
Ecosystems constantly change, yet managers often lack information to move beyond static habitat assumptions. As human impacts and geographic information systems advance, it is important and feasible to quantify past habitat boundary shifts to inform management decisions (e.g. protective perimeters) robust to near-term habitat changes. This is the case in eelgrass (Zostera spp.), an ecosystem engineer that forms dynamic, often protected meadows. Practitioners protect areas to avoid human stress to eelgrass, but they can lack quantitative descriptions of the near-term potential for eelgrass meadows to shift into unprotected areas. Here, we quantified interannual eelgrass meadow boundary shifts within 23 sites spanning 9 decades and 19° latitude. Eelgrass meadow boundaries typically shifted into areas tens of meters away from previous meadow edges, but sometimes much farther. Also, eelgrass meadows often vacated and later recolonized the same areas. By implication, eelgrass protection efforts may be enhanced by considering that presently vacant areas may be inhabited in the future, especially near currently existing meadows. Additionally, eelgrass meadows changed less over time at sites less modified by people within temperate landscapes compared to sites located within human-dominated, warmer, and drought-prone landscapes with limited water turnover. We thus hypothesize that eelgrass meadows change more over time within landscapes exposed to greater stressor regimes because they more frequently or intensely cycle through disturbance and recovery phases. These results inform tactical decisions seeking to mitigate impacts of human activities to eelgrass and underscore the potential synergy of monitoring, research, and adaptive management approaches to protect dynamic habitats.
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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) | 0.002 | 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 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".