Intertidal community responses to field‐based experimental warming
Bibliographic record
Abstract
As the climate warms, there is little doubt that ecosystems of the future will look different from those we see today. However, community responses to warming in the field are poorly understood. We examined the effects of field‐based warming on intertidal communities in the Salish Sea, which is a regional thermal ‘hot spot’ and therefore a model system for studying thermally stressed communities. We manipulated temperature at three tidal heights by deploying black‐ and white‐bordered settlement plates. Black plates increased in situ substratum temperature by an average of 2.6°C (maximum temperature, 40.9°C). Barnacles fared poorly on black plates in all zones. When overall thermal stress was highest (summer in the high intertidal zone) herbivores were absent. In lower tidal zones, herbivores were abundant on white plates but were scarce on black plates. The total percent cover of algae was unaffected by the temperature treatment, despite the fact that macroalgae were expected to be the least thermally tolerant functional group. However, we did find that ephemeral green algae exhibited a delay in phenology on black plates. We also found that species richness declined and invertebrate assemblage structure was altered due to warming. Results from this year long experiment suggest that communities in thermally stressful habitats respond to warming via the interplay between species‐specific thermal responses and secondary adaptive strategies such as behavioral microhabitat selection. Declines in diversity and changes in the invertebrate assemblage were due to the decline of local thermally‐stressed species and the lack of replacement by warm‐adapted species. Given the low variation in the species pool along the northeast Pacific coastline, the arrival of warm‐adapted species to the Salish Sea may not occur over relevant time scales, leaving local communities depauperate.
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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) | 0.003 | 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".