Climate Change Drives Bathymetric Shifts in Taxonomic and Trait Diversity of Deep‐Sea Benthic Communities
Bibliographic record
Abstract
Climate-induced changes in environmental gradients can cause shifts in ranges of organisms and community composition, with concomitant effects on ecosystem functions. Throughout geological time, deeper depths have been highlighted as refugia for biodiversity and ecosystem functions under a warming climate. Although the deep ocean provides several important ecosystem services, contemporary research on climate effects at the community and ecosystem levels has been limited to the upper 200 m of the water column. As a result, our knowledge of climate-induced impacts on the functions of deep-sea ecosystems is scarce. In this study, we examined climate-induced changes in deep-sea communities at a climate-change hotspot, the Gulf of Maine and adjacent continental slope in the Northwest Atlantic. We focused on deep-water coral communities, which are among the most diverse in the deep sea. Using a joint species distribution model, we projected and examined community composition, taxonomic diversity, and trait diversity of deep-water coral communities under two climate scenarios for the end of the century (2100). We found extensive shifts of suitable habitat for several coral genera from 500-1000 to 1500-2000 m, mostly attributed to warming in the upper 1000 m. This led to substantial reduction (30%-60%) in the existing taxonomic and functional richness at the upper continental slope, alongside gains in richness (10%-15%) at the lower continental slope and bathyal zone. Our study is the first to report extensive shifts in biodiversity from mesopelagic to bathyal depths, which will inevitably cause redistribution of ecosystem functions and services. These results showcase that climate change impacts at the ecosystem level are not restricted to shallow depths and highlight that further knowledge of them is essential for efficient conservation, planning, and management.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".