EFFECTS OF CLIMATE CHANGE ON GLOBAL SEAWEED COMMUNITIES
Bibliographic record
Abstract
Seaweeds are ecologically important primary producers, competitors, and ecosystem engineers that play a central role in coastal habitats ranging from kelp forests to coral reefs. Although seaweeds are known to be vulnerable to physical and chemical changes in the marine environment, the impacts of ongoing and future anthropogenic climate change in seaweed-dominated ecosystems remain poorly understood. In this review, we describe the ways in which changes in the environment directly affect seaweeds in terms of their physiology, growth, reproduction, and survival. We consider the extent to which seaweed species may be able to respond to these changes via adaptation or migration. We also examine the extensive reshuffling of communities that is occurring as the ecological balance between competing species changes, and as top-down control by herbivores becomes stronger or weaker. Finally, we delve into some of the ecosystem-level responses to these changes, including changes in primary productivity, diversity, and resilience. Although there are several key areas in which ecological insight is lacking, we suggest that reasonable climate-related hypotheses can be developed and tested based on current information. By strategically prioritizing research in the areas of complex environmental variation, multiple stressor effects, evolutionary adaptation, and population, community, and ecosystem-level responses, we can rapidly build upon our current understanding of seaweed biology and climate change ecology to more effectively conserve and manage coastal ecosystems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".