Climate change impacts on coastal ecosystems
Bibliographic record
Abstract
Abstract As the planet undergoes unprecedented climate changes, coastal ecosystems stand at the frontline of ocean-land interactions and environmental changes. This overview explores the various climate-related challenges transforming coastal ecosystems and their responses to these pressures. Key climate-related stressors—including warming, sea level rise, ocean acidification, changes to freshwater availability, and shifts in circulation and disturbance patterns—pose significant threats to both the structure and function of these ecosystems. These stressors impact every level of biological organization, with modern responses manifesting as ecosystem degradation and shifts toward simpler, less biodiverse states—trends likely to intensify with ongoing emissions. Compounded by local human disturbances, these stressors risk overwhelming the adaptive capacity of coastal ecosystems, restructuring coastal food webs, and compromising the essential ecosystem services that currently underpin productivity, storm protection, and water quality in coastal zones. Future trajectories of change in coastal ecosystems will largely depend on the extent of future greenhouse gas emissions and human activities in and around coastal zones. However, critical knowledge gaps remain, particularly regarding the interactions among stressors and the nature of ecological tipping points. Addressing these gaps through further research will be necessary to improve projections of future impacts and support the conservation and resilience of these valuable 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".