Increased Terrestrial Perturbations Modify Skeletal Properties and Mechanical Strength of Hard Corals
Bibliographic record
Abstract
Skeleton properties determine coral survival by influencing the range of hydraulic conditions colonies can withstand, selection of suitable habitat, ability to compete for space and light, repair damage and the overall fitness and ecological success of scleractinian corals. Skeletal properties of 16 coral species comprising 3 growth forms collected from Kenyan coral reef lagoons were investigated and found to vary considerably not only between species but between reefs as well, with corals exposed to both sediment and nutrients showing consistent lower skeleton density and strength but high porosity compared to those from sediment-unaffected reefs. Further, high skeletal density and strength but low porosity values were measured in branching relative to other growth forms. The present findings also suggest that the negative effects of nutrients on skeleton properties may be counteracted by high hydrodynamic energy, resulting in stronger skeletons in high hydrodynamic energy-nutrient-polluted reef habitats relative to pristine reefs. These findings have important ecological and management implications with regard to the existence, persistence, productivity and protective value of reefs, damage risks, maintenance and conservation of biological diversity with respect to future global climate change events. Consequently, appropriate watershed, reef and fisheries management options the impacts of local anthropogenic stresses (sediments, nutrients, overexploitation) would be expected to alleviate the effects of these disturbances and have the potential to minimize future large-scale coral reef damage resulting from increased and frequent global climate change events, such as increased ocean acidification (due to elevated atmospheric CO2) and sea surface temperature.
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".