Rocky intertidal community structure in oceanic islands: scales of spatial variability
Bibliographic record
Abstract
There is a clear bias in the literature on island ecology towards terrestrial rather than marine systems, which have remained comparatively poorly studied.Marine populations are typically open, and local production may have little impact on local recruitment, such that long-distance dispersal is an important determinant of population ecology.Since oceanic islands form discrete patches of habitat surrounded by a structurally different environment, we tested the general hypothesis that processes operating at the scale of islands have a greater influence on these populations than the processes operating at smaller, intra-island scales.A hierarchical design examined the patterns of abundance and distribution of conspicuous taxa at 3 tidal heights at a range of spatial scales, ranging from a few meters to hundreds of kilometres apart in the rocky intertidal of the Azores.Both uni-and multivariate analyses showed that at the largest scale (islands), significant variation was detected in the lower and mid-shore communities, but not on the upper shore.Along the vertical gradient of immersion there was a trend for increasing small-scale patchiness towards the top of the shore.The potential role of local environmental stress gradients and broad-scale oceanographic patterns of recruitment in structuring these assemblages is discussed.This study corroborates the suitability of the analytical tools used here to examine patterns of distribution over a range of spatial scales and its applicability in the field of island marine ecology.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".