Nestedness in insular floras: spatiotemporal variation and underlying mechanisms
Bibliographic record
Abstract
Nestedness is a characteristic of insular metacommunity structure. Relatively few studies, however, have attempted to evaluate temporal changes in nestedness, or elucidate the mechanisms underlying nestedness. I evaluated both spatial and temporal patterns of nestedness in the insular floras of four archipelagoes of small islands in the Bahamas and the potential underlying environmental gradients. The NODF (a nestedness metric based on overlap and decreasing fill) and the matrix temperature measure, T, were used to quantify nestedness in insular floras on small islands near Abaco, Andros, Great Exuma and the Exuma Cays, Bahamas. Two different null models were employed for each nestedness measure. Six environmental variables were evaluated in relation to nestedness by ordering islands according to gradients and recalculating NODF scores. All archipelagoes were significantly nested. Nestedness among sites contributed more to overall nestedness than did nestedness among species. NODF scores varied among archipelagoes, but were surprisingly constant over time. Ordering islands by vegetated area yielded the highest nestedness scores for three archipelagoes; ordering islands by protection from exposure yielded the highest nestedness score for one archipelago. Nestedness scores varied little over time even though species compositions changed, indicating that extinctions occurred in a deterministic manner. The relative importance of area suggests extinction is an important mechanism in producing nestedness. Attempting to determine the relative importance of immigrations or extinctions requires some assumptions, however, and both processes are likely cumulative in most cases.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".