Bibliographic record
Abstract
Among vertebrates, coral reef fishes are a spectacularly diverse group currently threatened by different forms of human activities. Such a situation has added impetus to the understanding of ecological processes that regulate their diversity. The aim of this dissertation is to assess the role of dispersal in processes that maintain the diversity of coral reef fishes at levels of integration ranging from populations to communities. I started by reviewing existing information of dispersal in coral reef fishes and showing that critical methodological artifacts, biases and alternative interpretations limit any conclusion on the extent to which reef fish populations are "open" or "closed" systems. I then used a variety of approaches and databases to show that during the process of dispersal species interchange propagules among populations (Chapters 2, 3, 4) likely affecting the dynamics of their populations, the geographical extent of their range (Chapter 5) and their presence in communities within the range (Chapter 6). These broad effects of dispersal on diversity patterns suggest that the maintenance of coral reef fish diversity will strongly depend on the extent to which conservation strategies warranty the connectivity that maintain such patterns. This thesis is one of the first attempt to unify principles for the development of a paradigm to apply dispersal theory to different levels of biological organization at different spatial scales.Dept. of Biological Sciences. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .M673. Source: Dissertation Abstracts International, Volume: 66-07, Section: B, page: 3518. Thesis (Ph.D.)--University of Windsor (Canada), 2005.
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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 | 0.001 | 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) | 0.005 | 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".