The genetic implications of habitat fragmentation for animalsThis review is one of a series dealing with some aspects of the impact of habitat fragmentation on animals and plants. This series is one of several virtual symposia focussing on ecological topics that will be published in the Journal from time to time.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The past decade has seen a rapid increase in the number of studies dealing with the genetic consequences of habitat fragmentation, in large part because of the increasing accessibility of techniques for assessing molecular genetic variation in wild populations. This body of work is extremely diverse and encompasses a variety of approaches that define and measure both habitat fragmentation and its potential genetic impacts. Here, I summarize the main questions that are being addressed, and approaches being taken, in empirical studies of the genetic impacts of habitat fragmentation in animals. Considerable effort has been spent in documenting how levels of genetic diversity, and the spatial distribution of that diversity, are altered by habitat fragmentation. However, proportionately less effort has been invested in directly examining specific genetic and evolutionary processes that may affect the persistence of populations inhabiting fragmented landscapes: inbreeding depression, the loss of adaptive potential, and the accumulation of deleterious mutations. One area in which considerable progress has been made over the past decade is in the development and application of novel methods for inferring demographic and landscape ecological characteristics of animals, particularly dispersal patterns, using genetic tools. In this area, a significant integration of genetic and ecological approaches in the study of fragmented populations is occurring.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it