Demography, genetic, and extinction process in a spatially structured population of lekking bird
Bibliographic record
Abstract
Abstract Understanding the mechanisms underlying biological extinctions is a critical challenge for conservation biologists. Both deterministic (e.g. habitat loss, fragmentation) and stochastic (i.e. demographic stochasticity, Allee effect) demographic processes are involved in population decline. Simultaneously, a decrease of population size has far-reaching consequences for genetics of populations by increasing the risk of inbreeding and the effects of genetic drift, which together inevitably results in a loss of genetic diversity and a reduced effective population size ( N e ). These genetic factors may retroactively affect vital rates (a phenomenon coined ‘inbreeding depression’), and therefore reduce population growth and accelerate the extinction process of small populations. To date, few studies have simultaneously examined the demographic and genetic mechanisms driving the extinction of wild populations, and have most of the time neglected the spatial structure of populations. In this study, we examined demographic and genetic factors involved in the extinction process of a spatially structured population of a lekking bird, the western capercaillie ( Tetrao urogallus ). To address this issue, we collected capture-recapture and genetic data over a 6-years period in Vosges mountains, France. Our study showed that the population of T . urogallus experienced a severe decline between 2010 and 2015. We did not detect any Allee effect on survival and recruitment. By contrast, individuals of both sexes dispersed to avoid small leks, suggesting a behavioral response to a mate finding Allee effect. In parallel to this demographic decline, the population showed a low genetic diversity and high inbreeding. In addition, the effective population sizes at both lek and population levels was low. Despite this, we did not detected evidence of inbreeding depression: neither survival nor recruitment were affected by individual inbreeding level. Our study underlines the benefit from combining demographic and genetic approaches to investigate processes that are involved in biological extinctions.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".