Conservation genetics of exploited Amazonian forest tree species and the impact of selective logging on inbreeding and gene dispersal in a population of Carapa guianensis
Bibliographic record
Abstract
The Amazon region is one of the richest areas on the planet in terms of its biodiversity and natural resources. The large scale harvesting of trees in this region is a relatively new activity, and it is uncertain whether the exploitation of timber species will result in depletion of forest genetic resources. To examine this, I have assessed levels of inbreeding, gene flow, and genetic diversity in populations of Amazonian forest trees undergoing logging. Because of their high variability within populations, microsatellite genetic markers were chosen for the study, and it was verified through an initial sampling experiment that this class of markers is sufficiently stable within somatic tissue of large and long-lived trees such that population studies could be undertaken with them. By sampling adult trees and seed progenies at several microsatellite loci, high levels of gene flow and low levels of inbreeding were found within populations of Sextonia rubra and Carapa guianensis, two important insect-pollinated Amazonian forest tree species. Comparing seed progeny collected before versus after selective logging of a population of Carapa guianensis, no measurable evidence was found that that the population genetic dynamics is impacted by logging. In particular, levels of inbreeding, gene flow, and population substructure were the same before and after logging. Comparing different populations distributed over the Amazon basin, a phylogeographical structure in the chloroplast DNA of Carapa guianensis that corresponds to major tributaries of the Amazon river was discovered, suggesting that seed dispersal through rivers may contribute to genetic connectivity among populations. Overall, the results of this thesis suggest that the large effective population sizes, the high levels of gene flow, and the low levels of inbreeding in exploited Amazonian tree populations may allow them to counteract potential negative genetic impacts of selective logging, at least at the levels of harvesting carried out during this study, and for the Carapa guianensis population investigated.
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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 | 0.000 | 0.001 |
| 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 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".