Breaking ecological barriers: anthropogenic disturbance leads to habitat transitions, hybridization, and high genetic diversity
Bibliographic record
Abstract
Genetic diversity is expected to erode in disturbed habitats through strong selection, local extinctions, and recolonization associated with genetic bottlenecks and restricted gene flow. Despite this general prediction and over three decades of population genetics studies, our understanding of the long-term effect of environmental disturbance on local and regional genetic diversity remains limited. We conducted a population genetic survey of the microcrustacean Daphnia across a landscape subject to anthropogenic stressors from a century of industrial mining. At the local scale we found moderate genetic diversity (i.e., low clonal diversity), characteristic of habitat-specific selective sweeps and local extinctions, but high diversity and strong genetic structure at the regional scale despite the shared watershed of many lakes and exceptional dispersal ability of daphniids. Many habitats experienced changes in species assemblages, with the obligate asexual Daphnia pulex lineages—known only to inhabit ponds—dominating disrupted urban lakes. This habitat transition (pond to lake) was likely facilitated by the disruption of ecological barriers maintaining the genomic separation of these young species. Thus, disrupted habitats can exhibit complex and unexpected genetic patterns of local extinctions and recolonizations, followed by habitat transitions, hybridization and potential speciation events that are difficult to predict and should not be underestimated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.014 |
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".