Urbanization drives genetic erosion and population structure in a historically connected carnivore population
Bibliographic record
Abstract
Abstract Urbanization is a dominant driver of habitat fragmentation globally, creating small, isolated wildlife populations vulnerable to accelerated genetic drift, reduced genetic diversity, and increased population differentiation. We investigated how urban development affects the genetic composition and structure of caracals ( Caracal caracal ) in Cape Town, South Africa using microsatellites and mitochondrial DNA sequence data. Sampling across four geographically disparate urban and rural populations revealed contrasting temporal patterns: mitochondrial markers indicated historical genetic connectivity among populations, while microsatellite data demonstrated recent genetic structuring driven primarily by urbanization. An extensively isolated urban population showed reduced allelic richness and pronounced genetic differentiation, reflecting urbanization as a strong barrier to gene flow. Within the isolated urban population, GPS-collared caracals demonstrated a degree of spatial genetic organization, with related individuals maintaining significantly higher home range overlap despite inhabiting a severely fragmented urban landscape. This kin-structured space use occurred despite caracals in the system having large home ranges compressed within a relatively small, isolated environment. Our findings reveal that urbanization has rapidly disrupted gene flow in this otherwise geographically widespread and adaptable carnivore, imposing a sufficient barrier to generate detectable genetic consequences within contemporary timeframes. The contrasting signals from historical versus contemporary molecular markers highlight urbanization’s role in fragmenting previously connected populations and demonstrates the value of multi-marker approaches for detecting anthropogenic impacts on wildlife populations. These results underscore urbanization’s capacity to rapidly alter population genetic dynamics, even in a highly mobile and adaptable carnivore.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".