Habitat alterations and population isolation: The caribou case
Bibliographic record
Abstract
Human-induced habitat alterations are one of the biggest threats to biodiversity globally. Habitat fragmentation particularly has been linked to increased risk of extirpations through decreases in dispersal leading to population isolation. Isolation of populations may be a result of three major scenarios: (1) Isolation by Distance (IBD), (2) Isolation by Environment (IBE), and (3) Isolation by Barrier (IBB). Recent results have shown that caribou (Rangifer tarandus), a threatened habitat specialist, are experiencing population isolation in Western Canada. Our work aims to discover drivers of population isolation of caribou owing to three potential hypotheses: Population isolation of caribou is a result of (H1) lack of food and shelter in the areas between habitat fragments, (H2) predation pressure and human infrastructure, or (H3) physical barriers to dispersal (roads, cutblocks, and non-road linear features), along with the null (H0): Isolation by Distance (IBD). Using Resource Selection Functions (RSFs) and Least-Cost Path analysis (LCP), cost distances associate with travel between habitat patches were created and compared to genetic distance between individuals using partial Mantel tests to understand which factors are driving population isolation in British Columbia’s caribou. Here we show that genetic patterns of isolation in caribou can be explained by a combination of geographic distance (IBD) and habitat (un)suitability in the areas between know population ranges –i.e. a form of IBE. Our findings demonstrate that habitat preferences are dictated by forest stand age (older forests), slope (flatter), and land cover type (open lichen woodlands and mixed conifer forests for example). Habitat preferences also differed seasonally, reflecting specific requirements linked to caribou life cycles Each additional isolation hypotheses (above) were also supported, but likely acting simultaneously; and we are using casual modeling to rank isolation factors. Using RSF models to create resistant surfaces allowed for the discovery of corridors of conservation concern. Our results allow for a better understanding of the relationship between loss of critical habitat, habitat fragmentation, and isolation of populations. Additionally, defining key ecological features that lead to the isolation of populations allows for targeted measures for the conservation of caribou, and of other sympatric species. Finally, our project originally links habitat to affected genetic diversity of species and is transferable to other terrestrial animals also impacted by fragmentation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".