Unraveling goitered gazelle (Gazella subgutturosa) diversification: insights from phylogeography and species distribution modeling
Bibliographic record
Abstract
Abstract The impact of climate fluctuations on the genetic diversity and distribution of species is of particular concern for large mammals that are already at risk of extinction. In this study, we investigated the genetic status of populations, the evolutionary relationships, and the current and future state of population dispersion of the goitered gazelle, Gazella subgutturosa, using 109 mtDNA sequences (cytb) and species distribution modeling. We assessed the impact of past (Last Glacial Maximum [lgm: 21 Kya] and Mid-Holocene [6 Kya]), current, and future (2070) climate on the phylogeography and spatial distribution of the species. Our results indicate evidence of divergence of two main clades (G. subgutturosa subgutturosa, and G. subgutturosa yarkandensis) (1.052 Mya) and a further split between two clades of G. s. subgutturosa (Middle Eastern and Central Iranian) in the middle Pleistocene. Historical species distribution models suggest the species’ range has not changed much across all periods examined, but there has been a decreasing trend from 21k to the current. Future climate projections (bcc-csm1 and ccsm4, rcp s 4.5 and 6 scenarios) predict a contraction of suitable habitat at the northern and southern edges of the species’ current distribution, shifting the range to the center of the study area. Biogeographic analyses suggest that vicariance and dispersal events have shaped the genetic structure of G. subgutturosa. Our findings suggest that the current genetic structure of the species is potentially related to Pleistocene climatic fluctuations and refuges (Alborz, Zagros, and Kope Dagh Mountains) during cold periods. The study highlights the importance of understanding the genetic status of populations and their evolutionary relationships to effectively prevent further declines of species at risk of extinction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".