Replication Data for: Ice age refugium shows potential of geohistorical data to guide modern conservation efforts
Bibliographic record
Abstract
This repository contains the code and data required to replicate Figures 3, 4, S1–S3, and Movies S1-S3 for the manuscript entitled "Geohistorical data reveal an ice age refugium with implications for modern conservation." Also contains the code required to perform the associated Monte Carlo simulations. Manuscript summary: Identifying refugia can provide important insights for conservationists planning protected areas. However, most current methods for identifying refugia emphasize short-term survivorship during a crisis rather than long-term recovery. Here, we propose a method for identifying refugia that emphasizes range re-expansion, and we present a case study using pollen data from three plant taxa over the past 20 kyr in northern Alaska, USA to evaluate the method’s validity. We identified a substantial decrease and subsequent recovery in spruce presence across the study region between 16.0–11.0 ka and tested the pattern’s significance using a Monte Carlo analysis. During this interval of relatively warm and dry regional climate, spruce persisted in one locality that acted as a source for post-crisis re-expansion, indicating that this locality was a refugium. Using this method to understand how successful refugia form in different crises would provide conservationists with more informative guidelines for planning protected areas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.089 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.602 | 0.336 |
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".