Genetic Variation in Abies religiosa for Quantitative Traits and Delineation of Elevational and Climatic Zoning for Maintaining Monarch Butterfly Overwintering Sites in Mexico, considering Climatic Change
Bibliographic record
Abstract
Abstract Conservation of Abies religiosa (sacred fir) within the Monarch Butterfly Biosphere Reserve (MBBR) in Mexico requires adaptive management to cope with expected climatic change, in order to have healthy trees for Danaus plexippus overwintering sites in the future. Open pollinated seeds from fifteen A. religiosa populations were collected along an elevational gradient (2850-3550 masl; one sampled population every 50 m of elevational difference). Seedlings were evaluated in a common garden test over a period of 30 months. We found significant differences (P < 0.03) among populations in total elongation, final height, date of growth cessation, foliage, stem and total dry weight, as well as frost damage. These differences were strongly associated with the Mean Temperature of the Coldest Month (MTCM; r 2 = 0.6222, P = 0.0005). Seedlings originating from lower elevation populations grew more but suffered more frost damage than those from higher elevations. Populations differentiate genetically when they are separated by 364 m in elevation. Such differentiation was used to delineate three elevational/climatic zones for seed collection, with limits defined at: 2650 masl or 9.7 °C of MTCM; 3000 masl or 8.5 °C; 3350 masl or 7.3 °C; and 3700 masl or 6.1 °C. Zonification for seedling deployment aiming to match a suitable climate in year 2030 (after projections using an ensemble of 18 General Circulation Models and a Representative Concentration Pathway 6.0 watts/ m 2 ), would have the same MTCM zone limits, but shifted 350 m upwards in elevation. This shift would exceed the highest elevations within the MBBR, necessitating the establishment of A. religiosa stands outside the MBBR, to serve as potential future overwintering sites.
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 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 | 0.001 | 0.001 |
| 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".