Continental synchrony and local responses: Climatic effects on spatiotemporal patterns of calving in a social ungulate
Bibliographic record
Abstract
Abstract Warming temperatures and advancing spring are affecting annual snow and ice cycles, as well as plant phenology, across the Arctic and boreal regions. These changes may be linked to observed population declines in wildlife, including barren‐ground caribou ( Rangifer tarandus ), a key species of Arctic environments. We quantified how barren‐ground caribou, characteristically both gregarious and migratory, synchronize births in time and aggregate births in space and investigated how these tactics are influenced by variable weather conditions. We analyzed movement patterns to infer calving dates for 747 collared female caribou from seven herds across northern North America, totaling 1255 calving events over a 15‐year period. By relating these events to local weather conditions during the 1‐year period preceding calving, we examined how weather influenced calving timing and the ability of caribou to reach their central calving area. We documented continental‐scale synchrony in calving, but synchrony was greatest within an individual herd for a given year. Weather conditions before and during gestation had contrasting effects on the timing and location of calving. Notably, a combination of unfavorable weather conditions during winter and spring, including the pre‐calving migration, resulted in a late arrival on the calving area or a failure to reach the greater calving area in time for calving. Though local weather conditions influenced calving timing differently among herds, warm temperatures and low wind speed, which are associated with soft, deep snow, during the spring and pre‐calving migration, generally affected the ability of female caribou to reach central calving areas in time to give birth. Delayed calving may have potential indirect consequences, including reduced calf survival. Overall, we detected considerable variability across years and across herds, but no significant trend for earlier calving by caribou, even as broad indicators of spring and snow phenology trend earlier. Our results emphasize the importance of monitoring the timing and location of calving, and to examine how weather during summer and winter are affecting calving and subsequent reproductive success.
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 | 0.000 | 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) | 0.001 | 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 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".