Evidence for a survival-driven traveling wave in a keystone boreal predator population
Bibliographic record
Abstract
Cyclical population dynamics are a common phenomenon in populations worldwide, yet the spatial organization of these cycles remains poorly understood. In this study, we investigated the spatial form and timing of a population collapse from 2018 to 2022 in Canada lynx ( Lynx canadensis ) across the northwest boreal forest. We analyzed survival, reproduction, and dispersal data from 143 individual global positioning system (GPS) collared lynx from populations across five study sites spanning interior Alaska to determine whether lynx displayed characteristics of a population wave following a concurrent wave in snowshoe hare ( Lepus americanus ) abundance. Reproductive rates declined across the study sites; however, site-level reproduction declined first in our easternmost study sites, supporting the idea of a population wave. Despite a clear increase in percent of dispersing lynx, there was no evidence of directional bias in dispersal following a hare population wave. Analysis did show increasingly poor survival for lynx dispersing to the east compared to combined resident and westward dispersal. This pattern is consistent with a survival-mediated population wave in lynx as the driver of the theorized population wave. The combination of these factors supports the idea of a hierarchical response to snowshoe hare population declines with a drop in lynx reproduction followed by increased dispersal, and finally reduced survival. All of this evidence is consistent with the expected characteristics of a population undergoing a traveling wave and supports the hypothesis that lynx presence may facilitate and mirror the underlying wave patterns in snowshoe hare.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".