Projected climate change effects on individual growth rates and size in a threatened pitviper
Bibliographic record
Abstract
• Shorter snow residence time is associated with smaller sizes in Eastern Massasauga. • Growth rate is influenced by both snow residence time and spring precipitation. • Predictions suggest Eastern Massasauga will grow relatively faster and have smaller sizes. • Female lifetime reproductive success may decrease due to climate change. Ectotherms are particularly vulnerable to climate change because they rely on the surrounding environment for thermoregulation. In snakes, prolonged warmer temperatures and precipitation changes may lead to faster growth and smaller body size. Our goal was to assess how climate change may impact future sizes and growth rates on an endangered pitviper species as a model organism. We hypothesized that climate change-induced shifts in growing season temperature, early growing season precipitation, and snow residence time (SRT) would impact growth rate and asymptotic size in the threatened Eastern Massasauga ( Sistrurus catenatus ) rattlesnake. We used capture-mark-recapture data from eleven sites across the species’ range to fit a set of non-linear models evaluating the effects of these three climate variables on asymptotic size and growth coefficient in a modified von Bertalanffy growth curve. We found that longer SRT resulted in larger asymptotic size. We also found support for both a negative relationship between SRT and growth rate and a positive relationship between precipitation and growth rate. We averaged all supported models and predicted growth and size in the 2080s under a stabilization (RCP 4.5) and a high (RCP 8.5) emission scenario. Under RCP 8.5, predicted increases in female growth rate ranged from 10% to 33%, whereas decreases in female size across sites ranged from 9% to 17%. Under this scenario female lifetime reproductive success will decrease, as faster growth is associated with increased mortality, early senescence, and poor offspring quality, and smaller body sizes will result in smaller and fewer young.
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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 | 0.000 |
| 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 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".