Pace and shape of life differences drive invasion trajectory in introduced lizards in Hawaii
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Fast life histories allow colonizing populations to rapidly escape the risk of stochastic extinction, while slow life histories can buffer against poor conditions. Thus, either strategy can be successful depending on the context of the invasion. Recent species-level trait compilations have found that introduced reptiles tend to have relatively fast life histories. However, life history is highly variable within species and may be shaped by the invasion process. Therefore, evaluating population-level traits is necessary for understanding the trajectory of specific invasions. We measured individual somatic growth and population growth under controlled field conditions in three species of introduced lizards in Hawaii, which share similar species-level traits, to determine how life history may be affecting community dynamics in this ongoing invasion. We found a trade-off along the fast-slow life history axis: Anolis sagrei grew the fastest and had the lowest survival, Phelsuma laticauda gre..., , , # Data from: Pace and shape of life differences drive invasion trajectory in introduced lizards in Hawaii
[https://doi.org/10.5061/dryad.bg79cnpkr](https://doi.org/10.5061/dryad.bg79cnpkr)
## Description of the data and file structure
Contains data and R files to reproduce the model from \"Pace and shape of life differences drive invasion trajectory in introduced lizards in Hawaii.\" The SVL is measured in mm, and the interval is measured in years.
### Files and variables
**Data files**: data files are denoted with X, which can take on the values ASAG, ACAR, or PLAT, denoting each of *Anolis sagrei*, *Anolis carolinensis*, or *Phelsuma laticauda*.
X_growth1.csv and X_growth2.csv: data for modeling growth using snout-vent length measurements
* SVL1_1: Lagged snout-vent-length data used as predictor variable
- SVL2_1: Snout_-vent-length data to be modeled
* growSex_1: Sex of the current animal
- growInd_1: Numeric variable used to uniquely identify an individual
* m_1: Time inter...,
创建时间:
2025-11-08



