DOI: 10.5061/dryad.1ns1rn96r
title: Environmental variability affects flexibility in activity onset at large geographic scales

description: Timing is an essential component of the phenotype, influencing organism
 fitness and fundamentally shaping ecological interactions. Although
 variation in the timing of activity can be substantial, the degree to
 which this variation stems from behavioral flexibility (within-individual
 variation) vs. consistent behavioral differences (among-individual
 variation) is poorly understood and represents a key knowledge gap as
 these have different ecological and evolutionary implications. Whereas
 flexibility in timing may be advantageous in novel circumstances,
 individuals could also make mistakes. Alternatively, consistent
 among-individual differences in timing may lead certain individuals to
 exhibit maladaptive behavior when confronting novel conditions (e.g.,
 light pollution or novel predators). We estimated activity onset from 1050
 captures of 483 individual white-footed mice, Peromyscus leucopus, across
 the upper Midwest, Northeast, Mid-Atlantic, and southern Appalachia
 regions of the United States. In each locale, we quantified the total
 phenotypic variation in activity onset and partitioned this into its
 within- and among-individual components. We then examined whether mice at
 locations experiencing more variable climate or residing in more
 structurally variable habitats exhibited differences in within- or
 among-individual variation in timing. We found that timing flexibility was
 always greater than consistency, and individuals from populations at
 cooler, drier sites with variable seasonal precipitation and temperature
 were more flexible than mice at warmer, wetter sites with less seasonal
 change in precipitation and temperature. Behavioral flexibility was not
 significantly associated with habitat structure heterogeneity. Our results
 reveal that most variation in timing across the range of this species
 derives from within-individual variation.
description: # Environmental variability affects individual variation in activity onset
 at large geographic scales ## Overview This dataset accompanies the
 manuscript *Environmental variability affects individual variation in
 activity onset at large geographic scales*. It contains two CSV files: 1.
 **`pele_data.csv`** — individual-level capture data for white-footed mice
 (*Peromyscus leucopus*) collected from March – October 2022 across 8 NEON
 sites across the upper Midwest, Northeast, Mid-Atlantic, and southern
 Appalachian regions of the United States as part of the National
 Ecological Observatory Network (NEON) monitoring protocol (NEON Doc #:
 NEON.DOC.000481). NEON sites used included BLAN: Blandy Experimental Farm,
 Virginia, HARV: Harvard Experimental Forest & Quabbin Watershed,
 Massachusetts, MLBS: Mountain Lake Biological Station, Virginia, ORNL: Oak
 Ridge National Laboratory, Tennessee, SCBI: Smithsonian Conservation
 Biology Institute, Virginia, SERC: Smithsonian Environmental Research
 Center, Maryland, STEI: Steigerwalt-Chequamegon, Wisconsin, and UNDE:
 University of Notre Dame Environmental Research Center, Michigan. These
 data were used in linear mixed-effects models to partition and estimate
 among- and within-individual variance in activity timing. 2.
 **`site_variance.csv`** — site-level summaries including among- and
 within-individual variance estimates, mean activity timing, mean-scaled
 variance metrics, and measures of environmental and climatic variability
 at each NEON site. Raw rodent capture data and raw environmental data
 (habitat and climate) are available in NEON data repositories (see
 'Data Availability). These data were used in linear models specifying
 variation in activity onset (Ii or Ir) as the response variable and
 climate or habitat variability as the predictor variable. ## File
 descriptions ### 1. `pele_data.csv` Each row represents a capture event
 for an individual mouse. | Column name | Description | Units / Notes | |
 -------------- |
 ------------------------------------------------------------------- |
 ----------------------- | | `siteID` | NEON site identifier | Character |
 | `process_date` | Date capture was processed | mm/dd/yyyy | | `sex` |
 Biological sex of individual | M = male, F = female | | `month` | Month of
 capture | 1–12 | | `IDunique` | Unique identifier for each individual |
 Integer | | `capture_date` | Date of capture | mm/dd/yyyy | |
 `capture_time` | Time of capture. All times are given in Central Daylight
 Time (CDT) | hh:mm:ss | | `hps` | Hours past sunset at capture | Numeric |
 | `prop_elapsed` | Proportion of nighttime elapsed at capture | 0 =
 sunset, 1 = sunrise | | `capnum` | Sequential capture number for the
 individual | Integer | ### 2. `site_variance.csv` Each row represents a
 NEON site, summarizing site-level variance estimates and environmental
 characteristics. | Column name | Description | Units / Notes | |
 ---------------- |
 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------- | | `siteID` | NEON site identifier | Character | | `Vi` | Among-individual variance in capture timing | Derived from mixed-effects model | | `Vr` | Within-individual (residual) variance in capture timing | Derived from mixed-effects model | | `totalVar` | Total variance in capture timing (`Vi + Vr`) | Numeric | | `mean_timing` | Mean capture time at the site | Proportion of nighttime elapsed (0 = sunset, 1 = sunrise) | | `Ii` | Mean-scaled individual variance | 100 × (Vi / mean\_timing²) or equivalent | | `Ir` | Mean-scaled residual variance | 100 × (Vr / mean\_timing²) or equivalent | | `PC1` | Climate principal component summarizing mean annual temperature, relative humidity, precipitation, and monthly variation in these variables. High values = warmer, wetter sites with lower average relative humidity, less seasonal variation in precipitation/temperature, and more seasonal variation in relative humidity | Numeric | | `buffer_cv` | Coefficient of variation in canopy height within trapping grid + 100 m buffer | Index of vegetation structural heterogeneity | | `buffer_meanTRI` | Mean terrain ruggedness index (TRI) within grid + 100 m buffer | Index of topographic heterogeneity | | `num_ids` | Number of unique individuals captured at the site | Integer | | `num_obs` | Total number of capture events at the site | Integer | | `num_obs_id` | Average number of captures per individual (`num_obs / num_ids`) | Numeric | ## Methods summary Data were collected via NEON small mammal box trapping protocols across 8 sites. From March – October 2022, small mammal sampling was conducted at eight sites across the upper Midwest, Northeast, Mid-Atlantic, and southern Appalachian regions of the United States as part of the National Ecological Observatory Network (NEON) monitoring protocol (NEON Doc #: NEON.DOC.000481). We determined capture timing using paired iButton Thermochron temperature loggers (Maxim Integrated Inc., San Jose, CA) deployed in each live trap. In this method, one logger measures temperature inside the trap, while the other measures just outside the trap door. The captured rodent’s body heat raises the temperature inside the trap and the time at which the temperature diverges indicates the time of capture. Linear mixed-effects models were used to partition among- and within-individual variation in the timing of animal capture. Individual capture times were standardized relative to sunset and expressed both as hours past sunset and proportion of night elapsed. Site-level environmental and climatic variables were derived from NEON climate data and NEON Lidar data, canopy height models, and digital terrain models. See 'Data Availability' for links to these data available in NEON data repositories. ## Data availability All data files (`pele_data.csv` and `site_variance.csv`) will be made publicly available in the Dryad repository upon manuscript acceptance. Additional datasets are archived by NEON and available in the following NEON data repositories: * Small mammal box trapping: [https://doi.org/10.48443/p4re-p954](https://doi.org/10.48443/p4re-p954) * Small mammal DNA extracts: [https://doi.org/10.15468/6mxmvr](https://doi.org/10.15468/6mxmvr) * Precipitation: [https://doi.org/10.48443/zj63-h785](https://doi.org/10.48443/zj63-h785) * Temperature and relative humidity: [https://doi.org/10.48443/k9vk-5k27](https://doi.org/10.48443/k9vk-5k27) * Canopy height models: [https://doi.org/10.48443/zzz8-pr54](https://doi.org/10.48443/zzz8-pr54) * Digital terrain models: [https://doi.org/10.48443/hj77-kf64](https://doi.org/10.48443/hj77-kf64) ## Acknowledgments This work was supported by the National Science Foundation (Award No. IOS-2110031). We thank the NEON small mammal teams and biorepository staff, Savannah Bartel, Amelia Weidemann, Elizabeth Locke, and Mark Fuka for assistance with iButton data collection, and Cristian D’Ambros for help with R code. NEON is sponsored by the NSF and operated under cooperative agreement by Battelle Memorial Institute.