This file briefly describes the data files included in the home range size and fidelity sleepy lizard dataset. Brief background: From 2009 through 2017, we attached GPS units to ~50-70 lizards in an ~1.2 km² study site near Bundey, South Australia (-33.888245, 139.310673). Throughout the lizards' activity season (the Australian Spring), the GPS units took regular reads on lizards' daily locations. Using these GPS data, as well as morphological, behavioral, and habitat data, we explored predictors of lizard home range (HR) size and fidelity through time. We also evaluated whether individuals exhibited consistent HR size and fidelities (i.e., repeatability, or personality).

• General Overview of the datasets
  • Main folder
  • Randomizations folder
• Column Descriptions by Dataset
  • Main folder
  • Randomizations folder

General Overview of the datasets

Main folder

The nine datasets in the main folder share many columns in common. We could have presented them as two datasets (HR size and fidelity), but to follow the organization of the different analyses we conducted in the manuscript, we split them into nine.

• HRsize50+95_Repeatability
  • This table contains the information needed to calculate repeatability of lizard 50% and 95% HR (home range) size. This dataset has been pre-filtered to lizards observed in the site in two or more years (the minimum required to have at least two HR size estimates).
• Fidelity50+95_Repeatability
  • This table contains the information needed to calculate repeatability of lizard 50% and 95% HR fidelity (as estimated by UDOI, the utilization distribution overlap index). This dataset has been pre-filtered to lizards observed in the site in three or more years (the minimum required to have at least two fidelity estimates).
• HRsize50+95_NoHabitat
  • This table contains the information needed to evaluate predictors of lizards' 50% and 95% home range sizes, not including habitat predictors.
  • This dataset includes lizards seen in one or more years in the site. Only lizards with observations for all predictors are included.
• HRsize50_Habitat
  • This table contains the information needed to evaluate predictors of lizards' 50% and 95% home range sizes, but including habitat predictors.
  • This dataset includes lizards seen in one or more years in the site. Only lizards with observations for all predictors are included.
  • Because we had habitat data for only 2015 through 2017, this dataset is restricted to lizards observed in those years.
• HRsize95_Habitat
  • This table contains the information needed to evaluate predictors of lizards' 50% and 95% home range sizes, but including habitat predictors.
  • This dataset includes lizards seen in one or more years in the site. Only lizards with observations for all predictors are included.
  • Because we had habitat data for only 2015 through 2017, this dataset is restricted to lizards observed in those years.
  • We have separate datasets for 50% and 95% HR size with habitat data because our habitat quality metrics were taken at discrete locations in the site. Some lizard HRs were small enough to not include any of our habitat assessment locations. Because 50% HRs are by definition smaller than 95%, there were more 50% than 95% HRs that did not have habitat information. So, filtering the data to observations where we had habitat data produced a different number of observations for the 50% and 95% datasets.
• BinomialInsite
  • This table contains the information needed to evaluate whether lizards were found in the field site in a future year.
• Fidelity50+95_NoHabitat
  • This table contains the information needed to evaluate predictors of lizards' 50% and 95% home range fidelities, not including habitat predictors.
  • This dataset includes lizards seen in two or more years in the site (the minimum required to have at least one fidelity observation). Only lizards with observations for all predictors are included.
• Fidelity50_Habitat
  • This table contains the information needed to evaluate predictors of lizards' 50% and 95% home range fidelities, but including habitat predictors.
  • This dataset includes lizards seen in two or more years in the site. Only lizards with observations for all predictors are included.
  • Because we had habitat data for only 2015 through 2017, this dataset is restricted to lizards observed in those years.
• Fidelity95_Habitat
  • This table contains the information needed to evaluate predictors of lizards' 50% and 95% home range fidelities, but including habitat predictors.
  • This dataset includes lizards seen in two or more years in the site. Only lizards with observations for all predictors are included.
  • Because we had habitat data for only 2015 through 2017, this dataset is restricted to lizards observed in those years.
  • For explanation on why we have separate 50% and 95% fidelity habitat datasets, see HRsize95_Habitat description. Same logic applies here as for that dataset.

Randomizations folder

The randomizations folder contains six datasets, all provided in the ".rds" format, which is native to the open source program 'R.' To read these files into R, use the function readRDS().

• Fidelity_Randomization
  • This rds file contains a large table with the randomized fidelity dataset.
  • Essentially, to ensure that sleepy lizards exhibited higher than random fidelity, we created a dataset of randomized HR fidelity values.
    • We calculated the HR fidelity between a lizard's HR in a baseline year and all the HRs that the lizard could have occupied in future years, assuming the observed HR in future years were the possible options.
  • This table contains the so-derived HR fidelities.
• PHR_Degree_Randomization
  • This rds file contains a large table with the randomized PHR/Degree dataset.
  • We generated this dataset to determine whether the observed relationship between PHR and Degree was a simple result of increasing HR size, rather than PHR/Degree themselves affecting HR size.
  • More details are in the linked manuscript, but the general idea is that we shifted lizards' home range randomly around the site, and then recalculated lizards' PHR and degree.
  • This table contains the randomized PHR and degree values.
• HRsize50_randomization_result
  • This rds file houses a table of the model results of the randomized PHR/Degree data, for the 50% HR analysis.
  • More specifically, for each PHR/Degree randomization, we used lme4 to run a linear model evaluating the relationship between the observed HR size and randomized PHR and Degree values.
  • The table provides the parameter effects for PHR and Degree from these models.
  • To replicate the results in the table, you will need to join the non-randomized HR size data onto the PHR_Degree_Randomization table, and then run an lme4 model for each randomization (for 50% HR size).
• HRsize50_habitat_randomization_result
  • This rds file houses a table of the model results of the randomized PHR/Degree data, for the 50% HR analysis with habitat variables.
  • More specifically, for each PHR/Degree randomization, we used lme4 to run a linear model evaluating the relationship between the observed HR size and randomized PHR and Degree values.
  • The table provides the parameter effects for PHR and Degree from these models.
  • To replicate the results in the table, you will need to join the non-randomized HR size data (habitat filtered version) onto the PHR_Degree_Randomization table, and then run an lme4 model for each randomization (for 50% HR size).
• HRsize95_randomization_result
  • This rds file houses a table of the model results of the randomized PHR/Degree data, for the 95% HR analysis.
  • More specifically, for each PHR/Degree randomization, we used lme4 to run a linear model evaluating the relationship between the observed HR size and randomized PHR and Degree values.
  • The table provides the parameter effects for PHR and Degree from these models.
  • To replicate the results in the table, you will need to join the non-randomized HR size data onto the PHR_Degree_Randomization table, and then run an lme4 model for each randomization (for 95% HR size).
• HRsize95_habitat_randomization_result
  • This rds file houses a table of the model results of the randomized PHR/Degree data, for the 95% HR analysis with habitat variables.
  • More specifically, for each PHR/Degree randomization, we used lme4 to run a linear model evaluating the relationship between the observed HR size and randomized PHR and Degree values.
  • The table provides the parameter effects for PHR and Degree from these models.
  • To replicate the results in the table, you will need to join the non-randomized HR size data (habitat filtered version) onto the PHR_Degree_Randomization table, and then run an lme4 model for each randomization (for 95% HR size).

Column Descriptions by Dataset

In this section, we provide descriptions of the columns within each dataset, all of which are tables. Columns whose name includes the moniker "_z" are standardized, which is also noted in the column description. "Standardized" means we removed the mean and divided by the standard deviation in order to scale a variable and make it unitless.

Main folder

Table: HRsize50+95_Repeatability.csv

Table: Fidelity50+95_Repeatability.csv

Table: HRsize50+95_NoHabitat.csv

Table: HRsize50_Habitat.csv

Table: HRsize95_Habitat.csv

Table: BinomialInsite.csv

Table: Fidelity50+95_NoHabitat.csv

Table: Fidelity50_Habitat.csv

Table: Fidelity95_Habitat.csv

Randomizations folder

Table: Fidelity_Randomization.rds

Table: PHR_Degree_Randomization.rds

Table: HRsize50_randomization_result.rds

Table: HRsize50_habitat_randomization_result.rds

Table: HRsize95_randomization_result.rds

Table: HRsize95_habitat_randomization_result.rds