All code used in the analysis of melanistic vs. non-melanistic jaguar and oncilla.
- Main Melanistic Analysis: includes all the code for cleaning, analyzing and plotting data
- Functions Used for Melanistic Analysis: all custom background functions used on Main Melanistic Analysis
Important Note: Data not included.
Data used in this was data obtained from camera trap photos with date and time recorded.
Columns needed for this analysis:
- Coloring: designation of record as "Melanistic" or "Non-melanistic"
- Date: date of observation in format %m/%d/%Y
- Time: time of record in decimal format
- Independent: with designations as "Yes" for observations of the same species at the same camera within 30 minutes or "No" for non-independent data
- Longitude: in decimal degrees
- Latitude: in decimal degrees
Important Note: Set timezone on computer to desired timezone for correct sunTime function calculation. Have not ironed out the designation of the timezone in the POSIXct and sunTime functions.
- cleans data
- calculats time in radians based on exact sunrise and sunset using sunTime function from overlap package (Meredith & Linkie, 2018)
- calculates Coefficient of Overlapping and related statistics using overlap package
- builds bar plots of proportion and number of each coloring (melanistic and non-melanistic) and designation as night or day
- builds circadian and lunar activity plots
- calculates Rao test for activity patterns
- overlapCI*: calculates Coefficient of Overlapping and confidence interval using overlap package (Ridout & Meredith, 2018). Follows the two-step method developed by Ridout & Linkie (2009) where sample sizes between 20 and 75 are run with a non-negative trigonometric sum distribution and sample sizes greater than 75 are run with a kernel density with a standard bandwidth of 1 and bandwidth adjustment of 0.8. Uses user-set number of replicates (numboot). In ours we ran it with 10000 replicates.
- watson2*: calculates U-squared statistics, modified to work with "tied" data (See: Zar, J. H. (1999). Biostatistical analysis. Upper Saddle River, NJ: Prentice Hall)
- watson2test*: approximates p-value of Watson's U-Squared, given two vectors (See: Tiku, M. L. (1965). Chi-Square approximations for the distributions of goodness-of-fit statistics U2N and W2N. Biometrika, 52. 630-633.
- w.stat*: calculates W statistic from 2 or more vectors of data (in Radians)
- w.prob*: approximates p-value of W statistic if given 2+ vectors of data (in radians)
- binning*: function used within chisquare function to bin data into desired number of bins
- chisquare*: calculates fisher test statistic (determined fisher test was better for general activity pattern analysis as the majority of species vectors did not meet assumptions for chi-square.
- overall: function that runs all functions above given two vectors of observations to compare
- theme_mooring: theme for bar plots
- pvalueRAO: function print.rao.spacing.test altered to save p-value range into data frame (Agostinelli, 2007). From package Circular (2017).
* means written by TJ Weigman
- Amy Eppert (Student in Department of Biology, Point Loma Nazarene University)
- TJ Weigman (Student in Department of Physics and Engineering, Point Loma Nazarene University)
- Initial functions for Coefficient of Overlapping and related statistics