For everything there is a season: Analysing periodic mortality patterns with the cyclomort r package

Many important demographic processes are seasonal, including survival. For many species, mortality risk is significantly higher at certain times of the year than at others, whether because resources are scarce, susceptibility to predators or disease is high, or both. Despite the importance of surviv...

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Bibliographic Details
Published inMethods in ecology and evolution Vol. 11; no. 1; pp. 129 - 138
Main Authors Gurarie, Eliezer, Thompson, Peter R., Kelly, Allicia P., Larter, Nicholas C., Fagan, William F., Joly, Kyle, Graham, Laura
Format Journal Article
LanguageEnglish
Published London John Wiley & Sons, Inc 01.01.2020
Subjects
boreal woodland caribou
Computer simulation
Confidence intervals
Demographics
Mortality
Mortality patterns
parametric survival modelling
periodic hazard function
Predators
Rangifer tarandus
Rangifer tarandus caribou
Rangifer tarandus granti
seasonal survival
Seasons
Survival
Wildlife
Workflow
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Summary:Many important demographic processes are seasonal, including survival. For many species, mortality risk is significantly higher at certain times of the year than at others, whether because resources are scarce, susceptibility to predators or disease is high, or both. Despite the importance of survival modelling in wildlife sciences, no tools are available to estimate the peak, duration and relative importance of these ‘seasons of mortality’. We present cyclomort, an r package that estimates the timing, duration and intensity of any number of mortality seasons with reliable confidence intervals. The package includes a model selection approach to determine the number of mortality seasons and to test whether seasons of mortality vary across discrete grouping factors. We illustrate the periodic hazard function model and workflow of cyclomort with simulated data. We then estimate mortality seasons of two caribou Rangifer tarandus populations that have strikingly different mortality patterns, including different numbers and timing of mortality peaks, and a marked change in one population over time. The cyclomort package was developed to estimate mortality seasons for wildlife, but the package can model any time‐to‐event processes with a periodic component.
ISSN:2041-210X
2041-210X
DOI:10.1111/2041-210X.13305