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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit the .Rmd file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# mort <img src="man/figures/logo.png" align="right" height="139" />
<!-- badges: start -->
[](https://app.codecov.io/gh/rosieluain/mort?branch=main)
<!-- badges: end -->
The goal of mort is to provide a framework to identify potential mortalities or expelled tags in passive acoustic telemetry arrays with non-overlapping receivers. The potential mortalities that are flagged by mort should be reviewed by the user, and considered for removal from the dataset.
Please note that this method is conservative, and therefore may overestimate the number of mortalities in the system. It is therefore not advised to use the results as estimates of survival or tagging effects. Rather, the purpose is to remove or reduce potential bias before conducting further analyses.
mort uses thresholds from the dataset itself, use-defined thresholds, and several customizable options, to allow application to a wide number of species and acoustic arrays. By providing a standardized framework for consideration of potential mortalities, we hope this tool will be useful and encourage greater reproducibility in acoustic telemetry research.
### Installation
You can install mort from CRAN with the line below.
``` r
install.packages("mort")
```
To install mort directly from GitHub, including any updates that might not be released on CRAN yet, use the line below. Note that you must have the package `devtools` installed.
``` r
devtools::install_github("rosieluain/mort")
```
### Package contents
Please see the package vignettes for more details, as well as guidelines and tips for the following functions.
#### Data preparation and visualization
`residences` condenses detection records into residence events, with a start time, end time, and duration. Residence events are used as the input for all other mort functions.
`mortsplot` generates plots of residence events using `ggplot2`. Plots are automatically formatted to maximize visibility of the dataset, and can be further modified using `ggplot2` commands. Interactive plots can also be generated using `plotly`.
#### Identifying potential mortalities or expelled tags
`morts` identifies potential mortalities or expelled tags, based on the duration of single residence events or cumulative residence events (see vignettes for a complete explanation). Thresholds are derived from the input dataset.
`infrequent` identifies potential mortalities or expelled tags from infrequent or intermittent detections. Thresholds and timeframes are defined by the user.
`review` examines new data to determine if an animal that was previously flagged as a mortality has moved, and may therefore be alive.
#### Data and process exploration
These are functions that may be called by `morts` and/or `infrequent`, depending on the options that are selected. These functions are fully documented so the user can explore their data and the process used by mort.
`stationchange` identifies the most recent station or location change for each animal (i.e., the last time each animal moved, and therefore was assumed to be alive).
`resmax` extracts the residence events that occurred prior to the most recent station change for each individual.
`resmaxcml` generates cumulative residence events (from the first time an animal was detected at a given station to the last time an animal was detected at the same station, ignoring gaps in detection) that occurred prior to the most recent station change for each individual.
`drift` creates drift events from sequential residence events, where detected movement between stations may be due to drifting of a dead animal or an expelled tag.
`season` selects residence events from user-specified seasons or periods of interest.
`backwards` shifts the start time of a flagged mortality earlier, if the residence event that triggered the flag was not the earliest consecutive residence event at that station/location.
### Disclaimer
mort is pretty new. Although it is has been tested extensively on a complex dataset, we expect that issues will arise as mort is applied to other datasets and systems. If you run into any issues or have any suggestions for improvements, please post an issue on [GitHub](https://github.com/rosieluain/mort/issues), and we'll see what we can do!