preyDataProcessing

Aggregated prey density across multiple watersheds

This package is for sourcing prey density across multiple watersheds and habitat types. Also included in this package are fish mass and and fork length data as well as associated environmental (temperature and dissolved oxygen) data. Data can be used as inputs into bioenergetic models.

Installation

# install.packages("remotes")
remotes::install_github("CVPIA-OSC/preyDataProcessing")

Usage

This package includes aggregated prey density data from participating authors.

# datasets within the package
data(package = 'preyDataProcessing')

About the Datasets

Datasets were aggregated from multiple authors and across many watersheds. For each dataset, the habitat type was assigned. Specific methods and supporting documents for data aggregation and decisions in every watershed are provided by author:

• Montgomery
• Corline
• Zeug
  • San Joaquin River
  • Merced River
• Cordoleani
• Guignard
• Zooper R Library

Information regarding compiled datasets is located here:

• prey density data aggregation

• habitat type definition and methodology

  • Note: must download HTML file and open in browser

• size class methodology

Prey Density Datasets

• all_prey_density

• monthly_prey_density

Fish Datasets:

• all_fish_data

• monthly_fish_data

Environmental Datasets:

• all_enviro_data

Joining Datasets

Datasets can be joined on site, see example below:

library(tidyverse)

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ ggplot2 3.4.0      ✔ purrr   0.3.5 
## ✔ tibble  3.1.8      ✔ dplyr   1.0.10
## ✔ tidyr   1.2.1      ✔ stringr 1.5.0 
## ✔ readr   2.1.3      ✔ forcats 0.5.2 
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()

## All data: 
all_prey <- preyDataProcessing::all_prey_density 
all_fish <- preyDataProcessing::all_fish_data
all_enviro <- preyDataProcessing::all_enviro_data 

# all prey density and fork length/mass data
all_prey_and_fish <- all_prey %>% left_join(all_fish) 

## Joining, by = c("habitat_type", "date", "author", "watershed", "site")

# join environmental data with prey density:
all_prey_and_enviro <- all_prey %>% left_join(all_enviro) 

## Joining, by = c("habitat_type", "date", "author", "watershed", "site")

## Monthly Data:
monthly_prey <- preyDataProcessing::monthly_prey_density
monthly_fish <- preyDataProcessing::monthly_fish_data

monthly_prey_and_fish <- monthly_prey %>% left_join(monthly_fish) 

## Joining, by = c("watershed", "habitat_type", "year", "month")

Dependencies

The preyDataProcessing data package provides data bioenergetic modeling within the CVPIA Open Science Collaborative.