In nwfsc-cb/srkw-status: Package for processing and exploring killer whale demographic data

knitr::opts_chunk$set(echo = FALSE, warning=FALSE, message=FALSE,
  comment = "#>"
)
library(kwdemog)
library(dplyr)
library(mgcv)
library(ggplot2)
library(rstanarm)
library(ggridges)
library(viridis)

data(orca)
year.end = as.numeric(substr(Sys.Date(),1,4))
refit_models = TRUE
report_start = year.end-5
# format whale names just for consistency
format_names = function(x) {
  for(i in 1:2) {
  indx = which(substr(x,2,2) == "0")
  x[indx] = paste0(substr(x[indx],1,1), substr(x[indx],3,nchar(x[indx])))
  }
  return(x)
}
data(ages2stages)
expanded = expand(orca,ages2stages=ages2stages)

expanded$animal = format_names(expanded$animal)
expanded$pod = format_names(expanded$pod)
expanded$matriline = format_names(expanded$matriline)
expanded$mom = format_names(expanded$mom)
expanded$dad = format_names(expanded$dad)

#report_dir = "projections/"
whaleData = expanded

Reproductive females

The number of reproductive aged females was at its lowest point in the late 1970s, in part because of the prior harvesting that occurred into the early 1970s (Fig. \ref{fig:ts-repro-females}). Though the overall number of reproductive females has been fluctuating between 25-35 for most of the last 40 years, there have been contrasting changes by pod, with declines in L pod females and increases in J pod (Fig. \ref{fig:ts-repro-females}). At the start of the survey in 1976, the distribution of females was skewed toward younger ages with few older, post-reproductive females. The distribution in recent years is more uniform across female ages (in other words, more females in their 30s, Fig. \ref{fig:plot-repro-females}).

```r"}

summarize repro females by year

repro = dplyr::filter(whaleData, pod %in% c("J1","K1","L1"), alive == 1, sexF1M2==1, age >=10, age<=42) repro$pod[which(repro$pod=="J1")]="J" repro$pod[which(repro$pod=="K1")]="K" repro$pod[which(repro$pod=="L1")]="L" repro$year = as.factor(repro$year)

ggplot(repro, aes(x = age, y = year, fill = ..x..)) + geom_density_ridges_gradient(scale = 1, rel_min_height = 0.01) + scale_fill_viridis(name = "Female age", option = "C") + labs(title = 'Ages of reproductive - aged female SRKW') + xlab("Age") + ylab("Year") + theme(axis.text.y = element_text(angle = 0, hjust = 1)) + scale_y_discrete(breaks=c("1980","1985","1990","1995","2000","2005","2010","2015","2020"), labels=c("1980","1985","1990","1995","2000","2005","2010","2015","2020")) + coord_flip() + theme_bw() + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))

```r"}
g1 = group_by(repro, year) %>% summarize(m = length(unique(animal)),SRKW="Total") %>% 
  ggplot(aes(year, m, group=SRKW,color=SRKW)) + geom_line(col="black") + geom_point() + 
  xlab("Year") + ylab("Reproductive aged females") + 
  scale_x_discrete(breaks=c("1980","1985","1990","1995","2000","2005","2010","2015","2020"),
        labels=c("1980","1985","1990","1995","2000","2005","2010","2015","2020"))+
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))+
  theme_bw()
g1

r"} g2 = group_by(repro, year, pod) %>% summarize(m = length(unique(animal))) %>% ggplot(aes(year, m, group=pod, color=pod)) + geom_line() + geom_point() + xlab("Year") + ylab("Reproductive aged females") + scale_x_discrete(breaks=c("1980","1985","1990","1995","2000","2005","2010","2015","2020"), labels=c("1980","1985","1990","1995","2000","2005","2010","2015","2020"))+ theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))+ theme_bw()+ scale_color_viridis(discrete = TRUE, end = 0.8) + scale_fill_viridis(discrete = TRUE, end = 0.8) g2

nwfsc-cb/srkw-status documentation built on Jan. 16, 2025, 1 a.m.