In Conte-Ecology/singlePassDetection: Compares detection corrected abundance estimates for single and multiple pass fish surveys

Shenandoah National Park brook trout data 72 sites in 1996-2010: not all sites were sampled every year & there is a mix of 1-pass and 3-pass surveys ========================================================================

working directory & libraries

rm(list=ls())

setwd('/Users/Dan/Documents/Research/Stream_Climate_Change/Brook_Trout/Compare_Single_Multiple_Pass/')
getwd()
library(reshape2)
library(rjags)
library(plyr)
library(ggplot2)
library(knitr)
library(arm)
library(boot)

Read in data

load("Data/Shen Dail Madsen data and results ver 6.8.RData") 

Compare to 3-pass DM model by Yoichiro

adult.dm <- filter(yearTotalAbund, filter = size2 == "adult")
adult.dm <- filter(adult.dm, filter = year2 != 1996)

colnames(adult.dm) <- c("year.num", "size", "N.pop", "total.lower", "total.upper", "year", "size2")
adult.dm$method <- "Dail-Madsen"
agg.adult$method <- "Single-Pass"
adult.compare <- rbind(adult.dm[, c("year", "N.pop", "method")], agg.adult[ , c("year", "N.pop", "method")])


ggplot(adult.compare, aes(x=year, y=N.pop, colour=method)) +
  #geom_errorbar(aes(ymin=total.lower, ymax=total.upper), width=0.5, size=1.2) +
  geom_line(size = 1.2) +
  geom_point(size = 3) +
  xlab("Year") +
  ylab("Estimated total adult abundance") +
  labs(title = "Yearly adult abundance over 72 sites in Shenandoah") +
  #theme(legend.position = c(2008, 6000))
  theme_bw()


yoy.dm <- filter(yearTotalAbund, filter = size2 == "YOY")
yoy.dm <- filter(yoy.dm, filter = year2 != 1996)

colnames(yoy.dm) <- c("year.num", "size", "N.pop", "total.lower", "total.upper", "year", "size2")
yoy.dm$method <- "Dail-Madsen"
agg.yoy$method <- "Single-Pass"
yoy.compare <- rbind(yoy.dm[, c("year", "N.pop", "method")], agg.yoy[ , c("year", "N.pop", "method")])


ggplot(yoy.compare, aes(x=year, y=N.pop, colour=method)) +
  #geom_errorbar(aes(ymin=total.lower, ymax=total.upper), width=0.5, size=1.2) +
  geom_line(size = 1.2) +
  geom_point(size = 3) +
  xlab("Year") +
  ylab("Estimated total YOY abundance") +
  labs(title = "Yearly YOY abundance over 72 sites in Shenandoah") +
  #theme(legend.position = c(2008, 6000))
  theme_bw()


adult.detect.1$detection.probabilities

cor(adult.dm$N.pop, agg.adult$N.pop)
cor(yoy.dm$N.pop, agg.yoy$N.pop)

summary(lm(adult.dm$N.pop ~ agg.adult$N.pop))
summary(lm(yoy.dm$N.pop ~ agg.yoy$N.pop))

abund <- rpois(10, 20)
year <- 1:10
count1 <- abund * 0.5
count2 <- rbinom(10, abund, 0.5)
flow <- rnorm(10) * (year - mean(year))/sd(year)
p <- 0.5 - flow * 0.18
count3 <- NA
for(i in 1:length(year)) { # effects of random flow when surveyed in different years
  count3[i] <- rbinom(1, abund, p[i])
}

df <- data.frame(year, abund, count1, count2)

gp1 <- ggplot(df, aes(year, abund)) +
  geom_point(size = 3) + geom_line(size = 1) +
  xlab("Year") + ylab("Abundance") +
  ylim(c(0, 30)) + 
  theme_bw() + 
  theme(axis.text=element_text(size=12),
        axis.title=element_text(size=14,face="bold"))
gp1

gp2 <- gp1 + geom_point(aes(year, count1), colour = "blue", size = 3) +
  geom_line(aes(year, count1), colour = "blue", size = 1)
gp2

gp3 <- gp2 + geom_point(aes(year, count2), colour = "red", size = 3) +
  geom_line(aes(year, count2), colour = "red", size = 1)
gp3

gp4 <- gp2 + geom_point(aes(year, count3), colour = "red", size = 3) +
  geom_line(aes(year, count3), colour = "red", size = 1, linetype = 2)
gp4

```r

coef(adult.detect.1) fixef(adult.glmm.p)

summary(adult.detect.1) summary(yoy.detect.1) summary(adult.glmm.p)

recruit.coefs survival.coefs.adult survival.coefs.yoy detect.coefs

Conte-Ecology/singlePassDetection documentation built on May 6, 2019, 12:51 p.m.