Set-up R Markdown AND adjust Working Directory (if necessary)

knitr::opts_chunk$set(echo = TRUE)
knitr::opts_knit$set ("C:/Users/16mfr/OneDrive/Desktop/Capstone/Data and Code - Copy/ANOVA&LR")
setwd("C:/Users/16mfr/OneDrive/Desktop/Capstone/Data and Code - Copy/ANOVA&LR")

Load packages

library(car)
library(dplyr)
library(lmtest)

Read and Prep Data
Data structure should include the following columns:
Unit, Month, Site, Vegetation Type, site CPUE, av_temp, av_do, av_pH, av_turbidity, av_conductivity
We log-transformed the site CPUE due to a non-normal distribution of data.

FykeLR = read.csv('FishLR.csv')
head(FykeLR)
FykeLR$logCPUE <- log(FykeLR$CPUE+1)
shapiro.test(FykeLR$logCPUE)
## 
##  Shapiro-Wilk normality test
## 
## data:  FykeLR$logCPUE
## W = 0.95506, p-value = 0.004245

Perform the Linear Regressions
Run a LR for logCPUE and each water quality parameter.
Regression Analyses - CPUE:Temp, CPUE:DO, CPUE:pH, CPUE:Turb, CPUE:Cond

FishLRtemp = lm(logCPUE ~ av_temp, data=FykeLR)
summary(FishLRtemp)
## 
## Call:
## lm(formula = logCPUE ~ av_temp, data = FykeLR)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.7422 -1.4226 -0.0274  1.1134  4.6922 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)  
## (Intercept)  0.80595    0.64256   1.254    0.213  
## av_temp      0.07139    0.02958   2.413    0.018 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.601 on 85 degrees of freedom
## Multiple R-squared:  0.06413,    Adjusted R-squared:  0.05312 
## F-statistic: 5.825 on 1 and 85 DF,  p-value: 0.01795
FishLRDO = lm(logCPUE ~ av_do, data=FykeLR)
summary(FishLRDO)
## 
## Call:
## lm(formula = logCPUE ~ av_do, data = FykeLR)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.7567 -1.3066 -0.1079  1.0906  5.0568 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  2.87407    0.37417   7.681 2.47e-11 ***
## av_do       -0.07620    0.04397  -1.733   0.0867 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.626 on 85 degrees of freedom
## Multiple R-squared:  0.03413,    Adjusted R-squared:  0.02276 
## F-statistic: 3.003 on 1 and 85 DF,  p-value: 0.08672
FishLRpH = lm(logCPUE ~ av_pH, data=FykeLR)
summary(FishLRpH)
## 
## Call:
## lm(formula = logCPUE ~ av_pH, data = FykeLR)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.4714 -1.3612 -0.1619  1.0537  5.1077 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)   4.1968     2.8425   1.476    0.144
## av_pH        -0.2390     0.3575  -0.668    0.506
## 
## Residual standard error: 1.651 on 85 degrees of freedom
## Multiple R-squared:  0.00523,    Adjusted R-squared:  -0.006473 
## F-statistic: 0.4469 on 1 and 85 DF,  p-value: 0.5056
FishLRTurb = lm(logCPUE ~ av_turbidity, data=FykeLR)
summary(FishLRTurb)
## 
## Call:
## lm(formula = logCPUE ~ av_turbidity, data = FykeLR)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.4010 -1.2907 -0.1455  1.0690  5.0101 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   2.405461   0.240498  10.002 5.09e-16 ***
## av_turbidity -0.006787   0.010513  -0.646     0.52    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.651 on 85 degrees of freedom
## Multiple R-squared:  0.004878,   Adjusted R-squared:  -0.006829 
## F-statistic: 0.4167 on 1 and 85 DF,  p-value: 0.5203
FishLRCond = lm(logCPUE ~ av_conductivity, data=FykeLR)
summary(FishLRCond)
## 
## Call:
## lm(formula = logCPUE ~ av_conductivity, data = FykeLR)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.9532 -1.3011 -0.0562  1.2375  4.1293 
## 
## Coefficients:
##                 Estimate Std. Error t value Pr(>|t|)   
## (Intercept)     0.288934   0.739224   0.391   0.6969   
## av_conductivity 0.003843   0.001374   2.796   0.0064 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.584 on 85 degrees of freedom
## Multiple R-squared:  0.08421,    Adjusted R-squared:  0.07344 
## F-statistic: 7.816 on 1 and 85 DF,  p-value: 0.006401

Time to plot!

# Temp
FishLRTempplot = plot(FykeLR$av_temp, FykeLR$logCPUE,col = "black",
       main = "Total Site logCPUE & Average Temperature Regression",
       abline(lm(FykeLR$logCPUE ~ FykeLR$av_temp)),
       cex = 1.3,
       pch = 16,
       xlab = "Total Site logCPUE",
       ylab = "Average Temperature (Celsius)")

# DO
FishLR_DOplot = plot(FykeLR$av_do,FykeLR$logCPUE,col = "black",
       main = "Total Site logCPUE & Average Dissolved Oxygen Regression",
       abline(lm(FykeLR$logCPUE~FykeLR$av_do)),
       cex = 1.3,
       pch = 16,
       xlab = "Total Site logCPUE",
       ylab = "Average Dissolved Oxygen (mg/L)")

# PH
FishLR_pHplot = plot(FykeLR$av_pH,FykeLR$logCPUE,col = "black",
       main = "Total Site logCPUE & Average pH Regression",
       abline(lm(FykeLR$logCPUE~FykeLR$av_pH)),
       cex = 1.3,
       pch = 16,
       xlab = "Total Site logCPUE",
       ylab = "Average pH")

# TURB
FishLR_Turbplot = plot(FykeLR$av_turbidity,FykeLR$logCPUE,col = "black",
       main = "Total Site logCPUE & Average Turbidity Regression",
       abline(lm(FykeLR$logCPUE~FykeLR$av_turbidity)),
       cex = 1.3,
       pch = 16,
       xlab = "Total Site logCPUE",
       ylab = "Average Turbidity (FNU)")

# COND
FishLR_Condplot = plot(FykeLR$av_conductivity,FykeLR$logCPUE,col = "black",
       main = "Total Site logCPUE & Average Conductivity Regression",
       abline(lm(FykeLR$logCPUE~FykeLR$av_conductivity)),
       cex = 1.3,
       pch = 16,
       xlab = "Total Site logCPUE",
       ylab = "Average Conductivity (uS/cm2)")