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authorKen Kellner <ken.kellner@gmail.com>2016-10-03 20:54:02 (GMT)
committerKen Kellner <ken.kellner@gmail.com>2016-10-03 20:54:02 (GMT)
commit51f8450fc856f5200a2023bb3dea6ca30d063bd5 (patch)
treead1d7c8d3431cedaeda467c0798047ee46d15fe7
parent71e4e8fbd92da8bc9bfefe08b23faef0b0b4514b (diff)
Finish modularizing figures. Upload semi-final TWS talk.
-rw-r--r--figures/fig3_mu_abun.R87
-rw-r--r--figures/fig4_mu_rich.R55
-rw-r--r--figures/fig6_hl_abun.R4
-rw-r--r--figures/fig7_hl_rich.R57
-rw-r--r--presentations/talk_tws2016.tex70
5 files changed, 62 insertions, 211 deletions
diff --git a/figures/fig3_mu_abun.R b/figures/fig3_mu_abun.R
index 360f238..e927f71 100644
--- a/figures/fig3_mu_abun.R
+++ b/figures/fig3_mu_abun.R
@@ -2,6 +2,9 @@
## Abundance Figure for Management Spatial Scale - Figure 3 ##
##############################################################
+#Read in figure script
+source('figures/figure_multidens.R')
+
#Read in output
load('output/mu_bird_abun.Rdata')
@@ -9,91 +12,13 @@ sp.include <- c('OVEN','REVI','ACFL',
'WOTH','WEWA','CERW',
'BAWW','HOWA','CARW',
'EATO','INBU','WEVI')
-nsp <- length(sp.include)
-
-#Location in 3x3 grid
-nrow <- 3
-ncol <- 4
-col.loc <- c(1,2,3,1,2,3,1,2,3,1,2,3)
-row.loc <- c(4,4,4,3,3,3,2,2,2,1,1,1)
-
-#Control figure width based on # of columns
-maxx <- 10
-adjx <- c(0,11,22)
-wi <- nrow*10+3
-xticks1 <- c(2,4,6,8,10)
-xticks2 <- xticks1+adjx[2]
-xticks3 <- xticks1+adjx[3]
-
-#Control figure height to fit all species figures
-maxy <- 5
-titleht<- maxy/4
-adjy <- c(0,(maxy+titleht),(maxy+titleht)*2,(maxy+titleht)*3)
-ht <- (maxy+titleht)*ncol
-yticks1 <- c(1,2,3,4)
-yticks2 <- yticks1+adjy[2]
-yticks3 <- yticks1+adjy[3]
-yticks4 <- yticks1+adjy[4]
-
-titlesz <- 0.8
-lwd <- 1
-
-cols <- gray(c(0,0.4,0.6))
-ltys <- c(1:3)
#Set up figure container
tiff(filename="figures/fig3_abun.tiff",width=90,height=118,units="mm",res=1000, pointsize=8,
compression = "lzw",type='cairo')
-par(mar = c(3,3,0.5,1) + 0.1, oma=c(0,0,0,0),mgp=c(0.6,0.6,0))
-
-plot(1,type='n',xlim=c(0,wi),ylim=c(0,ht),xaxt='n',yaxt='n',xaxs='i',yaxs='i',
- ylab="",xlab='')
-
-#Set up axes
-axis(1,at=c(xticks1,xticks2,xticks3),labels=rep(c(2,4,6,8,10),3),tcl=-0.3,cex.axis=0.8)
-axis(2,at=c(yticks1,yticks2,yticks3,yticks4),labels=rep(c(1,2,3,4),4),tcl=-0.3,cex.axis=0.8)
-
-title(xlab='Year',line=1.7)
-title(ylab=expression(paste("Density Index (males ha"^{-1},")")),line=1.7)
-
-#Draw lines dividing up plot into 3x3 grid
-abline(v=11)
-abline(v=22)
-abline(h=maxy)
-abline(h=maxy+titleht)
-abline(h=adjy[2]+maxy)
-abline(h=adjy[2]+maxy+titleht)
-abline(h=adjy[3]+maxy)
-abline(h=adjy[3]+maxy+titleht)
-abline(h=adjy[4]+maxy)
-abline(h=adjy[4]+maxy+titleht)
-
-#Iterate through species
-for (i in 1:nsp){
-
- ind <- which(species==sp.include[i])
-
- xloc <- c(1:10) + adjx[col.loc[i]] #Location on x-axis
-
- #Draw lines for each treatment
- for (j in 1:3){
- abun.vector <- colMeans(Ntreat[,,j,ind])+adjy[row.loc[i]] #Calculate yearly means for treatment j
- lines(xloc,abun.vector,lwd=lwd,lty=ltys[j],col=cols[j])
- lines(xloc[c(7,9)],abun.vector[c(7,9)],col=cols[j],lty=ltys[j])
- }
-
- #Draw vertical line at time of harvest
- segments(x0=mean(xloc[3:4]),y0=adjy[row.loc[i]],
- x1=mean(xloc[3:4]),y1=adjy[row.loc[i]]+maxy,lty=2)
-
- #Add species code
- text(adjx[col.loc[i]]+(maxx+1)/2,adjy[row.loc[i]]+maxy+titleht/2,sp.include[i])
-
-}
-
-#Draw legend
-legend(0,23.75,c('No Harvest','Even-Aged','Uneven-Aged'),cex=0.8,
- lwd=1,col=cols,bg="white",lty=ltys)
+multidens.figure(sp.include, scale='mu',nrow=4,ncol=3,maxy=5,
+ yticks=1:4,legendpos=c(2,1),
+ cols=gray(c(0,0.4,0.6)),ltys=1:3,lwd=1)
dev.off() \ No newline at end of file
diff --git a/figures/fig4_mu_rich.R b/figures/fig4_mu_rich.R
index 1421cbd..dcbec53 100644
--- a/figures/fig4_mu_rich.R
+++ b/figures/fig4_mu_rich.R
@@ -2,62 +2,17 @@
## Richness Figure for Management Spatial Scale - Figure 4 ##
#############################################################
+#Read in figure script
+source('figures/figure_richness.R')
+
#Read in output
load('output/mu_bird_abun.Rdata')
-#Set plotting options
-colors = gray(seq(0.1,0.4,length=3))
-figmax <- 28.5
-figmin <- 17
-pch <- c(17:19)
-lty <- c(1:3)
-
-#Functions to calculate 95% CI
-qu <- function(x){as.numeric(quantile(x,0.975,na.rm=T))}
-ql <- function(x){as.numeric(quantile(x,0.025,na.rm=T))}
-
-#Calculate treatment x year means
-rich.means <- rich.upper <- rich.lower <- matrix(NA,nrow=3,ncol=10)
-
-for (i in 1:3){
- rich.means[i,] <- colMeans(Rtreat[,,i])
- rich.lower[i,] <- apply(Rtreat[,,i],2,ql)
- rich.upper[i,] <- apply(Rtreat[,,i],2,qu)
-}
-
#Set up plot
tiff(filename="figures/fig4_rich.tiff",width=90,height=90,units="mm",res=1000, pointsize=8,
compression = "lzw",type='cairo')
-par(mar = c(4,3.5,0.5,1) + 0.1, oma=c(0,0,0,0),mgp=c(2.5,1,0))
-plot(1:10,rich.means[1,],ylim=c(figmin,figmax),
- main="",type='o',cex=2,lty=lty[1],col=colors[1],
- lwd=2,pch=pch[1],xaxt='n',xlab="Year",ylab='Richness',
- xlim=c(0.5,10.5))
-axis(side=1,at=c(1,3,5,7,9), labels=c('2006', '2008', '2010','2012','2014'),tck=0)
-
-#Error bars
-wd=0.1
-for (i in 1:10){
- for (j in 1:3){
- segments(i,rich.lower[j,i],i,rich.upper[j,i])
- segments(i-wd,rich.lower[j,i],i+wd,rich.lower[j,i])
- segments(i-wd,rich.upper[j,i],i+wd,rich.upper[j,i])
- }
-}
-
-#Draw lines
-for (j in 1:3){
- lines(1:10,rich.means[j,],type='o',cex=2,lty=lty[j],col=colors[j],
- lwd=2,pch=pch[j])
- lines(c(7,9),rich.means[j,c(7,9)],lty=lty[j],col=colors[j],lwd=2)
-}
-
-#Draw vertical line at time of harvest
-abline(v=3.5,lty=2)
-
-#Add legend
-legend('topleft',c('No Harvest','Even-Aged','Uneven-Aged'),cex=1,
- pch=pch,lwd=2,col=colors,bg="white",lty=lty)
+richness.figure(scale='mu',figmin=17,figmax=28.5,cols=gray(seq(0.1,0.4,length=3)),
+ pchs=17:19,ltys=1:3)
dev.off() \ No newline at end of file
diff --git a/figures/fig6_hl_abun.R b/figures/fig6_hl_abun.R
index 030e458..e34f076 100644
--- a/figures/fig6_hl_abun.R
+++ b/figures/fig6_hl_abun.R
@@ -2,9 +2,11 @@
## Abundance Figure for Harvest Spatial Scale - Figure 6 ##
############################################################
+#Read in figure script
+source('figure_multidens.R')
+
#Read in output
load('output/hl_bird_abun.Rdata')
-source('figure_multidens.R')
sp.include <- c('OVEN','REVI','ACFL',
'WOTH','WEWA','CERW',
diff --git a/figures/fig7_hl_rich.R b/figures/fig7_hl_rich.R
index 5971221..6e1c46a 100644
--- a/figures/fig7_hl_rich.R
+++ b/figures/fig7_hl_rich.R
@@ -2,64 +2,17 @@
## Richness Figure for Harvest Spatial Scale - Figure 7 ##
##########################################################
+#Read in figure script
+source('figures/figure_richness.R')
+
#Read in output
load('output/hl_bird_abun.Rdata')
-#Set plotting options
-
-colors <- gray(c(0,0.7,0.5,0.4,0.2))
-figmax <- 31
-figmin <- 16
-pch <- c(17,15,16,18,21)
-lty <- c(1:5)
-
-#Functions to calculate 95% CI
-qu <- function(x){as.numeric(quantile(x,0.975,na.rm=T))}
-ql <- function(x){as.numeric(quantile(x,0.025,na.rm=T))}
-
-#Calculate treatment x year means
-rich.means <- rich.upper <- rich.lower <- matrix(NA,nrow=5,ncol=10)
-
-for (i in 1:5){
- rich.means[i,] <- colMeans(Rtreat.harvest[,,i])
- rich.lower[i,] <- apply(Rtreat.harvest[,,i],2,ql)
- rich.upper[i,] <- apply(Rtreat.harvest[,,i],2,qu)
-}
-
#Set up plot
tiff(filename="figures/fig7_rich.tiff",width=90,height=90,units="mm",res=1000, pointsize=8,
compression = "lzw",type='cairo')
-par(mar = c(4,3.5,0.5,1) + 0.1, oma=c(0,0,0,0),mgp=c(2.5,1,0))
-plot(1:10,rich.means[1,],ylim=c(figmin,figmax),
- main="",type='o',cex=2,lty=lty[1],col=colors[1],
- lwd=2,pch=pch[1],xaxt='n',yaxt='n',xlab="Year",ylab='Richness',
- xlim=c(0.5,10.5))
-axis(side=1,at=c(1,3,5,7,9), labels=c('2006', '2008', '2010','2012','2014'),tck=0)
-axis(side=2,at=c(16,18,20,22,24,26,28,30),labels=c(16,18,20,22,24,26,28,30))
-
-#Error bars
-wd=0.1
-for (i in 1:10){
- for (j in 1:5){
- segments(i,rich.lower[j,i],i,rich.upper[j,i])
- segments(i-wd,rich.lower[j,i],i+wd,rich.lower[j,i])
- segments(i-wd,rich.upper[j,i],i+wd,rich.upper[j,i])
- }
-}
-
-#Draw lines
-for (j in 1:5){
- lines(1:10,rich.means[j,],type='o',cex=2,lty=lty[j],col=colors[j],
- lwd=2,pch=pch[j])
- lines(c(7,9),rich.means[j,c(7,9)],lty=lty[j],col=colors[j],lwd=2)
-}
-
-#Draw vertical line at time of harvest
-abline(v=3.5,lty=2)
-
-#Add legend
-legend('topleft',c('No Harvest','Clearcut','Patch Cut','Shelter','Single-tree'),cex=1,
- pch=pch,lwd=1,col=colors,bg="white",lty=lty)
+richness.figure(scale='hl',figmin=16,figmax=31,cols=gray(c(0,0.7,0.5,0.4,0.2)),
+ pchs=c(17,15,16,18,21),ltys=1:5)
dev.off() \ No newline at end of file
diff --git a/presentations/talk_tws2016.tex b/presentations/talk_tws2016.tex
index d752dee..db820f5 100644
--- a/presentations/talk_tws2016.tex
+++ b/presentations/talk_tws2016.tex
@@ -15,44 +15,60 @@
%\section{Introduction}
- \begin{frame}{Forest Maturation}
+ \begin{frame}{Conservation of Migratory Birds}
+
+ \textbf{Population Declines}\textsuperscript{1}
+
+ \bigskip
+
+ \textbf{Habitat Loss}
+ \begin{itemize}
+ \item Conversion of forest to agriculture/development\textsuperscript{1}
+ \item Fragmentation
+ \item Maturation of existing forest\textsuperscript{2}
+ \end{itemize}
+
+ \bigskip
+ \textsuperscript{1}\scriptsize{Robbins et al. 1989};
+ \textsuperscript{2}\scriptsize{Trani et al. 2001}
+
\end{frame}
\begin{frame}{Importance of Early-Successional Habitat}
- \begin{itemize}
- \item \textbf{74\%} of shrubland species are declining (Sauer et al. 2013)
- \item \textbf{51\%} of species use young forest habitat (Probst and Thompson 1996)
- \item Provides \textbf{food} and \textbf{cover}
- \end{itemize}
\begin{center}
\includegraphics[width=0.8\paperwidth]{images/clearcut.png}
\end{center}
+
+ \begin{itemize}
+ \item \textbf{74\%} of shrubland species are declining\textsuperscript{1}
+ \item \textbf{51\%} of species use young forest habitat\textsuperscript{2}
+ \end{itemize}
+ \textsuperscript{1}\scriptsize{Sauer et al. 2013};
+ \textsuperscript{2}\scriptsize{Probst \& Thompson 1996}
\end{frame}
\begin{frame}{Forest Management}
- \begin{columns}
- \begin{column}{0.48\textwidth}
- \begin{center}
- \textbf{Silviculture}
- \bigskip
-
- \includegraphics[width=0.4\paperwidth]{images/clearcut.png}
+ %\begin{columns}
+ %\begin{column}{0.48\textwidth}
+ \begin{center}
+ \includegraphics[width=0.8\paperwidth]{images/clearcut_long.png}
- Even-aged
+ \textbf{Even-aged:} Clearcuts, Shelterwoods
\bigskip
- \includegraphics[width=0.4\paperwidth]{images/singletree.png}
+ \includegraphics[width=0.8\paperwidth]{images/singletree_long.png}
- Uneven-aged
+ \textbf{Uneven-aged:} Single-tree \& group selection, patch cuts
\end{center}
- \end{column}
- \begin{column}{0.48\textwidth}
- \begin{center}
+ %\end{column}
+ %\begin{column}{0.48\textwidth}
+ % \begin{center}
+ % \textbf{Harvest Type}
- \end{center}
- \end{column}
- \end{columns}
+ % \end{center}
+ %\end{column}
+ %\end{columns}
\end{frame}
@@ -69,7 +85,7 @@
Are there consistent patterns:
\begin{itemize}
\item Based on \textbf{scale} and \textbf{intensity} of management?
- \item For "\textbf{early successional}" vs. "\textbf{mature forest}" birds?
+ \item For \textbf{shrubland} vs. \textbf{mature forest} birds?
\end{itemize}
\end{frame}
@@ -83,7 +99,7 @@
\textbf{Scale}
\begin{itemize}
- \item Spans 30 linear km
+ \item 3,603 ha study area
\item 100 years (in year 10)
\end{itemize}
@@ -271,8 +287,8 @@
\bigskip
\item Diversity of forest habitat and bird species richness are \textbf{positively related}:
\begin{itemize}
- \item Richness increased \textbf{18\%} following even-aged management
- \item Richness increased \textbf{22\%} following uneven-aged management
+ \item Richness increased \textbf{16\%} following even-aged management
+ \item Richness increased \textbf{19\%} following uneven-aged management
\end{itemize}
\end{itemize}
\end{frame}
@@ -328,7 +344,7 @@
\bigskip
- Kellner, K. F.; Ruhl, P. J.; Dunning Jr., J. B.; Riegel, J. K. and Swihart, R. K. \textit{In revision.} Multi-scale responses of breeding birds to experimental forest management in Indiana, USA. \textit{Forest Ecology and Management}.
+ Kellner, K. F.; Ruhl, P. J.; Dunning Jr., J. B.; Riegel, J. K. and Swihart, R. K. \textit{In press.} Multi-scale responses of breeding birds to experimental forest management in Indiana, USA. Forest Ecology and Management. doi: 10.1016/j.foreco.2016.10.008.
\end{frame}