1. Introductory videos and questions

Q1. What are 3 new(ish) developments in wildlife biologging technology?

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2.sdfghjk
3.sdfghjk

Q2. What are 3 management decisions or applications that could come from GPS collar data?

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Q3. Find a peer reviewed journal article that employs wildlife biologging, and briefly (max: 1 paragraph) describe its practical application to the study and wildlife management. Cite article using Journal of Wildlife Management (JWM) style (https://haywood.libguides.com/c.php?g=146410&p=3430227)

2. Opening & viewing the data

# installing required packages
#install.packages("ggplot2")
devtools::install_github("dkahle/ggmap", force=TRUE)

## WARNING: Rtools is required to build R packages, but is not currently installed.
## 
## Please download and install Rtools 4.0 from https://cran.r-project.org/bin/windows/Rtools/.

## Downloading GitHub repo dkahle/ggmap@HEAD

## stringi (1.7.6 -> 1.7.8) [CRAN]
## plyr    (1.8.7 -> 1.8.8) [CRAN]

## Installing 2 packages: stringi, plyr

## Installing packages into 'C:/Users/mgonza79/Documents/R/win-library/4.1'
## (as 'lib' is unspecified)

## 
##   There are binary versions available but the source versions are later:
##         binary source needs_compilation
## stringi  1.7.6  1.7.8              TRUE
## plyr     1.8.7  1.8.8              TRUE
## 
##   Binaries will be installed
## package 'stringi' successfully unpacked and MD5 sums checked

## Warning: cannot remove prior installation of package 'stringi'

## Warning in file.copy(savedcopy, lib, recursive = TRUE): problem copying C:
## \Users\mgonza79\Documents\R\win-library\4.1\00LOCK\stringi\libs\icudt69l.dat to
## C:\Users\mgonza79\Documents\R\win-library\4.1\stringi\libs\icudt69l.dat: Invalid
## argument

## Warning in file.copy(savedcopy, lib, recursive = TRUE): problem copying C:
## \Users\mgonza79\Documents\R\win-library\4.1\00LOCK\stringi\libs\x64\stringi.dll
## to C:\Users\mgonza79\Documents\R\win-library\4.1\stringi\libs\x64\stringi.dll:
## Permission denied

## Warning: restored 'stringi'

## package 'plyr' successfully unpacked and MD5 sums checked

## Warning: cannot remove prior installation of package 'plyr'

## Warning in file.copy(savedcopy, lib, recursive = TRUE): problem copying C:
## \Users\mgonza79\Documents\R\win-library\4.1\00LOCK\plyr\libs\x64\plyr.dll to C:
## \Users\mgonza79\Documents\R\win-library\4.1\plyr\libs\x64\plyr.dll: Permission
## denied

## Warning: restored 'plyr'

## 
## The downloaded binary packages are in
##  C:\Users\mgonza79\AppData\Local\Temp\RtmpiS6UrJ\downloaded_packages

## WARNING: Rtools is required to build R packages, but is not currently installed.
## 
## Please download and install Rtools 4.0 from https://cran.r-project.org/bin/windows/Rtools/.

## * checking for file 'C:\Users\mgonza79\AppData\Local\Temp\RtmpiS6UrJ\remotes35181ed9630a\dkahle-ggmap-c5d234c/DESCRIPTION' ... OK
## * preparing 'ggmap':
## * checking DESCRIPTION meta-information ... OK
## * checking for LF line-endings in source and make files and shell scripts
## * checking for empty or unneeded directories
## Removed empty directory 'ggmap/.github'
## * building 'ggmap_3.0.1.900.tar.gz'
##

## Installing package into 'C:/Users/mgonza79/Documents/R/win-library/4.1'
## (as 'lib' is unspecified)

#get working directory
getwd()

## [1] "C:/Users/mgonza79/Downloads"

#set working directory
setwd("C:/Users/mgonza79/Downloads")

#loading library
library(ggplot2, warn.conflicts = FALSE)

## Warning: package 'ggplot2' was built under R version 4.1.3

library(ggmap)

## i Google's Terms of Service: <https://mapsplatform.google.com>

## i Please cite ggmap if you use it! Use `citation("ggmap")` for details.

#Downloading and exploring the data
mydata<-readRDS("dataSWTH.rds")
head(mydata)

##                    ts      sig port motusTagID mfgID recvDeployLat
## 1 2018-08-03 10:19:27 -39.2407    3      30421   355       45.4307
## 2 2018-08-03 10:19:42 -42.7479    4      30421   355       45.4307
## 3 2018-08-03 10:19:49 -51.2009    5      30421   355       45.4307
## 4 2018-08-03 10:20:10 -44.5063    3      30421   355       45.4307
## 5 2018-08-03 10:20:31 -55.2335    4      30421   355       45.4307
## 6 2018-08-03 10:21:07 -50.4889    4      30421   355       45.4307
##   recvDeployLon          recvDeployName            recvSiteName antBearing
## 1      -73.9385 McGill_Bird_Observatory McGill_Bird_Observatory        120
## 2      -73.9385 McGill_Bird_Observatory McGill_Bird_Observatory        300
## 3      -73.9385 McGill_Bird_Observatory McGill_Bird_Observatory        220
## 4      -73.9385 McGill_Bird_Observatory McGill_Bird_Observatory        120
## 5      -73.9385 McGill_Bird_Observatory McGill_Bird_Observatory        300
## 6      -73.9385 McGill_Bird_Observatory McGill_Bird_Observatory        300
##           speciesEN         speciesFR         speciesSci   recvProjName
## 1 Swainson's Thrush Grive à dos olive Catharus ustulatus MONTREAL_MOULT
## 2 Swainson's Thrush Grive à dos olive Catharus ustulatus MONTREAL_MOULT
## 3 Swainson's Thrush Grive à dos olive Catharus ustulatus MONTREAL_MOULT
## 4 Swainson's Thrush Grive à dos olive Catharus ustulatus MONTREAL_MOULT
## 5 Swainson's Thrush Grive à dos olive Catharus ustulatus MONTREAL_MOULT
## 6 Swainson's Thrush Grive à dos olive Catharus ustulatus MONTREAL_MOULT

#determine the number of individuals
unique(mydata$motusTagID)

##  [1] 30421 31092 31093 31284 31285 31291 31297 31083 31088 31253
## Levels: 30421 31083 31088 31092 31093 31253 31284 31285 31291 31297

length(unique(mydata$motusTagID))

## [1] 10

3. Visualizing the data

ggplot(data = mydata, aes(x = as.POSIXct(round(ts, "hour")),y=as.factor(motusTagID), colour = recvSiteName))+theme_bw() + geom_point() +labs(x = "Time (rounded to hour)", y = "MotusTagID") +scale_colour_discrete(name = "Receiver")

Q4.1 Re-create the Time X MotusTagID plot with the subsetted data (31284)

#create subset data
subset31284 <- subset(mydata, motusTagID == 31284)

#create solo-bird plot
subset31284 <- subset(mydata, motusTagID == 31284)
ggplot(data = subset31284, aes(x = as.POSIXct(round(ts, "hour")),y=as.factor(motusTagID), colour = recvSiteName))+theme_bw() + geom_point() +labs(x = "Time (rounded to hour)", y = "MotusTagID") +scale_colour_discrete(name = "Receiver")

Q4.2 Create a signal-strength plot with the subsetted data (31284) using the following code;

ggplot(subset31284,aes(ts, sig, colour = as.factor(antBearing))) +geom_point() + facet_grid(recvSiteName ~ .) + theme_bw()

4. GGMAP

#Create a basemap using ggmap
gmap <- get_stamenmap(bbox = c(left = -95, right = -57,bottom = 0, top = 48), maptype ="terrain-background", zoom =6)

## i Map tiles by Stamen Design, under CC BY 3.0. Data by OpenStreetMap, under ODbL.

## i 77 tiles needed, this may take a while (try a smaller zoom?)

#view base map using the plot() function
plot(gmap)

Q5. Display the map you generated with the coordinate point GGMAP

#Add points to the map and display
#create coordinate map:
ggmap(gmap) + theme_bw() + geom_point(data = mydata, aes(x = recvDeployLon, y = recvDeployLat), shape = 21, colour = "black", fill = "yellow") +geom_path(data = mydata, aes(x = recvDeployLon, y = recvDeployLat, group = motusTagID, col = as.factor(motusTagID))) +scale_color_discrete(name = "MotusTagID")

5. Exploring the signal patterns in more detail

Q6. Display the graphs you’ve made in Section 5 into

#use bird 31088
tag31088 <- subset(mydata, motusTagID == 31088)
#visualize the detentions of this bird 31088
ggplot(tag31088,aes(ts, sig, colour = as.factor(antBearing))) +geom_point() + facet_grid(recvSiteName ~ .) +theme_bw()

#Subset to a period of 2 days. September 09-September 11
sub_31088 <- subset(tag31088, ts > "2018-09-09 00:00:00" & ts < "2018-09-11 06:00:00" )
#plot this
ggplot(sub_31088,aes(ts, sig, colour = as.factor(antBearing)))+geom_point() +facet_grid(recvSiteName ~ .) + theme_bw()

Q7. Do you see a pattern in the generated plot? What could cause this pattern? Write one clear explanation in a few sentences.

the pattern seem to correspond to diurnal fluctuation

Q8. What is your favourite species of bird? Briefly (max 1 paragraph) come up with a study idea for how you could use a biologger of your choice to learn something new about the behaviour or conservation concerns of that species. How would you use ggmap to demonstrate the findings? (consider: point maps, heat maps, contour plots, raster maps, etc.)

sdfghjkl

6. Closing informational videos

Q9. What did the backpack transmitter data tell us about Baltimore and his behaviour?

positiondfghj

Q10. Why do you think that this is important information to know about Snowy Owls?

sadfghjoihgfds

Lab 2: Biologging

Maria Lucia Gonzalez Torres

2022-11-14

1. Introductory videos and questions

Q1. What are 3 new(ish) developments in wildlife biologging technology?

Q2. What are 3 management decisions or applications that could come from GPS collar data?

Q3. Find a peer reviewed journal article that employs wildlife biologging, and briefly (max: 1 paragraph) describe its practical application to the study and wildlife management. Cite article using Journal of Wildlife Management (JWM) style (https://haywood.libguides.com/c.php?g=146410&p=3430227)

2. Opening & viewing the data

3. Visualizing the data

Q4.1 Re-create the Time X MotusTagID plot with the subsetted data (31284)

Q4.2 Create a signal-strength plot with the subsetted data (31284) using the following code;

4. GGMAP

Q5. Display the map you generated with the coordinate point GGMAP

5. Exploring the signal patterns in more detail

Q6. Display the graphs you’ve made in Section 5 into

Q7. Do you see a pattern in the generated plot? What could cause this pattern? Write one clear explanation in a few sentences.

6. Closing informational videos

Q9. What did the backpack transmitter data tell us about Baltimore and his behaviour?

Q10. Why do you think that this is important information to know about Snowy Owls?