This package was designed to import, manipulate, and plot data collected as a part of the NPS Northeast Temperate Inventory and Monitoring Network’s (NETN) Coastal Breeding Bird program at Boston Harbor Islands National Recreation Area (BOHA). For further information about the program visit https://www.nps.gov/im/netn/coastal-birds.htm.
The following surveys are conducted in this program:
This document introduces you to NETNCoastalBirds’s basic set of tools, and shows you how to apply them. For further documentation of the sampling design, survey methods and quality control procedures followed please consult Trocki et. al (2015).
Trocki, C. L., B. R. Mitchell, and P. W. C. Paton. 2015. Coastal breeding bird monitoring protocol for Boston Harbor Islands National Recreation Area: 2015 revision. Natural Resource Report NPS/NETN/NRR—2015/954. National Park Service, Fort Collins, Colorado.
NEED TO ADD DATA TO PACKAGE FROM GET FUNCTIONS AND
The package contains a few functions that pulls in either raw or summarized survey data corresponding to each survey type. There are two options to import data: (1) via an ODBC connection on MS Windows to a MS Access database named “NETNCB” or (2) direct import from data file.
returns a data.frame of incubating adults of DCCO, HERG, GBBG. Note that running this command requires the NETN Coastal Bird MS Access database entered as ‘NETNCB’ in Windows ODBC manager.
returns a data.frame of counts corresponding to life stages of COEI. The following lifestages, indicated in the variable column, are counted:
This returns a data.frame of counts of nests and their contents of multiple species and has the following data columns:
This returns a data.frame of individual detections of AMOY taken during the surveys, typically between May and July of each year. These surveys are used to determine the number of mating pairs and assess demography of this species during the year.
This returns a data.frame of AMOY mating pairs estimated from the repeat visits that you can access via GetAMOYData.
There are a few summary or aggregation functions that sum bird life stages by day or annually. The functions also return summaries of birds detected for each island surveyed per species and across all islands surveyed per species. Summaries can be conducted for single or multiple species by entering in species codes into the species argument of each function.
This function will sum the number of incubating Herring Gulls (HERG) detected in each year per island. The argument time must be provided and can take the value year or date.
glimpse(SumIncubation(time = "year", species = "HERG"))
#> Observations: 151
#> Variables: 8
#> $ Species_Code <chr> "HERG", "HERG", "HERG", "HERG", "HERG", "HERG", ...
#> $ CommonName <chr> "Herring Gull", "Herring Gull", "Herring Gull", ...
#> $ FullLatinName <chr> "Larus argentatus", "Larus argentatus", "Larus a...
#> $ Island <chr> "Button", "Button", "Button", "Button", "Calf", ...
#> $ time <fct> 2007, 2011, 2016, 2018, 2007, 2008, 2009, 2010, ...
#> $ value <dbl> 4, 8, 22, 25, 85, 118, 93, 65, 44, 60, 102, 122,...
#> $ n <int> 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, ...
#> $ variable <chr> "Incubating adults", "Incubating adults", "Incub...Note that to sum by year you enter time= year. To sum by day, enter time = date. The count is denoted in the value column of the returned data frame and n denotes the number of observations. Finally, variable denotes the life stage detected. When you don’t provide an argument to species, SumIncubation() will return all species surveyed.
Since there are numerous detections of Common Eider (COEI) per day and year, this function sums the number of birds detected in each year per island of 4 four life stages. The counts are summarized in the followig life stages: No. of females, No. of Females tending Duckings, No. lone Females, Mean creche size (no. duckings) from the Outer Islands. To sum counts by year:
glimpse(CrecheSum(time= "year"))
#> Observations: 448
#> Variables: 7
#> $ Species_Code <chr> "COEI", "COEI", "COEI", "COEI", "COEI", "COEI", ...
#> $ CommonName <chr> "Common Eider", "Common Eider", "Common Eider", ...
#> $ FullLatinName <chr> "Smateria mollissima", "Smateria mollissima", "S...
#> $ Island <chr> "Calf", "Calf", "Calf", "Calf", "Calf", "Calf", ...
#> $ time <dbl> 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, ...
#> $ variable <chr> "Adult female COEI tending", "Adult female COEI ...
#> $ value <dbl> 0, 64, 78, 18, 15, 10, 10, 60, 3, 80, 13, 8, 7, ...To sum by date in a year
glimpse(CrecheSum(time= "year"))
#> Observations: 448
#> Variables: 7
#> $ Species_Code <chr> "COEI", "COEI", "COEI", "COEI", "COEI", "COEI", ...
#> $ CommonName <chr> "Common Eider", "Common Eider", "Common Eider", ...
#> $ FullLatinName <chr> "Smateria mollissima", "Smateria mollissima", "S...
#> $ Island <chr> "Calf", "Calf", "Calf", "Calf", "Calf", "Calf", ...
#> $ time <dbl> 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, ...
#> $ variable <chr> "Adult female COEI tending", "Adult female COEI ...
#> $ value <dbl> 0, 64, 78, 18, 15, 10, 10, 60, 3, 80, 13, 8, 7, ...To sum daily surveys by each Observer enter CrecheSum(time="date", ByObserver= "yes" )
Adult incubating Common Terns are surveyed on Spinnaker Platform. This returns the annual
glimpse(CrecheSum(time= "year"))
#> Observations: 448
#> Variables: 7
#> $ Species_Code <chr> "COEI", "COEI", "COEI", "COEI", "COEI", "COEI", ...
#> $ CommonName <chr> "Common Eider", "Common Eider", "Common Eider", ...
#> $ FullLatinName <chr> "Smateria mollissima", "Smateria mollissima", "S...
#> $ Island <chr> "Calf", "Calf", "Calf", "Calf", "Calf", "Calf", ...
#> $ time <dbl> 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, ...
#> $ variable <chr> "Adult female COEI tending", "Adult female COEI ...
#> $ value <dbl> 0, 64, 78, 18, 15, 10, 10, 60, 3, 80, 13, 8, 7, ...This functions sums the number of nests and their contents by species and island. Similar arguments can be passed to the function as above. Summarize annual nest, egg, and chick counts for Common Eider by:
glimpse(SumNestSurveys(time= "year", species="COEI"))
#> Observations: 84
#> Variables: 8
#> $ Species_Code <chr> "COEI", "COEI", "COEI", "COEI", "COEI", "COEI", ...
#> $ CommonName <chr> "Common Eider", "Common Eider", "Common Eider", ...
#> $ FullLatinName <chr> "Smateria mollissima", "Smateria mollissima", "S...
#> $ Island <chr> "Calf", "Calf", "Calf", "Calf", "Calf", "Calf", ...
#> $ time <dbl> 2007, 2007, 2007, 2008, 2008, 2008, 2012, 2012, ...
#> $ Count_Method <chr> "Direct Count", "Direct Count", "Direct Count", ...
#> $ variable <chr> "Chicks", "Eggs", "Nests", "Chicks", "Eggs", "Ne...
#> $ value <dbl> 0, 264, 72, 0, 363, 95, 3, 97, 24, 2, 0, 266, 63...Sum annual nest counts of Glossy Ibis (GLIB) and Great Egret (GREG)
glimpse(SumNestSurveys(time= "year", species = c("GLIB","GREG") ))
#> Observations: 125
#> Variables: 8
#> $ Species_Code <chr> "GLIB", "GLIB", "GLIB", "GLIB", "GLIB", "GLIB", ...
#> $ CommonName <chr> "Glossy Ibis", "Glossy Ibis", "Glossy Ibis", "Gl...
#> $ FullLatinName <chr> "Plegadis falcinellus", "Plegadis falcinellus", ...
#> $ Island <chr> "Calf", "Calf", "Calf", "Calf", "Grape", "Great ...
#> $ time <dbl> 2007, 2009, 2012, 2016, 2013, 2009, 2013, 2007, ...
#> $ Count_Method <chr> "Direct Count", "Direct Count", "Direct Count", ...
#> $ variable <chr> "Nests", "Nests", "Nests", "Nests", "Nests", "Ne...
#> $ value <dbl> 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 3, ...This function creates a time series plot of bird detections using ggplot. The function was built to plot data in a data.frame created in one of the “Sum” functions described above, but will also plot a data.frame with the following column names: Species_Code, CommonName,FullLatinName,Island,time, ’value, andvariable`. The default plots time series of single or multiple species by Island into separate “facets”.
Let’s start by plotting annual detections of one species. For Double-Crested Cormorant incubating adults per island you would:
You can also plot detections of DCCO per island on the log-scale by:
To plot multiple species detected annually during boat-based incubation surveys you would:
Note that plot titles can only report one species at this time, so when plotting multiple species it is appropriate to turn this off by plot_title = "no". Also, to ad the plot legend to show detections by species add legend = TRUE.
You can also plot detections for one (or a group of) selected island(s) (assuming that species was surveyed there) by passing an island name to island.
You can also plot other survey data. Let’s try plotting ground-based nest survey data of COmmon Eider.
Since nest surveys collect data on nest, eggs per nest, and chicks per nest you can plot all of these variables (as in the above example) or a selection of them by entering arguments to
var; for instance, var= “Nests”` to plot nest counts per island.
It is often of interest to evaluate the detections of a species throughout the year. By changing the time argument in the summary functions to date you can plot daily detections. This tends to look best in a plot when specified for a year, which you can denote in the year argument. This plots detections of Common Eider life stages during the 2019 field season.