birdsize for the Breeding Bird Survey
birdsize is written to interface naturally with data
from the North American Breeding Bird Survey (Pardieck et al. 2019).
Beginning with data from a BBS route, birdsize can directly
simulate body size and basal metabolic rate measurements and calculate
year- or species-wide summary statistics.
Obtaining data
Data releases for the Breeding Bird Survey are available on ScienceBase, e.g. here.
The Data Retriever also provides an interface for downloading recent releases. Instructions for installing the Data Retriever for R are available here.
birdsize includes a demo dataset with the same column
names as the Breeding Bird Survey data available through ScienceBase or
the Retriever, but with synthetic data. For an explanation of each of
the column names, see the Help page for demo_route_raw or the
metadata available on ScienceBase.
demo_raw_data <- birdsize::demo_route_raw
head(demo_raw_data)
#> record_id routedataid countrynum statenum route rpid year AOU count10
#> 1 900000 9009911011994 900 99 1 101 1994 4730 8
#> 2 900001 9009911011995 900 99 1 101 1995 4730 13
#> 3 900002 9009911011996 900 99 1 101 1996 4730 8
#> 4 900003 9009911011997 900 99 1 101 1997 4730 9
#> 5 900004 9009911011998 900 99 1 101 1998 4730 10
#> 6 900005 9009911011999 900 99 1 101 1999 4730 12
#> count20 count30 count40 count50 stoptotal speciestotal
#> 1 12 15 12 15 5 62
#> 2 9 11 10 10 5 53
#> 3 11 9 13 15 5 56
#> 4 13 16 9 12 5 59
#> 5 6 12 8 7 5 43
#> 6 13 5 9 5 5 44Cleaning data
Following Harris et al. (2018), it is recommended to filter the raw
BBS data to remove taxa that are poorly sampled via the BBS methods
(e.g. nightbirds, waterbirds) and to remove unidenitifed taxa. The
filter_bbs_survey function performs this cleaning:
demo_clean_data <- birdsize::filter_bbs_survey(demo_raw_data)
head(demo_clean_data)
#> record_id routedataid countrynum statenum route rpid year AOU count10
#> 1 900000 9009911011994 900 99 1 101 1994 4730 8
#> 2 900001 9009911011995 900 99 1 101 1995 4730 13
#> 3 900002 9009911011996 900 99 1 101 1996 4730 8
#> 4 900003 9009911011997 900 99 1 101 1997 4730 9
#> 5 900004 9009911011998 900 99 1 101 1998 4730 10
#> 6 900005 9009911011999 900 99 1 101 1999 4730 12
#> count20 count30 count40 count50 stoptotal speciestotal
#> 1 12 15 12 15 5 62
#> 2 9 11 10 10 5 53
#> 3 11 9 13 15 5 56
#> 4 13 16 9 12 5 59
#> 5 6 12 8 7 5 43
#> 6 13 5 9 5 5 44Simulating individual-level measurements
The community_generate function will generate
individual-level size and BMR estimates for all individuals recorded in
a community data frame of the type available from ScienceBase, the
Retriever, or the included demo data:
set.seed(2022)
demo_community <- birdsize::community_generate(demo_clean_data)
head(demo_community)
#> record_id routedataid countrynum statenum route rpid year count10 count20
#> 1 900000 9009911011994 900 99 1 101 1994 8 12
#> 2 900000 9009911011994 900 99 1 101 1994 8 12
#> 3 900000 9009911011994 900 99 1 101 1994 8 12
#> 4 900000 9009911011994 900 99 1 101 1994 8 12
#> 5 900000 9009911011994 900 99 1 101 1994 8 12
#> 6 900000 9009911011994 900 99 1 101 1994 8 12
#> count30 count40 count50 stoptotal speciestotal AOU sim_species_id
#> 1 15 12 15 5 62 4730 4730
#> 2 15 12 15 5 62 4730 4730
#> 3 15 12 15 5 62 4730 4730
#> 4 15 12 15 5 62 4730 4730
#> 5 15 12 15 5 62 4730 4730
#> 6 15 12 15 5 62 4730 4730
#> individual_mass individual_bmr mean_size sd_size abundance sd_method
#> 1 40.44602 146.8560 37.475 3.300613 62 AOU lookup
#> 2 33.60224 128.6737 37.475 3.300613 62 AOU lookup
#> 3 34.51275 131.1501 37.475 3.300613 62 AOU lookup
#> 4 32.70726 126.2207 37.475 3.300613 62 AOU lookup
#> 5 36.38245 136.1775 37.475 3.300613 62 AOU lookup
#> 6 27.90115 112.6984 37.475 3.300613 62 AOU lookup
#> scientific_name
#> 1 Alauda arvensis
#> 2 Alauda arvensis
#> 3 Alauda arvensis
#> 4 Alauda arvensis
#> 5 Alauda arvensis
#> 6 Alauda arvensisThe first 15 columns (record_id through
AOU) are retained from the input data. For species in the
BBS, sim_species_id is identical to the AOU used for
species identification. scientific_name gives the
scientific name associated with the AOU. individual_mass
and individual_bmr are individual-level mass and
BMR estimates, with one for each individual recorded in the input data.
mean_size, sd_size, abundance,
and sd_method give the parameters used to generate the
individual-level estimates.
References
Harris DJ, Taylor SD, White EP. 2018. Forecasting biodiversity in breeding birds using best practices. PeerJ 6:e4278 https://doi.org/10.7717/peerj.4278
Pardieck, K.L., Ziolkowski Jr., D.J., Lutmerding, M., Aponte, V., and Hudson, M-A.R., 2019, North American Breeding Bird Survey Dataset 1966 - 2018 (ver. 2018.0): U.S. Geological Survey, Patuxent Wildlife Research Center, https://doi.org/10.5066/P9HE8XYJ.