Load metadata for sampling trips from the National Reference Stations (NRS)
or Continuous Plankton Recorder (CPR) survey. This unified function replaces
the survey-specific functions pr_get_NRSTrips() and pr_get_CPRTrips().
pr_get_trips(Survey = "NRS", ...)Survey type to retrieve trips for:
"NRS" - National Reference Station trips (default)
"CPR" - Continuous Plankton Recorder trips
Additional arguments passed to pr_add_Bioregions() when
Survey = "CPR". Currently supports:
near_dist_km - Distance in kilometres to pad bioregion boundaries when
assigning samples to regions (default behaviour uses exact boundaries)
A dataframe with trip information. Common columns include:
TripCode - Unique trip identifier
SampleTime_Local - Local sampling date and time
Year_Local, Month_Local - Temporal components
Latitude, Longitude - Geographic coordinates
Additional columns vary by survey:
NRS: StationCode, StationName
CPR: BioRegion - Australian marine bioregion assignment
NRS Trips: Returns information about each NRS sampling trip (voyage), including the trip code, station, date/time, and basic metadata. Only NRS project trips are included (SOTS trips are excluded). Samples designated as 'P' (plankton) samples or with no sample type designation are included.
CPR Trips: The CPR samples continuously as it is towed behind ships of
opportunity. Each "trip" represents a segment of the tow, typically covering
approximately 3 nautical miles. Samples are automatically assigned to
Australian marine bioregions using pr_add_Bioregions(). Bioregions include:
Temperate East, South-east, South-west, North, and North-west.
pr_get_info() for station-level metadata,
pr_add_Bioregions() for bioregion assignment details
# Get NRS trip metadata
dat <- pr_get_trips(Survey = "NRS")
# Get CPR trip metadata with default bioregion assignment
dat <- pr_get_trips(Survey = "CPR")
# Get CPR trips with expanded bioregion boundaries (250 km padding)
dat <- pr_get_trips(Survey = "CPR", near_dist_km = 250)
# Examine sampling frequency by station (NRS)
dat <- pr_get_trips(Survey = "NRS")
table(dat$StationName, dat$Year_Local)
#>
#> 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
#> Bonney Coast 0 0 0 0 0 0 0 0 0 0
#> Darwin 0 0 0 0 0 0 0 0 0 2
#> Esperance 0 0 0 0 0 0 0 4 3 4
#> Kangaroo Island 0 0 0 0 0 0 8 9 9 11
#> Maria Island 0 0 0 0 0 0 0 9 9 10
#> Ningaloo 0 0 0 0 0 0 0 0 1 4
#> North Stradbroke Island 0 0 0 0 0 0 4 15 12 12
#> Port Hacking 0 0 0 0 0 0 0 13 13 12
#> Port Hacking 4 11 12 12 9 5 11 11 1 0 0
#> Rottnest Island 0 0 0 0 0 0 0 2 9 11
#> Yongala 0 0 0 0 0 0 0 3 9 11
#>
#> 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
#> Bonney Coast 0 0 0 0 0 0 0 0 0 0
#> Darwin 14 6 11 11 10 10 10 10 11 10
#> Esperance 5 2 0 0 0 0 0 0 0 0
#> Kangaroo Island 3 4 7 6 4 4 4 4 3 4
#> Maria Island 11 11 13 9 10 11 10 10 9 12
#> Ningaloo 4 3 0 0 0 0 0 0 0 0
#> North Stradbroke Island 9 12 11 12 10 11 10 10 10 11
#> Port Hacking 10 12 12 10 10 10 10 11 9 9
#> Port Hacking 4 0 0 0 0 0 0 0 0 0 0
#> Rottnest Island 11 10 11 10 11 12 12 12 11 11
#> Yongala 12 11 12 12 12 12 12 12 12 12
#>
#> 2022 2023 2024 2025
#> Bonney Coast 0 0 3 3
#> Darwin 10 10 10 6
#> Esperance 0 0 0 0
#> Kangaroo Island 4 3 4 4
#> Maria Island 11 10 11 11
#> Ningaloo 0 0 0 0
#> North Stradbroke Island 10 12 8 5
#> Port Hacking 11 9 10 7
#> Port Hacking 4 0 0 0 0
#> Rottnest Island 10 11 10 10
#> Yongala 11 13 12 8
# Examine sampling effort by bioregion and year (CPR)
dat <- pr_get_trips(Survey = "CPR")
table(dat$BioRegion, dat$Year_Local)
#>
#> 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
#> Coral Sea 0 0 0 0 0 34 13 204 285 0 0
#> None 0 0 4 216 282 468 434 493 456 352 283
#> North 0 0 0 0 0 0 142 0 0 0 55
#> North-west 0 0 0 116 78 452 107 0 0 0 0
#> South-east 0 43 295 770 791 828 723 702 915 630 934
#> South-west 0 0 0 255 272 313 250 441 323 172 311
#> Southern Ocean Region 575 588 488 552 431 215 117 110 130 432 655
#> Temperate East 0 0 475 518 266 346 96 809 686 231 454
#>
#> 2018 2019 2020 2021 2022 2023 2024 2025
#> Coral Sea 0 10 0 0 0 0 0 0
#> None 140 876 376 373 332 547 413 232
#> North 0 61 0 0 23 0 0 0
#> North-west 0 34 0 0 187 0 0 0
#> South-east 952 852 584 279 306 212 509 427
#> South-west 83 54 5 0 95 140 116 40
#> Southern Ocean Region 1277 909 23 848 0 112 107 120
#> Temperate East 675 471 406 225 325 341 295 238