DOI: 10.5061/dryad.0cfxpnw8m
title: Survey data and code to estimate abundance of Brachyramphus murrelets, Icy Bay, Alaska, USA

description: A fundamental aspect of ecology is identifying and characterizing
 population processes. In population studies, we almost always use sampling
 to make inference about the biological population, which is the population
 of interest, and the part of the population at risk of sampling is
 referred to as the statistical population. Ideally, the statistical
 population is the same as, or accurately represents its corresponding
 biological population. However, in practice, they rarely align in space
 and time, which can lead to biased inference. We often view a population
 misalignment as a temporary emigration process and resolve it with
 replicate and/or repeat sampling, though this approach is not feasible for
 all species and habitats. We developed a hierarchical framework to
 estimate abundance of a biological population of the Kittlitz’s murrelet
 (Brachyramphus brevirostris), a highly mobile, non-territorial,
 ice-associated seabird of conservation concern in Alaska and eastern
 Russia. Our model combines datasets from boat and telemetry surveys to
 account for all components of detection probability, specifically using
 telemetry locations to estimate probability of presence (pp) and line
 transect distance sampling to estimate probability of detection (pd). By
 estimating pp directly, we were able to account for temporary emigration
 from the sampled area, which changed with shifting icefloes between
 sampling occasions. Between 2007 and 2012, annual pp was highly variable,
 ranging from 0.33 to 0.75 (median=0.50, standard deviation=0.02), but was
 not predictable using five environmental covariates. In years when two
 boat surveys were conducted, our model reduced the coefficient of
 variation (CV) of abundance estimates for the biological population
 compared to the statistical population by 13–35%, yet in the year with
 only one boat survey (2009), the CV skyrocketed about 10-fold, emphasizing
 the importance of a second survey if pp varies. Although we
 increased the precision of annual abundance estimates by accounting for
 pp, we did not see the same improvement in the temporal trend estimate.
 This result indicates that while we reduced within-year variance, we
 failed to account for a source(s) of variation across years, which we
 suspect is related to the propensity for murrelets to skip breeding in
 some years. Our model to account for a population misalignment is simple,
 flexible, and scalable for generating unbiased and precise abundance
 estimates of highly mobile species that occupy dynamic habitats where
 other open population models are not possible . Importantly, it improves
 inference of the biological population. We urge ecologists to think
 critically about the population in which they want to draw inference,
 especially as tracking technology improves and model complexity increases.
description: These data used to estimate abundance and trend of
 Kittlitz's murrelets were collected in Icy Bay, Alaska, USA between
 2005 and 2012. Boat survey data were gathered along line transects using
 distance sampling, and telemetry data were collected by flying aerial
 telemetry flights to locate radio-tagged murrelets during the breeding
 season. Methods are summarized in numerous publications, including the
 current manuscript in review at Peer Community In Ecology and several
 others described in the README file.
description: # Survey data and code to estimate abundance of *Brachyramphus murrelets*,
 Icy Bay, Alaska, USA ## Data description and file structure: These data
 were analyzed and summarized in a manuscript submitted to PCI Ecology as
 part of a special issue for the EURING Analytical Conference Proceedings,
 April 2023. The title of the manuscript is “Using multiple datasets to
 account for misalignment between statistical and biological populations
 for abundance estimation.” File structure is as follows:
 DataCode_BRMU_KISSLING_et_al \|- Data \| |- AbundanceResults \| |-
 BoatSurveys \| |- TelemetrySurveys \|- Code \| |- JAGS \| | |-
 AbundanceEstimation \| | |- ProbPresenceEstimation \| | |- TrendEstimation
 \| |- R \| | |- AbundanceEstimation \| | |- ProbPresenceEstimation \| | |-
 TrendEstimation \|- SupplementalInformation #### Data folder All raw data
 files are included in the folder "Data." Boat and telemetry
 survey data were collected between 2005 and 2012, using methods described
 in the manuscript. Briefly, boat survey data were gathered along line
 transects with distance sampling, usually twice per year during 1–15 July
 (deviations occurred in 2009 and are described in the manuscript).
 Telemetry data were acquired from radio-tagged murrelets tracked
 throughout the breeding season (May–August) from 2007 to 2012. Ice
 condition data were georeferenced and summarized in a GIS. Weather data
 were downloaded from
 [https://www.ncdc.noaa.gov/cdo-web/](https://www.ncdc.noaa.gov/cdo-web/)
 for the Icy Bay weather station. ##### AbundanceResults folder Includes
 one CSV file titled "AbundanceByWindow." Data fields are as
 follows: * Year - survey year * Type - window length (none = without
 probability of presence; mean = posterior mean probability of presence
 from 2007 to 2012; 1day = 1-day window of boat survey, etc.; see
 manuscript for more details) * TypeCat - window length by numerical
 category * Estimate - mean posterior estimate of abundance * SD = standard
 deviation of estimate * LCI = 95% lower credible interval * UCI = 95%
 upper credible interval * CV = coefficient of variation NA and blank cells
 indicate no data are available. ##### BoatSurveys folder Includes 14 CSV
 files titled BRMU_IB_Date_BS#, which indicates Brachyramphus Murrelet
 (BS), Icy Bay (IB), Survey Date, and Boat Survey (BS) Identifier. Note
 that data for 2016 and 2017 are not publicly available. See "Data and
 Code Availability Statement" in manuscript. Minimum data fields are
 as follows (not all fields are available in all years): * Date -
 mm/dd/yyyy * Transect - identification number * Strata - Main Bay (main),
 Taan Fjord (taan) * Weather - 0 = &lt;50% cloud cover; 1 = &gt;50% cloud
 cover; 2 = fog; 3 = mist to light rain; 4 = medium to heavy rain *
 SeaState - following Beaufort classification; 0 = glossy, 1 = rippled with
 small chop &lt; 1 ft; 2 = small chop with few whitecaps 1-2 ft; 3 = small
 chop with whitecaps 2-3 ft; 4 = choppy with lots of whitecaps/spray &gt; 3
 ft * Swell - nearest foot (ft) * Ice - none; trace (&lt;1% surface area);
 1%; 3%; 5%; 5-100% increments within 300 m of boat * Lat - latitude (WGS
 84) * Long - longitude (WGS 84) * Species - KIMU = Kittlitz's
 murrelets; MAMU = marbled murrelet; BRMU = unidentified Brachyramphus
 murrelet * GroupSize - number in group within 3 m of each other * Distance
 - perpendicular from transect line to center of group; measured in meters
 * Behavior - on water or flying * Comments - as needed * Plumage -
 alternate, basic, molting * ClosestDepth - measured in feet from closest
 endpoint * ClosestEndpoint - closest endpoint to bird location * Secchi -
 measured in meters * SST - sea surface temperature in Celsius * 0.5mTemp -
 ocean temperature at 0.5 m depth in Celsius * 1mTemp - ocean temperature
 at 1.0 m depth in Celsius * Time - time of location * Tide - tidal stage
 (falling, rising) * BinomialTide - binomial tidal stage (0 = falling, 1 =
 rising) * FirstTideTime - time of previous tidal switch * SecondTideTime -
 time of next tidal switch * FirstTideHeight - height in feet of previous
 tidal switch * SecondTideHeight - height in feet of next tidal switch *
 TideFraction - fraction of tidal cycle complete * RelativeStrength -
 relative strength of tidal cycle based on rule of twelfths (see Kissling
 et al. 2007 for explanation) * TotalTideHeight - total tidal height swing
 in feet * RelativeTideCurrentStrength - RelativeStrength multiplied by
 TotalTideHeight (see Kissling et al. 2007) NA and blank cells indicate no
 data are available. ##### TelemetrySurveys folder Includes three CSV files
 for (a) ice coverage in Icy Bay study area during each telemetry survey
 (IceAreaIB), (2) Yakutat weather (YAK_weather), and (3) telemetry survey
 data (TxLocsIceAnalysis_StrataWNests). Data fields are as follows: 1\.
 IceAreaIB * Date - mm/dd/yyyy * AllIceArea - Area (km2) of total ice (all
 categories) in Icy Bay study area * IceMinusBBArea - Area (km2) of all
 categories of ice except brash ice (sometimes called bergy bits; BB) in
 Icy Bay study area * AllIceCoreArea - Area (km2) of total ice (all
 categories) in Icy Bay state (where boat surveys were conducted) *
 PropIceCoreArea - Proportion of Icy Bay state inaccessible due to ice 2\.
 YAK_weather * Date - mm/dd/yyyy * PRCP - total precipitation (inches) *
 AWND - average daily wind speed (miles per hour) 3\.
 TxLocsIceAnalysis_StrataWNests * RecordID - unique record identifier *
 Species - KIMU = Kittlitz's murrelets; MAMU = marbled murrelet *
 BirdNo - unique bird identifier * Year - year of data collection * BirdId
 - unique tagged bird identifier (some birds were captured and/or tagged in
 more than one year) * Frequency - telemetry frequency * Attachment type -
 method used to attach transmitter * FlightID - unique identifier for
 flight * Date - mm/dd/yyyy of flight * JulianDate - of flight * Latitude -
 latitude of bird location (WGS 84) * Longitude - longitude of bird
 location (WGS 84) * Time - of location * Activity - whether bird was
 diving, resting, or at a nest * FlightDay - number of days after first tag
 deployed * SeasonAttach - during early or late capture session (see
 Kissling et al. 2015 for more details) * Age - age of bird * Sex - sex of
 bird * ReproStatus - reproductive status of bird * Ice_cond - category of
 ice condition in which bird was located based on flight ice map; based on
 Bowditch classification * Tide - tidal stage (falling, rising) *
 BinomialTide - binomial tidal stage (0 = falling, 1 = rising) *
 FirstTideTime - time of previous tidal switch * SecondTideTime - time of
 next tidal switch * FirstTideHeight - height in feet of previous tidal
 switch * SecondTideHeight - height in feet of next tidal switch *
 TideFraction - fraction of tidal cycle complete * RelativeStrength -
 relative strength of tidal cycle based on rule of twelfths (see Kissling
 et al. 2007 for explanation) * TotalTideHeight - total tidal height swing
 in feet * RelativeTideCurrentStrength - RelativeStrength multiplied by
 TotalTideHeight (see Kissling et al. 2007) * State - spatial state in
 which bird was located * Strata - spatial strata in which bird was located
 * InCore - binomial value describing whether bird was present in core
 sampled area or not (0 = not in core; 1 = in core) NA and blank cells
 indicate no data are available. #### Code folder Includes two folders; one
 for JAGS code and another for R code. ##### JAGS folder Includes three
 folders for each analysis: (a) AbundanceEstimation, (b)
 ProbPresenceEstimation, and (c) TrendEstimation. 1\. AbundanceEstimation
 Includes models to estimate abundance as follows:
 MultiSurveyAbundance_BioPopN_Avg_pp - estimates biological population in
 years when two boat surveys were conducted and no telemetry data were
 available (2005, 2016, 2017) MultiSurveyAbundance_BioPopN_W_pp - estimates
 biological population in years when two boat surveys were conducted and
 telemetry data were available (2007, 2008, 2010-2012)
 MultiSurveyAbundance_StatPopN_No_pp - estimates statistical population in
 years when two boat surveys were conducted (all years except 2009)
 SingleSurveyAbundance_BioPopN_W_pp - estimates biological population in
 years when one boat survey was conducted and telemetry data were available
 (2009) SingleSurveyAbundance_StatPopN_No_pp - estimates statistical
 population in years when one boat survey was conducted (2009) 2\.
 ProbPresenceEstimation Includes models to estimate and cross validate
 probability of presence (pp): ProbPresence - estimates probability of
 presence with all data ProbPresence_CrossValidation - estimates
 probability of presence with portion of data and predicts probability of
 presence with other portion 3\. TrendEstimation Includes state space model
 to estimate trend of statistical and biological populations:
 TrendEstimation_StateSpace - estimates temporal trend in abundance ##### R
 folder Includes three folders for each analysis: (a) AbundanceEstimation,
 (b) ProbPresenceEstimation, and (c) TrendEstimation. 1\.
 AbundanceEstimation Includes R code to estimate abundance of statistical
 and biological populations for 2005 and 2007-2012. 2\.
 ProbPresenceEstimation Includes R code to estimate and cross validate
 probability of presence (pp). 3\. TrendEstimation Includes R code to
 estimate trend of statistical and biological populations. ####
 Supplemental Information folder Includes results of each model run by year
 and the temporal trend across years. A folder for each year and trend
 includes summary results (*.txt), model output as an object (*.RDS), and
 the MCMC diagnostic plots. Note that these files have a different naming
 format, with "no_corep" referencing the statistical population
 and "corep" referencing the biological population. All of the
 annual results are summarized in the AbundanceByWindow.csv file
 (Data/AbundanceResults), which was used to estimate trend. ##
 Sharing/Access information Boat survey data also available in the North
 Pacific Pelagic Seabird Database:
 [https://www.usgs.gov/centers/alaska-science-center/science/north-pacific-pelagic-seabird-database](https://www.usgs.gov/centers/alaska-science-center/science/north-pacific-pelagic-seabird-database) Other publications that describe and use these data: Kissling, M.L., P.M. Lukacs, S.B. Lewis, S.M. Gende, and J. Waite. 2016. Breeding decisions of a declining seabird, the Kittlitz’s Murrelet. Marine Ornithology 44:171–182. Kissling, M.L., S.M. Gende, S.B. Lewis, and P.M. Lukacs. 2015. Reproductive performance of Kittlitz’s Murrelet in a glaciated landscape, Icy Bay, Alaska. The Condor: Ornithological Applications 117:237–248. Kissling, M.L., P.M. Lukacs, S.M. Gende, and S.B. Lewis. 2015. Multi-state mark-recapture model to estimate survival of a dispersed-nesting seabird, the Kittlitz’s murrelet. Journal of Wildlife Management 79:20–30. Kissling, M.L., Lukacs, P.M., Lewis, S.B., Gende, S.M., Kuletz, K.J., Hatch, N.R., Schoen, S.K., and Oehlers, S. 2011. Distribution and abundance of the Kittlitz’s Murrelet Brachyramphus brevirostris in selected areas of southeastern Alaska. Marine Ornithology 39(1):3–11. Kissling, M.L., M. Reid, P.M. Lukacs, S.M. Gende, and S. B. Lewis. 2007. Understanding abundance patterns of a declining seabird: implications for monitoring. Ecological Applications 17:2164–2174. ## Code/Software The RProject titled "DataCode_BRMU_Kissling_et_al" is provided for convenience. All code files are included in the folder "Code" and sub-folders "Jags" and "R," and are organized in folders for estimating abundance, probability of presence, and trend. Code files are annotated.