DOI: 10.5061/dryad.wh70rxx2m
title: Data from: Estimating waterfowl breeding pair and brood densities using distance sampling with uncrewed aerial systems

description: Wildlife management relies on effective methods to estimate population
 indices, which are crucial for understanding the status and trends of
 wildlife populations and the factors that influence their persistence.
 Biologists have conducted surveys of waterfowl since the 1950’s using a
 combination of aerial (fixed wing aircraft) and ground-based methods to
 account for imperfect detection. While some individuals may be missed by
 aerial observers, ground observers are assumed to detect all individuals.
 This allows for a visual correction factor to be applied to the initial
 aerial count. However, the assumption that ground-observers are detecting
 every individual is unlikely and can potentially lead to biased population
 estimates. We conducted breeding waterfowl surveys in Wisconsin during
 2022 and 2023 and recorded observations of duck pairs and broods using
 uncrewed aerial systems (UAS) equipped with thermal cameras, which have
 been shown to improve detection of many wildlife species. We flew UAS
 surveys along transects and employed distance sampling to estimate duck
 densities while accounting for imperfect detection. This can be
 accomplished by recording the distance at which birds are detected and
 fitting a detection function to the data, which models detection
 probability and excludes the need for two independent observers. Our
 overall goal was to determine if UAS distance sampling can be used to
 monitor breeding waterfowl and produce reliable population metrics. The
 archived datasets contain transect-based observations of waterfowl pairs
 and broods collected over both years of the study, along with their
 associated distances from the observation transect. Additional
 observational variables are also included to support analyses in this
 study.
description: # Data from: Estimating waterfowl breeding pair and brood densities using
 distance sampling with uncrewed aerial systems Dataset DOI:
 [10.5061/dryad.wh70rxx2m](https://doi.org/10.5061/dryad.wh70rxx2m) ##
 Description of the data and file structure The pair and brood data files
 contain observational data collected during both years (2022 & 2023)
 of UAS surveys in Wisconsin. Each row in the file represents a single
 event and includes associated survey information. If multiple observations
 were made on a transect during a single survey, there will be one row per
 observation. A positive detection is indicated by a "1" in the
 "Pairs" or "Broods" column, while transects with no
 observations have a single row with a "0" in the
 "Pairs" or "Broods" column. ### Files and variables
 #### File: BroodData.csv **Description:** UAS brood observations during
 the 2022 and 2023 field seasons ##### Variables * Effort: length of
 transect (km) * Region.Label: survey ID * Sample.Label: transect ID *
 object: unique identifier for each row of data * Study.Area: name of the
 study area * Area: total area surveyed (square km) * distance:
 perpendicular distance between the observation and the transect it was
 observed from * Date: date of the survey (m/d/y) * Broods: brood
 observation (1 = yes, 0 = no) * BroodAge: age class of observed brood (1 =
 downy young, 2 = incompletely feathered young, 3 = completely feathered
 young prior to flight) * Behavior: observed behavior upon detection (F =
 flight, L = look up, N = no change, NA = no behavior recorded, S = swim
 away) * Species: species of waterfowl observed #### File: PairData.csv
 **Description:** UAS pair observations during the 2022 and 2023 field
 seasons ##### Variables * Effort: length of transect (km) * Region.Label:
 survey ID * Sample.Label: transect ID * object: unique identifier for each
 row of data * Study.Area: name of the study area * Area: total area
 surveyed (square km) * distance: perpendicular distance between the
 observation and the transect it was observed from * Date: date of the
 survey (m/d/y) * Pairs: breeding pair observation (1 = yes, 0 = no) *
 Behavior: observed behavior upon detection (F = flight, L = look up, N =
 no change, NA = no behavior recorded, S = swim away) * Species: species of
 waterfowl observed ## Code/software The datasets can be viewed in
 Microsoft Excel or read into Program R for analysis. Data analysis was
 conducted in Program R version 4.3.1 using the ‘Distance’ package (Miller
 et al., 2019).