DOI: 10.5061/dryad.mkkwh719f
title: Monitoring active Osprey nests with drones is more time-efficient and less disturbing than conventional methods

description: Drones are used to monitor bird nesting sites at less accessible
 locations, such as on cliffs, human infrastructure, or within the tree
 canopy. While there are a growing number of studies documenting avian
 behavioral responses to various drones, there is a continued need to
 monitor taxa-specific responses to different drone models. We explored
 both the time efficiency and impact of different nest survey methods
 (drones, nest climbing, and observations from a bucket truck) and
 different drone model sizes (small, medium, large) on the nest defense
 behavior of breeding Ospreys. We conducted 166 surveys (126 drone, 25
 climbing, 15 bucket truck) at 85 active nests across three nesting stages.
 We found variation in 4 of 6 pre-defined behavioral categories, namely for
 calling, flying, at nest, and perching behaviors with survey method, sex,
 and nest stage. Females were more responsive to all survey methods
 compared to males and engaged in nest-protection behaviors most frequently
 during incubation. Ospreys spent greater time at their nests during drone
 surveys compared to other methods. Agitated calling and flying were also
 less frequent during drone surveys. We recorded defensive behaviors across
 all survey types and there were no strikes on drones or researchers. Drone
 size appeared to influence behavior, with female Ospreys spending, on
 average, 18% of survey time calling when surveyed with medium-sized drone
 compared to smaller (8%) or larger (6%) models. Surveys with drones took
 less time to complete compared to the other methods tested. Based on our
 findings, drones appear to be the best choice for monitoring Osprey nests
 as they are adaptable, time efficient, and result in less apparent
 disturbance to nesting Ospreys than other methods tested. Our research
 aids in setting best practices, optimizing drone size, and developing
 evidence-driven approaches for monitoring avian nests across a variety of
 landscapes and contexts.
description: # Monitoring active Osprey nests with drones is more time-efficient and
 less disturbing than conventional methods.
 [https://doi.org/10.5061/dryad.mkkwh719f](https://doi.org/10.5061/dryad.mkkwh719f) ## Description of the data and file structure **Monitoring active Osprey nests with drones is more time-efficient and less disturbing than conventional methods.** Document produced by Natasha Murphy, 14/11/2024.  This repository contains R code and data to run analyses as described in the paper titled *Monitoring active Osprey nests with drones is more time-efficient and less disturbing than conventional methods by Murphy et al*. This includes scripts for GLMMs, Dirichlet regression, sensitivity analysis, and Kruskal-Wallis rank sum tests. Data are provided with observer and pilot/climber names redacted.  Our final dataset comprised of both counts and duration for each of the behaviors. For behavioral counts, we built a generalized linear mixed model (GLMM) to examine the effects of survey method on specific Osprey behavioral groups, except for ‘other’ behaviors (i.e., copulation, feeding) as the model did not converge due to low sample size. As surveys were sometimes carried out opportunistically with various cooperative partners, we had an unbalanced survey design, so we investigated the potential impact of this unbalance on results by randomly sub-setting our drone data (n = 60, to allow for a reduced sample size but maintain model convergence) and comparing results from the full model to an average across 1000 iterations of the subset model. As computed variable estimates were within full model estimate confidence intervals, we are confident that our unbalanced design did not impact inferences.   The proportion of time spent in each behavior category per bird per survey was calculated by dividing time spent displaying a behavior by total survey length. We used a Dirichlet regression to model the proportion of time spent exhibiting each behavior against predictor variables of an interaction between survey method and sex, and an interaction between survey method and nesting stage. A Kruskal-Wallis rank sum test was conducted to test the difference in total time taken to conduct a survey across the three survey methods and drone size categories. ### Files and variables #### File: WB\_Dirichlet\_Regression.R **Description:** In this R script we modeled proportion of time spent exhibiting each behavior as the response variable against predictor variables of an interaction between survey method and sex, and an interaction between survey method and nesting stage. If there was an effect of the drone survey method, we again further explored the effect of drone size on the proportion of behaviors using an interaction between drone size and sex, and an interaction between nest stage and drone. #### File: WB\_GLMMs.R **Description:** In this R script we modeled total count of each behavior as the response variable against predictor variables of an interaction between survey method and sex, and an interaction between survey method and nesting stage with a nested random effect of nest ID within waterbody and log transformed survey length as an offset. If there was an effect of the drone survey on a behavioral group, we then explored the influence of drone model size on the given nesting Ospreys behavior. This script also includes our investigation into the potential impact of this unbalance on results by randomly sub-setting our drone data and comparing results from the full model to an average across 1000 iterations of the subset model. #### File: WB\_Flight\_time.R **Description:** In this R script, we use a Kruskal-Wallis rank sum test to test the difference in total time taken to conduct a survey across the three survey methods and drone size categories #### File: Behavior\_OSPR\_-\_B\_COUNT.csv **Description:** Count data. ##### Variables * SURVEYID: Unique survey ID. No units. * BIRDID: Unique bird ID. No units. * FILEID: Name of the raw .wav file. No units. * DATE: Units are dates, m.dd.yyyy * YEAR: Units are years. * STAGE: Nesting stage; chicks at nest, incubation, occupation. No units.  * NEST HEIGHT: Units in meters.  * OBS: Observer name [redacted]. No units. * Pilot_climber: Pilot or climber name [redacted]. No units. * NEST_TYPE: Nest substrate type. No units. * NEST_ID: Unique nest ID. No units.  * WATER: Waterbody where the nest was located. No units.  * LAT: Units are latitude.  * LONG: Units are longitude.  * START: Start time of the survey. Units are time. * END: End time of the survey.  Units are time. * WIND: Wind direction. Units are cardinal directions. * SEX: Male, female, or unknown. No units.  * SURVEY_METHOD: Survey method; climbing, bucket truck, or drone. No units.  * TYPE: Drone model type. No units.  * SIZE: Drone model size - will be NA if this a bucket or climbing survey. No units.  The following columns represent counts of each behaviour (units are numeric counts); * IF: Initial flush. * AF: Additional flush after returning the nest. * PR: Perching, relaxed * PU: Perching, alert. * DP: Defensive posture. * D: Diving attach.  * C: Contact with drone or climber. * OS: Out of sight. * CA: Alarm calls. * CS: Scream calls.  * GC: Guard calls. * FY: Flying. * RN: Returned to nest. * FE: Feeding. * CP: Copulation.  * ON: At the nest. #### File: Behavior\_OSPR\_-\_B\_DURATION.csv **Description:** Duration data.  ##### Variables * SURVEYID: Unique survey ID. No units. * BIRDID: Unique bird ID. No units. * FILEID: Name of the raw .wav file. No units. * DATE: Units are dates, m.dd.yyyy * STAGE: Nesting stage; young in nest, incubation, occupation. No units. * \#AD: Number of adults present during the survey. No units. * \#EGGS: Number of eggs present during the survey. No units. * \#CHICKS: Number of chicks present during the survey. No units. * OBS: Observer name [redacted]. No units. * Pilot_climber: Pilot/Climber name [redacted]. No units. * NEST_TYPE: Nest substrate type. No units. * WATER: Waterbody where the nest was located. No units. * NEST_ID: Unique nest ID. No units. * LAT: Units are latitude.  * LONG: Units are longitude.  * START: Start time (units are timestamps) of the survey.  * END: End time (units are timestamps) of the survey.  * SEX: Male, female, unknown. No units. * SURVEY_METHOD: Survey method; climbing, bucket truck, drone. No units. * UAV: Drone model. Will be NA if no drone used in the survey. No units. * TIME: Timestamp. Units are timestamps.  * BEHAVIOR: Behaviour, using the codes defined in the Count data set. Also includes END to indicate end of the survey. No units. ## Code/software All analyses were performed in R (version 4.2.2; R Core Team, 2021). We recommend this R version as we are aware of some issues with newer R versions and R packages used.