DOI: 10.5061/dryad.hqbzkh1s7
title: Data from: Maximizing the detection probabilities of dusky grouse for population monitoring

description: Despite its status as a game species in the western United States,
 rigorous monitoring of dusky grouse (Dendragapus obscurus) populations is
 limited. Obtaining an adequate number of observations for effective
 population monitoring of dusky grouse is challenging due to
 difficult-to-reach montane habitats, cryptic behaviors, and limited
 personnel, time, and funds at conservation agencies. While habitat
 accessibility and survey effort constraints may be outside a manager’s
 control, identifying the most effective protocols to better detect a
 target species is possible and will improve monitoring programs. Our
 objectives were to 1) evaluate field-based protocols for maximizing dusky
 grouse detections and 2) identify survey conditions and timing that
 maximize the probability of detecting dusky grouse in western Montana. We
 conducted replicated point-count surveys with and without electronic
 playback of grouse calls in spring and summer 2019, and spring surveys
 solely with electronic playback in 2020–2021. We used N-mixture models to
 compare the probability of detecting dusky grouse in spring versus summer
 sampling and evaluate the effects of electronic playback of grouse calls,
 route type (off-trail, trail, and road), weather, background noise, day,
 and time on the probability of detection. Spring sampling yielded
 substantially more dusky grouse detections than summer sampling. The use
 of electronic playback of female sooty grouse calls in the spring
 increased detection probability, but dusky grouse chick distress calls
 during the summer did not improve detection rates. The probability of
 detecting a dusky grouse was similar across the different route types
 (off-trail, trail, and road), and maximized on clear days, with little
 wind and background noise, with surveys occurring 9–162 minutes
 post-sunrise during 3–23 May. By examining the effects of different
 factors on dusky grouse probability of detection, our results provide
 necessary information for the development of effective protocols for field
 surveys for population monitoring of dusky grouse.
description: Data consists of point-count surveys conducted in western
 Montana, off-trail in spring and summer 2019, and on roads and trails in
 springs 2020 and 2021.  During the 2019 season, we surveyed each point
 three times on three different mornings within a 2-week period, and during
 the 2020 and 2021 seasons, 4 point-counts were conducted within the same
 morning. In 2019, surveys consisted of two 4-minute
 consecutive point-counts, the first without electronic playback, and the
 second with electronic playback played used a portable speaker. During the
 spring, we used electronic playback of a female sooty grouse call (cantus,
 whinny, and cackle) and in the summer we used a dusky grouse chick
 distress call. Playback recordings consisted of 30 seconds of playback,
 then 30 seconds of silence, repeated for the entire 4-minute
 period. In 2020 and 2021, surveys were only conducted
 using electronic playback of a female dusky grouse call (cantus and
 cackle). During all years of the study, all dusky
 grouse observations (visual and auditory) were recorded, with observers
 trained to not record the same individual twice within a single survey.
 Point-count surveys were conducted between dawn and 11am on days without
 precipitation and minimum (&lt; 19 km/hr) wind speed. We recorded
 survey conditions, which included day (relative to the first day of the
 survey period, which was 10 April), minutes since sunrise, background
 noise level, temperature (C), precipitation (fog, rain, snow, or none),
 wind speed (km/hr), and cloud cover (0-15%, 16-50%, 51-80%,
 81-100%).
description: # Maximizing the detection probabilities of dusky grouse for population
 monitoring
 [https://doi.org/10.5061/dryad.hqbzkh1s7](https://doi.org/10.5061/dryad.hqbzkh1s7) ## Description of the data and file structure Data consists of point-count surveys conducted in western Montana, off-trail in spring and summer 2019, and on roads and trails in springs 2020 and 2021.  During the 2019 season, we surveyed each point three times on three different mornings within a 2-week period, and during the 2020 and 2021 seasons, 4 point-counts were conducted within the same morning. In 2019, surveys consisted of two 4-minute consecutive point-counts, the first without electronic playback, and the second with electronic playback played used a portable speaker. During the spring, we used electronic playback of a female dusky grouse call (cantus, whinny, and cackle) and in the summer we used a chick distress call. Playback recordings consisted of 30 seconds of playback, then 30 seconds of silence, repeated for the entire 4-minute period. In 2020 and 2021, surveys were only conducted using electronic playback of a female dusky grouse call (cantus and cackle). During all years of the study, all dusky grouse observations (visual and auditory) were recorded, with observers trained to not record the same individual twice within a single survey. Point-count surveys were conducted between dawn and 11am on days without precipitation and minimum (&lt; 19 km/hr) wind speed. We recorded survey conditions, which included day (relative to the first day of the survey period, which was 10 April), minutes since sunrise, background noise level, temperature (C), precipitation (fog, rain, snow, or none), wind speed (km/hr), and cloud cover (0-15%, 16-50%, 51-80%, 81-100%). All missing data represented as NA. ### Files and variables #### File: DuskySpringSurveys.csv **Description:** point count surveys conducted in spring 2019, and contains the year, season, transect number, point ID, visit number, whether playback was used (NoPlayback or Playback), and the number of dusky grouse observations (DUGR). Within the dusky grouse observations, NA is used if a point-count was not successfully completed. ##### Variables * Year: Survey Year * Season: Sampling Period (Spring or Summer) * Transect: Transect ID (or Name) * Point ID: Point ID (Point-count survey site ID/Name) * Visit: visit number (1, 2, or 3) * Playback: if playback was used (NoPlayback, Playback) * DUGR: number of dusky grouse observed #### File: DuskySummerSurveys.csv **Description:** point-count surveys conducted in summer 2019, and contains the year, season, transect number, point ID, visit number, whether playback was used (NoPlayback or Playback), and the number of dusky grouse observations (DUGR). Within the dusky grouse observations, NA is used if a point-count was not successfully completed. ##### Variables * Year: Survey Year * Season: Sampling Period (Spring or Summer) * Transect: Transect ID (or Name) * Point ID: Point ID (Point-count survey site ID/Name) * Visit: visit number (1, 2, or 3) * Playback: if playback was used (NoPlayback, Playback) * DUGR: number of dusky grouse observed #### File: duskydata\_det.csv **Description:** point-count surveys conducted in 2020 and 2021, and includes survey year, point name, and for each visit (1, 2, 3, 4): minutes since sunrise, survey day (Day 1 = April 10), number of observers (Num.Obs), cloud cover, precipitation (A.N = None, F = fog, R = precipitation, S = snow), wind speed, temperature (Celsius), noise level, MFWP Region, route type (road, trail), transect name, and number of dusky grouse observed for each visit (X1, X2, X3, X4). ##### Variables * SurveyYear: Survey Year * PointName: Point ID (Point-count survey site ID/Name) * Minutes1: minutes since sunrise for visit 1 * Minutes2: minutes since sunrise for visit 2 * Minutes3: minutes since sunrise for visit 3 * Minutes4: minutes since sunrise for visit 4 * Days1: day during the survey period (April 10 = Day 1) for visit 1 * Days2: day during the survey period (April 10 = Day 1) for visit 2 * Days3: day during the survey period (April 10 = Day 1) for visit 3 * Days4: day during the survey period (April 10 = Day 1) for visit 4 * Num.Obs1: number of observers during the point-count for visit 1 * Num.Obs2: number of observers during the point-count for visit 2 * Num.Obs3: number of observers during the point-count for visit 3 * Num.Obs4: number of observers during the point-count for visit 4 * CloudCover1: % cloud cover (0-15, 16-50, 51-80, 81-100) for visit 1 * CloudCover2: % cloud cover (0-15, 16-50, 51-80, 81-100) for visit 2 * CloudCover3: % cloud cover (0-15, 16-50, 51-80, 81-100) for visit 3 * CloudCover4: % cloud cover (0-15, 16-50, 51-80, 81-100) for visit 4 * Precip1: precipitation (A.N = none, F = fog, R = rain, S = snow) for visit 1 * Precip2: precipitation (A.N = none, F = fog, R = rain, S = snow) for visit 2 * Precip3: precipitation (A.N = none, F = fog, R = rain, S = snow) for visit 3 * Precip4: precipitation (A.N = none, F = fog, R = rain, S = snow) for visit 4 * Wind1: average wind speed (km/hr) during the point count for visit 1 * Wind2: average wind speed (km/hr) during the point count for visit 2 * Wind3: average wind speed (km/hr) during the point count for visit 3 * Wind4: average wind speed (km/hr) during the point count for visit 4 * Temp1: temperature (Celsius) during the point-count for visit 1 * Temp2: temperature (Celsius) during the point-count for visit 2 * Temp3: temperature (Celsius) during the point-count for visit 3 * Temp4: temperature (Celsius) during the point-count for visit 4 * NoiseLevel1: background noise level during the point count for visit 1 (0 = no background noise, 1 = slight background noise, but no auditory impairment, 2 = some background noise and some auditory impairment, and 3 = high levels of background noise and auditory impairment) * NoiseLevel2: background noise level during the point count for visit 2 (0 = no background noise, 1 = slight background noise, but no auditory impairment, 2 = some background noise and some auditory impairment, and 3 = high levels of background noise and auditory impairment) * NoiseLevel3: background noise level during the point count for visit 3 (0 = no background noise, 1 = slight background noise, but no auditory impairment, 2 = some background noise and some auditory impairment, and 3 = high levels of background noise and auditory impairment) * NoiseLevel4: background noise level during the point count for visit 4 (0 = no background noise, 1 = slight background noise, but no auditory impairment, 2 = some background noise and some auditory impairment, and 3 = high levels of background noise and auditory impairment) * Region: refers to MFWP administrative region * Type: route type (Road or Trail) * TransectName: Transect ID (or Name) * X1: number of dusky grouse observed during visit 1 * X2: number of dusky grouse observed during visit 2 * X3: number of dusky grouse observed during visit 3 * X4: number of dusky grouse observed during visit 4 #### File: route\_type\_data.csv **Description:** **:** point-count surveys conducted in 2019, 2020 and 2021, and includes route type (road, trail, off-trail), survey year, point name, and for each visit (1, 2, 3, 4): minutes since sunrise, survey day (Day 1 = April 10), cloud cover, precipitation (A.N = None, F = fog, R = precipitation, S = snow), wind speed, temperature (Celsius), MFWP Region, transect name, and number of dusky grouse observed for each visit (X1, X2, X3, X4). ##### Variables * PointName: Point ID (Point-count survey site ID/Name) * SurveyYear: Survey Year * Type: walking route type: off-trail, trail, road * Region: refers to MFWP administrative region * X1: number of dusky grouse observed during visit 1 * X2: number of dusky grouse observed during visit 2 * X3: number of dusky grouse observed during visit 3 * X4: number of dusky grouse observed during visit 4 * CloudCover1: % cloud cover (0-15, 16-50, 51-80, 81-100) for visit 1 * CloudCover2: % cloud cover (0-15, 16-50, 51-80, 81-100) for visit 2 * CloudCover3: % cloud cover (0-15, 16-50, 51-80, 81-100) for visit 3 * CloudCover4: % cloud cover (0-15, 16-50, 51-80, 81-100) for visit 4 * Days1: day during the survey period (April 10 = Day 1) for visit 1 * Days2: day during the survey period (April 10 = Day 1) for visit 2 * Days3: day during the survey period (April 10 = Day 1) for visit 3 * Days4: day during the survey period (April 10 = Day 1) for visit 4 * Minutes1: minutes since sunrise for visit 1 * Minutes2: minutes since sunrise for visit 2 * Minutes3: minutes since sunrise for visit 3 * Minutes4: minutes since sunrise for visit 4 * Precip1: precipitation (A.N = none, F = fog, R = rain, S = snow) for visit 1 * Precip2: precipitation (A.N = none, F = fog, R = rain, S = snow) for visit 2 * Precip3: precipitation (A.N = none, F = fog, R = rain, S = snow) for visit 3 * Precip4: precipitation (A.N = none, F = fog, R = rain, S = snow) for visit 4 * Temp1: temperature (Celsius) during the point-count for visit 1 * Temp2: temperature (Celsius) during the point-count for visit 2 * Temp3: temperature (Celsius) during the point-count for visit 3 * Temp4: temperature (Celsius) during the point-count for visit 4 * Wind1: average wind speed (km/hr) during the point count for visit 1 * Wind2: average wind speed (km/hr) during the point count for visit 2 * Wind3: average wind speed (km/hr) during the point count for visit 3 * Wind4: average wind speed (km/hr) during the point count for visit 4 #### File: SI\_FemaleData.csv **Description:** point-count surveys conducted in 2020 and 2021, female data only. Includes survey year, point name, and number of dusky grouse observed for each visit (V1, V2, V3, V4). ##### Variables * SurveyYear: Survey Year * PointName: Point ID (Point-count survey site ID/Name) * V1: number of dusky grouse observed during visit 1 * V2: number of dusky grouse observed during visit 2 * V3: number of dusky grouse observed during visit 3 * V4: number of dusky grouse observed during visit 4 #### File: SI\_MaleData.csv **Description:** point-count surveys conducted in 2020 and 2021, male data only. Includes survey year, point name, and number of dusky grouse observed for each visit (V1, V2, V3, V4). ##### Variables * SurveyYear: Survey Year * PointName: Point ID (Point-count survey site ID/Name) * V1: number of dusky grouse observed during visit 1 * V2: number of dusky grouse observed during visit 2 * V3: number of dusky grouse observed during visit 3 * V4: number of dusky grouse observed during visit 4 #### File: SI\_ObserverData.csv **Description:** point-count surveys conducted in 2020 and 2021, and includes survey year, point name, and for each visit (1, 2, 3, 4): minutes since sunrise, survey day (Day 1 = April 10), number of observers (Num.Obs), cloud cover, precipitation (A.N = None, F = fog, R = precipitation, S = snow), wind speed, temperature (Celsius), noise level, MFWP Region, route type (road, trail), transect name, observer affiliation (state biologist, university biologist, and volunteer), and number of dusky grouse observed for each visit (X1, X2, X3, X4). ##### Variables * SurveyYear: Survey Year * PointName: Point ID (Point-count survey site ID/Name) * Minutes1: minutes since sunrise for visit 1 * Minutes2: minutes since sunrise for visit 2 * Minutes3: minutes since sunrise for visit 3 * Minutes4: minutes since sunrise for visit 4 * Days1: day during the survey period (April 10 = Day 1) for visit 1 * Days2: day during the survey period (April 10 = Day 1) for visit 2 * Days3: day during the survey period (April 10 = Day 1) for visit 3 * Days4: day during the survey period (April 10 = Day 1) for visit 4 * Num.Obs1: number of observers conducting the point-counts * CloudCover1: % cloud cover (0-15, 16-50, 51-80, 81-100) for visit 1 * CloudCover2: % cloud cover (0-15, 16-50, 51-80, 81-100) for visit 2 * CloudCover3: % cloud cover (0-15, 16-50, 51-80, 81-100) for visit 3 * CloudCover4: % cloud cover (0-15, 16-50, 51-80, 81-100) for visit 4 * Precip1: precipitation (A.N = none, F = fog, R = rain, S = snow) for visit 1 * Precip2: precipitation (A.N = none, F = fog, R = rain, S = snow) for visit 2 * Precip3: precipitation (A.N = none, F = fog, R = rain, S = snow) for visit 3 * Precip4: precipitation (A.N = none, F = fog, R = rain, S = snow) for visit 4 * Wind1: average wind speed (km/hr) during the point count for visit 1 * Wind2: average wind speed (km/hr) during the point count for visit 2 * Wind3: average wind speed (km/hr) during the point count for visit 3 * Wind4: average wind speed (km/hr) during the point count for visit 4 * Visit1: 1 = first visit going along route, 2 = return visit going along route * Visit2: 1 = first visit going along route, 2 = return visit going along route * Visit3: 1 = first visit going along route, 2 = return visit going along route * Visit4: 1 = first visit going along route, 2 = return visit going along route * Temp1: temperature (Celsius) during the point-count for visit 1 * Temp2: temperature (Celsius) during the point-count for visit 2 * Temp3: temperature (Celsius) during the point-count for visit 3 * Temp4: temperature (Celsius) during the point-count for visit 4 * NoiseLevel1: background noise level during the point count for visit 1 (0 = no background noise, 1 = slight background noise, but no auditory impairment, 2 = some background noise and some auditory impairment, and 3 = high levels of background noise and auditory impairment) * NoiseLevel2: background noise level during the point count for visit 2 (0 = no background noise, 1 = slight background noise, but no auditory impairment, 2 = some background noise and some auditory impairment, and 3 = high levels of background noise and auditory impairment) * NoiseLevel3: background noise level during the point count for visit 3 (0 = no background noise, 1 = slight background noise, but no auditory impairment, 2 = some background noise and some auditory impairment, and 3 = high levels of background noise and auditory impairment) * NoiseLevel4: background noise level during the point count for visit 4 (0 = no background noise, 1 = slight background noise, but no auditory impairment, 2 = some background noise and some auditory impairment, and 3 = high levels of background noise and auditory impairment) * Region: MFWP adminstrative region * Type: route type (trail or road) * TransectName: Transect ID (or Name), there are multiple points/sites (PointID) along a transect * X1: number of dusky grouse observed during visit 1 * X2: number of dusky grouse observed during visit 2 * X3: number of dusky grouse observed during visit 3 * X4: number of dusky grouse observed during visit 4 * Org: observer affiliation (state biologist, university biologist, volunteer) ## Code/software SpringPlaybackEffect.R = describes the analysis for evaluating the effect of playback on probablity of detection during spring point-count surveys SummerPlaybackEffect.R = describes the analysis for evaluating the effect of playback on probablity of detection during summer point-count surveys RouteType.R = describes the analysis for evaluting the effect of route type on probablity of detection SurveyConditions.R = describes the analysis for evaluating temporal, weather, and ambient noise levels on probability of detection SupportingInfo_SexSpecificAnalysis.R = supporting information analysis: evaluates models for predicting the probablity of detecting male or female dusky grouse during spring point-count surveys SI_ObserverAnalysis.R = supporting information analysis: evaluates the effect of observer number and observer affiliation on probablity of detection during spring point-count surveys