A New Method for Estimating Numbers of Duck Broods

Bennett, Carl L.

doi:10.2307/3798139

Cited by 2 publications

(2 citation statements)

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“…We used the same data-recording procedures as for walk-up surveys and observers recorded weather conditions at the start of the survey and at hourly intervals thereafter. Because heavy rain, fog, and high wind have been shown to reduce detection of waterfowl broods (Diem and Lu 1960, Bennett 1967, Rumble and Flake 1982, Giudice 2001), we did not conduct roadside or walk-up surveys under conditions of heavy rain, fog, or wind speeds .25 km/ hour. We rescheduled canceled surveys for the next suitable day.…”

Section: Roadside Brood Surveysmentioning

confidence: 99%

“…A few studies have estimated detection probabilities over replicate surveys by using observationally marked broods identified on the basis of species, brood size, and age class (Gollop and Marshall 1954). Bennett (1967) conducted multiple brood surveys on a Michigan, USA, impoundment over a 3-day period and then used a catchper-unit-effort method to estimate number of observation periods necessary to observe all broods. Ringelman and Flake (1980) estimated brood visibility by surveying individual wetlands for 16 continuous hours and dividing the number of broods observed during any 15-minute interval by total broods observed any time that day, thus assuming all broods were eventually seen at least once.…”

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confidence: 99%

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Estimating Detection Probabilities of Waterfowl Broods From Ground‐Based Surveys

Pagano

Arnold

2009

J Wildl Manag

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Brood:pair ratios could provide an economical method for assessing spatial or temporal variation in waterfowl productivity, but such estimators are severely biased by incomplete detection of broods. We conducted 3 sequential counts of 1,357 waterfowl broods in northeastern North Dakota, USA, and used closed‐population mark‐recapture models to estimate total brood abundance while controlling for variation in detection probabilities (p). Blue‐winged teal (Anas discors) broods had the lowest average detection probability (p = 0.305), whereas diving‐duck broods had the highest average detectability (p = 0.571). Detection was generally highest in morning or evening, but temporal patterns varied among species and there was no survey window that maximized detection probabilities for all species. Detection probabilities averaged 0.108 (SD = 0.056) higher for an experienced observer versus an inexperienced observer. Detection probabilities were 0.044 higher for roadside versus walk‐up surveys and increased with increasing brood size, total brood abundance, survey date, wind speed, temperature, cloud cover, and amount of time spent surveying each wetland. Detection probabilities declined with increasing wetland size and amount of tall peripheral vegetation. Our mark‐recapture results indicated that a traditional unreplicated brood survey would have missed 67.5% of estimated broods, summed over all species. Use of closed‐population mark‐recapture techniques provided an effective method for reducing this bias and identifying and quantifying factors that reduce detection probabilities of waterfowl broods. We recommend that future brood surveys incorporate 2 or 3 temporally segregated replicate counts to allow for formal estimation of detection probabilities.

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Section: Roadside Brood Surveysmentioning

confidence: 99%

mentioning

confidence: 99%