ESTIMATING DETECTION PROBABILITY AND DENSITY FROM POINT-COUNT SURVEYS: A COMBINATION OF DISTANCE AND DOUBLE-OBSERVER SAMPLING

Abstract Point counts are the method most commonly used to estimate abundance of birds, but they often fail to account properly for incomplete and variable detection probabilities. We developed a technique that combines distance and double-observer sampling to estimate detection probabilities and effective area surveyed. We applied this paired-observer, variable circular-plot (POVCP) technique to point-count surveys (n = 753) conducted in closed-canopy forests of southeast Alaska. Distance data were analyzed for each species to model a detection probability for each observer and calculate an estimate of density. We then multiplied each observer's density estimates by a correction factor to adjust for detection probabilities <1 at plot center. We compared analytical results from four survey methods: single-observer fixed-radius (50-m) plot; single-observer, variable circular-plot (SOVCP); double-observer fixed-radius (50-m) plot; and POVCP. We examined differences in detection probabilities at plot center, effective area surveyed, and densities for five bird species: Pacific-slope Flycatcher (Empidonax difficilis), Winter Wren (Troglodytes troglodytes), Golden-crowned Kinglet (Regulus satrapa), Hermit Thrush (Catharus guttatus), and Townsend's Warbler (Dendroica townsendi). Average detection probabilities for paired observers increased ≈8% (SE = 2.9) for all species once estimates were corrected for birds missed at plot center. Density estimators of fixed-radius survey methods were likely negatively biased, because the key assumption of perfect detection was not met. Density estimates generated using SOVCP and POVCP were similar, but standard errors were much lower for the POVCP survey method. We recommend using POVCP when study objectives require precise estimates of density. Failure to account for differences in detection probabilities and effective area surveyed results in biased population estimators and, therefore, faulty inferences about the population in question. Estimaciones de la Densidad y de las Probabilidades de Detección a Partir de Muestreos Utilizando Conteos en Puntos: Una Combinación de Muestreos de Distancia y de Doble Observador

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Field evaluation of distance-estimation error during wetland-dependent bird surveys

Wildlife Research ◽

10.1071/wr11161 ◽

2012 ◽

Vol 39 (4) ◽

pp. 311 ◽

Cited By ~ 8

Author(s):

Christopher P. Nadeau ◽

Courtney J. Conway

Keyword(s):

Detection Probability ◽

Estimation Error ◽

Distance Estimation ◽

Field Evaluation ◽

Field Trials ◽

Survey Period ◽

Estimation Errors ◽

Point Count ◽

Survey Point ◽

Count Surveys

Context The most common methods to estimate detection probability during avian point-count surveys involve recording a distance between the survey point and individual birds detected during the survey period. Accurately measuring or estimating distance is an important assumption of these methods; however, this assumption is rarely tested in the context of aural avian point-count surveys. Aims We expand on recent bird-simulation studies to document the error associated with estimating distance to calling birds in a wetland ecosystem. Methods We used two approaches to estimate the error associated with five surveyor’s distance estimates between the survey point and calling birds, and to determine the factors that affect a surveyor’s ability to estimate distance. Key results We observed biased and imprecise distance estimates when estimating distance to simulated birds in a point-count scenario (error = –9 m, s.d.error = 47 m) and when estimating distances to real birds during field trials (error = 39 m, s.d.error = 79 m). The amount of bias and precision in distance estimates differed among surveyors; surveyors with more training and experience were less biased and more precise when estimating distance to both real and simulated birds. Three environmental factors were important in explaining the error associated with distance estimates, including the measured distance from the bird to the surveyor, the volume of the call and the species of bird. Surveyors tended to make large overestimations to birds close to the survey point, which is an especially serious error in distance sampling. Conclusions Our results suggest that distance-estimation error is prevalent, but surveyor training may be the easiest way to reduce distance-estimation error. Implications The present study has demonstrated how relatively simple field trials can be used to estimate the error associated with distance estimates used to estimate detection probability during avian point-count surveys. Evaluating distance-estimation errors will allow investigators to better evaluate the accuracy of avian density and trend estimates. Moreover, investigators who evaluate distance-estimation errors could employ recently developed models to incorporate distance-estimation error into analyses. We encourage further development of such models, including the inclusion of such models into distance-analysis software.

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A Double-Observer Approach for Estimating Detection Probability and Abundance From Point Counts

The Auk ◽

10.1093/auk/117.2.393 ◽

2000 ◽

Vol 117 (2) ◽

pp. 393-408 ◽

Cited By ~ 81

Author(s):

James D. Nichols ◽

James E. Hines ◽

John R. Sauer ◽

Frederick W. Fallon ◽

Jane E. Fallon ◽

...

Keyword(s):

Detection Probability ◽

Bird Species ◽

Field Trials ◽

Bird Abundance ◽

Point Count ◽

Point Counts ◽

Avian Abundance ◽

Detection Probabilities ◽

Sources Of Variation ◽

Double Observer

Abstract Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated “primary” observer indicates to another (“secondary”) observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss varying proportions of the birds actually present, and observer and bird species were found to be relevant sources of variation in detection probabilities. Overall detection probabilities (probability of being detected by at least one of the two observers) estimated using the double-observer approach were very high (>0.95), yielding precise estimates of avian abundance. We consider problems with the approach and recommend possible solutions, including restriction of the approach to fixed-radius counts to reduce the effect of variation in the effective radius of detection among various observers and to provide a basis for using spatial sampling to estimate bird abundance on large areas of interest. We believe that most questions meriting the effort required to carry out point counts also merit serious attempts to estimate detection probabilities associated with the counts. The double-observer approach is a method that can be used for this purpose.

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Maximizing detection probability of wetland-dependent birds during point-count surveys in northwestern Florida

The Wilson Journal of Ornithology ◽

10.1676/07-041.1 ◽

2008 ◽

Vol 120 (3) ◽

pp. 513-518 ◽

Cited By ~ 31

Author(s):

Christopher P. Nadeau ◽

Courtney J. Conway ◽

Bradley S. Smith ◽

Thomas E. Lewis

Keyword(s):

Detection Probability ◽

Point Count ◽

Count Surveys

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A Removal Model for Estimating Detection Probabilities From Point-Count Surveys

The Auk ◽

10.1093/auk/119.2.414 ◽

2002 ◽

Vol 119 (2) ◽

pp. 414-425 ◽

Cited By ~ 30

Author(s):

George L. Farnsworth ◽

Kenneth H. Pollock ◽

James D. Nichols ◽

Theodore R. Simons ◽

James E. Hines ◽

...

Keyword(s):

Detection Probability ◽

Time Of Day ◽

Probability Of Detection ◽

Point Count ◽

Great Smoky Mountains ◽

Point Counts ◽

Detection Probabilities ◽

Acadian Flycatcher ◽

Removal Model ◽

Count Surveys

AbstractUse of point-count surveys is a popular method for collecting data on abundance and distribution of birds. However, analyses of such data often ignore potential differences in detection probability. We adapted a removal model to directly estimate detection probability during point-count surveys. The model assumes that singing frequency is a major factor influencing probability of detection when birds are surveyed using point counts. This may be appropriate for surveys in which most detections are by sound. The model requires counts to be divided into several time intervals. Point counts are often conducted for 10 min, where the number of birds recorded is divided into those first observed in the first 3 min, the subsequent 2 min, and the last 5 min. We developed a maximum-likelihood estimator for the detectability of birds recorded during counts divided into those intervals. This technique can easily be adapted to point counts divided into intervals of any length. We applied this method to unlimited-radius counts conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. We found differences in detection probability among species. Species that sing frequently such as Winter Wren (Troglodytes troglodytes) and Acadian Flycatcher (Empidonax virescens) had high detection probabilities (∼90%) and species that call infrequently such as Pileated Woodpecker (Dryocopus pileatus) had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. We used the same approach to estimate detection probability and density for a subset of the observations with limited-radius point counts.

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Singing in the suburbs: point count surveys efficiently reveal habitat associations for nocturnal Orthoptera across an urban-to-rural gradient

Journal of Insect Conservation ◽

10.1007/s10841-020-00273-9 ◽

2020 ◽

Vol 24 (6) ◽

pp. 1031-1043

Author(s):

Darin J. McNeil ◽

Christina M. Grozinger

Keyword(s):

Site Occupancy ◽

Habitat Associations ◽

Survey Method ◽

Population Declines ◽

Detection Rates ◽

Point Count ◽

Point Counts ◽

Focal Species ◽

Habitat Gradient ◽

Count Surveys

Abstract As evidence for global insect population declines continues to amass, several studies have indicated that Orthoptera (grasshoppers, crickets, and katydids) are among the most threatened insect groups. Understanding Orthoptera populations across large spatial extents requires efficient survey protocols, however, many previously established methods are expensive and/or labor-intensive. One survey method widely employed in wildlife biology, the aural point count, may work well for crickets and katydids (suborder: Ensifera) because males produce conspicuous, species-specific mating calls. We conducted repeated point count surveys across an urban-to-rural gradient in central Pennsylvania. Occupancy analyses of ten focal species indicated that, although detection probability rates varied by species from 0.43 to 0.98, detection rates compounded over five visits such that all focal species achieved cumulative > 0.90. Factors associated with site occupancy varied among species with some positively associated with urbanization (e.g., Greater Anglewing, Microcentrum rhombifolium), some negatively associated with urbanization (e.g., Sword-bearing Conehead, Neoconocephalus ensiger), and others exhibiting constant occupancy across a habitat gradient (e.g., Common True Katydid, Pterophylla camellifolia). Our community-level analysis revealed that different species’ habitat associations interacted such that intermediate levels of urbanization (i.e., suburbs) hosted the highest number of species. Implications for insect conservation Ultimately, our analyses clearly support the concept that aural point counts paired with static occupancy modeling can serve as an important tool for monitoring night-singing Orthoptera populations. Applications of point count surveys by both researchers and citizen scientists may improve our understanding Ensifera populations and help in the global conservation of these threatened insects.

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Characterizing urban butterfly populations: the case for purposive point-count surveys

Urban Ecosystems ◽

10.1007/s11252-019-00880-8 ◽

2019 ◽

Vol 22 (6) ◽

pp. 1083-1096

Author(s):

Bret J. Lang ◽

Philip M. Dixon ◽

Robert W. Klaver ◽

Jan R. Thompson ◽

Mark P. Widrlechner

Keyword(s):

Point Count ◽

Count Surveys

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EFFECTS OF VEGETATION AND BACKGROUND NOISE ON THE DETECTION PROCESS IN AUDITORY AVIAN POINT-COUNT SURVEYS

The Auk ◽

10.1525/auk.2008.111008 ◽

2008 ◽

Vol 125 (4) ◽

pp. 998-998 ◽

Cited By ~ 3

Author(s):

KRISHNA PACIFICI ◽

THEODORE R. SIMONS ◽

KENNETH H. POLLOCK

Keyword(s):

Background Noise ◽

Point Count ◽

Detection Process ◽

Count Surveys

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Field Comparison of Removal and Modified Double-Observer Modeling for Estimating Detectability and Abundance of Birds

The Auk ◽

10.1093/auk/121.3.865 ◽

2004 ◽

Vol 121 (3) ◽

pp. 865-876

Author(s):

Jeffrey E. Moore ◽

Daniel M. Scheiman ◽

Robert K. Swihart

Keyword(s):

Count Data ◽

Bird Abundance ◽

Density Estimates ◽

North Central ◽

Point Count ◽

Detection Probabilities ◽

True Detection ◽

Sources Of Variation ◽

True Population ◽

Double Observer

Abstract For point-count data to reliably index bird abundance or density, estimates must be corrected for variation in detection probabilities across species, observers, and environmental conditions. Removal and double-observer modeling are two recently developed statistical techniques for estimating detection probabilities and bird abundance. We collected point-count data in north-central Indiana and used a Huggins closed-capture model in MARK to directly compare those two methods. We found that when detection probabilities were relatively high for individual observers, the two methods yielded similar estimates of density for nearly all 17 species modeled. However, when true detection probabilities for observers were relatively low, removal estimates of detectability and density were biased high and low, respectively, perhaps because of the effect of low-detection probability on the removal estimator or smaller sample sizes associated with less-skilled observers. In general, we consider removal modeling a more desirable approach than double-observer modeling because it requires half as many observers, allows more sources of variation in detectability to be modeled, and estimates abundance or density of the true population of birds. By contrast, double-observer modeling estimates only the abundance of the “apparent” population (i.e. those birds that are visually or audibly conspicuous). For species that vocalize infrequently or are otherwise elusive, the apparent population may be significantly smaller than the true population. However, double-observer modeling is more robust to violations of the assumption of population closure and may outperform removal methods when data are collected by less-experienced observers.

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