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

The Auk ◽  
2000 ◽  
Vol 117 (2) ◽  
pp. 393-408 ◽  
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.

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

The Auk ◽  
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.

Problems with Avian Point Counts for Estimating Density of Northern Bobwhite—A Case Study

2011 ◽  
Vol 2 (1) ◽  
pp. 117-121 ◽  
Author(s):  
Roger D. Applegate ◽  
Robert E. Kissell ◽  
E. Daniel Moss ◽  
Edward L. Warr ◽  
Michael L. Kennedy
Keyword(s):  
Count Data ◽  
Distance Sampling ◽  
Bird Species ◽  
Northern Bobwhite ◽  
Model Fit ◽  
Point Count ◽  
Point Counts ◽  
Occupancy Estimation ◽  
Detection Probabilities

Abstract Point count data are used increasingly to provide density estimates of bird species. A favored approach to analyze point count data uses distance sampling theory where model selection and model fit are important considerations. We used uniform and half normal models and assessed model fit using χ2 analysis. We were unsuccessful in fitting models to 635 northern bobwhite Colinus virginianus observations from 85 avian point locations spanning 6 y (P ≤ 0.05). Most observations (74%) occurred in the outermost (>100-m) distance radius. Our results violated the assumptions that all observations at the point are detected. The assumption that birds were assigned to the correct distance interval also was probably violated. We caution managers in implementing avian point counts with distance sampling when estimating northern bobwhite population density. We recommend exploring other approaches such as occupancy-estimation and modeling for estimating detection probabilities.

scholarly journals Estimating Detection Probability and Density from Point-Count Surveys: A Combination of Distance and Double-Observer Sampling

The Auk ◽  
2006 ◽  
Vol 123 (3) ◽  
pp. 735-752 ◽  
Author(s):  
Michelle L. Kissling ◽  
Edward O. Garton
Keyword(s):  
Detection Probability ◽  
Survey Methods ◽  
Effective Area ◽  
Survey Method ◽  
Density Estimates ◽  
Point Count ◽  
Detection Probabilities ◽  
Fixed Radius ◽  
Count Surveys ◽  
Double Observer

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

scholarly journals Experimental Analysis of The Auditory Detection Process on Avian Point Counts

The Auk ◽  
2007 ◽  
Vol 124 (3) ◽  
pp. 986-999 ◽  
Author(s):  
Theodore R. Simons ◽  
Mathew W. Alldredge ◽  
Kenneth H. Pollock ◽  
John M. Wettroth
Keyword(s):  
Census Data ◽  
Laptop Computer ◽  
Point Count ◽  
Point Counts ◽  
Avian Abundance ◽  
Abundance Estimates ◽  
Auditory Detection ◽  
Detection Probabilities ◽  
Mp3 Players ◽  
Bird Census

AbstractWe have developed a system for simulating the conditions of avian surveys in which birds are identified by sound. The system uses a laptop computer to control a set of amplified MP3 players placed at known locations around a survey point. The system can realistically simulate a known population of songbirds under a range of factors that affect detection probabilities. The goals of our research are to describe the sources and range of variability affecting point-count estimates and to find applications of sampling theory and methodologies that produce practical improvements in the quality of bird-census data. Initial experiments in an open field showed that, on average, observers tend to undercount birds on unlimited-radius counts, though the proportion of birds counted by individual observers ranged from 81% to 132% of the actual total. In contrast to the unlimited-radius counts, when data were truncated at a 50-m radius around the point, observers overestimated the total population by 17% to 122%. Results also illustrate how detection distances decline and identification errors increase with increasing levels of ambient noise. Overall, the proportion of birds heard by observers decreased by 28 ± 4.7% under breezy conditions, 41 ± 5.2% with the presence of additional background birds, and 42 ± 3.4% with the addition of 10 dB of white noise. These findings illustrate some of the inherent difficulties in interpreting avian abundance estimates based on auditory detections, and why estimates that do not account for variations in detection probability will not withstand critical scrutiny.Análisis Experimentales del Proceso de Detección Auditiva en Puntos de Conteo de Aves

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

The Auk ◽  
2002 ◽  
Vol 119 (2) ◽  
pp. 414-425 ◽  
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.

scholarly journals Incorporating Availability for Detection in Estimates of Bird Abundance

The Auk ◽  
2007 ◽  
Vol 124 (1) ◽  
pp. 96-106 ◽  
Author(s):  
Duane R. Diefenbach ◽  
Matthew R. Marshall ◽  
Jennifer A. Mattice ◽  
Daniel W. Brauning
Keyword(s):  
Survey Methods ◽  
Distance Sampling ◽  
Sampling Period ◽  
Bird Abundance ◽  
Point Counts ◽  
Variance Estimators ◽  
Bird Survey ◽  
Detection Probabilities ◽  
Ammodramus Henslowii ◽  
Further Development

Abstract Several bird-survey methods have been proposed that provide an estimated detection probability so that bird-count statistics can be used to estimate bird abundance. However, some of these estimators adjust counts of birds observed by the probability that a bird is detected and assume that all birds are available to be detected at the time of the survey. We marked male Henslow's Sparrows (Ammodramus henslowii) and Grasshopper Sparrows (A. savannarum) and monitored their behavior during May-July 2002 and 2003 to estimate the proportion of time they were available for detection. We found that the availability of Henslow's Sparrows declined in late June to <10% for 5- or 10-min point counts when a male had to sing and be visible to the observer; but during 20 May-19 June, males were available for detection 39.1% (SD = 27.3) of the time for 5-min point counts and 43.9% (SD = 28.9) of the time for 10-min point counts (n = 54). We detected no temporal changes in availability for Grasshopper Sparrows, but estimated availability to be much lower for 5-min point counts (10.3%, SD = 12.2) than for 10-min point counts (19.2%, SD = 22.3) when males had to be visible and sing during the sampling period (n = 80). For distance sampling, we estimated the availability of Henslow's Sparrows to be 44.2% (SD = 29.0) and the availability of Grasshopper Sparrows to be 20.6% (SD = 23.5). We show how our estimates of availability can be incorporated in the abundance and variance estimators for distance sampling and modify the abundance and variance estimators for the double-observer method. Methods that directly estimate availability from bird counts but also incorporate detection probabilities need further development and will be important for obtaining unbiased estimates of abundance for these species. Incorporación de la Disponibilidad para la Detección en las Estimaciones de Abundancia de Aves

scholarly journals A Fixed-radius Point Count Method for Nonbreeding and Breeding Season Use

The Auk ◽  
1986 ◽  
Vol 103 (3) ◽  
pp. 593-602 ◽  
Author(s):  
Richard L. Hutto ◽  
Sandra M. Pletschet ◽  
Paul Hendricks
Keyword(s):  
Bird Species ◽  
Common Species ◽  
Bird Abundance ◽  
Point Count ◽  
Bird Density ◽  
Count Method ◽  
Species Abundances ◽  
Fixed Radius ◽  
Point Count Method ◽  
A Site

Abstract We provide a detailed description of a fixed-radius point count method that carries fewer assumptions than most of the currently popular methods of estimating bird density and that can be used during both the nonbreeding and breeding seasons. The method results in three indices of bird abundance, any of which can be used to test for differences in community composition among sites, or for differences in the abundance of a given bird species among sites. These indices are (1) the mean number of detections within 25 m of the observer, (2) the frequency of detections within 25 m of the observer, and (3) the frequency of detections regardless of distance from the observer. The overall ranking of species abundances from a site is similar among the three indices, but discrepancies occur with either rare species that are highly detectable at great distances or common species that are repulsed by, or inconspicuous when near, the observer. We argue that differences in the behavior among species will preclude an accurate ranking of species by abundance through use of this or any other counting method in current use.

scholarly journals Power to Detect Trend in Short-Term Time Series of Bird Abundance

The Condor ◽  
2007 ◽  
Vol 109 (4) ◽  
pp. 943-948
Author(s):  
Wayne E. Thogmartin ◽  
Brian R. Gray ◽  
Maureen Gallagher ◽  
Neal Young ◽  
Jason J. Rohweder ◽  
...  
Keyword(s):  
Sample Size ◽  
Short Duration ◽  
Bird Species ◽  
Population Monitoring ◽  
Short Term ◽  
Wet Prairie ◽  
Bird Abundance ◽  
Point Counts ◽  
Study Sites ◽  
Species Specific

Abstract Avian point counts for population monitoring are often collected over a short timespan (e.g., 3–5 years). We examined whether power was adequate (power ≥0.80) in short-duration studies to warrant the calculation of trend estimates. We modeled power to detect trends in abundance indices of eight bird species occurring across three floodplain habitats (wet prairie, early successional forest, and mature forest) as a function of trend magnitude, sample size, and species-specific sampling and among-year variance components. Point counts (5 min) were collected from 365 locations distributed among 10 study sites along the lower Missouri River; counts were collected over the period 2002 to 2004. For all study species, power appeared adequate to detect trends in studies of short duration (three years) at a single site when exponential declines were relatively large in magnitude (more than −5% year−1) and the sample of point counts per year was ≥30. Efforts to monitor avian trends with point counts in small managed lands (i.e., refuges and parks) should recognize this sample size restriction by including point counts from offsite locations as a means of obtaining sufficient numbers of samples per strata. Trends of less than −5% year−1 are not likely to be consistently detected for most species over the short term, but short-term monitoring may still be useful as the basis for comparisons with future surveys.

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

The Auk ◽  
2006 ◽  
Vol 123 (3) ◽  
pp. 735 ◽  
Author(s):  
Michelle L. Kissling ◽  
Edward O. Garton
Keyword(s):  
Detection Probability ◽  
Point Count ◽  
Count Surveys ◽  
Double Observer

Bird communities and vegetation associations across a treeline ecotone in the Mealy Mountains, Labrador, which is an understudied part of the boreal forest

2015 ◽  
Vol 93 (6) ◽  
pp. 477-486 ◽  
Author(s):  
Keith P. Lewis ◽  
Brian M. Starzomski
Keyword(s):  
Species Composition ◽  
Bird Species ◽  
Bird Communities ◽  
Tree Cover ◽  
Strong Impact ◽  
Avian Diversity ◽  
Bird Abundance ◽  
Treeline Ecotone ◽  
Point Counts ◽  
Deciduous Shrub

We examined the factors structuring bird communities across a complex subarctic treeline in the Mealy Mountains, Labrador, Canada. Using point counts of bird abundance in 2007 and 2008, we show that changes in vegetation driven by elevation are strongly correlated with avian community structure in this treeline ecotone system. Overall, avian diversity was higher in the forest compared with other habitat classes (krummholz, deciduous shrub, and alpine). There were strong correlations between avian diversity and vegetation richness, as well as structure, among and within habitat class in 2008. Numerous habitat types (subset of habitat class) were correlated with avian composition, although some species were clearly habitat generalists. Contrary to expectation, avian species composition was associated with physiognomy (vegetation structure) in alpine and deciduous shrub, and with either physiognomy or floristics (vegetation species composition) in krummholz and forest. Given the strong impact of elevation on vegetation and the demonstrated influence on bird communities, we note that for bird species whose near-southernmost populations are found in the Mealy Mountains, climate change is likely to have a strong negative effect if alpine tundra habitat is lost. Furthermore, forest bird species are likely to benefit from the increased tree cover as treeline moves poleward and upward.

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