Estimating Detection Probabilities from Multiple-Observer Point Counts (Estimación de Probabilidades de Detección a Partir de Conteos en Puntos Hechos por Varios Observadores)

The Auk ◽  
2006 ◽  
Vol 123 (4) ◽  
pp. 1172-1182
Author(s):  
Mathew W. Alldredge ◽  
Kenneth H. Pollock ◽  
Theodore R. Simons
Keyword(s):  
Point Counts ◽  
Detection Probabilities ◽  
Multiple Observer

ESTIMATING DETECTION PROBABILITIES FROM MULTIPLE-OBSERVER POINT COUNTS

The Auk ◽  
2006 ◽  
Vol 123 (4) ◽  
pp. 1172 ◽  
Author(s):  
Mathew W. Alldredge ◽  
Kenneth H. Pollock ◽  
Theodore R. Simons
Keyword(s):  
Point Counts ◽  
Detection Probabilities ◽  
Multiple Observer

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 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

Occupancy Modeling of Woodpeckers: Maximizing Detections for Multiple Species With Multiple Spatial Scales

2014 ◽  
Vol 5 (2) ◽  
pp. 198-207 ◽  
Author(s):  
Jeremy A. Baumgardt ◽  
Joel D. Sauder ◽  
Kerry L. Nicholson
Keyword(s):  
Detection Probability ◽  
Spatial Scales ◽  
Parameter Estimates ◽  
Management Decisions ◽  
Point Counts ◽  
Area Of Occupancy ◽  
Unit Scale ◽  
Detection Probabilities ◽  
Pileated Woodpeckers ◽  
Multiple Species

Abstract Numerous forest birds benefit from woodpecker presence or have similar habitat requirements. Monitoring populations of forest woodpeckers can be useful for management decisions regarding these and other forest species. Usefulness of monitoring efforts depends on methods used and the quality of resulting parameter estimates. Estimating the proportion of area occupied by a species can be an attractive and affordable alternative to abundance or survival estimates. The purpose of this study was to assess the distribution and area of occupancy for pileated woodpeckers (Drycopus pileatus) and American three-toed woodpeckers (Picoides dorsalis) in north-central Idaho, and to compare occupancy estimates using silent point counts, playback surveys, and playback surveys that incorporated estimates of detection probability (p). We used a hierarchical multiscale framework that allowed estimation of occupancy at two spatial scales and applied a removal design such that repeat visits to sampling stations was not necessary to estimate p. The initial naïve estimate of occupancy (using presence–absence data) for pileated woodpecker was 0.39, which increased to 0.59 using playback surveys. The corrected estimate of occupancy at the 1-km2 unit scale was 0.70. The naïve estimates of occupancy for American three-toed woodpeckers using silent point counts and playback surveys were 0.14 and 0.34, respectively. The unbiased estimate of occupancy at the 1-km2 unit scale was 0.71. Detection probabilities are known to vary spatially and temporally for numerous reasons. Thus, comparisons of naïve estimates of occupancy to monitor forest woodpeckers would be imprudent and could lead to poor management decisions. We recommend incorporating detection probability for monitoring wildlife species and show how this can be done within a single sampling framework for species that utilize the landscape at disparate scales.

scholarly journals Estimating Detection Probabilities From Multiple-Observer Point Counts

The Auk ◽  
2006 ◽  
Vol 123 (4) ◽  
pp. 1172-1182 ◽  
Author(s):  
Mathew W. Alldredge ◽  
Kenneth H. Pollock ◽  
Theodore R. Simons
Keyword(s):  
Individual Differences ◽  
Large Scale ◽  
Detection Distance ◽  
Independent Observer ◽  
Closed Population ◽  
Point Count ◽  
Point Counts ◽  
Individual Bird ◽  
Abundance Estimates ◽  
Detection Probabilities

Abstract Point counts are commonly used to obtain indices of bird population abundance. We present an independent-observer point-count method, a generalization of the dependent-observer approach, based on closed-population capture- recapture methods. The approach can incorporate individual covariates, such as detection distance, to account for individual differences in detection probabilities associated with measurable sources of variation. We demonstrate a negative bias in two-observer estimates by comparing abundance estimates from two- and four- observer point counts. Models incorporating data from four independent observers were capable of accounting for this bias. Modeling individual bird differences in detection probabilities produced abundance estimates 15–21% higher than models that did not account for individual differences, in four out of five data sets analyzed. Although independent-observer methods are expensive and impractical for large- scale applications, we believe they can provide important insights into the sources and degree of perception bias (i.e., probability of detecting an individual, given that it is available for detection) in avian point-count estimates. Therefore, they may be useful in a two-stage sampling framework to calibrate larger surveys based on single-observer estimates. Estimación de Probabilidades de Detección a Partir de Conteos en Puntos Hechos por Varios Observadores

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 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.

Theory and application of mark - recapture and related techniques to aerial surveys of wildlife

2008 ◽  
Vol 35 (4) ◽  
pp. 268 ◽  
Author(s):  
Richard Barker
Keyword(s):  
Conditional Independence ◽  
Survey Design ◽  
Imperfect Detection ◽  
Mark Recapture ◽  
Closed Population ◽  
Aerial Surveys ◽  
Detection Probabilities ◽  
Complete Independence ◽  
Multiple Observer ◽  
Observer Studies

The key difficulty in assessing animal numbers from the air is that not all animals are seen by the observers. Methods for estimating detection probabilities, or accounting for imperfect detection, are reviewed including double surveys, use of sightability models, mark–resight, and mark–recapture. The assumptions needed for each method are considered as well as issues concerning survey design. For closed-population mark–recapture modelling particular attention is given to multiple observer studies. An emphasis is that an assumption of complete independence in double-observer studies is rarely justifiable and that independent observers will generally only satisfy an assumption of conditional independence and not complete independence.

scholarly journals Variability in Grassland Bird Counts Related to Observer Differences and Species Detection Rates

The Auk ◽  
2003 ◽  
Vol 120 (4) ◽  
pp. 1168-1179 ◽  
Author(s):  
Duane R. Diefenbach ◽  
Daniel W. Brauning ◽  
Jennifer A. Mattice
Keyword(s):  
Survey Methods ◽  
Distance Sampling ◽  
Monitoring Program ◽  
Detection Rates ◽  
Species Detection ◽  
Point Counts ◽  
Grasshopper Sparrow ◽  
Transect Line ◽  
Detection Probabilities ◽  
Henslow's Sparrow

Abstract Differences among observers in ability to detect and identify birds has been long recognized as a potential source of error when surveying terrestrial birds. However, few published studies address that issue in their methods or study design. We used distance sampling with line transects to investigate differences in detection probabilities among observers and among three species of grassland songbirds: Henslow's Sparrow (Ammodramus henslowii), Grasshopper Sparrow (A. savannarum), and Savannah Sparrow (Passerculus sandwichensis). Our review of 75 papers published in 1985–2001 found that the most commonly used methods were fixed-width transects (31%, 23 papers) and fixed-radius point counts (20%, 15 papers). The median half-width of fixed-width strip transects used by researchers was 50 m, but our results indicated detection probabilities were <1.0 at distances >25 m for most observers and species. Beyond 50 m from the transect line, we found that as many as 60% of birds were missed by observers and that the proportion missed differed among observers and species. Detection probabilities among observers ranged from 0.43 to 1.00 for Henslow's Sparrow, from 0.44 to 0.66 for Grasshopper Sparrow, and from 0.60 to 0.72 for Grasshopper Sparrow for birds detected within 58–100 m of the transect line. Using our estimates of detection probabilities for Henslow's Sparrows among six observers in a computer simulation of a monitoring program, we found that bird counts from fixed-width transects required an additional 2–3 years of monitoring to detect a given decline in abundance compared to density estimates that used a method to correct for missed birds. We recommend that researchers employ survey methods that correct for detection probabilities <1.0.

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.

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