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 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 Time-of-Detection Method for Estimating Abundance From Point-Count Surveys

The Auk ◽  
2007 ◽  
Vol 124 (2) ◽  
pp. 653-664 ◽  
Author(s):  
Mathew W. Alldredge ◽  
Kenneth H. Pollock ◽  
Theodore R. Simons ◽  
Jaime A. Collazo ◽  
Susan A. Shriner
Keyword(s):  
Theoretic Model ◽  
Data Sets ◽  
Point Count ◽  
Great Smoky Mountains ◽  
Detection Process ◽  
Detection Approach ◽  
Detection Probabilities ◽  
Capture Recapture ◽  
Valid Comparison ◽  
Count Surveys

Abstract Point-count surveys are often used to collect data on the abundance and distribution of birds, generally as an index of relative abundance. Valid comparison of these indices assumes that the detection process is comparable over space and time. These restrictive assumptions can be eliminated by estimating detection probabilities directly. We generalize a recently proposed removal model for estimating detection probabilities using a time-of-detection approach, which can account for more sources of variation in point-count data. This method is specifically designed to account for variation in detection probabilities associated with singing rates of birds. Our model accounts for both availability bias and detection bias by modeling the combined probability that a bird sings during the count, and the probability that it is detected given that it sings. The model requires dividing the count into several intervals and recording detections of individual birds in each interval. We develop maximum-likelihood estimators for this approach and provide a full suite of models based on capture-recapture models, including covariate models. We present two examples of this method: one for four species of songbirds surveyed in Great Smoky Mountains National Park using three unequal intervals, and one for the Pearly-eyed Thrasher (Margarops fuscatus) surveyed in Puerto Rico using four equal intervals. Models incorporating individual heterogeneity were selected for all data sets using information-theoretic model-selection techniques. Detection probabilities varied among count-time intervals, which suggests that birds may be responding to observers. We recommend applying this method to surveys with four or more equal intervals to reduce assumptions and to take full advantage of standard capture-recapture software. The time-of-detection approach provides a better understanding of the detection process, especially when singing rates of individual birds affect detection probabilities. Estimación de la Abundancia en Puntos de Conteo Mediante el Método del Tiempo de Detección

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.

Factors affecting detection probability, effective area surveyed, and species misidentification in grassland bird point counts

The Condor ◽  
2019 ◽  
Vol 121 (3) ◽  
Author(s):  
Elizabeth A Rigby ◽  
Douglas H Johnson
Keyword(s):  
Wind Speed ◽  
Detection Probability ◽  
Effective Area ◽  
Probability Of Detection ◽  
Bird Songs ◽  
Grassland Bird ◽  
Point Count ◽  
Factors Affecting ◽  
Logistic Regression Models ◽  
Point Counts

ABSTRACT We simulated bird surveys using recorded bird songs to assess factors affecting detection probability in grassland bird point counts. We used mixed effects logistic regression models to estimate effects of those factors and to estimate and visualize the variation in the area around the observer where birds can be perceived (the perception area). We simulated surveys with 8,926 binary opportunities for detection in Minnesota grasslands in 2011 and 2012. Species, distance to the observer, wind speed and direction, observer, and density of vegetation all affected detection of recorded bird songs. Species had a strong effect; the size of the predicted perception area around the observer differed by an order of magnitude among species. Wind also had a strong effect on detection. As wind speed increased, probability of detection downwind of the observer was reduced and the perception area around the observer became smaller and more asymmetrical. The effective distance at which an observer is more likely to detect a bird than not detect it may differ among species and angles to the wind, even within the same survey. Eight of 10 species had low probability of misidentification (≤0.03), but Grasshopper Sparrow (Ammodramus savannarum) and LeConte’s Sparrow (Ammospiza leconteii) were frequently misidentified (probability = 0.09–0.24 among observers), contributing to a low rate of correct detection for those species. We recommend collecting point-count data within distance bands so that data can be analyzed based on the effective radius for each species and standardizing surveys across wind conditions to reduce variation in detection probability.

scholarly journals Analysis of Low Probability of Detection Capability for Chaotic Standard Map-Based FH-OFDMA System

2021 ◽  
Vol 11 (5) ◽  
pp. 2198
Author(s):  
Junwoo Jung ◽  
Jaesung Lim ◽  
Sungyeol Park ◽  
Haengik Kang ◽  
Seungbok Kwon
Keyword(s):  
Detection Probability ◽  
Probability Of Detection ◽  
Lower Probability ◽  
Symbol Sequence ◽  
Ofdma System ◽  
Standard Map ◽  
Detection Probabilities ◽  
Low Probability ◽  
Transmitted Symbol ◽  
Basic Symbol

A frequency hopping orthogonal frequency division multiple access (FH-OFDMA) can provide low probability of detection (LPD) and anti-jamming capabilities to users against adversary detectors. To obtain an extreme LPD capability that cannot be provided by the basic symbol-by-symbol (SBS)-based FH pattern, we proposed two FH patterns, namely chaotic standard map (CSM) and cat map for FH-OFDMA systems. In our previous work, through analysis of complexity to regenerate the transmitted symbol sequence, at the point of adversary detectors, we found that the CSM had a lower probability of intercept than the cat map and SBS. It is possible when a detector already knows symbol and frame structures, and the detector has been synchronized to the FH-OFDMA system. Unlike the previous work, here, we analyze whether the CSM provides greater LPD capability than the cat map and SBS by detection probability using spectrum sensing technique. We analyze the detection probability of the CSM and provide detection probabilities of the cat map and SBS compared to the CSM. Based on our analysis of the detection probability and numerical results, it is evident that the CSM provides greater LPD capability than both the cat map and SBS-based FH-OFDMA systems.

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

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.

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

Sign in / Sign up

Export Citation Format

Share Document