Correcting wildlife counts using detection probabilities

2005 ◽  
Vol 32 (3) ◽  
pp. 211 ◽  
Author(s):  
Gary C. White
Keyword(s):  
Detection Probability ◽  
Distance Sampling ◽  
Probability Of Detection ◽  
Mark Recapture ◽  
Additional Information ◽  
Release Studies ◽  
Detection Probabilities ◽  
Minimum Number ◽  
Capture And Release ◽  
Wildlife Populations

One of the most pervasive uses of indices of wildlife populations is uncorrected counts of animals. Two examples are the minimum number known alive from capture and release studies, and aerial surveys where the detection probability is not estimated from a sightability model, marked animals, or distance sampling. Both the mark–recapture and distance-sampling estimators are techniques to estimate the probability of detection of an individual animal (or cluster of animals), which is then used to correct a count of animals. However, often the number of animals in a survey is inadequate to compute an estimate of the detection probability and hence correct the count. Modern methods allow sophisticated modelling to estimate the detection probability, including incorporating covariates to provide additional information about the detection probability. Examples from both distance and mark–recapture sampling are presented to demonstrate the approach.

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.

Estimating detection probabilities of tagged fish migrating past fixed receiver stations using only local information

2010 ◽  
Vol 67 (4) ◽  
pp. 641-658 ◽  
Author(s):  
Michael C. Melnychuk ◽  
Carl J. Walters
Keyword(s):  
Detection Probability ◽  
Radio Telemetry ◽  
Model Parameters ◽  
Migration Routes ◽  
Mark Recapture ◽  
The Pacific ◽  
Detection Probabilities ◽  
Acoustic Tags ◽  
Attenuation Models ◽  
Local Detection

We developed a method to predict the probability of detecting acoustic tags crossing a receiver station using only detection information at that station. This method is suitable for acoustic or radio telemetry studies in which individually tagged animals migrate past fixed stations (where a station may consist of one or more receivers). It is based on fitting attenuation models to sequences of detections and missed transmissions of individually coded tags in fish migrating past stations of the Pacific Ocean Shelf Tracking Project (POST). We used estimated attenuation model parameters from detected fish at each station to predict the number of fish that crossed the station undetected, which in turn was used to calculate the local detection probability. This estimator was correlated (r = 0.54–0.81 in river and coastal habitats) with mark–recapture estimates of detection probability (pmr) that use nonlocal detection information at stations further along migration routes. This local detection probability estimate can be used as a covariate of pmr in mark–recapture models and can predict approximate values of pmr at final detection stations where pmr is not estimable because of the lack of recaptures further along migration routes.

scholarly journals Horizontal or vertical? Camera trap orientations and recording modes for detecting potoroos, bandicoots and pademelons

2014 ◽  
Vol 36 (1) ◽  
pp. 60 ◽  
Author(s):  
Brendan D. Taylor ◽  
Ross L. Goldingay ◽  
John M. Lindsay
Keyword(s):  
Detection Probability ◽  
New South ◽  
Population Monitoring ◽  
Camera Trap ◽  
Probability Of Detection ◽  
Camera Traps ◽  
North East ◽  
South Wales ◽  
Detection Probabilities ◽  
The Stability

Camera traps can detect rare and cryptic species, and may enable description of the stability of populations of threatened species. We investigated the relative performance of cameras oriented horizontally or vertically, and recording mode (still and video) to detect the vulnerable long-nosed potoroo (Potorous tridactylus) as a precursor to population monitoring. We established camera traps for periods of 13–21 days across 21 sites in Richmond Range National Park in north-east New South Wales. Each camera trap set consisted of three KeepGuard KG680V cameras directed at a bait container – one horizontal and one vertical camera in still mode and one horizontal camera in video mode. Potoroos and bandicoots (Perameles nasuta and Isoodon macrourus) were detected at 14 sites and pademelons (Thylogale stigmatica and T. thetis) were detected at 19 sites. We used program Presence to compare detection probabilities for each camera category. The detection probability for all three taxa groups was lowest for the vertical still and similar for the horizontal cameras. The detection probability (horizontal still) was highest for the potoroos (0.43) compared with the bandicoots (0.16) and pademelons (0.25). We estimate that the horizontal stills camera could achieve a 95% probability of detection of a potoroo within 6 days compared with 8 days using a vertical stills camera. This suggests that horizontal cameras in still mode have great potential for monitoring the dynamics of this potoroo population.

scholarly journals Simultaneous Modelling of Movement, Measurement Error, and Observer Dependence in Double-Observer Distance Sampling Surveys

2017 ◽  
Author(s):  
By Paul B. Conn ◽  
Ray T. Alisauskas
Keyword(s):  
Measurement Error ◽  
Detection Probability ◽  
Marginal Likelihood ◽  
Distance Sampling ◽  
Mark Recapture ◽  
Animal Groups ◽  
Animal Abundance ◽  
Helicopter Survey ◽  
Using Data ◽  
Double Observer

Mark-recapture distance sampling uses detections, non-detections and recorded distances of animals encountered in transect surveys to estimate abundance. However, commonly available distance sampling estimators require that distances to target animals are made without error and that animals are stationary while sampling is being conducted. In practice these requirements are often violated. In this paper, we describe a marginal likelihood framework for estimating abundance from double-observer data that can accommodate movement and measurement error when observations are made consecutively (as with front and rear observers) and when animals are randomly distributed when detected by the first observer. Our framework requires that two observers independently detect and record binned distances to observed animal groups, as we well as a binary indicator for whether animals were moving or not. We then assume that stationary animals are subject to measurement error whereas moving animals are subject to both movement and measurement error. Integrating over unknown animal locations, we construct a marginal likelihood for detection, movement, and measurement error parameters. Estimates of animal abundance are then obtained using a modified Horvitz-Thompson-like estimator. In addition, unmodelled heterogeneity in detection probability can be accommodated through observer dependence parameters. Using simulation, we show that our approach yields low bias compared to approaches that ignore movement and/or measurement error, including in cases where there is considerable detection heterogeneity. We demonstrate our approach using data from a double-observer waterfowl helicopter survey.

Does variable probability of detection compromise the use of indices in aerial surveys of medium-sized mammals?

2005 ◽  
Vol 32 (3) ◽  
pp. 245 ◽  
Author(s):  
John P. Tracey ◽  
Peter J. S. Fleming ◽  
Gavin J. Melville
Keyword(s):  
Detection Probability ◽  
Sampling Period ◽  
Aerial Survey ◽  
Species Group ◽  
Probability Of Detection ◽  
Individual Species ◽  
Aerial Surveys ◽  
South Wales ◽  
Maximum Likelihood Methods ◽  
Wildlife Populations

Although aerial surveys are an effective and commonly used method of monitoring wildlife populations, variable detection probability may result in unreliable indices or biased estimates of absolute abundance. Detection probability can vary between sites, sampling periods, species, group sizes, vegetation types and observers. These variables were examined in helicopter surveys of a suite of medium-sized mammals in a hilly environment in central eastern New South Wales. Maximum-likelihood methods were used to investigate the effects of these variables on detection probability, which was derived using the double-count technique. Significant differences were evident between species in the overall analysis, and group size, vegetation, observer pair and sampling period for various individual species when analysed separately. The implications for monitoring wildlife populations between sites and across time are discussed. This paper emphasises that aerial survey indices may be effective in detecting large differences in population size but can be improved by quantifying detection probabilities for a range of variables.

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.

Advances in Fish Tagging and Marking Technology

2012 ◽  
Keyword(s):  
Detection Probability ◽  
Radio Telemetry ◽  
Mark Recapture ◽  
Extra Effort ◽  
Probability Estimates ◽  
Abundance Estimates ◽  
Detection Probabilities ◽  
Acoustic Tags ◽  
Fish Detection

<i>Abstract</i>.—A common assumption in acoustic or radio telemetry studies is that tag transmission strength is homogeneous for a particular tag type, which in turn supports the assumption that detection ranges or mark–recapture detection probabilities are homogenous among tagged fish. Variation among tags in acoustic intensity could reduce precision in detection probability estimates that do not account for it, and therefore possibly in the precision of survival or abundance estimates. Simple methods are suggested for quantifying variation in tag strength prior to tagging fish and incorporating these measurements into mark–recapture models. At little extra effort to the researcher, these measurements could explain part of the variation in detection probability estimates and therefore could increase the precision of survival or abundance estimates of migrating fish. This potential source of variation in detection probabilities was investigated in a case study with migrating salmon smolts. An index of tag strength was quantified while coded acoustic tags were activated prior to tagging fish. Detection and survival probabilities were estimated with standard mark–recapture methods for the downstream and early ocean migration. A model that included the tag strength index as an additive covariate of detection probabilities had a reasonable level of support compared to a model without the index, suggesting that this source of variation should not be ignored.

scholarly journals A comparison of mark - recapture distance-sampling methods applied to aerial surveys of eastern grey kangaroos

2008 ◽  
Vol 35 (4) ◽  
pp. 320 ◽  
Author(s):  
Rachel M. Fewster ◽  
Anthony R. Pople
Keyword(s):  
Goodness Of Fit ◽  
Distance Sampling ◽  
Density Estimates ◽  
Mark Recapture ◽  
Transect Line ◽  
Aerial Surveys ◽  
Commercial Harvest ◽  
Coefficients Of Variation ◽  
Detection Probabilities ◽  
Full Independence

Aerial surveys of kangaroos (Macropus spp.) in Queensland are used to make economically important judgements on the levels of viable commercial harvest. Previous analysis methods for aerial kangaroo surveys have used both mark–recapture methodologies and conventional distance-sampling analyses. Conventional distance sampling has the disadvantage that detection is assumed to be perfect on the transect line, while mark–recapture methods are notoriously sensitive to problems with unmodelled heterogeneity in capture probabilities. We introduce three methodologies for combining together mark–recapture and distance-sampling data, aimed at exploiting the strengths of both methodologies and overcoming the weaknesses. Of these methods, two are based on the assumption of full independence between observers in the mark–recapture component, and this appears to introduce more bias in density estimation than it resolves through allowing uncertain trackline detection. Both of these methods give lower density estimates than conventional distance sampling, indicating a clear failure of the independence assumption. The third method, termed point independence, appears to perform very well, giving credible density estimates and good properties in terms of goodness-of-fit and percentage coefficient of variation. Estimated densities of eastern grey kangaroos range from 21 to 36 individuals km–2, with estimated coefficients of variation between 11% and 14% and estimated trackline detection probabilities primarily between 0.7 and 0.9.

The closed-subpopulation method and estimation of population size from mark-recapture and ancillary data

2000 ◽  
Vol 78 (2) ◽  
pp. 320-326 ◽  
Author(s):  
Frank AM Tuyttens
Keyword(s):  
Population Size ◽  
Ancillary Data ◽  
Mark Recapture ◽  
Animal Populations ◽  
Accuracy And Precision ◽  
Population Size Estimates ◽  
Minimum Number ◽  
Flexible Framework ◽  
And Performance ◽  
Better Than

The algebraic relationships, underlying assumptions, and performance of the recently proposed closed-subpopulation method are compared with those of other commonly used methods for estimating the size of animal populations from mark-recapture records. In its basic format the closed-subpopulation method is similar to the Manly-Parr method and less restrictive than the Jolly-Seber method. Computer simulations indicate that the accuracy and precision of the population estimators generated by the basic closed-subpopulation method are almost comparable to those generated by the Jolly-Seber method, and generally better than those of the minimum-number-alive method. The performance of all these methods depends on the capture probability, the number of previous and subsequent trapping occasions, and whether the population is demographically closed or open. Violation of the assumption of equal catchability causes a negative bias that is more pronounced for the closed-subpopulation and Jolly-Seber estimators than for the minimum-number-alive. The closed-subpopulation method provides a simple and flexible framework for illustrating that the precision and accuracy of population-size estimates can be improved by incorporating evidence, other than mark-recapture data, of the presence of recognisable individuals in the population (from radiotelemetry, mortality records, or sightings, for example) and by exploiting specific characteristics of the population concerned.

Differences in microhabitat selection patterns between a remnant and constructed landscape following management intervention

2017 ◽  
Vol 44 (3) ◽  
pp. 248 ◽  
Author(s):  
Jose W. Valdez ◽  
Kaya Klop-Toker ◽  
Michelle P. Stockwell ◽  
Loren Fardell ◽  
Simon Clulow ◽  
...  
Keyword(s):  
Aquatic Vegetation ◽  
Management Strategies ◽  
Probability Of Detection ◽  
Microhabitat Use ◽  
Microhabitat Selection ◽  
Habitat Creation ◽  
Litoria Aurea ◽  
Use Of Resources ◽  
Detection Probabilities ◽  
Future Management

Context Achieving successful conservation outcomes in habitat creation and reintroductions requires an understanding of how species use their habitat and respond to these interventions. However, few initiatives directly compare microhabitat selection between remnant and managed habitats to measure effectiveness and evaluate outcomes. Probability of detection is also rarely included in studies on microhabitat use, which may lead to erroneous conclusions if detectability varies between variables. Methods In this study, we used the endangered green and golden bell frog (Litoria aurea) to compare differences in microhabitat-use patterns in both a remnant and a constructed habitat. A detectability study was also conducted to determine detection probabilities among microhabitats. Key results Aquatic vegetation was used more than expected in both the remnant and constructed habitats, and rock piles were utilised less than expected in the constructed habitat, despite their recommendation in most habitat templates. We found that detection probabilities altered the outcomes of abundance estimates for nearly all the measured microhabitat variables. Conclusions Future management for this species should focus on providing high proportions of aquatic vegetation. Furthermore, although rock piles have been utilised greatly in past L. aurea habitat creation, placing large rocks on a managed site is expensive and time consuming. Future management initiatives may need to focus on providing smaller proportion of rocks, which would be a more appropriate use of resources. Implications With conservation management projects increasing over the next few decades, understanding habitat use before implementing strategies should be a priority as it will provide important insights and inform decision-making for optimum habitat creation and restoration. Furthermore, accounting for detectability in microhabitat use studies is essential to avoid wrong conclusions that may negatively affect the success of ecological management strategies.

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