The Experts below are selected from a list of 267 Experts worldwide ranked by ideXlab platform
Stephen T. Buckland - One of the best experts on this subject based on the ideXlab platform.
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The effect of animal movement on Line Transect estimates of abundance.
PloS one, 2015Co-Authors: Richard Glennie, Stephen T. Buckland, Len ThomasAbstract:Line Transect sampling is a distance sampling method for estimating the abundance of wild animal populations. One key assumption of this method is that all animals are detected at their initial location. Animal movement independent of the Transect and observer can thus cause substantial bias. We present an analytic expression for this bias when detection within the Transect is certain (strip Transect sampling) and use simulation to quantify bias when detection falls off with distance from the Line (Line Transect sampling). We also explore the non-Linear relationship between bias, detection, and animal movement by varying detectability and movement type. We consider animals that move in randomly orientated straight Lines, which provides an upper bound on bias, and animals that are constrained to a home range of random radius. We find that bias is reduced when animal movement is constrained, and bias is considerably smaller in Line Transect sampling than strip Transect sampling provided that mean animal speed is less than observer speed. By contrast, when mean animal speed exceeds observer speed the bias in Line Transect sampling becomes comparable with, and may exceed, that of strip Transect sampling. Bias from independent animal movement is reduced by the observer searching further perpendicular to the Transect, searching a shorter distance ahead and by ignoring animals that may overtake the observer from behind. However, when animals move in response to the observer, the standard practice of searching further ahead should continue as the bias from responsive movement is often greater than that from independent movement.
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Design and analysis of Line Transect surveys for primates
International Journal of Primatology, 2010Co-Authors: Stephen T. Buckland, Len Thomas, Andrew J. Plumptre, Eric RexstadAbstract:Line Transect surveys are widely used for estimating abundance of primate populations. The method relies on a small number of key assumptions, and if these are not met, substantial bias may occur. For a variety of reasons, primate surveys often do not follow what is generally considered to be best practice, either in survey design or in analysis. The design often comprises too few Lines (sometimes just 1), subjectively placed or placed along trails, so lacks both randomization and adequate replication. Analysis often involves flawed or inefficient models, and often uses biased estimates of the locations of primate groups relative to the Line. We outLine the standard method, emphasizing the assumptions underlying the approach. We then consider options for when it is difficult or impossible to meet key assumptions. We explore the performance of these options by simulation, focusing particularly on the analysis of primate group sizes, where many of the variations in survey methods have been developed. We also discuss design issues, field methods, analysis, and potential alternative methodologies for when standard Line Transect sampling cannot deliver reliable abundance estimates.
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Line Transect Sampling of Primates: Can Animal-to-Observer Distance Methods Work?
International Journal of Primatology, 2010Co-Authors: Stephen T. Buckland, Len Thomas, Andrew J. Plumptre, Eric RexstadAbstract:Line Transect sampling is widely used for estimating abundance of primate populations. Researchers commonly use animal-to-observer distances (AODs) in analysis, in preference to perpendicular distances from the Line, which is in marked contrast with standard practice for other applications of Line Transect sampling. We formalize the mathematical shortcomings of approaches based on AODs, and show that they are likely to give strongly biased estimates of density. We review papers that claim good performance for the method, and explore this performance through simulations. These confirm strong bias in estimates of density using AODs. We conclude that AOD methods are conceptually flawed, and that they cannot in general provide valid estimates of density.
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Double-observer Line Transect methods: levels of independence.
Biometrics, 2009Co-Authors: Stephen T. Buckland, Jeffrey L Laake, David L. BorchersAbstract:Double-observer Line Transect methods are becoming increasingly widespread, especially for the estimation of marine mammal abundance from aerial and shipboard surveys when detection of animals on the Line is uncertain. The resulting data supplement conventional distance sampling data with two-sample mark-recapture data. Like conventional mark-recapture data, these have inherent problems for estimating abundance in the presence of heterogeneity. Unlike conventional mark-recapture methods, Line Transect methods use knowledge of the distribution of a covariate, which affects detection probability (namely, distance from the Transect Line) in inference. This knowledge can be used to diagnose unmodeled heterogeneity in the mark-recapture component of the data. By modeling the covariance in detection probabilities with distance, we show how the estimation problem can be formulated in terms of different levels of independence. At one extreme, full independence is assumed, as in the Petersen estimator (which does not use distance data); at the other extreme, independence only occurs in the limit as detection probability tends to one. Between the two extremes, there is a range of models, including those currently in common use, which have intermediate levels of independence. We show how this framework can be used to provide more reliable analysis of double-observer Line Transect data. We test the methods by simulation, and by analysis of a dataset for which true abundance is known. We illustrate the approach through analysis of minke whale sightings data from the North Sea and adjacent waters.
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Line Transect methods for plant surveys.
Biometrics, 2007Co-Authors: Stephen T. Buckland, David L. Borchers, Alison Johnston, Peter A. Henrys, Tiago A. MarquesAbstract:Interest in surveys for monitoring plant abundance is increasing, due in part to the need to quantify the rate of loss of biodiversity. Line Transect sampling offers an efficient way to monitor many species. However, the method does not work well in some circumstances, for example on small survey plots, when the plant species has a strongly aggregated distribution, or when plants that are on the Line are not easily detected. We develop a crossed design, together with methods that exploit the additional information from such a design, to address these problems. The methods are illustrated using data on a colony of cowslips.
Jay Barlow - One of the best experts on this subject based on the ideXlab platform.
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accounting for subgroup structure in Line Transect abundance estimates of false killer whales pseudorca crassidens in hawaiian waters
PLOS ONE, 2014Co-Authors: Amanda L Bradford, Karin A Forney, Erin M. Oleson, Jay BarlowAbstract:For biological populations that form aggregations (or clusters) of individuals, cluster size is an important parameter in LineTransect abundance estimation and should be accurately measured. Cluster size in cetaceans has traditionally been represented as the total number of individuals in a group, but group size may be underestimated if group members are spatially diffuse. Groups of false killer whales (Pseudorca crassidens) can comprise numerous subgroups that are dispersed over tens of kilometers, leading to a spatial mismatch between a detected group and the theoretical framework of LineTransect analysis. Three stocks of false killer whales are found within the U.S. Exclusive Economic Zone of the Hawaiian Islands (Hawaiian EEZ): an insular main Hawaiian Islands stock, a pelagic stock, and a Northwestern Hawaiian Islands (NWHI) stock. A ship-based Line-Transect survey of the Hawaiian EEZ was conducted in the summer and fall of 2010, resulting in six systematic-effort visual sightings of pelagic (n=5) and NWHI (n=1) false killer whale groups. The maximum number and spatial extent of subgroups per sighting was 18 subgroups and 35 km, respectively. These sightings were combined with data from similar previous surveys and analyzed within the conventional Line-Transect estimation framework. The detection function, mean cluster size, and encounter rate were estimated separately to appropriately incorporate data collected using different methods. Unlike previous Line-Transect analyses of cetaceans, subgroups were treated as the analytical cluster instead of groups because subgroups better conform to the specifications of Line-Transect theory. Bootstrap values (n=5,000) of the Line-Transect parameters were randomly combined to estimate the variance of stock-specific abundance estimates. Hawai’i pelagic and NWHI false killer whales were estimated to number 1,552 (CV=0.66; 95% CI=479–5,030) and 552 (CV=1.09; 95% CI=97–3,123) individuals, respectively. Subgroup structure is an important factor to consider in LineTransect analyses of false killer whales and other species with complex grouping patterns.
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ABUNDANCE OF BLUE AND HUMPBACK WHALES IN THE EASTERN NORTH PACIFIC ESTIMATED BY CAPTURE‐RECAPTURE AND Line‐Transect METHODS
Marine Mammal Science, 2004Co-Authors: John Calambokidis, Jay BarlowAbstract:We estimated humpback and blue whale abundance from 1991 to 1997 off the west coast of the U.S. and Mexico comparing capture-recapture models based on photographically identified animals and Line-Transect methods from ship-based surveys. During photo-identification research we obtained 4,212 identifications of 824 humpback whales and 2,403 identifications of 908 blue whales primarily through non-systematic small-boat surveys along the coast of California, Oregon, and Washington. Line-Transect surveys from NOAA ships in 1991, 1993, and 1996 covered approximately 39,000 km along the coast of Baja California, California, Oregon, and Washington out to 555 km from shore. The nearshore and clumped distribution of humpback whales allowed photographic identification from small boats to cost-effectively sample a substantial portion of the population, but made it difficult to obtain effective samples in the Line-Transect surveys covering broad areas. The humpback capture-recapture estimates indicated humpback whale abundance increased over the six years (from 569 to 837). The broader more offshore distribution of blue whales made it harder to obtain a representative sample of identification photographs, but was well suited to the Line-Transect estimates. The Line-Transect estimates, after correction for missed animals, indicated approximately 3,000 blue whales (CV ¼ 0.14). Capture-recapture estimates of blue whales were lower than this: approximately 2,000 when using photographs obtained from the Line-Transect surveys as one of the samples. Comparison of the results from the two methods provides validation, as well as insight into potential biases associated with each method.
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abundance of blue and humpback whales in the eastern north pacific estimated by capture recapture and Line Transect methods
Marine Mammal Science, 2004Co-Authors: John Calambokidis, Jay BarlowAbstract:We estimated humpback and blue whale abundance from 1991 to 1997 off the west coast of the U.S. and Mexico comparing capture-recapture models based on photographically identified animals and Line-Transect methods from ship-based surveys. During photo-identification research we obtained 4,212 identifications of 824 humpback whales and 2,403 identifications of 908 blue whales primarily through non-systematic small-boat surveys along the coast of California, Oregon, and Washington. Line-Transect surveys from NOAA ships in 1991, 1993, and 1996 covered approximately 39,000 km along the coast of Baja California, California, Oregon, and Washington out to 555 km from shore. The nearshore and clumped distribution of humpback whales allowed photographic identification from small boats to cost-effectively sample a substantial portion of the population, but made it difficult to obtain effective samples in the Line-Transect surveys covering broad areas. The humpback capture-recapture estimates indicated humpback whale abundance increased over the six years (from 569 to 837). The broader more offshore distribution of blue whales made it harder to obtain a representative sample of identification photographs, but was well suited to the Line-Transect estimates. The Line-Transect estimates, after correction for missed animals, indicated approximately 3,000 blue whales (CV ¼ 0.14). Capture-recapture estimates of blue whales were lower than this: approximately 2,000 when using photographs obtained from the Line-Transect surveys as one of the samples. Comparison of the results from the two methods provides validation, as well as insight into potential biases associated with each method.
Len Thomas - One of the best experts on this subject based on the ideXlab platform.
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The effect of animal movement on Line Transect estimates of abundance.
PloS one, 2015Co-Authors: Richard Glennie, Stephen T. Buckland, Len ThomasAbstract:Line Transect sampling is a distance sampling method for estimating the abundance of wild animal populations. One key assumption of this method is that all animals are detected at their initial location. Animal movement independent of the Transect and observer can thus cause substantial bias. We present an analytic expression for this bias when detection within the Transect is certain (strip Transect sampling) and use simulation to quantify bias when detection falls off with distance from the Line (Line Transect sampling). We also explore the non-Linear relationship between bias, detection, and animal movement by varying detectability and movement type. We consider animals that move in randomly orientated straight Lines, which provides an upper bound on bias, and animals that are constrained to a home range of random radius. We find that bias is reduced when animal movement is constrained, and bias is considerably smaller in Line Transect sampling than strip Transect sampling provided that mean animal speed is less than observer speed. By contrast, when mean animal speed exceeds observer speed the bias in Line Transect sampling becomes comparable with, and may exceed, that of strip Transect sampling. Bias from independent animal movement is reduced by the observer searching further perpendicular to the Transect, searching a shorter distance ahead and by ignoring animals that may overtake the observer from behind. However, when animals move in response to the observer, the standard practice of searching further ahead should continue as the bias from responsive movement is often greater than that from independent movement.
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Design and analysis of Line Transect surveys for primates
International Journal of Primatology, 2010Co-Authors: Stephen T. Buckland, Len Thomas, Andrew J. Plumptre, Eric RexstadAbstract:Line Transect surveys are widely used for estimating abundance of primate populations. The method relies on a small number of key assumptions, and if these are not met, substantial bias may occur. For a variety of reasons, primate surveys often do not follow what is generally considered to be best practice, either in survey design or in analysis. The design often comprises too few Lines (sometimes just 1), subjectively placed or placed along trails, so lacks both randomization and adequate replication. Analysis often involves flawed or inefficient models, and often uses biased estimates of the locations of primate groups relative to the Line. We outLine the standard method, emphasizing the assumptions underlying the approach. We then consider options for when it is difficult or impossible to meet key assumptions. We explore the performance of these options by simulation, focusing particularly on the analysis of primate group sizes, where many of the variations in survey methods have been developed. We also discuss design issues, field methods, analysis, and potential alternative methodologies for when standard Line Transect sampling cannot deliver reliable abundance estimates.
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Line Transect Sampling of Primates: Can Animal-to-Observer Distance Methods Work?
International Journal of Primatology, 2010Co-Authors: Stephen T. Buckland, Len Thomas, Andrew J. Plumptre, Eric RexstadAbstract:Line Transect sampling is widely used for estimating abundance of primate populations. Researchers commonly use animal-to-observer distances (AODs) in analysis, in preference to perpendicular distances from the Line, which is in marked contrast with standard practice for other applications of Line Transect sampling. We formalize the mathematical shortcomings of approaches based on AODs, and show that they are likely to give strongly biased estimates of density. We review papers that claim good performance for the method, and explore this performance through simulations. These confirm strong bias in estimates of density using AODs. We conclude that AOD methods are conceptually flawed, and that they cannot in general provide valid estimates of density.
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field trials of Line Transect methods applied to estimation of desert tortoise abundance
Journal of Wildlife Management, 2001Co-Authors: David R. Anderson, Bruce C Lubow, Philip A Medica, Paul Stephen Corn, Len Thomas, Kenneth P Burnham, Ronald W MarlowAbstract:We examine the degree to which field observers can meet the assumptions underlying Line Transect sampling to monitor populations of desert tortoises (Gopherus agassizii). We present the results of 2 field trials using artificial tortoise models in 3 size classes. The trials were conducted on 2 occasions on an area south of Las Vegas, Nevada, where the density of the test population was known. In the first trials, conducted largely by experienced biologists who had been involved in tortoise surveys for many years, the density of adult tortoise models was well estimated (-3.9% bias), while the bias was higher (-20%) for subadult tortoise models. The bias for combined data was -12.0%. The bias was largely attributed to the failure to detect all tortoise models on or near the Transect centerLine. The second trials were conducted with a group of largely inexperienced student volunteers and used somewhat different searching methods, and the results were similar to the first trials. Estimated combined density of subadult and adult tortoise models had a negative bias (-7.3%), again attributable to failure to detect some models on or near the centerLine. Experience in desert tortoise biology, either comparing the first and second trials or in the second trial with 2 experienced biologists versus 16 novices, did not have an apparent effect on the quality of the data or the accuracy of the estimates. Observer training, specific to Line Transect sampling, and field testing are important components of a reliable survey. Line Transect sampling represents a viable method for large-scale monitoring of populations of desert tortoise; however, field protocol must be improved to assure the key assumptions are met.
Eric Rexstad - One of the best experts on this subject based on the ideXlab platform.
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Design and analysis of Line Transect surveys for primates
International Journal of Primatology, 2010Co-Authors: Stephen T. Buckland, Len Thomas, Andrew J. Plumptre, Eric RexstadAbstract:Line Transect surveys are widely used for estimating abundance of primate populations. The method relies on a small number of key assumptions, and if these are not met, substantial bias may occur. For a variety of reasons, primate surveys often do not follow what is generally considered to be best practice, either in survey design or in analysis. The design often comprises too few Lines (sometimes just 1), subjectively placed or placed along trails, so lacks both randomization and adequate replication. Analysis often involves flawed or inefficient models, and often uses biased estimates of the locations of primate groups relative to the Line. We outLine the standard method, emphasizing the assumptions underlying the approach. We then consider options for when it is difficult or impossible to meet key assumptions. We explore the performance of these options by simulation, focusing particularly on the analysis of primate group sizes, where many of the variations in survey methods have been developed. We also discuss design issues, field methods, analysis, and potential alternative methodologies for when standard Line Transect sampling cannot deliver reliable abundance estimates.
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Line Transect Sampling of Primates: Can Animal-to-Observer Distance Methods Work?
International Journal of Primatology, 2010Co-Authors: Stephen T. Buckland, Len Thomas, Andrew J. Plumptre, Eric RexstadAbstract:Line Transect sampling is widely used for estimating abundance of primate populations. Researchers commonly use animal-to-observer distances (AODs) in analysis, in preference to perpendicular distances from the Line, which is in marked contrast with standard practice for other applications of Line Transect sampling. We formalize the mathematical shortcomings of approaches based on AODs, and show that they are likely to give strongly biased estimates of density. We review papers that claim good performance for the method, and explore this performance through simulations. These confirm strong bias in estimates of density using AODs. We conclude that AOD methods are conceptually flawed, and that they cannot in general provide valid estimates of density.
Omar Eidous - One of the best experts on this subject based on the ideXlab platform.
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A bias-corrected histogram estimator for Line Transect sampling
Communications in Statistics - Theory and Methods, 2018Co-Authors: Omar Eidous, Fahid Al-eiboodAbstract:ABSTRACTThe classical histogram method has already been applied in Line Transect sampling to estimate the parameter f(0), which in turns is used to estimate the population abundance D or the popula...
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A Weighted Exponential Model for Grouped Line Transect Data
Mathematics and Statistics, 2017Co-Authors: Fahid Al-eibood, Omar EidousAbstract:This paper considers a parametric model for grouped data collected via Line Transect technique. The weighted exponential model is studied and investigated when the data are assumed to be grouped in the intervals. The maximum likelihood method is adopted for purpose of estimation. The resultant estimator of the population abundance is compared with the corresponding estimator that developed for ungrouped data by using the Laake stakes real data.
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Double Kernel Method Using Line Transect Sampling
Austrian Journal of Statistics, 2016Co-Authors: Omar Eidous, Mohammed K. ShakhatrehAbstract:A double kernel method as an alternative to the classical kernel method is proposed to estimate the population abundance by using Line Transect sampling. The proposed method produces an estimator that is essentially a kernel type of estimator use the kernel estimator twice to improve the performances of the classical kernel estimator. The feasibility of using bootstrap techniques to estimate the bias and variance of the proposed estimator is also addressed. Some numerical examples based on simulated and real data are presented. The results show that the proposed estimator outperforms existing classical kernel estimator in most considered cases.
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A Weighted Half-Normal Model for Line Transect Sampling
International Journal of Mathematics and Statistics, 2016Co-Authors: Omar Eidous, Fahid Al-eiboodAbstract:A weighted half-normal model is suggested to fit the data collected via Line Transect technique. The proposed model is appealing since it satisfies the standard assumptions of any reliable model in the scope of Line Transect technique. It is monotonically decreasing and it has a shoulder at the origin. The estimators of the population abundance that derived under the model were compared with some existing parametric estimators. The simulation results demonstrate the good performances of these estimators over the existing ones in many considered cases.
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a new kernel estimator for abundance using Line Transect sampling without the shoulder condition
Journal of The Korean Statistical Society, 2012Co-Authors: Omar EidousAbstract:Abstract Estimation of the parameter f ( 0 ) (the probability density function at the left boundary x = 0 ) is the key problem in Line Transect sampling to estimate the population abundance, D . The usual reflection kernel method is specially designed to estimate f ( 0 ) under the assumption that f ( 1 ) ( 0 ) = 0 , the first derivative of the probability density function at x = 0 is zero. This assumption is known as the shoulder condition assumption in Line Transect sampling. This paper suggests a new adaptive version of the reflection kernel method to estimate f ( 0 ) when f ( 1 ) ( 0 ) ≠ 0 . The proposed method produces a class of estimators for f ( 0 ) which are as simple and interpretable as the usual reflection kernel estimator, while holding theoretical and practical advantages. The asymptotic properties of the proposed estimator are derived, and some important special cases of this estimator are investigated and studied. Theoretical and practical results show the good potential properties of the proposed estimator over the boundary kernel estimator.