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Capture Probabilities (capture + probability)
Selected AbstractsCapture,Recapture When Time and Behavioral Response Affect Capture ProbabilitiesBIOMETRICS, Issue 2 2000Anne Chao Summary. We consider a capture,recapture model in which capture probabilities vary with time and with behavioral response. Two inference procedures are developed under the assumption that recapture probabilities bear a constant relationship to initial capture probabilities. These two procedures are the maximum likelihood method (both unconditional and conditional types are discussed) and an approach based on optimal estimating functions. The population size estimators derived from the two procedures are shown to be asymptotically equivalent when population size is large enough. The performance and relative merits of various population size estimators for finite cases are discussed. The bootstrap method is suggested for constructing a variance estimator and confidence interval. An example of the deer mouse analyzed in Otis et al. (1978, Wildlife Monographs62, 93) is given for illustration. [source] Empirical comparison of density estimators for large carnivoresJOURNAL OF APPLIED ECOLOGY, Issue 1 2010Martyn E. Obbard Summary 1. Population density is a critical ecological parameter informing effective wildlife management and conservation decisions. Density is often estimated by dividing capture,recapture (C,R) estimates of abundance () by size of the study area, but this relies on the assumption of geographic closure , a situation rarely achieved in studies of large carnivores. For geographically open populations is overestimated relative to the size of the study area because animals with only part of their home range on the study area are available for capture. This bias (,edge effect') is more severe when animals such as large carnivores range widely. To compensate for edge effect, a boundary strip around the trap array is commonly included when estimating the effective trap area (). Various methods for estimating the width of the boundary strip are proposed, but / estimates of large carnivore density are generally mistrusted unless concurrent telemetry data are available to define. Remote sampling by cameras or hair snags may reduce study costs and duration, yet without telemetry data inflated density estimates remain problematic. 2. We evaluated recently developed spatially explicit capture,recapture (SECR) models using data from a common large carnivore, the American black bear Ursus americanus, obtained by remote sampling of 11 geographically open populations. These models permit direct estimation of population density from C,R data without assuming geographic closure. We compared estimates derived using this approach to those derived using conventional approaches that estimate density as /. 3. Spatially explicit C,R estimates were 20,200% lower than densities estimated as /. AICc supported individual heterogeneity in capture probabilities and home range sizes. Variable home range size could not be accounted for when estimating density as /. 4.Synthesis and applications. We conclude that the higher densities estimated as / compared to estimates from SECR models are consistent with positive bias due to edge effects in the former. Inflated density estimates could lead to management decisions placing threatened or endangered large carnivores at greater risk. Such decisions could be avoided by estimating density by SECR when bias due to geographic closure violation cannot be minimized by study design. [source] CAPTURE-RECAPTURE ESTIMATES OF HECTOR'S DOLPHIN ABUNDANCE AT BANKS PENINSULA, NEW ZEALANDMARINE MAMMAL SCIENCE, Issue 2 2005Andrew M. Gormley Abstract Capture-recapture techniques have been extensively used to estimate survival rates of Hector's dolphins at Banks Peninsula, but not abundance. We analyzed nine seasons of photo-identification data using a model-fitting approach in the computer program MARK, and then used MARK's estimates of capture probabilities to calculate the abundance of distinctive individuals. We extrapolated these estimates to include unmarked individuals using five seasons of data on the proportion of identifiable individuals in this population, obtained from "random photography." This capture-recapture approach suggests a 1996 population of about 1,100 (CV = 0.21). This is very similar to the 1997 line-transect estimate of about 900 (CV = 0.28), especially considering that the two techniques do not necessarily measure the same thing. An important advantage of the capture-recapture approach stems from the inherent versatility of photo-ID data. If the sampling design is appropriate, an unbiased abundance estimate can be achieved as a spin-off from work directed at other questions. However, in our view, line-transect estimates are easier to interpret because the sampling design is explicit. [source] PHOTOGRAPHIC IDENTIFICATION OF NORTHERN BOTTLENOSE WHALES (HYPEROODON AMPULLATUS): SOURCES OF HETEROGENEITY FROM NATURAL MARKSMARINE MAMMAL SCIENCE, Issue 1 2001Shannon Gowans Abstract The use of natural marks in capture-recapture studies can lead to unequal capture probabilities. This paper examined a catalog of northern bottlenose whale (Hyperoodon ampullatus) photographs from the Gully, Nova Scotia, to identify potential sources of heterogeneity. This information can be used to select appropriate individuals and photographs to include in analyses. Individual northern bottlenose whales were sufficiently marked to uniquely identify individuals (x,= 14.5 marks/individual; range 1-67), but not all mark types persisted over time. Reliable marks were defined as mark types that were not lost over the nine-yeat study period (notches, back indentation, and mottled patches). Individuals were considered reliably marked if they possessed at least one back indentation or mottled patch (located within one dorsal fin width, at the base of the dorsal fin) or a notch on the dorsal fin. Sixty-six percent (SE = 5%) of the population were reliably marked. Longterm analyses (months to years) should use only reliably marked individuals, and the results scaled to account for the rest of the population. Our results also showed that photographic quality affected an observer's ability to identify individuals. For this catalog, quantitative analysis indicated only photographs of Q , 4 (on a 6-point scale with 6 representing the highest quality) should be included in mark-recapture analyses sensitive to heterogeneity. [source] A new method for estimating the size of small populations from genetic mark,recapture dataMOLECULAR ECOLOGY, Issue 7 2005CRAIG R. MILLER Abstract The use of non-invasive genetic sampling to estimate population size in elusive or rare species is increasing. The data generated from this sampling differ from traditional mark,recapture data in that individuals may be captured multiple times within a session or there may only be a single sampling event. To accommodate this type of data, we develop a method, named capwire, based on a simple urn model containing individuals of two capture probabilities. The method is evaluated using simulations of an urn and of a more biologically realistic system where individuals occupy space, and display heterogeneous movement and DNA deposition patterns. We also analyse a small number of real data sets. The results indicate that when the data contain capture heterogeneity the method provides estimates with small bias and good coverage, along with high accuracy and precision. Performance is not as consistent when capture rates are homogeneous and when dealing with populations substantially larger than 100. For the few real data sets where N is approximately known, capwire's estimates are very good. We compare capwire's performance to commonly used rarefaction methods and to two heterogeneity estimators in program capture: Mh -Chao and Mh -jackknife. No method works best in all situations. While less precise, the Chao estimator is very robust. We also examine how large samples should be to achieve a given level of accuracy using capwire. We conclude that capwire provides an improved way to estimate N for some DNA-based data sets. Capwire is available at http://www.cnr.uidaho.edu/lecg/. [source] Using Mixtures to Model Heterogeneity in Ecological Capture-Recapture StudiesBIOMETRICAL JOURNAL, Issue 6 2008Shirley Pledger Abstract Modelling heterogeneity of capture is an important problem in estimating animal abundance from capturerecapture data, with underestimation of abundance occurring if different animals have intrinsically high or low capture probabilities. Mixture models are useful in many cases to model the heterogeneity. We summarise mixture model results for closed populations, using a skink data set for illustration. New mixture models for heterogeneous open populations are discussed, and a closed population model is shown to have new and potentially effective applications in community analysis. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Capture,Recapture Estimation Using Finite Mixtures of Arbitrary DimensionBIOMETRICS, Issue 2 2010Richard Arnold Summary Reversible jump Markov chain Monte Carlo (RJMCMC) methods are used to fit Bayesian capture,recapture models incorporating heterogeneity in individuals and samples. Heterogeneity in capture probabilities comes from finite mixtures and/or fixed sample effects allowing for interactions. Estimation by RJMCMC allows automatic model selection and/or model averaging. Priors on the parameters stabilize the estimates and produce realistic credible intervals for population size for overparameterized models, in contrast to likelihood-based methods. To demonstrate the approach we analyze the standard Snowshoe hare and Cottontail rabbit data sets from ecology, a reliability testing data set. [source] Applications and Extensions of Chao's Moment Estimator for the Size of a Closed PopulationBIOMETRICS, Issue 4 2007Louis-Paul Rivest Summary This article revisits Chao's (1989, Biometrics45, 427,438) lower bound estimator for the size of a closed population in a mark,recapture experiment where the capture probabilities vary between animals (model Mh). First, an extension of the lower bound to models featuring a time effect and heterogeneity in capture probabilities (Mth) is proposed. The biases of these lower bounds are shown to be a function of the heterogeneity parameter for several loglinear models for Mth. Small-sample bias reduction techniques for Chao's lower bound estimator are also derived. The application of the loglinear model underlying Chao's estimator when heterogeneity has been detected in the primary periods of a robust design is then investigated. A test for the null hypothesis that Chao's loglinear model provides unbiased abundance estimators is provided. The strategy of systematically using Chao's loglinear model in the primary periods of a robust design where heterogeneity has been detected is investigated in a Monte Carlo experiment. Its impact on the estimation of the population sizes and of the survival rates is evaluated in a Monte Carlo experiment. [source] A Multiple-Record Systems Estimation Method that Takes Observed and Unobserved Heterogeneity into AccountBIOMETRICS, Issue 2 2004Elena Stanghellini Summary. We present a model to estimate the size of an unknown population from a number of lists that applies when the assumptions of (a) homogeneity of capture probabilities of individuals and (b) marginal independence of lists are violated. This situation typically occurs in epidemiological studies, where the heterogeneity of individuals is severe and researchers cannot control the independence between sources of ascertainment. We discuss the situation when categorical covariates are available and the interest is not only in the total undercount, but also in the undercount within each stratum resulting from the cross-classification of the covariates. We also present several techniques for determining confidence intervals of the undercount within each stratum using the profile log likelihood, thereby extending the work of Cormack (1992, Biometrics48, 567,576). [source] Survival of Bowhead Whales, Balaena mysticetus, Estimated from 1981,1998 Photoidentification DataBIOMETRICS, Issue 4 2002Judith Zeh Summary. Annual survival probability of bowhead whales, Balaena mysticetus, was estimated using both Bayesian and maximum likelihood implementations of Cormack and Jolly-Seber (JS) models for capture-recapture estimation in open populations and reduced-parameter generalizations of these models. Aerial photographs of naturally marked bowheads collected between 1981 and 1998 provided the data. The marked whales first photographed in a particular year provided the initial ,capture' and ,release' of those marked whales and photographs in subsequent years the ,recaptures'. The Cormack model, often called the Cormack-Jolly-Seber (CJS) model, and the program MARK were used to identify the model with a single survival and time-varying capture probabilities as the most appropriate for these data. When survival was constrained to be one or less, the maximum likelihood estimate computed by MARK was one, invalidating confidence interval computations based on the asymptotic standard error or profile likelihood. A Bayesian Markov chain Monte Carlo (MCMC) implementation of the model was used to produce a posterior distribution for annual survival. The corresponding reduced-parameter JS model was also fit via MCMC because it is the more appropriate of the two models for these photoidentification data. Because the CJS model ignores much of the information on capture probabilities provided by the data, its results are less precise and more sensitive to the prior distributions used than results from the JS model. With priors for annual survival and capture probabilities uniform from 0 to 1, the posterior mean for bowhead survival rate from the JS model is 0.984, and 95% of the posterior probability lies between 0.948 and 1. This high estimated survival rate is consistent with other bowhead life history data. [source] Capture,Recapture When Time and Behavioral Response Affect Capture ProbabilitiesBIOMETRICS, Issue 2 2000Anne Chao Summary. We consider a capture,recapture model in which capture probabilities vary with time and with behavioral response. Two inference procedures are developed under the assumption that recapture probabilities bear a constant relationship to initial capture probabilities. These two procedures are the maximum likelihood method (both unconditional and conditional types are discussed) and an approach based on optimal estimating functions. The population size estimators derived from the two procedures are shown to be asymptotically equivalent when population size is large enough. The performance and relative merits of various population size estimators for finite cases are discussed. The bootstrap method is suggested for constructing a variance estimator and confidence interval. An example of the deer mouse analyzed in Otis et al. (1978, Wildlife Monographs62, 93) is given for illustration. [source] Population Ecology of the Riparian Frog Eleutherodactylus cuneatus in CubaBIOTROPICA, Issue 3 2010Ansel Fong G. ABSTRACT A population of the poorly known riparian frog Eleutherodactylus cuneatus was studied for 1 yr along a mountain stream in eastern Cuba. We examined population structure, seasonal and daily activity, growth, and habitat use using mark-recapture and call-point counts. Juveniles were observed during all survey periods with a spike in March. Higher numbers of adults were present in May,July, associated with longer day length, warmer temperatures, and the onset of the rainy season. This was coincident with higher calling activity away from the stream, suggesting an increase in both reproductive and nonreproductive activity in the warmer months between May and September. The number of individuals peaked at 2000,2200 h, but high numbers of individuals were visible throughout the night. Lower activity levels were observed throughout the day. Population size estimates were 84,131 adults and 124,304 juveniles, with averages of 110 and 236 individuals, survival rates were high but capture probabilities were low for a 5-d period in March 2004. Growth rate was negatively related to the size of recaptured individuals, although decreases in growth rate were slight. Frogs were found either in the water (49.7%), or in the banks and on the ground adjacent to the stream where most individuals were found on the ground under the cover of rocks, leaf litter, or large palm fronds. These results provide baseline knowledge of E. cuneatus population dynamics and ecology needed for a rapid detection of any decline this population may undergo in the future. Abstract in Spanish is available at http://www.blackwell-synergy.com/loi/btp [source] Cover Picture: Fabrication of Multicomponent Microsystems by Directed Three-Dimensional Self-Assembly (Adv. Funct.ADVANCED FUNCTIONAL MATERIALS, Issue 5 2005Mater. Abstract Directed three-dimensional self-assembly to assemble and package integrated semiconductor devices is demonstrated by Jacobs and Zheng on p.,732. The self-assembly process uses geometrical shape recognition to identify different components and surface-tension between liquid solder and metal-coated areas to form mechanical and electrical connections. The components (top left) self-assemble in a turbulent flow (center) and form functional multi-component microsystems (bottom right) by sequentially adding parts to the assembly solution. The technique provides, for the first time, a route to enable the realization of three-dimensional heterogeneous microsystems that contain non-identical parts, and connecting them electrically. We have developed a directed self-assembly process for the fabrication of three-dimensional (3D) microsystems that contain non-identical parts and a statistical model that relates the process yield to the process parameters. The self-assembly process uses geometric-shape recognition to identify different components, and surface tension between liquid solder and metal-coated areas to form mechanical and electrical connections. The concept is used to realize self-packaging microsystems that contain non-identical subunits. To enable the realization of microsystems that contain more than two non-identical subunits, sequential self-assembly is introduced, a process that is similar to the formation of heterodimers, heterotrimers, and higher aggregates found in nature, chemistry, and chemical biology. The self-assembly of three-component assemblies is demonstrated by sequentially adding device segments to the assembly solution including two hundred micrometer-sized light-emitting diodes (LEDs) and complementary metal oxide semiconductor (CMOS) integrated circuits. Six hundred AlGaInP/GaAs LED segments self-assembled onto device carriers in two minutes, without defects, and encapsulation units self-assembled onto the LED-carrier assemblies to form a 3D circuit path to operate the final device. The self-assembly process is a well-defined statistical process. The process follows a first-order, non-linear differential equation. The presented model relates the progression of the self-assembly and yield with the process parameters,component population and capture probability,that are defined by the agitation and the component design. [source] Testing assumptions of mark,recapture theory in the coral reef fish Lutjanus apodusJOURNAL OF FISH BIOLOGY, Issue 3 2008C. L. Wormald This study tested assumptions of the Cormack,Jolly,Seber capture,mark,recapture (CMR) model in a population of the tropical snapper Lutjanus apodus in the central Bahamas using a combination of laboratory and field studies. The suitability of three different tag types [passive integrated transponder (PIT) tag, T-anchor tag and fluorescent dye jet-injected into the fins] was assessed. PIT tags were retained well, whereas T-anchor tags and jet-injected dye were not. PIT tags had no detectable effect on the rates of growth or survival of individuals. The capture method (fish trapping) was found to provide a representative sample of the population; however, a positive trap response was identified and therefore the assumption of equal capture probability was violated. This study illustrates an approach that can be used to test some of the critical assumptions of the CMR theory and it demonstrates that CMR methods can provide unbiased estimates of growth and mortality of L. apodus provided that trap response is explicitly modelled when estimating survival probability. [source] ESTIMATION IN RICKER'S TWO-RELEASE METHOD: A BAYESIAN APPROACHAUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 2 2006Shen-Ming Lee Summary The Ricker's two-release method is a simplified version of the Jolly-Seber method, from Seber's Estimation of Animal Abundance (1982), used to estimate survival rate and abundance in animal populations. This method assumes there is only a single recapture sample and no immigration, emigration or recruitment. In this paper, we propose a Bayesian analysis for this method to estimate the survival rate and the capture probability, employing Markov chain Monte Carlo methods and a latent variable analysis. The performance of the proposed method is illustrated with a simulation study as well as a real data set. The results show that the proposed method provides favourable inference for the survival rate when compared with the modified maximum likelihood method. [source] Estimation of Rates of Births, Deaths, and Immigration from Mark,Recapture DataBIOMETRICS, Issue 1 2009R. B. O'Hara Summary The analysis of mark,recapture data is undergoing a period of development and expansion. Here we contribute to that by presenting a model which includes both births and immigration, as well as the usual deaths. Data come from a long-term study of the willow tit (Parus montanus), where we can assume that all births are recorded, and hence immigrants can also be identified as birds captured as adults for the first time. We model the rates of immigration, birth rate per parent, and death rates of juveniles and adults. Using a hierarchical model allows us to incorporate annual variation in these parameters. The model is fitted to the data using Markov chain Monte Carlo, as a Bayesian analysis. In addition to the model fitting, we also check several aspects of the model fit, in particular whether survival varies with age or immigrant status, and whether capture probability is affected by previous capture history. The latter check is important, as independence of capture histories is a key assumption that simplifies the model considerably. Here we find that the capture probability depends strongly on whether the individual was captured in the previous year. [source] | |||||||||||||