The effect of electric fishing on the subsequent capture of fish*

Experiments show that the first of a series of replicate electric fishings can cause a decrease in catchability so that the second and subsequent catches are made from what is, effectively, a reduced population. Depletion (DeLury) estimates can be thus seriously low. Species affected are roach Rutilus rutilus (L.), gudgeon Gobio gobio (L.), rudd Scardinius erythophthalmus (L.) and, from other published data, probably rainbow trout Salmo gairdneri Richardson and eels Anguilla anguilla (L.). Being caught does not, apparently, cause fish to become less catchable. The reason why an electric field causes a proportion of a population to become uncatchable is obscure but it may be that refractory behaviour is involved; the effect lasts for between 3 and 24 h. A method is given for adjusting DeLury estimates for decreased catchability.     

Modeling association among demographic parameters in analysis of open population capture-recapture data

We present a hierarchical extension of the Cormack-Jolly-Seber (CJS) model for open population capture-recapture data. In addition to recaptures of marked animals, we model first captures of animals and losses on capture. The parameter set includes capture probabilities, survival rates, and birth rates. The survival rates and birth rates are treated as a random sample from a bivariate distribution, thus the model explicitly incorporates correlation in these demographic rates. A key feature of the model is that the likelihood function, which includes a CJS model factor, is expressed entirely in terms of identifiable parameters; losses on capture can be factored out of the model. Since the computational complexity of classical likelihood methods is prohibitive, we use Markov chain Monte Carlo in a Bayesian analysis. We describe an efficient candidate-generation scheme for Metropolis-Hastings sampling of CJS models and extensions. The procedure is illustrated using mark-recapture data for the moth Gonodontis bidentata.     

Bayesian methods for multiple capture-recapture surveys

To estimate the total size of a closed population, a multiple capture-recapture sampling design can be used. This sampling design has been used traditionally to estimate the size of wildlife populations and is becoming more widely used to estimate the size of hard-to-count human populations. This paper presents Bayesian methods for obtaining point and interval estimates from data gathered from capture-recapture surveys. A numerical example involving the estimation of the size of a fish population is given to illustrate the methods.     

大中型兽类种群数量估算的研究进展

大中型兽类种群数量的估算是动物生态学中重要的基本问题, 受到研究者、管理者和公众的共同关注。国际上从20世纪中期开始研究该问题, 已出现了多种研究方法和相应案例, 且还在快速发展, 但世界各地仍有很多物种的种群数量尚未知晓。在我国, 从20世纪80年代开始调查大中型兽类种群数量, 取得了重要进展, 也还有很多物种的种群数量尚不清楚。因此, 有必要归纳国际上种群数量估算的研究进展, 同时, 总结国内研究的现状、优势和趋势, 供研究者参考。本文首先选择估算大中型兽类种群数量的原理、数据来源和模型这3个要素归纳出简明的研究框架, 将现有的多种方法置于其中予以阐述。在该框架下, 根据估算原理分为4大类方法, 为距离取样法、标志重捕法、基于遇见率法和遥感影像直接计数法。针对每一大类方法, 论述其基本原理模型和模型假设, 说明能实现该原理的相应数据来源(视觉观测、红外相机拍摄、DNA微卫星识别、卫星定位跟踪、声音监测或遥感影像)的特点及如何实现该原理, 评价其适用性及优缺点, 并选择其中具有可比性的方法予以比较评价。其次, 参照该研究框架, 总结我国的研究现状, 分析未来发展的优势和趋势: 我国的红外相机数据积累充分, 可以发展以此为数据源的距离取样法、标志重捕法和基于遇见率法; 发展以粪便样品为数据来源的距离取样法和粪便DNA标志重捕法; 相比地面调查数据, 获取高分辨率遥感影像数据更容易, 尽量以此估算符合适用条件的大中型兽类的种群数量。最后, 本文提出了适用于我国大中型兽类种群数量的估算方法的选择流程, 供研究者参考。     

昆虫种群密度的二项抽样估计模型研究进展

昆虫种群密度的二项抽样估计模型主要有两类,一类是根据空间分布型理论演绎而来,另一类是根据样方中有虫样方比例或不大于某一阈值密度T头的样方比例与平均密度的经验关系拟合的．本文综述了这两类模型、模型的变异分析、模型的理论抽样数估计等方面的研究进展．     

Review of capture-recapture methods applicable to noninvasive genetic sampling

The use of noninvasive genetic sampling to identify individual animals for capture-recapture studies has become widespread in the past decade. Strong emphasis has been placed on the field protocols and genetic analyses with fruitful results. Little attention has been paid to the capture-recapture application for this specific type of data beyond stating the effects of assumption violations. Here, we review the broad class of capture-recapture methods that are available for use with DNA-based capture-recapture data, noting the array of biologically interesting parameters such as survival, emigration rates, state transition rates and the finite rate of population change that can be estimated from such data. We highlight recent developments in capture-recapture theory specifically designed for noninvasive genetic sampling data.     

Median Ranked Set Sampling with Size Biased Probability of Selection

Median ranked set sampling may be combined with size biased probability of selection. A two-phase sample is assumed. In the first phase, units are selected with probability proportional to their size. In the second phase, units are selected using median ranked set sampling to increase the efficiency of the estimators relative to simple random sampling. There is also an increase in the efficiency relative to ranked set sampling (for some probability distribution functions). There will be a loss in efficiency depending on the amount of errors in ranking the units, the median ranked set sampling can be used to reduce the errors in ranking the units selected from the population. Estimators of the population mean and the population size are considered. The median ranked set sampling with probability proportion to size and with errors in ranking is considered and compared with ranked set sampling with errors in ranking. Computer simulation results for some probability distributions are also given.     

Smoothing population size estimates for time-stratified mark-recapture experiments using Bayesian P-splines

Petersen-type mark-recapture experiments are often used to estimate the number of fish or other animals in a population moving along a set migration route. A first sample of individuals is captured at one location, marked, and returned to the population. A second sample is then captured farther along the route, and inferences are derived from the numbers of marked and unmarked fish found in this second sample. Data from such experiments are often stratified by time (day or week) to allow for possible changes in the capture probabilities, and previous methods of analysis fail to take advantage of the temporal relationships in the stratified data. We present a Bayesian, semiparametric method that explicitly models the expected number of fish in each stratum as a smooth function of time. Results from the analysis of historical data from the migration of young Atlantic salmon (Salmo salar) along the Conne River, Newfoundland, and from a simulation study indicate that the new method provides more precise estimates of the population size and more accurate estimates of uncertainty than the currently available methods.     

Estimation of Finite and Closed Population Size: An Inverse Sampling Approach with Unequal Recapture Probability

Based on capture-mark-recapture sampling methods the problem of estimating unknown population size was considered. The sampling started with the assumption that at the beginning of the experiment all the individuals were unmarked, and the unmarked individuals caught in each sample will be marked and returned to the original population before the next sample is drawn. It is also assumed that the population is closed by birth, death, emigration and immigration. Using a general inverse sampling approach, the unknown population size N is estimated by a maximum likelihood estimator (MLE), and a simple form for approximate MLE is obtained. The probability function for S (the minimum number of samples required to be drawn to have L (L ≥ 1) samples, each of which contains at least one marked individual) and the form for E[S] are also obtained. In addition, corrections and improvements of some previous works in this field are given.     

A simulation study of how simple mark-recapture methods can be combined with destructive subsampling to facilitate surveys of flying insects

Mark-recapture techniques are used for studies of animal populations. With only three sampling occasions, both Bailey's triple-catch (BTC) and Jolly-Seber's (J-S) stochastic method can be applied. As marking and handling of fragile organisms may harm them, and thereby affect their chances of being recaptured, handling should be minimized. This can be achieved by taking a subsample before the main sample at the second sampling occasion. Individuals in the main sample are marked and released, whereas those in the subsample are only used for identifying recaptures. Monte-Carlo simulation was used to compare the subsampling method with the ordinary mark-recapture methods. Model-generated populations were sampled with and without subsampling to provide estimates of population size, loss, and dilution rates. The estimated parameters were compared with their true values to identify biases associated with the sampling methods, using 81 different combinations of population size, dilution rate, loss rate, and sampling effort. Each combination was replicated 1,000 times. In no cases did subsampling perform more poorly than the ordinary methods. J-S was slightly more accurate than BTC to estimate the population size, but only when sampling effort was high. The relative biases associated with estimates of dilution and loss rates were substantial, but declined with increasing population size and sampling effort. Confidence limits for the population parameters generally were reliable and tended to be conservative. We therefore conclude that ordinary mark-recapture methods can be supplemented with subsampling without sacrificing accuracy. Subsampling is especially advantageous in cases where marks are difficult to observe under field conditions.     

Density estimates of two endangered nocturnal lemur species from northern Madagascar: new results and a comparison of commonly used methods

Very little information is known of the recently described Microcebus tavaratra and Lepilemur milanoii in the Daraina region, a restricted area in far northern Madagascar. Since their forest habitat is highly fragmented and expected to undergo significant changes in the future, rapid surveys are essential to determine conservation priorities. Using both distance sampling and capture-recapture methods, we estimated population densities in two forest fragments. Our results are the first known density and population size estimates for both nocturnal species. In parallel, we compare density results from four different approaches, which are widely used to estimate lemur densities and population sizes throughout Madagascar. Four approaches (King, Kelker, Muller and Buckland) are based on transect surveys and distance sampling, and they differ from each other by the way the effective strip width is estimated. The fifth method relies on a capture-mark-recapture (CMR) approach. Overall, we found that the King method produced density estimates that were significantly higher than other methods, suggesting that it generates overestimates and hence overly optimistic estimates of population sizes in endangered species. The other three distance sampling methods provided similar estimates. These estimates were similar to those obtained with the CMR approach when enough recapture data were available. Given that Microcebus species are often trapped for genetic or behavioral studies, our results suggest that existing data can be used to provide estimates of population density for that species across Madagascar.     

Estimating Population Size for Continuous-Time Capture-Recapture Models Via Sample Coverage

An estimation procedure using the idea of sample coverage is proposed to estimate population size for capture-recapture experiments in continuous time. The capture rates (intensity) are allowed to vary by time and individuals (heterogeneity). Only capture frequency history are sufficient for estimating population size while capture times and sequential orders of animals caught are irrelevant for the analysis. An example is given for illustration. The performance of the proposed estimation procedure is also investigated by simulation.     

Non-invasive genetic monitoring of wild central chimpanzees

Background

An assessment of population size and structure is an important first step in devising conservation and management plans for endangered species. Many threatened animals are elusive, rare and live in habitats that prohibit directly counting individuals. For example, a well-founded estimate of the number of great apes currently living in the wild is lacking. Developing methods to obtain accurate population estimates for these species is a priority for their conservation management. Genotyping non-invasively collected faecal samples is an effective way of evaluating a species'' population size without disruption, and can also reveal details concerning population structure.

Methodology/Principal Findings

We opportunistically collected wild chimpanzee faecal samples for genetic capture-recapture analyses over a four-year period in a 132 km² area of Loango National Park, Gabon. Of the 444 samples, 46% yielded sufficient quantities of DNA for genotyping analysis and the consequent identification of 121 individuals. Using genetic capture-recapture, we estimate that 283 chimpanzees (range: 208–316) inhabited the research area between February 2005 and July 2008. Since chimpanzee males are patrilocal and territorial, we genotyped samples from males using variable Y-chromosome microsatellite markers and could infer that seven chimpanzee groups are present in the area. Genetic information, in combination with field data, also suggested the occurrence of repeated cases of intergroup violence and a probable group extinction.

Conclusions/Significance

The poor amplification success rate resulted in a limited number of recaptures and hence only moderate precision (38%, measured as the entire width of the 95% confidence interval), but this was still similar to the best results obtained using intensive nest count surveys of apes (40% to 63%). Genetic capture-recapture methods applied to apes can provide a considerable amount of novel information on chimpanzee population size and structure with minimal disturbance to the animals and represent a powerful complement to traditional field-based methods.     

Estimating population size for capture-recapture data when capture probabilities vary by time and individual animal.

There have been no estimators of population size associated with the capture-recapture model when the capture probabilities vary by time and individual animal. This work proposes a nonparametric estimation technique that is appropriate for such a model using the idea of sample coverage, which is defined as the proportion of the total individual capture probabilities of the captured animals. A simulation study was carried out to show the performance of the proposed estimation procedure. Numerical results indicate that it generally works satisfactorily when the coefficient of variation of the individual capture probabilities is relatively large. An example is also given for illustration.     

Jolly - Seber 法估算长爪沙鼠种群参数的适用性探讨

以2000 年6 月～10 月群居性长爪沙鼠野生种群的标志重捕资料为依据, 采用Jolly - Seber 模型估算了该鼠种群参数, 结果表明, 长爪沙鼠个体间具等捕性(Leslie 法检验) , 研究期间取样个体的重捕率平均为89.7 %(77.4 % ～ 100 %) ; 参数估计结果具有合理的生物学意义, 认为采用该模型估算长爪沙鼠种群参数是适用的。     

Markov Systematic Sampling

In this paper, a new systematic sampling scheme with Markovian behaviour which yields positive first order inclusion probabilities for all units and positive second order inclusion probabilities for all pairs of units is introduced. The suggested method has been compared with sample random sampling, stratified random sampling, linear systematic sampling and systematic sampling with two random starts for the populations exhibiting exponential trend, autocorrelatedness and randomness. Throughout the discussion, the sample size is assumed to be even and the population size is a multiple of the sample size. The suggested method works well for estimating a finite population total for the population exhibiting exponential trend.     

CAPTURE-RECAPTURE ESTIMATES OF HECTOR'S DOLPHIN ABUNDANCE AT BANKS PENINSULA, NEW ZEALAND

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.     

基于标记-重捕模型开展野生动物红外相机种群监测的方法及案例

红外相机技术的广泛应用推动了动物种群生态学研究方法的发展和革新, 特别是基于标记-重捕模型框架通过非损伤取样方式对物种数量和密度等种群参数的可靠估计, 为保护濒危物种和评估保护成效提供了有力的科学依据。对于身体上具有独特天然标记的动物(如多数猫科动物), 可依据红外相机拍摄身体上的独特斑点或条纹鉴别个体, 再运用标记-重捕模型, 估计动物种群数量、密度等参数。本文概述了标记-重捕模型的基本原理、特点以及国内外的应用, 特别是近年来发展出的空间标记-重捕模型。总结了从相机布设到数据分析的具体流程、操作原则, 并以青城山家猫为实例, 展示了应用红外相机数据通过空间标记-重捕模型估计种群密度和数量的基本步骤。最后展望了该模型在种群动态、景观廊道设计、资源选择等方面的应用和发展趋势。     

Improved procedures for estimation of disease prevalence using ranked set sampling

Ranked set sampling (RSS) is a sampling procedure that can be considerably more efficient than simple random sampling (SRS). When the variable of interest is binary, ranking of the sample observations can be implemented using the estimated probabilities of success obtained from a logistic regression model developed for the binary variable. The main objective of this study is to use substantial data sets to investigate the application of RSS to estimation of a proportion for a population that is different from the one that provides the logistic regression. Our results indicate that precision in estimation of a population proportion is improved through the use of logistic regression to carry out the RSS ranking and, hence, the sample size required to achieve a desired precision is reduced. Further, the choice and the distribution of covariates in the logistic regression model are not overly crucial for the performance of a balanced RSS procedure.