scholarly journals Bayesian Estimation of Population Size via Capture-Recapture Model with Time Variation and Behavioral Response

2015 ◽  
Vol 05 (01) ◽  
pp. 1-13
Author(s):  
Xiaoyin Wang ◽  
Zhuoqiong He ◽  
Dongchu Sun
Keyword(s):  
Bayesian Estimation ◽  
Population Size ◽  
Time Variation ◽  
Behavioral Response ◽  
Capture Recapture

Estimating the population size of people who inject drugs in Ho Chi Minh City, Vietnam: A two-survey capture-recapture exercise (Preprint)

2019 ◽  
Author(s):  
Abu Abdul-Quader
Keyword(s):  
Population Size ◽  
Illicit Drugs ◽  
People Who Inject Drugs ◽  
Care Service ◽  
Ho Chi Minh City ◽  
Size Estimation ◽  
Population Size Estimates ◽  
Capture Recapture ◽  
The City ◽  
Size Estimates

BACKGROUND Population size estimation of people who inject drugs (PWID) in Ho Chi Minh City (HCMC), Vietnam relied on the UNAIDS Estimation and Projection Package and reports from the city police department. The two estimates vary widely. OBJECTIVE To estimate the population size of people who inject drugs in Ho Chi Minh City, Vietnam METHODS Using Respondent-driven sampling (RDS), we implemented two-source capture-recapture method to estimate the population size of PWID in HCMC in 2017 in 7 out of 24 districts. The study included men or women aged at least 18 years who reported injecting illicit drugs in the last 90 days and who had lived in the city the past six months. We calculated two sets of size estimates, the first assumed that all participants in each survey round resided in the district where the survey was conducted, the second, used the district of residence as reported by the participant. District estimates were summed to obtain an aggregate estimate for the seven districts. To calculate the city total, we weighted the population size estimates for each district by the inverse of the stratum specific sampling probabilities. RESULTS The first estimate resulted in a population size of 19,155 (95% CI: 17,006–25,039). The second one generated a smaller population size estimate of 12,867 (95% CI: 11,312–17,393). CONCLUSIONS The two-survey capture-recapture exercise provided two disparate estimates of PWID in HCMC. For planning HIV prevention and care service needs among PWID in HCMC, both estimates may need to be taken into consideration together with size estimates from other sources.

scholarly journals The wildcat Felis silvestris in northern Turkey: assessment of status using camera trapping

Oryx ◽  
2011 ◽  
Vol 45 (1) ◽  
pp. 112-118 ◽  
Author(s):  
Özgün Emre Can ◽  
İrfan Kandemi̇r ◽  
İnci̇ Togan
Keyword(s):  
Population Size ◽  
Camera Traps ◽  
Sampling Effort ◽  
Felis Silvestris ◽  
Forest Patch ◽  
Western Turkey ◽  
Lack Of Information ◽  
The Status ◽  
Capture Recapture ◽  
Estimate Population Size

AbstractThe wildcat Felis silvestris is a protected species in Turkey but the lack of information on its status is an obstacle to conservation initiatives. To assess the status of the species we interviewed local forestry and wildlife personnel and conducted field surveys in selected sites in northern, eastern and western Turkey during 2000–2007. In January–May 2006 we surveyed for the wildcat using 16 passive infrared-trigged camera traps in Yaylacı k Research Forest, a 50-km2 forest patch in Yenice Forest in northern Turkey. A total sampling effort of 1,200 camera trap days over 40 km2 yielded photo-captures of eight individual wildcats over five sampling occasions. Using the software MARK to estimate population size the closed capture–recapture model M0, which assumes a constant capture probability among all occasions and individuals, best fitted the capture history data. The wildcat population size in Yaylacı k Research Forest was estimated to be 11 (confidence interval 9–23). Yenice Forest is probably one of the most important areas for the long-term conservation of the wildcat as it is the largest intact forest habitat in Turkey with little human presence, and without human settlements, and with a high diversity of prey species. However, it has been a major logging area and is not protected. The future of Yenice Forest and its wildcat population could be secured by granting this region a protection status and enforcing environmental legislation.

scholarly journals Estimation of a closed population size of tadpoles in temporary pond

2017 ◽  
Vol 78 (2) ◽  
pp. 328-336
Author(s):  
M. S. C. S. Lima ◽  
J. Pederassi ◽  
C. A. S. Souza
Keyword(s):  
Population Size ◽  
Bayes Theorem ◽  
Venn Diagram ◽  
Temporary Pond ◽  
Larval Phase ◽  
Closed Population ◽  
Lotic Environment ◽  
Capture Recapture ◽  
Kolmogorov Smirnov ◽  
Smirnov Test

Abstract The practice of capture-recapture to estimate the diversity is well known to many animal groups, however this practice in the larval phase of anuran amphibians is incipient. We aimed at evaluating the Lincoln estimator, Venn diagram and Bayes theorem in the inference of population size of a larval phase anurocenose from lotic environment. The adherence of results was evaluated using the Kolmogorov-Smirnov test. The marking of tadpoles for later recapture and methods measurement was made with eosin methylene blue. When comparing the results of Lincoln-Petersen estimator corresponding to the Venn diagram and Bayes theorem, we detected percentage differences per sampling, i.e., the proportion of sampled anuran genera is kept among the three methods, although the values are numerically different. By submitting these results to the Kolmogorov-Smirnov test we have found no significant differences. Therefore, no matter the estimator, the measured value is adherent and estimates the total population. Together with the marking methodology, which did not change the behavior of tadpoles, the present study helps to fill the need of more studies on larval phase of amphibians in Brazil, especially in semi-arid northeast.

The eastern horseshoe bat, Rhinolophus megaphyllus, in south-east Queensland, Australia: colony demography and dynamics, activity levels, seasonal weight changes, and capture-recapture analyses

2001 ◽  
Vol 28 (4) ◽  
pp. 425 ◽  
Author(s):  
R. A. Young
Keyword(s):  
Population Size ◽  
Colony Size ◽  
Activity Levels ◽  
Adult Males ◽  
Weight Changes ◽  
Adult Females ◽  
Colony Demography ◽  
Capture Recapture ◽  
Horseshoe Bat ◽  
Size Estimates

During this study, 634 eastern hoseshoe bats, Rhinolophus megaphyllus, were captured at three colonies in south-east Queensland, with most data coming from two colonies (Anjuramba mine and Ravensbourne cave). Colony size, sex ratios, age structure, and colony function varied between colonies and with season. Capture–recapture data of banded bats was used to monitor movement patterns, seasonal weight changes, colony-size estimates at Anjuramba (JOLLY model), and the recapture frequency according to sex and age. The JOLLY estimator of the population size over-estimated the actual population at Anjuramba on most occasions but paralleled changes in population size. Of the 319 bats banded, 21.9% were recaptured, with only one recovery involving a movement between roosts. Adult males have a high roost-site fidelity and are more sedentary than adult females. The recapture rate and recapture frequency for adult males was significantly higher than for adult females. R. megaphyllus is active throughout the year but may enter torpor for short periods, with more females than males observed in torpor. There was no significant association between torpor and season. Longevity records of 7 years and 1 month were recorded for a sub-adult female and 7 years and 7 months for a juvenile female.

scholarly journals Estimating abundance of a recovering transboundary brown bear population with capture-recapture models

2021 ◽  
Author(s):  
Cecile Vanpe ◽  
Blaise Piedallu ◽  
Pierre-Yves Quenette ◽  
Jerome Sentilles ◽  
Guillaume Queney ◽  
...  
Keyword(s):  
Population Size ◽  
Conservation Status ◽  
Brown Bear ◽  
Home Range Size ◽  
Management Decision ◽  
Lower Survival Rate ◽  
Population Size Estimates ◽  
Management Decision Making ◽  
Annual Population ◽  
Capture Recapture

Abundance of small populations of large mammals may be assessed using complete counts of the different individuals detected over a time period, so-called minimum detected size (MDS). However, as population is growing larger and its distribution is expanding wider, the risk of under-estimating population size using MDS is increasing sharply due to the rarely fulfilled assumption of perfect detection of all individuals of the population, and as a result, the need to report uncertainty in population size estimates becomes crucial. We addressed these issues within the framework of the monitoring of the critically endangered Pyrenean brown bear population that was on the edge of extinction in the mid-1990s with only five individuals remaining, but was reinforced by 11 bears originated from Slovenia since then. We used Pollock's closed robust design (PCRD) capture-recapture models applied to the cross-border non-invasive sampling data from France, Spain and Andorra to provide the first published annual abundance estimates of the Pyrenean brown bear population and its trends over time. Annual population size increased and displayed a fivefold rise between 2008 and 2020, reaching > 60 individuals in 2020. Detection heterogeneity among individuals may stem from intraspecific home range size disparities making it more likely to find signs of individuals who move more. We found a lower survival rate in cubs than in adults and subadults, since the formers suffer from more mortality risks (such as infanticides, predations, mother death or abandonments) than the latters. Our study provides evidence that the PCRD capture-recapture modelling approach can provide reliable estimates of the size of and trend in large mammal populations, while minimizing bias due to inter-individual heterogeneity in detection probabilities and allowing the quantification of sampling uncertainty surrounding these estimates. Such information is vital for informing management decision-making and assessing population conservation status.

Bayesian analysis of capture-recapture model and diagnostic test in clinical trials

2014 ◽  
Author(s):  
◽  
Dan Zheng
Keyword(s):  
Clinical Trials ◽  
Simulation Study ◽  
Behavioral Response ◽  
Bayesian Method ◽  
Original Method ◽  
Potential Bias ◽  
The Em Algorithm ◽  
Em Method ◽  
Capture Recapture ◽  
Simulation Results

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Capture-recapture models have been widely used to estimate the size of a target wildlife population. There are three major sources of variations that can affect capture probabilities: time (i.e., capture probabilities vary with time or trapping occasion), behavioral response (i.e., capture probabilities vary due to a trap response of animals to the first capture), and heterogeneity (i.e., capture probabilities vary by individual animal). There are eight models regarding possible combinations of these factors, including M0, Mt, Mb, Mh, Mtb, Mth, Mbh, and Mtbh. A capture-recapture model (Mb model) was created to present the behavioral response effect. The objective Bayesian analysis for the population size was developed and compared with common maximum likelihood estimates (MLEs). Simulation results demonstrate the advantages of the objective Bayesian over MLEs. Two real examples about a deer mouse are presented and one R package (OBMbpkg) was built for application. Companion diagnostics (CDx) for personalized medicine is commonly applied to in vitro diagnostic (IVD) industry and clinical trials for specific disease or treatment with biomarkers (e.g. molecular targets). The Bayesian method with Gibbs sampler was used to estimate the potential bias caused by imperfect CDx under the targeted design, where only patients with a positive diagnosis were enrolled the clinical trials. A simulation study was conducted to evaluate the performance of the Bayesian method and to compare with the EM algorithm. The Bayesian model selection method with G-prior was used to test treatment effects of targeted drugs for patients with biomarkers under the targeted design. A simulation study was conducted to evaluate the performance of the Bayesian method and to compare it with the original method and EM method when sample size is small. Eventually a biomarker-stratified design was studied, while patients enrolled in clinical trials could be divided into two groups (i.e., those with a positive or negative diagnosis). Both the EM algorithm and Bayesian method were used to estimate the potential bias caused by imperfect CDx. Simulation results demonstrate the advantages of the Bayesian method over the original method and EM method.

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