Estimator Selection for Closed-Population Capture: Recapture

1998 ◽  
Vol 3 (2) ◽  
pp. 131 ◽  
Author(s):  
Thomas R. Stanley ◽  
Kenneth P. Burnham
2017 ◽  
Vol 78 (2) ◽  
pp. 328-336
Author(s):  
M. S. C. S. Lima ◽  
J. Pederassi ◽  
C. A. S. Souza

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.


1990 ◽  
Vol 73 (6) ◽  
pp. 1593-1602 ◽  
Author(s):  
A.J. McAllister ◽  
J.A. Vesely ◽  
T.R. Batra ◽  
A.J. Lee ◽  
C.Y. Lin ◽  
...  

2020 ◽  
Vol 18 (1) ◽  
pp. 2-23
Author(s):  
Ross M. Gosky ◽  
Joel Sanqui

Capture-Recapture models are useful in estimating unknown population sizes. A common modeling challenge for closed population models involves modeling unequal animal catchability in each capture period, referred to as animal heterogeneity. Inference about population size N is dependent on the assumed distribution of animal capture probabilities in the population, and that different models can fit a data set equally well but provide contradictory inferences about N. Three common Bayesian Capture-Recapture heterogeneity models are studied with simulated data to study the prevalence of contradictory inferences is in different population sizes with relatively low capture probabilities, specifically at different numbers of capture periods in the study.


2019 ◽  
Vol 11 (5) ◽  
pp. 13531-13544 ◽  
Author(s):  
Devavrat Pawar ◽  
Howard P. Nelson ◽  
Divya R.L. Pawar ◽  
Sarika Khanwilkar

Reliable population estimate of apex predators, such as the Leopard Panthera pardus fusca, is important as they indicate ecosystem health, enable evaluation of the effectiveness of conservation efforts and provide a benchmark for future management decisions.  The present study is the first to estimate abundance of Leopard along with possible prey profile in Kuno Wildlife Sanctuary (KWLS), in central Madhya Pradesh (M.P.), India.  For systematic sampling, two study habitats, 15km² each, were identified, one close to the park entrance and the other away from the park entrance.  Sampling was carried out between March and April 2017, for a period of 18 days in each of the two study habitats, ‘good’ and ‘poor’, initially based on situation in reference to park-entry.  Each habitat was divided into five blocks each, and each block subdivided into three, 1km² observation units.  In all, 16 trail cameras were placed in pairs, one set at a time in five of the blocks, over a six–day period.  The total sampling effort was 180 trap-nights.  The trigger speed was set to 3 frames per 10 seconds, and repeated only after 20 minutes interval on infra-red detection of object.  The data was analysed using closed population capture–recapture analyses in Program MARK, to estimate Leopard abundance.  Seventy-eight Leopard detections representing eight unique individuals were found in the 30km² study site.  Seven Leopards were detected in the good habitat and one in the poor habitat. The estimate for Leopard abundance for the good habitat was 11 Leopards (SE 4.6, 95% CI = 8 – 31 individuals).  Due to limited captures/recaptures in the poor habitat, abundance could not be estimated for this habitat class.


2020 ◽  
pp. 253-259
Author(s):  
David A. Paton ◽  
Lyndon Brooks ◽  
Daniel Burns ◽  
Trish Franklin ◽  
Wally Franklin ◽  
...  

The humpback whales (Megaptera novaeangliae) that migrate along the east coast of Australia were hunted to near extinction during the lastcentury. This remnant population is part of Breeding Stock E. Previous abundance estimates for the east Australian portion of Breeding Stock Ehave been based mainly on land-based counts. Here we present a capture-recapture abundance estimate for this population using photo-identificationdata. These data were collected at three locations on the migration route (Byron Bay – northern migration, Hervey Bay and Ballina – southernmigration) in order to estimate the population of humpback whales that migrated along the east coast of Australia in 2005. The capture-recapturedata were analysed using a variety of closed population models with a model-averaged estimate of 7,041 (95% CI 4,075–10,008) whales.


2019 ◽  
Vol 9 (20) ◽  
pp. 11569-11583 ◽  
Author(s):  
Soumen Dey ◽  
Mohan Delampady ◽  
Arjun M. Gopalaswamy

2014 ◽  
Vol 37 (1) ◽  
pp. 23-33
Author(s):  
P. Sarmento ◽  
◽  
J. Cruz ◽  
C. Eira ◽  
C. Fonseca ◽  
...  

Many species that occur at low densities are not accurately estimated using capture–recapture methods as such techniques assume that populations are well–defined in space. To solve this bias, spatially explicit capture–recapture (SECR) models have recently been developed. These models incorporate movement and can identify areas where it is more likely for individuals to concentrate their activity. In this study, we used data from camera–trap surveys of common genets (Genetta genetta) in Serra da Malcata (Portugal), designed to compare abundance estimates produced by SECR models with traditional closed–capture models. Using the SECR models, we observed spatial heterogeneity in genet distribution and density estimates were approximately two times lower than those obtained from the closed population models. The non–spatial model estimates were constrained to sampling grid size and likely underestimated movements, thereby overestimating density. Future research should consider the incorporation of cost–weighed models that can include explicit hypothesis on how environmental variables influence the distance metric.


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