Capture-Recapture and Removal Methods for Sampling Closed Populations.

1984 ◽  
Vol 33 (3) ◽  
pp. 326
Author(s):  
S. M. Taylor ◽  
G. C. White ◽  
D. R. Anderson ◽  
K. P. Burnham ◽  
D. L. Otis
Keyword(s):  
Capture Recapture ◽  
Closed Populations

On continuous‐time capture‐recapture in closed populations

Biometrics ◽  
2019 ◽  
Vol 76 (3) ◽  
pp. 1028-1033 ◽  
Author(s):  
Wei Zhang ◽  
Simon J. Bonner
Keyword(s):  
Continuous Time ◽  
Capture Recapture ◽  
Closed Populations

Heterogeneous Capture-Recapture Models with Covariates: A Partial Likelihood Approach for Closed Populations

Biometrics ◽  
2011 ◽  
Vol 67 (4) ◽  
pp. 1659-1665 ◽  
Author(s):  
Jakub Stoklosa ◽  
Wen-Han Hwang ◽  
Sheng-Hai Wu ◽  
Richard Huggins
Keyword(s):  
Partial Likelihood ◽  
Capture Recapture ◽  
Likelihood Approach ◽  
Closed Populations

Quantitative Methods for Estimating the Size of a Drug-Using Population

1993 ◽  
Vol 23 (2) ◽  
pp. 185-216 ◽  
Author(s):  
Thomas D. Wickens
Keyword(s):  
Drug Use ◽  
System Dynamics ◽  
Quantitative Methods ◽  
Linear Models ◽  
Markov Models ◽  
Partially Observed ◽  
Capture Recapture ◽  
Closed Populations ◽  
Log Linear ◽  
Dynamics Models

The author describes several of the most important quantitative procedures for estimating the size of an unobserved or partially observed population, with specific application to the estimation of the prevalence of drug use. The methods discussed include synthetic estimation, truncated Poisson estimates, multiple-capture surveys in both closed populations (the capture-recapture model and log-linear models) and open populations (the Jolly-Seber model and Markov models), and, more briefly, system dynamics models.

Capture-Recapture and Removal Methods for Sampling Closed Populations

1984 ◽  
Vol 48 (1) ◽  
pp. 304
Author(s):  
Estelle Russek ◽  
G. C. White ◽  
D. R. Anderson ◽  
K. P. Burnham ◽  
D. L. Otis
Keyword(s):  
Capture Recapture ◽  
Closed Populations

Capture-Recapture: Closed Populations

1998 ◽  
pp. 297-356
Author(s):  
Linda J. Young ◽  
Jerry H. Young
Keyword(s):  
Capture Recapture ◽  
Closed Populations

Capture-Recapture and Removal Methods for Sampling Closed Populations.

1984 ◽  
Vol 147 (1) ◽  
pp. 119
Author(s):  
Eric Renshaw ◽  
G. C. White ◽  
D. R. Anderson ◽  
K. P. Burnham ◽  
D. L. Otis
Keyword(s):  
Capture Recapture ◽  
Closed Populations

scholarly journals Spatial integrated models foster complementarity between monitoring programs in producing large-scale ecological indicators

2021 ◽  
Author(s):  
Valentin Lauret ◽  
Helene Labach ◽  
Daniel Turek ◽  
Sophie Laran ◽  
Olivier Gimenez
Keyword(s):  
Population Dynamics ◽  
Large Scale ◽  
Distance Sampling ◽  
Integrated Model ◽  
Integrated Models ◽  
Ecological Data ◽  
Continental Scale ◽  
Monitoring Programs ◽  
Capture Recapture ◽  
Closed Populations

AbstractOver the last decades, large-scale conservation projects have emerged that require collecting ecological data over broad spatial and temporal coverage. Yet, obtaining relevant information about large-scale population dynamics from a single monitoring program is challenging, and often several sources of data, possibly heterogeneous, need to be integrated.In this context, spatial integrated models combine multiple data types into a single analysis to quantify population dynamics of a targeted population. Using available information at different spatial or temporal scales, spatial integrated models have the potential to produce detailed ecological estimates that would be difficult to obtain if data were analyzed separately. So far, these models are available for open populations to estimate demographic parameters (survival, recruitment), therefore requiring data collected in long-term monitoring programs. In conservation biology however, we often need to quantify population abundance and density in closed populations.In this paper, we showcase the implementation of spatial integrated models to closed populations in a conservation context. We analyzed spatial capture-recapture data together with distance-sampling data to estimate abundance and density. Focusing on the Mediterranean bottlenose dolphins (Tursiops truncatus) as a case study, we combined 21,464 km of photo-identification boat surveys collecting spatial capture-recapture data with 24,624 km of aerial line-transect following a distance-sampling protocol. We compared the performances of the spatial integrated model, with that of the distance sampling model, and the spatial capture-recapture model separated. We discussed the benefits of using a spatial integrated model in the context of the assessment of French Mediterranean bottlenose dolphin conservation status to inform continental scale public policies.Overall, we emphasize the usefulness of spatial integrated model to make the most of available datasets in a conservation context. Spatial integrated models are widely applicable and relevant to conservation research and biodiversity assessment at large spatial scales.

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