Abundance estimation based on optimal estimating function with missing covariates in capture–recapture studies

2019 ◽  
Vol 152 ◽  
pp. 15-20
Author(s):  
Yang Liu ◽  
Xiuzhen Zhang ◽  
Mengke Li ◽  
Guanfu Liu ◽  
Lin Zhu
Keyword(s):  
Abundance Estimation ◽  
Missing Covariates ◽  
Estimating Function ◽  
Capture Recapture

scholarly journals Comparing performance of multiple non-invasive genetic capture–recapture methods for abundance estimation: a case study with the Sonoran pronghorn Antilocapra americana sonoriensis

Oryx ◽  
2018 ◽  
Vol 54 (3) ◽  
pp. 412-420 ◽  
Author(s):  
Susannah P. Woodruff ◽  
Paul M. Lukacs ◽  
Lisette P. Waits
Keyword(s):  
Abundance Estimation ◽  
Antilocapra Americana ◽  
Single Session ◽  
Monitoring Cost ◽  
Non Invasive ◽  
Trade Offs ◽  
Individual Session ◽  
Antilocapra Americana Sonoriensis ◽  
Capture Recapture ◽  
The Cost

AbstractDemographic monitoring is required in threatened species management, yet effective and efficient monitoring is challenging for species that are difficult to capture or susceptible to capture stress. One possible monitoring approach for such species is non-invasive genetic sampling with capture–recapture methods (genetic capture–recapture). We evaluated the performance of genetic capture–recapture in a challenging model system, monitoring the threatened Sonoran pronghorn Antilocapra americana sonoriensis. In an effort to determine the best (i.e. efficient, accurate, precise, cost-effective) method for abundance estimation, we used simulations to examine the optimal genetic capture–recapture faecal sampling design for this population. We simulated encounter histories for 100–300 individuals, with 0.33–3.33 samples/individual/session, in 1–3 sampling sessions. We explored trade-offs between sample size, number of sessions and multi-session (MARK) versus single-session (capwire) closed capture–recapture abundance estimators, and an accurate and precise estimate. We also compared the cost between the genetic capture–recapture approaches and current aerial monitoring methods. Abundance was biased positively in capwire and negatively in MARK. Bias increased and precision decreased with fewer samples/individual/session. Annual genetic capture–recapture monitoring cost was nearly twice the cost of aerial surveys, although genetic capture–recapture methods provided much higher precision. However at the current estimated abundance (c. 200), the same level of precision achieved with aerial methods can be obtained by collecting 0.75 samples/individual in a single session, for an annual cost saving of > USD 4,000. This approach of comparing estimator performance and cost can easily be applied to other systems and is a useful evaluation for managers to implement prior to designing capture–recapture studies.

scholarly journals Improving abundance estimation by combining capture-recapture and occupancy data: example with a large carnivore

2014 ◽  
Vol 51 (6) ◽  
pp. 1733-1739 ◽  
Author(s):  
Laetitia Blanc ◽  
Eric Marboutin ◽  
Sylvain Gatti ◽  
Fridolin Zimmermann ◽  
Olivier Gimenez
Keyword(s):  
Abundance Estimation ◽  
Large Carnivore ◽  
Capture Recapture

scholarly journals Coping with intrasexual behavioral differences: Capture-recapture abundance estimation of male cheetah

2018 ◽  
Vol 8 (18) ◽  
pp. 9171-9180
Author(s):  
Sarah Edwards ◽  
Manuela Fischer ◽  
Bettina Wachter ◽  
Joerg Melzheimer
Keyword(s):  
Abundance Estimation ◽  
Behavioral Differences ◽  
Capture Recapture

scholarly journals How Ideas from Ecological Capture-Recapture Models May Inform Multiple Systems Estimation Analyses

2020 ◽  
pp. 001112872097431
Author(s):  
Hannah Worthington ◽  
Rachel McCrea ◽  
Ruth King ◽  
Kyle Shane Vincent
Keyword(s):  
Historical Development ◽  
Abundance Estimation ◽  
Population Changes ◽  
Multiple Sources ◽  
Data Share ◽  
Multiple Systems ◽  
Modeling Methods ◽  
Common Structure ◽  
Animal Populations ◽  
Capture Recapture

Abundance estimation, for both human and animal populations, informs policy decisions and population management. Capture-recapture and multiple sources data share a common structure; the population can be partially enumerated and individuals are identifiable. Consequently, the analytical methods were developed simultaneously. However, whilst ecological models have been developed to describe highly complex, biologically realistic scenarios, for example modeling population changes through time and combining different forms of data, multiple systems estimation has changed comparatively less so. In this paper we provide a brief description of the historical development of ecological and epidemiological capture-recapture and discuss the associated underlying differences that have led to model divergence. We identify three key areas where ecological modeling methods may inform and improve multiple systems estimation.

scholarly journals Capture–recapture abundance estimation using a semi-complete data likelihood approach

2016 ◽  
Vol 10 (1) ◽  
pp. 264-285 ◽  
Author(s):  
Ruth King ◽  
Brett T. McClintock ◽  
Darren Kidney ◽  
David Borchers
Keyword(s):  
Complete Data ◽  
Abundance Estimation ◽  
Capture Recapture ◽  
Likelihood Approach
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