scholarly journals Estimating abundance with interruptions in data collection using open population spatial capture–recapture models

Ecosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
Author(s):  
Cyril Milleret ◽  
Pierre Dupont ◽  
Joseph Chipperfield ◽  
Daniel Turek ◽  
Henrik Brøseth ◽  
...  
Keyword(s):  
Data Collection ◽  
Open Population ◽  
Capture Recapture

scholarly journals Estimating abundance with interruptions in data collection using open population spatial capture-recapture models

2019 ◽  
Author(s):  
Cyril Milleret ◽  
Pierre Dupont ◽  
Joseph Chipperfield ◽  
Daniel Turek ◽  
Henrik Brøseth ◽  
...  
Keyword(s):  
Life History ◽  
Data Collection ◽  
Life History Strategies ◽  
List Type ◽  
Systematic Bias ◽  
Field Sampling ◽  
Data Set ◽  
Non Invasive ◽  
Open Population ◽  
Capture Recapture

AbstractThe estimation of population size remains one of the primary goals and challenges in ecology and provides a basis for debate and policy in wildlife management. Despite the development of efficient non-invasive sampling methods and robust statistical tools to estimate abundance, maintenance of field sampling is still subject to economic and logistic constraints. These can result in intentional or unintentional interruptions in sampling and cause gaps in data time series, posing a challenge to abundance estimation, and ultimately conservation and management decisions.We applied an open population spatial capture-recapture (OPSCR) model to simulations and a real case study to test the reliability of abundance inferences models to interruption in data collection. Using individual detections occurring over consecutive sampling occasions, OPSCR models allow the estimation of abundance from individual detection data while accounting for lack of demographic and geographic closure between occasions. First, we simulated sampling data with interruptions in field sampling of different lengths and timing. We checked the performance of an OPSCR model in deriving abundance for species with slow and intermediate life history strategies. Finally, we introduced artificial sampling interruptions of various magnitudes and timing to a five-year non-invasive monitoring data set of wolverines (Gulo gulo) in Norway and quantified the consequences for OPSCR model predictions.Inferences from OPSCR models were reliable even with temporal interruptions in monitoring. Interruption did not cause any systematic bias, but increased uncertainty. Interruptions occurring at occasions towards the beginning and the end of the sampling caused higher uncertainty. The loss in precision was more severe for species with a faster life history strategy.We provide a reliable framework to estimate abundance even in the presence of sampling interruptions. OPSCR allows monitoring studies to provide contiguous abundance estimates to managers, stakeholders, and policy makers even when data are non-contiguous. OPSCR models do not only help cope with unintentional interruptions during sampling but also offer opportunities for using intentional sampling interruptions during the design of cost-effective population surveys.

scholarly journals Sex‐specific population dynamics of ocelots in Belize using open population spatial capture–recapture

Ecosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
Author(s):  
Christopher B. Satter ◽  
Ben C. Augustine ◽  
Bart J. Harmsen ◽  
Rebecca J. Foster ◽  
Marcella J. Kelly
Keyword(s):  
Population Dynamics ◽  
Specific Population ◽  
Open Population ◽  
Capture Recapture

scholarly journals On the Estimation of Dispersal and Movement of Birds

The Condor ◽  
2004 ◽  
Vol 106 (4) ◽  
pp. 720-731 ◽  
Author(s):  
William L. Kendall ◽  
James D. Nichols
Keyword(s):  
Robust Design ◽  
Nonlinear Dynamic ◽  
Detection Probability ◽  
Cross Correlation ◽  
Statistical Methodology ◽  
Open Population ◽  
Abundance Estimates ◽  
Capture Recapture ◽  
Over Time

Abstract The estimation of dispersal and movement is important to evolutionary and population ecologists, as well as to wildlife managers. We review statistical methodology available to estimate movement probabilities. We begin with cases where individual birds can be marked and their movements estimated with the use of multisite capture-recapture methods. Movements can be monitored either directly, using telemetry, or by accounting for detection probability when conventional marks are used. When one or more sites are unobservable, telemetry, band recoveries, incidental observations, a closed- or open-population robust design, or partial determinism in movements can be used to estimate movement. When individuals cannot be marked, presence-absence data can be used to model changes in occupancy over time, providing indirect inferences about movement. Where abundance estimates over time are available for multiple sites, potential coupling of their dynamics can be investigated using linear cross-correlation or nonlinear dynamic tools. Sobre la Estimación de la Dispersión y el Movimiento de las Aves Resumen. La estimación de la dispersión y el movimiento es importante para los ecó logos evolutivos y de poblaciones, así como también para los encargados del manejo de vida silvestre. Revisamos la metodología estadística disponible para estimar probabilidades de movimiento. Empezamos con casos donde aves individuales pueden ser marcadas y sus movimientos estimados con el uso de métodos de captura-repactura para múltiples sitios. Los movimientos pueden ser monitoreados ya sea directamente, usando telemetría o teniendo en cuenta las probabilidades de detección cuando se usan marcas convencionales. Cuando uno o más sitios no pueden ser observados, se puede estimar el movimiento usando telemetría, recuperación de anillos, observaciones circunstanciales, un diseño poblacional robusto cerrado o abierto, o determinismo parcial de los movimientos. Cuando los individuos no pueden ser marcados, se pueden usar datos de presencia-ausencia para modelar los cambios en el tiempo de la ocupación, brindando inferencias indirectas sobre los movimientos. Cuando las estimaciones de abundancia a lo largo del tiempo están disponibles para varios sitios, se puede investigar la interrelación potencial de sus dinámicas usando correlaciones cruzadas lineales o herramientas para dinámica no lineal.

scholarly journals Open population maximum likelihood spatial capture‐recapture

Biometrics ◽  
2019 ◽  
Vol 75 (4) ◽  
pp. 1345-1355 ◽  
Author(s):  
Richard Glennie ◽  
David L. Borchers ◽  
Matthew Murchie ◽  
Bart J. Harmsen ◽  
Rebecca J. Foster
Keyword(s):  
Maximum Likelihood ◽  
Open Population ◽  
Capture Recapture ◽  
Population Maximum

Estimating the size of an open population using sparse capture-recapture data

Biometrics ◽  
2017 ◽  
Vol 74 (1) ◽  
pp. 280-288 ◽  
Author(s):  
Richard Huggins ◽  
Jakub Stoklosa ◽  
Cameron Roach ◽  
Paul Yip
Keyword(s):  
Open Population ◽  
Capture Recapture

scholarly journals Estimating age-specific survival when age is unknown: open population capture-recapture models with age structure and heterogeneity

2013 ◽  
Vol 4 (7) ◽  
pp. 654-664 ◽  
Author(s):  
Eleni Matechou ◽  
Shirley Pledger ◽  
Murray Efford ◽  
Byron J.T. Morgan ◽  
David L. Thomson
Keyword(s):  
Age Structure ◽  
Open Population ◽  
Capture Recapture

scholarly journals Abundance and survival estimates of the southeastern Pacific humpback whale stock from 1991–2006 photo-identification surveys in Ecuador

2020 ◽  
pp. 301-307 ◽  
Author(s):  
Fernando Félix ◽  
Cristina Castro ◽  
Jeffrey L. Laake
Keyword(s):  
Annual Variation ◽  
Humpback Whales ◽  
Collaborative Effort ◽  
Transient Effect ◽  
Photo Identification ◽  
Migration Timing ◽  
Open Population ◽  
Southeastern Pacific ◽  
Capture Recapture ◽  
Wintering Areas

Southeastern Pacific humpback whales (Breeding Stock G) breed along the northwestern coast of South America and farther north up to CostaRica. Photo-identification surveys conducted aboard whalewatching vessels during the migration/breeding season from June to September between1991 and 2006 off the coast of Ecuador (2°S, 81°W) have produced a database of 1,511 individual whales. Comparisons of photographs produced190 between-year re-sightings of 155 individual whales. Closed and open capture-recapture models were used to estimate abundance and survival.The best estimate of abundance in 2006 with the Chapman modified-Petersen was 6,504 (95% CI: 4,270–9,907; CV = 0.21). Abundance estimatesfrom open population models were considerably lower due to heterogeneity in capture probability which produced a ‘transient’ effect. Our bestestimate of true survival was 0.919 (95% CI: 0.850–0.958). Heterogeneity most likely occurred from inter-annual variation in sampling and unknownstructure and variation in the migration timing and corridor. A more extensive collaborative effort including other wintering areas further north aswell as integrating breeding-feeding data will help to reduce heterogeneity and increase precision in abundance and survival estimates.

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