Designing cost-effective capture-recapture surveys for improving the monitoring of survival in bird populations

Lieury, Nicolas; Devillard, Sébastien; Besnard, Aurélien; Giménez, Olivier; Hameau, Olivier; Ponchon, Cécile; Millon, Alexandre

doi:10.1016/j.biocon.2017.08.011

Cited by 18 publications

(15 citation statements)

References 38 publications

(37 reference statements)

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“…Few studies achieve complete detection and therefore multiple sampling occasions are required in order to minimise any associated biases (Lebreton et al 1992). In agreement, our analyses demonstrated that the accuracy of survival estimation, and the ability to detect sources of variation were improved greatly when time series were extended (also see Lieury et al 2017). Our study also demonstrated that in longer survey designs, the estimation of adult survival rates was only marginally improved by conducting mark-recapture field studies that target both adults and chicks, as opposed to adults only.…”

Section: Discussionsupporting

confidence: 80%

When is enough … enough? Effective sampling protocols for estimating the survival rates of seabirds with mark-recapture techniques

2018

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The ability to relate geographic differences in population trends to individual demographic processes is largely limited by the logistic and financial commitments associated with conducting long-term, population-specific studies. Consequently, many populations and species lack the empirical evidence of population change that is required to support evidence-based policy action. Lower intensity mark-recapture studies, such as those undertaken by citizen scientists, provide an opportunity to improve the spatial representation of survival estimates for birds. Colonial breeding makes seabirds particularly suited to this because, for many species, large numbers of breeding birds and chicks can be located relatively easily. We conducted a sensitivity analysis that evaluated the statistical power associated with using different mark-recapture survey designs to estimate a fixed "true" survival rate and detect sources of temporal variation and individual heterogeneity within the population. Isolating temporal variation with a good degree (90%) of certainty required the highest levels of survey effort. Based on the assessed survey designs, we recommend studies that have a ten-year trajectory and a recapture rate of 0.6, aim to mark at least 200 new adults per year. The recommended number of marked individuals will decrease if it is possible to achieve higher rates of recapture. Lower rates of juvenile survival and delayed reproduction mean that seabird mark-recapture survey designs that target both chicks and adults offer only marginal improvements in resolving the survival rates of adults, when compared to designs targeting adults only. However, collecting juvenile mark-recapture data provides access to age-specific vital rates that are also valuable for assessing the population dynamics of seabirds. Implementing minimum effort guidelines potentially enables the 2 effective management of smaller mark-recapture studies, thus minimising the risk that studies fail to achieve the data conditions necessary for robust estimation of survival rates.

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Section: Discussionsupporting

confidence: 80%

When is enough … enough? Effective sampling protocols for estimating the survival rates of seabirds with mark-recapture techniques

2018

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“…unmarked individuals, dead recoveries) into OPSCR models could help further mitigate the negative impact of interruptions on the precision of parameter estimates (see Chandler and Clark (2014) for an example). Previous studies testing the cost-efficiency of non-spatial CR surveys have focused on the importance of study duration, proportion of different individuals sampled, and detection probability (Lieury et al 2017). Unless the study species requires close monitoring due to short response times for management interventions (e.g.…”

Section: Resultsmentioning

confidence: 99%

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

Milleret

Dupont

Chipperfield

et al. 2019

Preprint

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The 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.

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“…For instance, the presented approach could be adapted to consider the time variations of the force of infection to account for epidemic cases or to incorporate parameters to account for a potential disease-induced mortality (discussed in Appendix S1: Section S1). In contrast, if the main interest is on the survival probability, putting more effort on resighting (independently of recapture) could improve the precision of the estimates (Lahoz-Monfort et al 2014, Lieury et al 2017), but integrating cross-sectional data will provide no added benefit (Appendix S1: Fig. The sampling design will of course have to be adapted to the main objective of the survey (Yoccoz et al 2001).…”

Section: Fig 2 Continuedmentioning

confidence: 99%

“…S6b, top panel). In contrast, if the main interest is on the survival probability, putting more effort on resighting (independently of recapture) could improve the precision of the estimates (Lahoz-Monfort et al 2014, Lieury et al 2017), but integrating cross-sectional data will provide no added benefit (Appendix S1: Fig. S6a, middle panel).…”

Section: Fig 2 Continuedmentioning

confidence: 99%

Next‐generation serology: integrating cross‐sectional and capture–recapture approaches to infer disease dynamics

Gamble¹,

Garnier

Chambert

et al. 2020

Ecology

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Two approaches have been classically used in disease ecology to estimate epidemiological parameters from field studies: cross-sectional sampling from unmarked individuals and longitudinal capture-recapture setups, which generally involve more limited numbers of marked individuals due to cost and logistical constraints. Although the benefits of longitudinal setups are increasingly acknowledged in the disease ecology community, cross-sectional data remain largely overrepresented in the literature, probably because of the inherent costs of longitudinal surveys. In this context, we used simulated data to compare the performances of cross-sectional and longitudinal designs to estimate the force of infection (i.e., the rate at which susceptible individuals become infected). Then, inspired from recent method developments in quantitative ecology, we explore the benefits of integrating both cross-sectional (seroprevalences) and longitudinal (individuals histories) data sets. In doing so, we investigate the effects of host species life history, antibody persistence, and degree of a priori knowledge and uncertainty on demographic and epidemiological parameters, as those are expected to affect in different ways the level of inference possible from the data. Our results highlight how those elements are important to consider in determining optimal sampling designs. In the case of long-lived species exposed to infectious agents resulting in persistent antibody responses, integrated designs are especially valuable as they benefit from the performances of longitudinal designs even with relatively small longitudinal sample sizes. As an illustration, we apply this approach to a combination of empirical and simulated data inspired from a case of bats exposed to a rabies virus. Overall, this work highlights that serology field studies could greatly benefit from the opportunity of integrating cross-sectional and longitudinal designs.

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Designing cost-effective capture-recapture surveys for improving the monitoring of survival in bird populations

Cited by 18 publications

References 38 publications

When is enough … enough? Effective sampling protocols for estimating the survival rates of seabirds with mark-recapture techniques

When is enough … enough? Effective sampling protocols for estimating the survival rates of seabirds with mark-recapture techniques

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

Next‐generation serology: integrating cross‐sectional and capture–recapture approaches to infer disease dynamics

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