Investigations into the distribution of sample sizes for determining age composition of multiple species

Hulson, Peter-John F.; Hanselman, Dana H.; Shotwell, S. Kalei

doi:10.7755/fb.115.3.4

Cited by 7 publications

(6 citation statements)

References 5 publications

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“…() and Walleye Pollock Gadus chalcogrammus in Hulson et al. () did not have as large a recruitment SD as those of Bocaccio in He et al. () or Cisco in our study (σ r ; sardine = 0.73, Walleye Pollock = 0.70, Boccacio = 1, Cisco full model estimate = 4.5).…”

Section: Discussioncontrasting

confidence: 47%

“…Although as a counter example, Hulson et al. () found that age composition sample size had a greater impact on SCAA uncertainty for species with higher recruitment variability compared with those with lower recruitment variability. In addition, Ono et al.…”

Section: Discussionmentioning

confidence: 99%

“…; Hulson et al. ). Fewer studies have directly examined the effect of both the amount of data collected and specifically how they were collected in relation to assessment model performance.…”

mentioning

confidence: 98%

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Data Quality, Data Quantity, and Its Effect on an Applied Stock Assessment of Cisco in Thunder Bay, Ontario

Fisch

Bence

2020

N American J Fish Manag

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Stock assessments, or population models developed to support fishery management decisions, require informative data to produce reliable estimates. However, resources available to collect these data are limited. Thus, information relating the effects of different data collection schema on stock assessment performance should be of interest to fishery managers. We used an existing data set on a stock of Cisco Coregonus artedi in Thunder Bay to simulate various degrees of reduction in available data. We considered both cluster subsampling of biological data from the commercial fishery harvest (which determine the observed harvest age composition) and reductions in the frequency of hydroacoustic surveys in order to examine their effect on fits of an age-structured stock assessment model for the stock. Our results indicate that reductions in the frequency of hydroacoustic surveys would have a greater effect on applied stock assessment performance for Thunder Bay Cisco than would reductions in biological sampling to randomly selected temporal clusters of the fishery harvest. Reduction in the frequency of the hydroacoustic survey resulted in different point estimates and larger estimated uncertainty for spawning biomass and natural mortality rate compared with the original assessment model. This was likely largely driven by increases in lag between the final year of the survey and the current year of the assessment. The lower influence of reduced biological sampling may be due to the highly variable nature of Cisco recruitment, where large or "boom" year-classes were still evident in the reduced biological samples, combined with information from survey age compositions. We suggest a priority be placed on performing hydroacoustic surveys with some regularity, such that when they are performed, they are done extensively to minimize uncertainty (measurement error). The data subsampling approach used here could be used in many assessments to determine if a reduction in sampling of various types could be implemented without materially changing assessment results.

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Section: Discussioncontrasting

confidence: 47%

Section: Discussionmentioning

confidence: 99%

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Data Quality, Data Quantity, and Its Effect on an Applied Stock Assessment of Cisco in Thunder Bay, Ontario

Fisch

Bence

2020

N American J Fish Manag

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“…When ages are determined from scales, biases are not expected; however, when ages are determined from length, biases can exist [20]. The sample size used to derive age-length frequency has an influence on the accuracy of the age-length relationship [27,28]; the uncertainty in age structure owing to age-length data needs to be considered.…”

Section: Introductionmentioning

confidence: 99%

Detection of fish movement patterns across management unit boundaries using age-structured Bayesian hierarchical models with tag-recovery data

Zhou

Jiao

2020

PLoS ONE

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Tagging studies have been widely conducted to investigate the movement pattern of wild fish populations. In this study, we present a set of length-based, age-structured Bayesian hierarchical models to explore variabilities and uncertainties in modeling tag-recovery data. These models fully incorporate uncertainties in age classifications of tagged fish based on length and uncertainties in estimated population structure. Results of a tagging experiment conducted by the Ontario Ministry of Natural Resources and Forestry (OMNRF) on yellow perch in Lake Erie was analyzed as a case study. A total of 13,694 yellow perch were tagged with PIT tags from 2009 to 2015; 322 of these were recaptured in the Ontario commercial gillnet fishery and recorded by OMNRF personnel. Different movement configurations modeling the tag-recovery data were compared, and all configurations revealed that yellow perch individuals in the western basin (MU1) exhibited relatively strong site fidelity, and individuals from the central basin (MU2 and MU3) moved within this basin, but their movements to the western basin (MU1) appeared small. Model with random effects of year and age on movement had the best performance, indicating variations in movement of yellow perch across the lake among years and age classes. This kind of model is applicable to other tagging studies to explore temporal and age-class variations while incorporating uncertainties in age classification.

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“…For instance, multi-stage design is very common in the monitoring of fish populations, whereby fish are caught at different sampling sites, all or a high proportion of the fish in that catch are measured for length, but only a sub-sample of the measured fish are aged. Comparisons of different sub-sampling designs for collecting and studying the distribution of a particular trait, such as age composition of a populations (Kimura, 1977; Pennington, Burmeister & Hjellvik, 2002; Chih, 2009; Hulson, Hanselman & Shotwell, 2016), have been more thoroughly studied in fisheries science than in other ecology fields (Kosmelj, Cedilnik & Kalan, 2001; Stafford et al, 2006; Smith et al, 2011; Brown et al, 2013). Thus, the sampling design to gather data on population abundance (stage 1) is paramount in ecological research, but also the sub-sampling design to gather data on traits-structure in the population (stage 2 or 3) can have a major impact on the population estimates, which will be used as reference points for assessment and management.…”

Section: Introductionmentioning

confidence: 99%

A simulation framework for evaluating multi-stage sampling designs in populations with spatially structured traits

Puerta

Ciannelli

Johnson

2019

PeerJ

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Selecting an appropriate and efficient sampling strategy in biological surveys is a major concern in ecological research, particularly when the population abundance and individual traits of the sampled population are highly structured over space. Multi-stage sampling designs typically present sampling sites as primary units. However, to collect trait data, such as age or maturity, only a sub-sample of individuals collected in the sampling site is retained. Therefore, not only the sampling design, but also the sub-sampling strategy can have a major impact on important population estimates, commonly used as reference points for management and conservation. We developed a simulation framework to evaluate sub-sampling strategies from multi-stage biological surveys. Specifically, we compare quantitatively precision and bias of the population estimates obtained using two common but contrasting sub-sampling strategies: the random and the stratified designs. The sub-sampling strategy evaluation was applied to age data collection of a virtual fish population that has the same statistical and biological characteristics of the Eastern Bering Sea population of Pacific cod. The simulation scheme allowed us to incorporate contributions of several sources of error and to analyze the sensitivity of the different strategies in the population estimates. We found that, on average across all scenarios tested, the main differences between sub-sampling designs arise from the inability of the stratified design to reproduce spatial patterns of the individual traits. However, differences between the sub-sampling strategies in other population estimates may be small, particularly when large sub-sample sizes are used. On isolated scenarios (representative of specific environmental or demographic conditions), the random sub-sampling provided better precision in all population estimates analyzed. The sensitivity analysis revealed the important contribution of spatial autocorrelation in the error of population trait estimates, regardless of the sub-sampling design. This framework will be a useful tool for monitoring and assessment of natural populations with spatially structured traits in multi-stage sampling designs.

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Investigations into the distribution of sample sizes for determining age composition of multiple species

Cited by 7 publications

References 5 publications

Data Quality, Data Quantity, and Its Effect on an Applied Stock Assessment of Cisco in Thunder Bay, Ontario

Data Quality, Data Quantity, and Its Effect on an Applied Stock Assessment of Cisco in Thunder Bay, Ontario

Detection of fish movement patterns across management unit boundaries using age-structured Bayesian hierarchical models with tag-recovery data

A simulation framework for evaluating multi-stage sampling designs in populations with spatially structured traits

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