Evaluation of sampling designs for different fishery groups in the Yangtze River estuary, China

Ma, Jin; Tian, Shu; Gao, Chunxia; Kindong, Richard; Zhao, Jianguo

doi:10.1016/j.rsma.2020.101373

Cited by 3 publications

(13 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The performances were evaluated by REE, RB, and CV, which expressed their precision, deviation, and dispersion, respectively. It is well understood that simple random sampling could provide an unbiased mean of the population (Li et al, 2015;Ma et al, 2020). However, a better sampling should pay more attention to not only bias mitigation but also precision improvement (Cochran, 1977).…”

Section: Discussionmentioning

confidence: 99%

“…It was expected that stratification should make intra-stratum homogeneity and inter-stratum heterogeneity (Manly et al, 2002;Miller et al, 2007). An appropriate stratification enhanced the ability of SRS to estimate the mean of the population (Ma et al, 2020). When sampling C. mystus eggs, more accuracy was found in Design 3 than in Design 2.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Sampling Designs for Monitoring Ichthyoplankton in the Estuary Area: A Case Study on Coilia mystus in the Yangtze Estuary

Long

et al. 2022

Front. Mar. Sci.

View full text Add to dashboard Cite

A fishery-independent survey can provide detailed information for fishery assessment and management. However, the sampling design for the survey on ichthyoplankton in the estuary area is still poorly understood. In this study, we developed six stratified schemes with various sample sizes, attempting to find cost-efficient sampling designs for monitoring Coilia mystus ichthyoplankton in the Yangtze Estuary. The generalized additive model (GAM) with the Tweedie distribution was used to quantify the “true” distribution of C. mystus eggs and larvae, based on the data from the fishery-independent survey in 2019–2020. The performances of different sampling designs were evaluated by relative estimation error (REE), relative bias (RB), and coefficient of variation (CV). The results indicated that appropriate stratifications with intra-stratum homogeneity and inter-stratum heterogeneity could improve precision. The stratified schemes should be divided not only between the North Branch and South Branch but between river and sea. No less than two stratifications in the South Branch could also get better performance. The sample sizes of 45–55 were considered as the cost-efficient range. Compared to other monitoring programs, monitoring ichthyoplankton in the estuary area required a more complex stratification and a higher resolution sampling. The design ideology and optimization methodology in our study would provide references to sampling designs for ichthyoplankton in the estuary area.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Sampling Designs for Monitoring Ichthyoplankton in the Estuary Area: A Case Study on Coilia mystus in the Yangtze Estuary

Long

et al. 2022

Front. Mar. Sci.

View full text Add to dashboard Cite

show abstract

“…Based on the survey data from 2004 to 2016, a GAM was used to establish the relationship between the density (tail/haul) of each fishery group and environmental factors for each season (Ma et al. 2020).…”

Section: Methodsmentioning

confidence: 99%

“…Systematic sampling had higher precision and accuracy for estimating population density than SRS and StS in most cases, while StS with proportional allocation scheme showed better estimating performance in some cases (Ma et al. 2020). How do the two sampling designs perform under a continuously higher quantity of survey stations for estimating fishery populaiton density in the YRE?…”

mentioning

confidence: 99%

“…Therefore, the main objectives of this study were (1) to investigate the impact of a larger continuous quantity of survey stations on the survey sampling precision using a computer simulation method based on the optimal sampling design obtained by Ma et al. (2020) and (2) to guide fishery‐independent survey effort (e.g., number of stations to sample) for different fishery groups in the YRE in the context of the “Great Protection of the Yangtze River” strategy and to meet assessment objectives of the Yangtze River 10‐year fishing ban.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Optimization of Sampling Effort for Different Fishery Groups in the Yangtze River Estuary, China

Zhao

Yang

2022

Mar Coast Fish

Self Cite

View full text Add to dashboard Cite

The Yangtze River Estuary (YRE) plays an important role in the conservation of fishery resources in the Yangtze River basin, and the Chinese government has established a special fishing ban management area at the YRE. To assess effects of the fishing ban, survey design and appropriate effort need to be determined and implemented. This study used long-term trawl survey data of the YRE (2004YRE ( -2017 to explore the effects of survey effort (8-30 continuous survey stations selected by systematic and stratified sampling) on precision and accuracy of estimates of abundance of different fishery groups in the YRE. Estimated precision for a given number of survey stations varied by season and fishery group. Precision of systematic sampling fluctuated with the number of stations. Precision of stratified sampling with a proportional allocation scheme gradually increased with the number of survey stations. We suggest including 15-20 survey stations for all fishery groups sampled using the examined sampling methods.This study provides a research reference for selecting the survey effort (number of survey stations) for a fishery-independent survey in the YRE under the backgroud of conservation.

show abstract

Transparent reporting items for simulation studies evaluating statistical methods: Foundations for reproducibility and reliability

Williams,

Yang,

Lagisz

et al. 2024

Methods Ecol Evol

View full text Add to dashboard Cite

Simulation studies are essential tools to assess statistical methods. Functioning as controlled experiments, simulations generate data from known underlying processes. However, unclear or incomplete reporting of simulation studies can impact their interpretability and reproducibility, potentially leading to the misuse of statistical methods. While Morris et al. (2019, Stat Med, 38, p. 2074) recently provided guidance on the planning and conduct of simulation studies for statistical method evaluation, there is currently no comprehensive set of reporting guidelines in ecology and evolutionary biology. Here, we propose 11 reporting items for statistical simulation studies extending on Morris and colleagues' guidance. These items span across three stages: planning, coding and analysis. We also clarify the terminology related to statistical components and the broad purposes of statistical simulation studies. To highlight our proposed reporting items with current practices, we surveyed 100 articles in ecology and evolution journals that included a simulation study evaluating a statistical method. Our survey found room for improvement in more transparent reporting to ensure clear evaluation of statistical methods. Most notably, only a small proportion of articles reported a Monte Carlo uncertainty (17%; 17 out of 98), and 32% (32 out of 100) articles did not provide code. Beyond the proposed reporting items, we discuss the benefits of open science tools to enhance the reproducibility of simulation studies. Specifically, we propose the registration of statistical simulation studies to enhance planning, reporting and collaboration. We aim to instigate discussions to improve the reporting of simulation studies for statistical method research. The reporting items we propose, along with open science tools, serve as a template for developing standards and guidelines for simulation studies evaluating statistical methods. These reporting guidelines will help enhance reproducibility and indirectly encourage more consideration in the design and conduct of these simulation studies.

show abstract

Evaluation of sampling designs for different fishery groups in the Yangtze River estuary, China

Cited by 3 publications

References 20 publications

Sampling Designs for Monitoring Ichthyoplankton in the Estuary Area: A Case Study on Coilia mystus in the Yangtze Estuary

Sampling Designs for Monitoring Ichthyoplankton in the Estuary Area: A Case Study on Coilia mystus in the Yangtze Estuary

Optimization of Sampling Effort for Different Fishery Groups in the Yangtze River Estuary, China

Transparent reporting items for simulation studies evaluating statistical methods: Foundations for reproducibility and reliability

Contact Info

Product

Resources

About