A comparative study of optimization methods and conventional methods for sampling design in fishery-independent surveys

Liu, Yong; Chen, Yong; Jia-hua, Cheng

doi:10.1093/icesjms/fsp157

Cited by 26 publications

(27 citation statements)

References 30 publications

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“…This is consistent with previous studies which suggest that SYS tends to be more accurate than stratified random design (Cochran, 2007;Ripley, 2004). The desirable properties of SYS generally embodies in providing better support for kriging methods which aim to obtain estimates of spatial distribution (Liu et al, 2009). In this study, SYS was demonstrated to out-perform random and stratified random designs for estimating the population mean in terms of precision and efficiency.…”

Section: Discussionsupporting

confidence: 90%

“…Scientific sampling designs help scientists to have a representative view of target population with limited efforts. In fisheries, because of different characteristics of target species (e.g., spatial structure) and objectives of sampling (e.g., estimators), different sampling designs are required to gain maximal efficiency (Liu et al, 2009;Simmonds and Fryer, 1996;Wang et al, 2009). Of the sampling designs, simple random sample without replacement (SRS) is more commonly used as a null design for comparing the efficiency (relative variance) of different sampling schemes than as an optimal practical fishery survey design (Pooler and Smith, 2005;Skibo et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, it is important and necessary to optimize the sampling design and maximize the information output from limited sampling efforts. Computer simulations are commonly used for evaluating and comparing different sampling designs in identifying optimal sampling design (Liu et al, 2009;Simmonds and Fryer, 1996). The sampling process of proposed designs is simulated on hypothetical "true" populations.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

IAn evaluation of an inshore bottom trawl survey design for American lobster (Homarus americanus) using computer simulations

Cao

Chen²,

Chang³

et al. 2014

J. Northw. Atl. Fish. Sci.

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. 2014. An evaluation of an inshore bottom trawl survey design for American lobster (Homarus americanus) using computer simulations. J. Northw. Atl. Fish. Sci., 46: 27-39. doi:10.2960/J.v46.m696 Abstract This paper evaluates the performance of six possible sampling designs to estimate the population abundance index for American lobster using computer simulations. These designs include simple random sampling (SRS), systematic sampling (SYS) and stratified random sampling with four stratification schemes (i.e., based on region, depth, sediment and region × depth). For the stratified random design with region and depth being used for stratification, we evaluated the performances of different strategies for allocating sampling efforts. Simulations were implemented on the "true" populations which were estimated annually from 2002 to 2008 for both spring and fall based on a general additive model model developed in a separate study. Relative Estimation Error (REE), Relative Bias (RB) and design effect were used to measure the precision, accuracy and efficiency of mean estimation for different designs. On average, SYS tended to yield the most precise and efficient estimate of mean with specified sample size. However, its estimates tended to be biased and its performance varied with sample sizes and realizations of "true" population, thus changed with lobster distribution. Appropriate stratification, such as using depth to determine strata, significantly improved the precision and efficiency over SRS. Sediment, which is related to lobster distribution, was found to have little contribution to the improvement of the performance over SRS when it is used to determine strata. Also, allocating samples to each stratum based on variance or mean of previous year improved precision and efficiency. This study suggests that current design (i.e., region-depth stratified design) used in the survey had stable performance across years and seasons.

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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IAn evaluation of an inshore bottom trawl survey design for American lobster (Homarus americanus) using computer simulations

Cao

Chen²,

Chang³

et al. 2014

J. Northw. Atl. Fish. Sci.

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“…Among all these available criteria, the MMSD is optimal for its flexibility to handle fixed samples, constraints and weights. Thus, the SSA + MMSD is the best method for generating even sampling designs and has received extremely wide applications (van Groenigen et al 2000a, b;Tapia 2004;Debba et al 2005Debba et al , 2008Tapia et al 2005;Debba 2006;Simbahan and Dobermann 2006;Zhao et al 2008;Liu et al 2009). Different defects, however, exist within these methods as well.…”

Section: Introductionmentioning

confidence: 99%

Even sampling designs generation by charges repulsion simulation

Chen

Pan

Wang

et al. 2011

Environ Monit Assess

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Evenly distributed sampling design is generally considered as an efficient sampling design. It is widely used in sampling for the environmental survey. In this paper, we present a novel method for generating N evenly distributed samples within a given irregular polygon via simulating the movements of some ideal homogeneous point charges. Initially, charges are randomly put into the sampling region; then, they are freed and held orderly; and after enough runs, the charges will finally reach a stable state with all of them having a zero resultant force and velocity; and so they distribute evenly within the region. Their layout can thus be considered as an evenly distributed sampling design. The main advantages of this method are: (1) it is easy to understand and implement; (2) it is efficient in both running and generating better designs. Analysis and experimental results indicate that this method is an efficient and robust method for generating even sampling designs for 2D polygonal sampling region.

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“…However, according to Liu et al [14], stratified design may not be the best for a fisheryindependent survey under some special conditions. Our results suggest that sampling design based on the criterion of minimization of the mean of the shortest distance (MMSD) [15] was the best [14].…”

Section: Introductionmentioning

confidence: 99%

An adaptive sampling method based on optimized sampling design for fishery-independent surveys with comparisons with conventional designs

et al. 2011

Self Cite

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The adaptive cluster sampling method is widely applied in terrestrial systems; however, it is not suitable for fisheries surveys because of the high cost of unlimited sampling in practice. An adaptive approach is often used in fisheries surveys to allocate sampling effort, usually following a stratified random design. Development of an adaptive sampling method based on optimized sampling design (this design has been suggested by previous study for fishery-independent surveys) has been not yet carried out. An adaptive sampling method based on optimized sampling design using the criterion of minimization of the mean of the shortest distance (MMSD) in the first phase was constructed in this study and compared with five other sampling designs: simple random, stratified random, adaptive based on stratified sampling, systematic, and optimum design based on the MMSD criterion. This design performed neither the best nor the worst among the six sampling designs considered in this study, but its advantages were obvious when the sampling effort saved using this design was considered in the comparison. This method tends to be more flexible and find fish aggregations more precisely. It is based on a more objective sampling design in the first phase compared with other adaptive sampling designs based on stratified sampling designs. We suggest that this design be considered in developing fishery-independent survey programs.

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A comparative study of optimization methods and conventional methods for sampling design in fishery-independent surveys

Cited by 26 publications

References 30 publications

IAn evaluation of an inshore bottom trawl survey design for American lobster (Homarus americanus) using computer simulations

IAn evaluation of an inshore bottom trawl survey design for American lobster (Homarus americanus) using computer simulations

Even sampling designs generation by charges repulsion simulation

An adaptive sampling method based on optimized sampling design for fishery-independent surveys with comparisons with conventional designs

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