Optimization of stratification scheme for a fishery-independent survey with multiple objectives

XU Binduo; REN Yiping; CHEN Yong; XUE Ying; ZHANG Chongliang; WAN Rong

doi:10.1007/s13131-015-0739-z

多目标渔业资源科学调查的分层方案设计优化

doi: 10.1007/s13131-015-0739-z

1.
中国海洋大学水产学院青岛 266003, 中国;美国缅因大学海洋学院缅因 04469, 美国
2.
中国海洋大学水产学院青岛 266003, 中国
3.
美国缅因大学海洋学院缅因 04469, 美国;中国海洋大学水产学院青岛 266003, 中国
4.
中国海洋大学水产学院青岛 266003, 中国;青岛海洋科学与技术国家实验室海洋渔业科学与食物产出过程功能实验室青岛 266000, 中国

基金项目: The Public Science and Technology Research Funds Projects of Ocean under contract No. 201305030; the Specialized Research Fund for the Doctoral Program of Higher Education under contract No. 20120132130001.

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出版历程
- 收稿日期: 2015-04-30
- 修回日期: 2015-07-29

Optimization of stratification scheme for a fishery-independent survey with multiple objectives

1.
College of Fisheries, Ocean University of China, Qingdao 266003, China;School of Marine Sciences, University of Maine, Orono, Maine 04469, USA
2.
College of Fisheries, Ocean University of China, Qingdao 266003, China
3.
School of Marine Sciences, University of Maine, Orono, Maine 04469, USA;College of Fisheries, Ocean University of China, Qingdao 266003, China
4.
College of Fisheries, Ocean University of China, Qingdao 266003, China;Laboratory for Marine Fisheries and Aquaculture, Qingdao National Laboratory for Marine Science and Technology Qingdao, 266000, China

摘要

摘要: 渔业资源科学调查常用于收集高质量的生物学和生态学数据以进行渔业资源评估与管理。渔业资源调查设计优化十分必要,其有助于在经济有效的采样努力量下提高调查估计量的精度。对于估计单鱼种资源量指数和物种多样性指数为主的多目标渔业资源调查设计,本研究应用模拟方法评价和优化了分层随机采样设计的分层方案。在不同月份,对于不同调查目标,分别比较了不同分层方案设计的表现。对于大多数指标,与简单随机采样设计相比,分层方案设计可以提高调查估计量的精度。目前采用的具有5层的分层随机采样设计表现最好。通过分层方案设计可以补偿由于采样努力量降低造成的估计量精度的下降,采样努力量的减少有助于降低调查成本、减轻调查拖网对于种群数量较低鱼种的不利影响。本研究表明对于不同的调查目标,最优化的分层方案设计不同。调查后分析有助于改善渔业资源调查的分层方案设计。
- 渔业资源科学调查 /
- 最优化 /
- 分层随机采样 /
- 分层方案设计 /
- 计算机模拟
Abstract: Fishery-independent surveys are often used for collecting high quality biological and ecological data to support fisheries management. A careful optimization of fishery-independent survey design is necessary to improve the precision of survey estimates with cost-effective sampling efforts. We developed a simulation approach to evaluate and optimize the stratification scheme for a fishery-independent survey with multiple goals including estimation of abundance indices of individual species and species diversity indices. We compared the performances of the sampling designs with different stratification schemes for different goals over different months. Gains in precision of survey estimates from the stratification schemes were acquired compared to simple random sampling design for most indices. The stratification scheme with five strata performed the best. This study showed that the loss of precision of survey estimates due to the reduction of sampling efforts could be compensated by improved stratification schemes, which would reduce the cost and negative impacts of survey trawling on those species with low abundance in the fishery-independent survey. This study also suggests that optimization of a survey design differed with different survey objectives. A post-survey analysis can improve the stratification scheme of fishery-independent survey designs.
- fishery-independent survey /
- optimization /
- stratified random sampling /
- stratification scheme /
- computer simulation

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参考文献(42)

Andrew N L, Chen Y. 1997. Optimal sampling for estimating the size structure and mean size of abalone caught in a New South Wales fishery. Fishery Bulletin, 95:403-413

Ault J S, Diaz G A, Smith S G, et al. 1999. An efficient sampling survey design to estimate pink shrimp population abundance in Biscayne Bay, Florida. North American Journal of Fisheries Management, 19(3):696-712

Blaber S J M, Cyrus D P, Albaret J-J, et al. 2000. Effects of fishing on the structure and functioning of estuarine and nearshore ecosystems.ICES Journal of Marine Science, 57(3):590-602

Blanchard J L, Maxwell D L, Jennings S. 2008. Power of monitoring surveys to detect abundance trends in depleted populations:the effects of density-dependent habitat use, patchiness, and climate change. ICES Journal of Marine Science, 65(1):111-120

Cadima E L, Caramelo A M, Afonso-Dias M, et al. 2005. Sampling Methods Applied to Fisheries Science:A Manual. FAO Fisheries Technical Paper 434. Rome:Food and Agriculture Organization Carlsson D, Kanneworff P, Folmer O, et al. 2000. Improving the West Greenland trawl survey for shrimp (Pandalus borealis). Journal of Northwest Atlantic Fishery Science, 27:151-160

Chen Dagang. 1991. Fishery Ecology in the Yellow Sea and Bohai Sea(in Chinese). Beijing:China Ocean Press Chen Y. 1996. A Monte Carlo study on impacts of the size of subsample catch on estimation of fish stock parameters. Fisheries Research, 26(3-4):207-223

Chen Yong, Sherman S, Wilson C, et al. 2006. A comparison of two fishery-independent survey programs used to define the population structure of American lobster (Homarus americanus) in the Gulf of Maine. Fishery Bulletin, 104(2):247-255

Cochran W G. 1977. Sampling Techniques. 3rd ed. New York:John Wiley & Sons, 428

Folmer O, Pennington M. 2000. A statistical evaluation of the design and precision of the shrimp trawl survey off West Greenland.

Fisheries Research, 49(2):165-178

Francis R I C C. 1984. An adaptive strategy for stratified random trawl surveys. New Zealand Journal of Marine and Freshwater Research, 18(1):59-71

Gavaris S, Smith S J. 1987. Effect of allocation and stratification strategies on precision of survey abundance estimates for Atlantic cod (Gadus morhua) on the Eastern Scotian Shelf. Journal of Northwest Atlantic Fishery Science, 7:137-144

Greenstreet S P R, Piet G J. 2008. Assessing the sampling effort required to estimate a species diversity in the groundfish assemblages of the North Sea. Marine Ecology Progress Series, 364:181-197

Gunderson D R. 1993. Surveys of Fisheries Resources. New York:John Wiley & Sons

Hilborn R, Walters C J. 1992. Quantitative Fisheries Stock Assessment:Choice, Dynamics and Uncertainty. New York:Chapman and Hall

Jennings S, Kaiser M J, Reynolds J D. 2001. Marine Fisheries Ecology.Oxford:Blackwell Science

Jiao Y, Chen Y, Schneider D, et al. 2004. A simulation study of impacts of error structure on modeling stock-recruitment data using generalized linear models. Canadian Journal of Fisheries and Aquatic Sciences, 61(1):122-133

Jin Xianshi, Tang Qisheng. 1996. Changes in fish species diversity and dominant species composition in the Yellow Sea. Fisheries Research, 26(3-4):337-352

Lazzari M A, Sherman S, Kanwit J K. 2003. Nursery use of shallow habitats by epibenthic fishes in Maine nearshore waters. Estuarine, Coastal and Shelf Science, 56(1):73-78

Liu Yong, Chen Yong, Cheng Jiahua. 2009. A comparative study of optimization methods and conventional methods for sampling design in fishery-independent surveys. ICES Journal of Marine Science, 66(9):1873-1882

Lohr S L. 2009. Sampling:Design and Analysis. 2nd ed. Boston:Brooks/Cole Ludwig J A, Reynolds J F. 1988. Statistical Ecology. New York:John Wiley & Sons Lunsford C R, Haldorson L, Fujioka J T, et al. 2001. Distribution patterns and survey design considerations of Pacific Ocean perch(Sebastes alutus) in the Gulf of Alaska. In:Kruse G H, Bez N, Booth A, et al., eds. Spatial Processes and Management of Marine Populations. Alaska Sea Grant Program, Fairbanks, 281-302

Manly B F J, Akroyd J A M, Walshe K A R. 2002. Two-phase stratified random surveys on multiple populations at multiple locations.New Zealand Journal of Marine and Freshwater Research, 36(3):581-591

Mier K L, Picquelle S J. 2008. Estimating abundance of spatially aggregated populations:comparing adaptive sampling with other survey designs. Canadian Journal of Fisheries and Aquatic Sciences, 65, 176-197

Miller T J, Skalski J R, Ianelli J N. 2007. Optimizing a stratified sampling design when faced with multiple objectives. ICES Journal of Marine Science, 64(1):97-109

Paloheimo J E, Chen Y. 1996. Estimating fish mortalities and cohort sizes. Canadian Journal of Fisheries and Aquatic Sciences, 53(7):1572-1579

Scheirer K, Chen Y, Wilson C. 2004. A comparative study of American lobster fishery sea and port sampling programs in Maine:1998-2000. Fisheries Research, 68(1-3):343-350

Secor H, Rooker J R. 2005. Connectivity in the life histories of fishes that use estuaries. Estuarine, Coastal and Shelf Science, 64(1):1-3

Simmonds E J, Fryer R J. 1996. Which are better, random or systematic acoustic surveys? A simulation using North Sea herring as an example. ICES Journal of Marine Science, 53(1):39-50

Smith S G, Ault J S, Bohnsack J A, et al. 2011. Multispecies survey design for assessing reef-fish stocks, spatially explicit management performance, and ecosystem condition. Fisheries Research, 109(1):25-41

Smith S J, Gavaris S. 1993. Improving the precision of abundance estimates of Eastern Scotian Shelf Atlantic cod from bottom trawl surveys. North American Journal of Fisheries Management, 13(1):35-47

Smith S J, Lundy M J. 2006. Improving the precision of design-based scallop drag surveys using adaptive allocation methods. Canadian Journal of Fisheries and Aquatic Sciences, 63(7):1639-1646

Smith S J, Robert G. 1998. Getting more out of your survey designs:an application to Georges Bank scallops (Placopecten magellanicus).In:Jamieson G S, Campbell A, eds. Proceedings of the North Pacific Symposium on Invertebrate Stock Assessment and Management. Special Publication Canadian Journal of Fisheries and Aquatic Sciences, 125:3-13

Smith S J, Tremblay M J. 2003. Fishery-independent trap surveys of lobsters (Homarus americanus):design considerations. Fisheries Research, 62(1):65-75

Sokal R R, Rohlf F J. 2012. Biometry:the Principles and Practice of Statistics in Biological Research. 4th ed. New York:W. H. Freeman and Company

Som R K. 1973. A Manual of Sampling Techniques. London:Heinemann Education Books Ltd Su Zhenming, Quinn T J Ⅱ. 2003. Estimator bias and efficiency for adaptive cluster sampling with order statistics and a stopping rule. Environmental and Ecological Statistics, 10(1):17-41

Sun Yuanyuan, Zan Xiaoxiao, Xu Binduo, et al. 2014. Growth, mortality and optimum catchable size of Hexagrammos otakii in Haizhou Bay and its adjacent waters. Periodical of Ocean University of China (in Chinese), 44(9):46-52

Tang Qingsheng, Ye Maozhong. 1990. Exploitation and Protection of the Fishery Resources in the Coastal Waters of Shandong Province (in Chinese). Beijing:China Agriculture Press Taylor J R. 1997. An Introduction to Error Analysis:the Study of Uncertainties in Physical Measurements. 2nd ed. Sausalito, CA, USA:University Science Books Thompson S K, Seber G A F. 1996. Adaptive Sampling. New York:John Wiley & Sons Thompson S K. 1990. Adaptive cluster sampling. Journal of the American Statistical Association, 85(412):1050-1059

Wang Xiaolin, Xu Binduo, Ji Yupeng, et al. 2013. Fish community structure and its relationships with environmental factors in Haizhou Bay and adjacent waters of East China in winter.Chinese Journal of Applied Ecology (in Chinese), 24(6):1707-1714

Xu Binduo, Jin Xianshi. 2005. Variations in fish community structure during winter in the southern Yellow Sea over the period 1985-2002. Fisheries Research, 71(1):79-91

Xu Binduo, Zhang Chongliang, Xue Ying, et al. 2015. Optimization of sampling effort for a fishery-independent survey with multiple goals. Environmental Monitoring and Assessment, 187:252

Yu Hao, Jiao Yan, Su Zhenming, et al. 2012. Performance comparison of traditional sampling designs and adaptive sampling designs for fishery-independent surveys:A simulation study. Fisheries Research, 113(1):173-181

Zhang Yuying, Brzezinski D, Chang J H, et al. 2011. Spatial structuring of fish community in association with environmental variables in the coastal Gulf of Maine. Journal of Northwest Atlantic Fishery Science, 43:47-64

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文章访问数: 1726
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多目标渔业资源科学调查的分层方案设计优化

doi: 10.1007/s13131-015-0739-z

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出版历程

Optimization of stratification scheme for a fishery-independent survey with multiple objectives

计量

出版历程

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