Comparison of different sampling designs for macrozoobenthos survey in a tidal flat

被引:2
作者
Wang, Jing [1 ]
Zhang, Chongliang [1 ,2 ]
Xue, Ying [1 ,2 ]
Xu, Binduo [1 ,2 ]
Ren, Yiping [1 ,2 ]
Chen, Yong [3 ]
机构
[1] Ocean Univ China, Coll Fisheries, Qingdao 266003, Peoples R China
[2] Pilot Natl Lab Marine Sci & Technol Qingdao, Lab Marine Fisheries Sci & Food Prod Proc, Qingdao 266237, Peoples R China
[3] Univ Maine, Sch Marine Sci, Orono, ME 04469 USA
基金
国家重点研发计划;
关键词
Macrozoobenthos; Species abundance; Sampling design; Optimization; Simulation study; MONTE-CARLO; SEA; INVERTEBRATES;
D O I
10.1016/j.rsma.2020.101113
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Macrozoobenthos survey programs often tend to be costly and time-consuming, which call for the development of cost-effective sampling designs. In this study, ordinary kriging interpolation was used to estimate the values at unsurveyed locations based on macrozoobenthos survey data in tidal flat as the true' values for this simulation study. Three potential survey designs, including simple random sampling (SRS), stratified random sampling (StRS) and cluster sampling (CS), were compared in estimating abundance indices of three macrozoobenthic species and species diversity index. A computer simulation study was developed to evaluate if sampling efforts could be reduced while maintaining data quality for quantifying the survey objectives. In general, StRS performed the best in estimating the target indices over different seasons, followed by CS and SRS. Sampling efforts in the three sampling designs could be reduced while relatively high precision and accuracy of estimates could still be achieved. This study suggests that cost and negative impacts of survey on the tidal flat ecosystem can be substantially reduced if proper studies can be done to optimize the survey design based on computer simulation study. Such a post-survey simulation study could improve survey designs and aid to acquire the optimal sampling efforts to achieve the most important survey goals. Although applied to one system, the framework developed in this study can be also applicable to other survey programs. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页数:6
相关论文
共 37 条
[21]  
Schabenberger O., 2005, Statistical Methods for Spatial Data Analysis
[22]   Which are better, random or systematic acoustic surveys? A simulation using North Sea herring as an example [J].
Simmonds, EJ ;
Fryer, RJ .
ICES JOURNAL OF MARINE SCIENCE, 1996, 53 (01) :39-50
[23]  
Simon M., 2011, ENCY EARTH SCI SERIE
[24]   Evaluation of sampling designs for red sea urchins Strongylocentrotus franciscanus in British Columbia [J].
Skibo, Karen M. ;
Schwarz, Carl J. ;
Peterman, Randall M. .
NORTH AMERICAN JOURNAL OF FISHERIES MANAGEMENT, 2008, 28 (01) :219-230
[25]   Multispecies survey design for assessing reef-fish stocks, spatially explicit management performance, and ecosystem condition [J].
Smith, Steven G. ;
Ault, Jerald S. ;
Bohnsack, James A. ;
Harper, Douglas E. ;
Luo, Jiangang ;
McClellan, David B. .
FISHERIES RESEARCH, 2011, 109 (01) :25-41
[26]  
Solan M, 2005, COAST ESTUAR STUD, V60, P105
[27]   Biodiversity hotspot for marine invertebrates around the Dokdo, East Sea, Korea: Ecological checklist revisited [J].
Song, Sung Joon ;
Park, Jinsoon ;
Ryu, Jongseong ;
Rho, Hyun Soo ;
Kim, Won ;
Khim, Jong Seong .
MARINE POLLUTION BULLETIN, 2017, 119 (02) :162-170
[28]   Monte Carlo simulations of benthic macroinvertebrate populations: estimates using random, stratified, and gradient sampling [J].
Statzner, B ;
Gore, JA ;
Resh, VH .
JOURNAL OF THE NORTH AMERICAN BENTHOLOGICAL SOCIETY, 1998, 17 (03) :324-337
[29]   ADAPTIVE CLUSTER SAMPLING [J].
THOMPSON, SK .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1990, 85 (412) :1050-1059
[30]   Spatial distribution of benthic macrofauna in the Central Arctic Ocean [J].
Vedenin, Andrey ;
Gusky, Manuela ;
Gebruk, Andrey ;
Kremenetskaia, Antonina ;
Rybakova, Elena ;
Boetius, Antje .
PLOS ONE, 2018, 13 (10)