Comparison of sampling effort allocation strategies in a stratified random survey with multiple objectives

Stratified random survey is commonly used to estimate abundance indices of fish populations in multispecies survey,providing reliable data for stock assessment and fisheries management.In some cases,however,the sample size is relatively small because of the limitation of survey cost or other factors.The allocation methods of sampling efforts among strata in stratified random surveys with small sample size may need adjustment compared with traditional approaches.In this study,two sampling stations were allocated to each stratum first and then the remaining sampling units were allocated among strata using five traditional allocation methods.In order to distinguish them from traditional methods,we called them adjusted methods in this study.A simulation study was conducted to compare the performances of different allocation strategies of sampling efforts in a stratified random survey for estimating abundance indices of multiple target species.Relative estimation error(REE)and relative bias(RB)were used to measure the precision and accuracy of estimates of abundance indices under different allocation schemes of sampling efforts in the multispecies survey.The performances of different allocation schemes in estimating abundance indices varied greatly for different species over different seasons.The adjusted Neyman allocation scheme could significantly reduce the REE and RB of estimates of abundance index for single species survey.For multiple species surveys,the adjusted average-Neyman allocation method,the adjusted Yate allocation method,the adjusted proportional allocation method and current allocation method had relatively high accuracy and precision of estimates of abundance indices for four species in terms of the total_(REE) and total_(RB).Though the adjusted average-Neyman allocation scheme did not always have the best performance,it was the optimal one considering the accuracy and precision of estimates of abundance indices for all species simultaneously.The allocation of sampling efforts among strata in stratified random surveys targeting for estimating abundance indices of multiple species should comprehensively consider the variance of abundance of different species in stratum and the seasonal changes.

Revealing an Invasion Risk of Fish Species in Qingdao Underwater World by Environmental DNA Metabarcoding

Environmental DNA(eDNA)metabarcoding has emerged as a potentially powerful tool to monitor invasive fish species.As an alternative(or complementary)tool for biodiversity monitoring,e DNA metabarcoding had been used to detect species in aquariums,which represents an important transit avenue for introducing non-indigenous species with high population densities.In this study,eDNA metabarcoding as well as morphological characterization were used to reveal the diversity of non-indigenous species in a large aquarium at Qingdao Underwater World.Environmental DNA metabarcoding of 14 water samples at five locations from the Big Water Tank detected 24 non-indigenous species and four putative non-indigenous operational taxonomic units(OTUs).In contrast,only 20 non-indigenous species were observed by morphological characterization.Some species undetected by morphological characterization,such as Oreochromis niloticus(Linnaeus,1758),are highly adaptable to various environments and/or have invaded preferred regions where they threaten native aquatic species.eDNA metabarcoding also detected seven local fishes that were not identified by morphological characterization.However,analysis of OTU diversity among stations and sample replications revealed that eDNA varied within and/or between stations.Increasing sampling effort as well as negative controls are required to increase the detection rate of species and to eliminate false-positive OTUs.