Impacts of sampling design on the abundance estimation of Portunus trituberculatus using crab pots

Fishery-independent surveys can provide high-quality data and support fishery assessment and management.Optimization of sampling design is crucial to increase the quality of fishery surveys.Crab pots are important fishing gears used to catch crabs.We analyzed the impacts of sampling design of crab pots on the abundance of Portunus trituberculatus in the Changjiang(Yangtze)River estuary to the Hangzhou Bay and its adjacent waters in East China Sea.The crab pots were cylindrical,240 mm in height and 600 mm in diameter of the iron ring.Our sampling designs(including fixed-station sampling,simple random sampling,stratified fixed-station sampling,and stratified random sampling),three number of stations(9,16,and 24),and three numbers of crab pots(500,1000,and 3000)were simulated and compared with the“true”abundance that obtained from bottom trawl surveys in the study area in 2007.The scenarios with 16 stations were set in stratification as a control group for comparison with unstratified designs.Results show that simple random sampling can obtain more stable results than fixed-station sampling in the abundance estimation of P.trituberculatus.In addition,stratified sampling resulted in more accurate abundance than unstratified sampling.The accuracy of the simulated results improved with the increase of the number of stations.No remarkable differences in the results were found among the scenarios of different number of crab pots at each station.However,resource-intensive areas exerted great impacts on simulation results.Thus,prior information or pre-survey results about resource abundance and density distribution are necessary.This study may serve as a reference for future sampling designs of crab pots of P.trituberculatus and other species.

Impacts of the sampling design on the abundance index estimation of Portunus trituberculatus using bottom trawl

In the survey of fishery resources,the sampling design will directly impact the accuracy of the estimation of the abundance.Therefore,it is necessary to optimize the sampling design to increase the quality of fishery surveys.The distribution and abundance of fisheries resource estimated based on the bottom trawl survey data in the Changjiang River(Yangtze River)Estuary-Hangzhou Bay and its adjacent waters in 2007 were used to simulate the"true"situation.Then the abundance index of Portunus trituberculatus were calculated and compared with its true index to evaluate the impacts of different sampling designs on the abundance estimation.Four sampling methods(including fixed-station sampling,simple random sampling,stratified fixed-station sampling,and stratified random sampling)were simulated.Three numbers of stations(9,16 and 24)were assumed for the scenarios of fixed-station sampling and simple random sampling without stratification.While 16 stations were assumed for the scenarios with stratification.Three reaction distances(1.5 m,3 m and 5 m)of P.trituberculatus to the bottom line of trawl were also assumed to adapt to the movement ability of the P.trituberculatus for different ages,seasons and substrate conditions.Generally speaking,compared with unstratified sampling design,the stratified sampling design resulted in more accurate abundance estimation of P.trituberculatus,and simple random sampling design is better than fixed-station sampling design.The accuracy of the simulated results was improved with the increase of the station number.The maximum relative estimation error(REE)was 163.43%and the minimum was 49.40%for the fixed-station sampling scenario with 9 stations,while 38.62%and 4.15%for 24 stations.With the increase of reaction distance,the relative absolute bias(RAB)and REE gradually decreased.Resource-intensive area and the seasons with high density variances have significant impacts on simulation results.Thus,it will be helpful if there are prior information or pre-survey results about density distribution.The current study can provide reference for the future sampling design of bottom trawl of P.trituberculatus and other species.

Temporal patterns of three sympatric pheasant species in the Nanling Mountains: N-mixture modeling applied to detect abundance

Background:The reliability of long‑term population estimates is crucial for conservation and management purposes.Most previous studies assume that count indices are proportionally related to abundance;however,this assumption may not hold when detection varies spatially and temporally.We examined seasonal variations in abundance of three bird species(Cabot’s Tragopan Tragopan caboti,Silver Pheasant Lophura nycthemera,and Whitenecklaced Partridge Arborophila gingica)along an elevational gradient,using N‑mixture models that take into account imperfect detection in our bird data.Methods:Camera‑trapping was used to monitor temporal activity patterns of these species at Guangdong Nanling National Nature Reserve from December 2013 to November 2017(4 seasons per year).For abundance analysis(N‑mixture modeling),we divided a year into 4 seasons,i.e.3 months per season,and performed the analysis by season.Elevation was incorporated into the N‑mixture model as a covariate that may affect abundance.We compared the N‑mixture model with a null model(no covariate model)and selected the better model based on AIC values to make an inference.Results:From 24 sampling sites,we obtained 6786 photographs of 8482 individuals of 44 bird species and 26 mammal species.Silver Pheasant was photographed much more frequently and showed higher temporal activity frequency than White‑necklaced Partridge or Cabot’s Tragopan.Silver Pheasant was camera‑captured most frequently in summer,and other two species in winters.All three species had two daytime activity peaks:between 6:00 a.m.and 10:00 a.m.,and between 5:00 p.m.and 7:00 p.m.,respectively.Our estimated abundance and detection probability from the N‑mixture model were variable by season.In particular,all three species showed greater abundance in summer than in winter,and estimated abundance patterns of all three species were more similar with observed cameratrapping counts in summers.Moreover,in winter,elevation had a positive impact on abundance of Silver Pheasant and Cabot’s Tragopan,but not on White‑necklaced Partridge.Conclusions:Our results demonstrate that the N‑mixture model performed well in the estimation of temporal population abundance at local fixed permanent plots in mountain habitat in southern China,based on the modeling of repeated camera‑trapping counts.The seasonal differences in abundance of the three endemic bird species and the strong effect of elevation on abundance of two species in winter were only indicative of variations in spatio‑temporal distribution within species and between species.In identifying suitable habitat for endemic pheasants,the positive elevational effect also suggests that more attention should be paid to conservation of areas with higher elevation in the Nanling Mountains.

Dealing with detection error in site occupancy surveys: what can we do with a single survey?

Aim Site occupancy probabilities of target species are commonly used in various ecological studies,e.g.to monitor current status and trends in biodiversity.Detection error introduces bias in the estimators of site occupancy.Existing methods for estimating occupancy probability in the presence of detection error use replicate surveys.These methods assume population closure,i.e.the site occupancy status remains constant across surveys,and independence between surveys.We present an approach for estimating site occupancy probability in the presence of detection error that requires only a single survey and does not require assumption of population closure or independence.In place of the closure assumption,this method requires covariates that affect detection and occupancy.Methods Penalized maximum-likelihood method was used to estimate the parameters.Estimability of the parameters was checked using data cloning.Parametric boostrapping method was used for computing confidence intervals.Important Findings The single-survey approach facilitates analysis of historical datasets where replicate surveys are unavailable,situations where replicate surveys are expensive to conduct and when the assumptions of closure or independence are not met.This method saves significant amounts of time,energy and money in ecological surveys without sacrificing statistical validity.Further,we show that occupancy and habitat suitability are not synonymous and suggest a method to estimate habitat suitability using single-survey data.