Temporal variations of food web in a marine bay ecosystem based on LIM-MCMC model

Climate change has led to significant fluctuations in marine ecosystems,including alterations in the structure and function of food webs and ecosystem status.Coastal ecosystems are critical to the functioning of the earth’s lifesupporting systems.However,temporal variations in most of these ecosystems have remained unclear so far.In this study,we employed a linear inverse model with Markov Chain Monte Carlo(LIM-MCMC)combined with ecological network analysis to reveal the temporal variations of the food web in Haizhou Bay of China.Food webs were constructed based on diet composition data in this ecosystem during the year of 2011 and 2018.Results indicated that there were obvious temporal variations in the composition of food webs in autumn of 2011 and 2018.The number of prey and predators for most species in food web decreased in 2018 compared with 2011,especially for Trichiurus lepturus,zooplankton,Amblychaeturichthys hexanema,and Loligo sp.Ecological network analysis showed that the complexity of food web structure could be reflected by comprehensive analysis of compartmentalized indicators.Haizhou Bay ecosystem was more mature and stable in 2011,while the ecosystem’s self-sustainability and recovery from disturbances were accelerated from 2011 to 2018.These findings contribute to our understanding of the dynamics of marine ecosystems and highlight the importance of comprehensive analysis of marine food webs.This work provides a framework for assessing and comparing temporal variations in marine ecosystems,which provides essential information and scientific guidance for the Ecosystem-based Fisheries Management.

Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters

Habitat suitability index(HSI)models have been widely used to analyze the relationship between species abundance and environmental factors,and ultimately inform management of marine species.The response of species abundance to each environmental variable is different and habitat requirements may change over life history stages and seasons.Therefore,it is necessary to determine the optimal combination of environmental variables in HSI modelling.In this study,generalized additive models(GAMs)were used to determine which environmental variables to be included in the HSI models.Significant variables were retained and weighted in the HSI model according to their relative contribution(%)to the total deviation explained by the boosted regression tree(BRT).The HSI models were applied to evaluate the habitat suitability of mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent areas in 2011 and 2013–2017.Ontogenetic and seasonal variations in HSI models of mantis shrimp were also examined.Among the four models(non-optimized model,BRT informed HSI model,GAM informed HSI model,and both BRT and GAM informed HSI model),both BRT and GAM informed HSI model showed the best performance.Four environmental variables(bottom temperature,depth,distance offshore and sediment type)were selected in the HSI models for four groups(spring-juvenile,spring-adult,falljuvenile and fall-adult)of mantis shrimp.The distribution of habitat suitability showed similar patterns between juveniles and adults,but obvious seasonal variations were observed.This study suggests that the process of optimizing environmental variables in HSI models improves the performance of HSI models,and this optimization strategy could be extended to other marine organisms to enhance the understanding of the habitat suitability of target species.

Fishery biology of whitespotted conger Conger myriaster(Brevoort, 1856) in the Yellow Sea and East China Sea

Whitespotted conger Conger myriaster is a commercially important species in the seas around China, Korea and Japan. The coastal waters of China serve as an important feeding ground for congers, but the spatio-temporal variations in the fishery and biological characteristics of the population have been rarely evaluated and less well understood in this area. We studied the growth, spawning and feeding characteristics of C. myriaster on the basis of samples collected from October 2016 to April 2017 in the Yellow Sea and East China Sea. A total of 529 specimens were collected, with ages ranging from 1 to 6 years and total length ranging from 132 mm to 834 mm. The parameters of von Bertalanffy growth equation L∞ and k were 1 026 mm and 0.226 a^–1, respectively;the sex ratio was 88:0 (female: male) in the East China Sea and 2.67:1 in the South Yellow Sea;the development stage of ovary ranged from peri-nucleolus stage to secondary yolk globule stage, and the testis of two males was at midmeiotic stage;Crustacean was the major prey for conger of small length, and food source shift to fish with somatic growth. The results showed substantial differences from previous studies in Japan and Korean waters, as well as from China seas in the 1980s, suggesting potential spatiotemporal changes in the biological characteristics of C. myriaster. This study may improve current understanding of the fishery biology of C. myriaster in the Yellow Sea and East China Sea.

Spatio-temporal distribution of Konosirus punctatus spawning and nursing ground in the South Yellow Sea

In recent years,Konosirus punctatus has accounted for a large portion in catch composition and become important economic species in the South Yellow Sea.However,the distribution of K.punctatus early life stages is still poorly understood.In this study,generalized additive models with Tweedie distribution were used to analyze the relationships between K.punctatus ichthyoplankton and environmental factors(longitude and latitude,sea surface temperature(SST),sea surface salinity(SSS)and depth),and predict distribution K.punctatus spawning ground and nursing ground,based on samplings collected in 6 months during 2014–2017.The results showed that K.punctatus’spawning ground were mainly distributed in central and north study area(from 33.0°N to 37.0°N).By comparison,the nursing ground shifted southward,which were approximately located along central and south coast of study area(from 31.7°N to 35.5°N).The optimal models identified that suitable SST,SSS and depth for eggs were 19–26℃,25–30 and 9–23 m,respectively.The suitable SSS for larvae were 29–31.The K.punctatus spawning habit might have changed in the past decades,which was a response to increasing SST and fishing pressure.That needs to be proved in further study.The study provides references of conservation and exploitation for K.punctatus.

Combining otolith elemental signatures with multivariate analytical models to verify the migratory pattern of Japanese Spanish mackerel(Scomberomorus niphonius) in the southern Yellow Sea

Japanese Spanish mackerel,Scomberomorus niphonius,is a commercially important,highly migratory species that is widely distributed throughout the northwestern Pacific region.However,its life history and migratory patterns are only partially understood.This study used otolith chemistry to investigate the migratory pattern of S.niphonius in the southern Yellow Sea,an important fishing ground.Transverse sections of otoliths from 15 age-1 spawning or spent individuals,comprising up to one complete migration cycle,were analyzed from the core to the margin by using laser ablation inductively coupled plasma mass spectrometry.The ratios of the element to Ca were integrated with microstructural analysis to produce age-related elemental profiles.Combining multielemental analysis of otolith composition with multivariate analytical models,we quantified structural changes in otolith chemistry profiles.Results revealed there were diverse changing patterns of otolith chemistry profiles for detected elements and the elements of Na,Mg,Sr and Ba were important for the chronological signal.Five clusters were identified through chronological clustering,representing the five life stages from the early stage to the spawning stage.Variation of Ba:Ca ratio was most informative,showing a step-decreasing pattern in the first four stages and a rebound in the spawning stage.These results support the hypothesized migratory pattern of S.niphonius:hatching and spending their early life in the coastal sandy ridges system of the southern Yellow Sea,migrating northeastward and offshore for feeding during juvenile stage,aggregating in early October and migrating outward to the Jeju Island for wintering,and returning to the coastal waters for spawning.This study demonstrated the value of life-history related otolith chemistry profiles combined with multivariate analytical models was a means to verify the migration patterns of S.niphonius at regional scales with potential application in fisheries assessment and management.

Impacts of sample size for stomach content analysis on the estimation of ecosystem indices

This study used Ecopath model of the Jiaozhou Bay as an example to evaluate the effect of stomach sample size of three fish species on the projection of this model. The derived ecosystem indices were classified into three categories:(1) direct indices, like the trophic level of species, influenced by stomach sample size directly;(2)indirect indices, like ecology efficiency(EE) of invertebrates, influenced by the multiple prey-predator relationships;and(3) systemic indices, like total system throughout(TST), describing the status of the whole ecosystem. The influences of different stomach sample sizes on these indices were evaluated. The results suggest that systemic indices of the ecosystem model were robust to stomach sample sizes, whereas specific indices related to species were indicated to be with low accuracy and precision when stomach samples were insufficient.The indices became more uncertain when the stomach sample sizes varied for more species. This study enhances the understanding of how the quality of diet composition data influences ecosystem modeling outputs. The results can also guide the design of stomach content analysis for developing ecosystem models.

Evaluating the eff ect of input variables on quantifying the spatial distribution of croaker Johnius belangerii in Haizhou Bay,China

A habitat model has been widely used to manage marine species and analyze relationship between species distribution and environmental factors.The predictive skill in habitat model depends on whether the models include appropriate explanatory variables.Due to limited habitat range,low density,and low detection rate,the number of zero catches could be very large even in favorable habitats.Excessive zeroes will increase the bias and uncertainty in estimation of habitat.Therefore,appropriate explanatory variables need to be chosen first to prevent underestimate or overestimate species abundance in habitat models.In addition,biotic variables such as prey data and spatial autocovariate(SAC)of target species are often ignored in species distribution models.Therefore,we evaluated the eff ects of input variables on the performance of generalized additive models(GAMs)under excessive zero catch(>70%).Five types of input variables were selected,i.e.,(1)abiotic variables,(2)abiotic and biotic variables,(3)abiotic variables and SAC,(4)abiotic,biotic variables and SAC,and(5)principal component analysis(PCA)based abiotic and biotic variables and SAC.Belanger’s croaker Johnius belangerii is one of the dominant demersal fish in Haizhou Bay,with a large number of zero catches,thus was used for the case study.Results show that the PCA-based GAM incorporated with abiotic and biotic variables and SAC was the most appropriate model to quantify the spatial distribution of the croaker.Biotic variables and SAC were important and should be incorporated as one of the drivers to predict species distribution.Our study suggests that the process of input variables is critical to habitat modelling,which could improve the performance of habitat models and enhance our understanding of the habitat suitability of target species.

Feeding ecology of Japanese Spanish mackerel(Scomberomorus niphonius)along the eastern coastal waters of China

Feeding activities provide necessary nutrition and energy to support the reproduction and development of fish populations.The feeding ecology and dietary plasticity of fish are important factors determining their recruitment and population dynamics.As a top predator,Japanese Spanish mackerel(Scomberomorus niphonius)supports one of the most valuable fisheries in China.In this study,the feeding ecology and diet composition of Japanese Spanish mackerel spawning groups were analysed based on samples collected from six spawning grounds along the eastern coastal waters of China during spring(March to May)in 2016 and 2017.Both stomach contents and stable isotope analysis were conducted.Stomach content analysis showed that spawning groups of Japanese Spanish mackerel mainly fed on fish,consuming more than 40 different prey species.Diets were significantly different among sampling locations.The most important prey species were Stolephorus in Fuzhou,Japanese anchovy Engraulis japonicus in Xiangshan,Euphausia pacifica in Lüsi,sand lance Ammodytes personatus in Qingdao and Weihai,and Leptochela gracilis in Laizhou Bay.Stable isotope analysis showed that the trophic level of Japanese Spanish mackerel was relatively high and generally increased with latitude from south to north.In the 1980 s,the diet of Japanese Spanish mackerel was dominated solely by Japanese anchovies in the eastern coastal waters of China.The results in the present study showed that the importance of Japanese anchovies declined considerably,and this fish was not the most dominant diet in most of the investigated waters.Both the spatial variations in diet composition and changes in the dominant diet over the long term indicated the high adaptability of Japanese Spanish mackerel to the environment.Combining the results of stomach analysis and stable isotope analysis from different tissues provided more comprehensive and accurate dietary information on Japanese Spanish mackerel.The study provides essential information about the feeding ecology of Japanese Spanish mackerel and will benefit the management of its populations in the future.

Performance evaluation of fixed-station sampling design for a fishery-independent survey with multiple objectives

Fixed-station sampling design was widely used in fishery-independent surveys because of its characteristics of convenient sampling station setting,but the non-probabilistic(fixed)nature made it more uncertainty of drawing inferences on population.The performance of fixed-station sampling design for multispecies survey has not been evaluated,and we are uncertain if the design could detect the temporal trends of different populations in multispecies fishery-independent survey.In this study,spatial distribution of abundance indices for three species with different spatial distribution patterns including small yellow croaker(Larimichthys polyactis),whitespotted conger(Conger myriaster)and Fang’s blenny(Enedrias fangi)were simulated using ordinary kriging interpolation as the“true”population distribution.The performance of fixed-station sampling design was compared with simple random sampling design by resampling the simulated“true”populations in this simulation study.The results showed that the fixed-station sampling design had the power to detect the seasonal trends of species abundance.The effectiveness of fixed-station sampling design were different in different species distribution patterns.When the species had even distribution,fixed-station sampling design could get high quality abundance data;when the distribution was uneven with heterogeneity or patchiness,fixed-station sampling design tended to underestimate or overestimate the abundance.Evidently,the estimates of abundance index based on the fixedstation sampling design must be calibrated cautiously while applying them for fisheries stock assessment and management.This study suggested that fixed-station sampling design could catch the temporal dynamics of population abundance,but the abundance estimates from the fixed-station sampling design could not be treated as the absolute estimates of populations.

Evaluating multispecies survey designs using a joint species distribution model

Survey designs should be efficient as marine survey programs are usually expensive and time-consuming;however,surveys have rarely been evaluated for multiple species.In the present study,we evaluated multispecies fisheries surveys with respect to three influential factors,i.e.,sampling methods,estimation methods and sample size.A joint species distribution model(JSDM)developed in north Yellow Sea,China was used as the operating model to simulate the spatial distribution of multiple species simultaneously.We examined the precision of multispecies abundance estimation using diverse sampling methods[random sampling(RDS),systematic sampling(SYS),stratified random sampling(SRS),generalized random-tessellation stratified sampling(GRT)and spatial coverage sampling(SPC)],estimation methods[arithmetic mean(Arm),universal kriging(Ukr),multivariate distribution model(Mvd),and boral model(Brm)],and a range of sample sizes(from 30 to 300).The results showed significant differences in estimation among sampling methods,where GRT and SYS yielded less relative absolute bias(RAB)over all and RDS showed the least precision.Regarding estimation methods,Mvd and Arm showed the best performances and Brm yielded the least precision.Significant interactions existed between sampling and estimation methods.Arm worked best with GRT,likewise Mvd with SYS and Ukr with SPC.SPC and Mvd showed the best performances for a small sample size(N=30),and all sampling and estimation methods provided similar results for a large sample size(N=300).Generally,doubling sample size resulted in a decrease of RAB by 0.097 on average,a rate depending on species,sampling and estimation methods.This study contributed to an integrative framework for evaluating designs of multispecies fisheries surveys.

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.