Community characteristics of macrobenthos in the Huanghe(Yellow River) Estuary during water and sediment discharge regulation

The community characteristics of macrobenthos in the Huanghe（Yellow River） Estuary is influenced by a combination of natural and anthropogenic factors. Here, we investigated short-term changes（1-month） in macrobenthic community structure in response to water and sediment discharge regulation（WSDR） in 2011.Specifically, we sampled the macrobenthos at 18 sampling stations situated at four distances（5, 10, 20, and 40 km）from the mouth of the Huanghe Estuary before（mid-June）, during（early-July）, and after（mid-July） WSDR. The results showed that a total of 73, 72, and 85 species were collected before, during, and after WSDR, respectively.Then, 13, 1, and 16 dominant species were detected at this three periods. Four phyla were primarily detected at all three periods（Annelida, Mollusca, Arthropoda, and Echinodermata）. However, while Mollusca and Annelida were the most important phyla in our study, Echinodermata and Annelida were the most important phyla in 1982,demonstrating major changes to community structure over a 3-decadal period. All stations were of high quality BOPA index before WSDR, whereas two and three stations were of reduced quality BOPA index during and after WSDR, respectively. The results of ABC curves showed that had incurred disturbed conditions after human activities WSDR. Most important of all, multivariate analyses and RDA analysis indicated that the structure of the macrobenthic community was closely linked to environment factors, including that organic content factor caused the distribution of macrobenthic community mostly during WSDR, while water depth after WSDR affected the macro benthos community structure seriously, and during WSDR, the environment factor influencing it was not single, including organic content, sulfide content, Hg and As. These differences may have been due to changes in water transparency negatively impacting the growth and development of macrobenthos, due to specific lifehistory requirements. Our results demonstrate that anthropogenic activity is having both long-term（3 decadal）and short term（1-month） impacts on the structure of the macrobenthic community of the Huanghe Estuary. In conclusion, human activities WSDR influence the habitat environment of macro benthos, including the water temperature, nutrients, bioturbation, and so on. Therefore, we suggest the necessity to strengthen regulations of land-derived organic pollutant input to maintain the ecological balance of the Huanghe Estuary.

A New model to forecast fishing ground of Scomber japonicus in the Yellow Sea and East China Sea

The pelagic species is closely related to the marine environmental factors, and establishment of forecasting model of fishing ground with high accuracy is an important content for pelagic fishery. The chub mackerel（Scomber japonicus） in the Yellow Sea and East China Sea is an important fishing target for Chinese lighting purse seine fishery. Based on the fishery data from China＇s mainland large-type lighting purse seine fishery for chub mackerel during the period of 2003 to 2010 and the environmental data including sea surface temperature（SST）, gradient of the sea surface temperature（GSST）, sea surface height（SSH） and geostrophic velocity（GV）, we attempt to establish one new forecasting model of fishing ground based on boosted regression trees. In this study, the fishing areas with fishing effort is considered as one fishing ground, and the areas with no fishing ground are randomly selected from a background field, in which the fishing areas have no records in the logbooks. The performance of the forecasting model of fishing ground is evaluated with the testing data from the actual fishing data in 2011. The results show that the forecasting model of fishing ground has a high prediction performance, and the area under receiver operating curve（AUC） attains 0.897. The predicted fishing grounds are coincided with the actual fishing locations in 2011, and the movement route is also the same as the shift of fishing vessels, which indicates that this forecasting model based on the boosted regression trees can be used to effectively forecast the fishing ground of chub mackerel in the Yellow Sea and East China Sea.