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The effect of substrate grain size on burrowing ability and distribution characteristics of Perinereis aibuhitensis
Tao Sun, Chun’e Liu, Xingzuo Li, Dongzhengyang An, Hairui Yu, Zheng Ma, Feng Liu
doi: 10.1007/s13131-019-1348-z
Perinereis aibuhitensis (Grube, 1878) lives in marine sediments of estuary or shoal areas, where substrate has some crucial environmental factors affecting its burrowing and distribution. In order to provide basic data for the habitat selection and suitability evaluations of the artificial aquaculture of P. aibuhitensis, this paper conducted a quantified analysis of its burrowing ability and explored its behavioral preferences in different substrates, including mud (<75 μm), fine sand (125–250 μm), medium sand (250–500 μm), coarse sand (500–2 000 μm), gravel (2 000–4 000 μm) and ceramsite (4 000–8 000 μm). The research results revealed that substrate grain size significantly affected the burrowing time, burrowing rate, burrowing depth and distribution rate (P<0.01). Moreover, P. aibuhitensis demonstrated preferential selections relating to substrate grain sizes, had higher burrowing ability in ceramsite, mud and fine sand compared with other substrates. The strongest burrowing ability and the highest distribution rate were observed in ceramsite. The study indicated that P. aibuhitensis was sensitive to substrate grain size, which also had an impact on its burrowing process and population distribution. In the natural sea, substrates mainly composed of mud and fine sand are fit for aquaculture and stock enhancement. Based on behavioral preferences and ecological rehabilitation function of P. aibuhitensis, this paper proposes a symbiotic system of marine animals and halophytes, and constructs an ecosystem model of " Marine fish-Halophytes-Perinereis aibuhitensis” with P. aibuhitensis as the link.
key words: Perinereis aibuhitensis, substrate, grain size, burrowing ability, distribution characteristics
Evaluation on data assimilation of a global high resolution wave-tide-circulation coupled model using the tropical Pacific TAO buoy observations
Junqiang SHI, Xunqiang YIN, Qi SHU, Bin XIAO, Fangli QIAO
doi: 10.1007/s13131-018-1196-2
In order to evaluate the assimilation results from a global high resolution ocean model, the buoy observations from tropical atmosphere ocean (TAO) during August 2014 to July 2015 are employed. The horizontal resolution of wave-tide-circulation coupled ocean model developed by The First Institute of Oceanography (FIOCOM model) is 0.1°×0.1°, and ensemble adjustment Kalman filter is used to assimilate the sea surface temperature (SST), sea level anomaly (SLA) and Argo temperature/salinity profiles. The simulation results with and without data assimilation are examined. First, the overall statistic errors of model results are analyzed. The scatter diagrams of model simulations versus observations and corresponding error probability density distribution show that the errors of all the observed variables, including the temperature, isotherm depth of 20°C (D20), salinity and two horizontal component of velocity are reduced to some extent with a maximum improvement of 54% after assimilation. Second, time-averaged variables are used to investigate the horizontal and vertical structures of the model results. Owing to the data assimilation, the biases of the time-averaged distribution are reduced more than 70% for the temperature and D20 especially in the eastern Pacific. The obvious improvement of D20 which represents the upper mixed layer depth indicates that the structure of the temperature after the data assimilation becomes more close to the reality and the vertical structure of the upper ocean becomes more reasonable. At last, the physical processes of time series are compared with observations. The time evolution processes of all variables after the data assimilation are more consistent with the observations. The temperature bias and RMSE of D20 are reduced by 76% and 56% respectively with the data assimilation. More events during this period are also reproduced after the data assimilation. Under the condition of strong 2014/2016 El Niño, the Equatorial Undercurrent (EUC) from the TAO is gradually increased during August to November in 2014, and followed by a decreasing process. Since the improvement of the structure in the upper ocean, these events of the EUC can be clearly found in the assimilation results. In conclusion, the data assimilation in this global high resolution model has successfully reduced the model biases and improved the structures of the upper ocean, and the physical processes in reality can be well produced.
key words: tropical Pacific, tropical atmosphere ocean, data assimilation, evaluation
Succession of causative species during spring blooms in the East China Sea: coupled biophysical numerical modeling
Ke SUN, Zhongfeng QIU, Yijun HE, Wei FAN, Zexun WEI
doi: 10.1007/s13131-016-0964-0
In the East China Sea (ECS), the succession of causative species responsible for blooms is a recurrent phenomenon during the spring, which changes from diatoms to dinoflagellates. Observations from space andin situ cruises captured this pattern of succession during spring of 2005. In this study, we coupled two biological models, which were developed previously forSkeletonema costatum andProrocentrum donghaiense, into a circulation model tailored for the ECS. The coupled biophysical model was used to hindcast the blooms and to test the hypothesis proposed in earlier studies that phosphate (PO43–) is the first-order decider of the succession. The coupled model successfully reproduced the hydrodynamics (as described in a companion paper by Sun et al., the spatiotemporal distribution of the chlorophylla (Chla) concentration, and the species succession reasonably well. By analyzing the effects of different factors on the surface Chla distribution, we confirmed that the offshore boundaries of the blooms were confined by PO43–. In addition, we suggest that surface wind fields may modulate the horizontal distribution of blooms. Thus, during the dispersal of blooms, surface winds coupled with PO43– may control the succession of blooms in the ECS. The proposed coupled model provides a benchmark to facilitate future improvements by including more size classes for organisms, multiple nutrient schemes, and additional processes.
key words: Skeletonema costatum, Prorocentrum donghaiense, species succession, biophysical model, East China Sea
A new merged dataset of global ocean chlorophyll a concentration with higher spatial and temporal coverage
Yanfang XIAO, Jie ZHANG, Tingwei CUI, Ling SUN
doi: 10.1007/s13131-018-1249-6
Understanding the ocean’s role in the global carbon cycle and its response to environmental change requires a high spatio-temporal resolution of observation. Merging ocean color data from multiple sources is an effective way to alleviate the limitation of individual ocean color sensors (e.g., swath width and gaps, cloudy or rainy weather, and sun glint) and to improve the temporal and spatial coverage. Since the missions of Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) and Medium-spectral Resolution Imaging Spectrometer (MERIS) ended on December 11, 2010 and May 9, 2012, respectively, the number of available ocean color sensors has declined, reducing the benefits of the merged ocean color data with respect to the spatial and temporal coverage. In present work, Medium Resolution Spectral Imager (MERSI)/FY-3 of China is added in merged processing and a new dataset of global ocean chlorophyll a (Chl a) concentration (2000–2015) is generated from the remote sensing reflectance (Rrs (λ)) observations of MERIS, Moderate-resolution imaging spectra-radiometer (MODIS)-AQUA, Visible infrared Imaging Radiometer (VIIRS) and MERSI. These data resources are first merged into unified remote sensing reflectance data, and then Chl a concentration data are inversed using the combined Chl a algorithm of color index-based algorithm (CIA) and OC3. The merged data products show major improvements in spatial and temporal coverage from the addition of MERSI. The average daily coverage of merged products is approximately 24% of the global ocean and increases by approximately 9% when MERSI data are added in the merging process. Sampling frequency (temporal coverage) is greatly improved by combining MERSI data, with the median sampling frequency increasing from 15.6% (57 d/a) to 29.9% (109 d/a). The merged Chl a products herein were validated by in situ measurements and comparing them with the merged products using the same approach except for omitting MERSI and GlobColour and MEaSUREs merged data. Correlation and relative error between the new merged Chl a products and in situ observation are stable relative to the results of the merged products without the addition of MERSI. Time series of the Chl a concentration anomalies are similar to the merged products without adding MERSI and single sensors. The new merged products agree within approximately 10% of the merged Chl a product from GlobColour and MEaSUREs.
key words: merged data, ocean color, chlorophyll a, CIA, FY-3 MERSI, VIIRS

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