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.

Implication of community-level ecophysiological parameterization to modelling ecosystem productivity:a case study across nine contrasting forest sites in eastern China

Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.

Discussion of skill improvement in marine ecosystem dynamic models based on parameter optimization and skill assessment

Marine ecosystem dynamic models(MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM skill, and it attempts to establish a technical framework to inspire further ideas concerning MEDM skill improvement. The skill of MEDMs can be improved by parameter optimization(PO), which is an important step in model calibration. An effi cient approach to solve the problem of PO constrained by MEDMs is the global treatment of both sensitivity analysis and PO. Model validation is an essential step following PO, which validates the effi ciency of model calibration by analyzing and estimating the goodness-of-fi t of the optimized model. Additionally, by focusing on the degree of impact of various factors on model skill, model uncertainty analysis can supply model users with a quantitative assessment of model confi dence. Research on MEDMs is ongoing; however, improvement in model skill still lacks global treatments and its assessment is not integrated. Thus, the predictive performance of MEDMs is not strong and model uncertainties lack quantitative descriptions, limiting their application. Therefore, a large number of case studies concerning model skill should be performed to promote the development of a scientifi c and normative technical framework for the improvement of MEDM skill.

Adjoint Assimilation in Marine Ecosystem Models and an Example of Application

This paper aims at a review of the work carried out to date on the adjoint assimilation of data in marine ecosys-tem models since 1995. The structure and feature of the adjoint assimilation in marine ecosystem models are also introduced. To illustrate the application of the adjoint technique and its merits, a 4-variable ecosystem model coupled with a 3-D physical model is established for the Bohai Sea and the Yellow Sea. The chlorophyll concentration data derived from the SeaWiFS o-cean colour data are assimilated in the model with the technique. Some results are briefly presented.

Role of cancer stem cell ecosystem on breast cancer metastasis and related mouse models

Breast cancer metastasis is responsible for most breast cancer-related deaths and is influenced by many factors within the tumor ecosystem,including tumor cells and microenvironment.Breast cancer stem cells(BCSCs)constitute a small population of cancer cells with unique characteristics,including their capacity for self-renewal and differentiation.Studies have shown that BCSCs not only drive tumorigenesis but also play a crucial role in promoting metastasis in breast cancer.The tumor microenvironment(TME),composed of stromal cells,immune cells,blood vessel cells,fibroblasts,and microbes in proximity to cancer cells,is increasingly recognized for its crosstalk with BCSCs and role in BCSC survival,growth,and dissemination,thereby influencing metastatic ability.Hence,a thorough understanding of BCSCs and the TME is critical for unraveling the mechanisms underlying breast cancer metastasis.In this review,we summarize current knowledge on the roles of BCSCs and the TME in breast cancer metastasis,as well as the underlying regulatory mechanisms.Furthermore,we provide an overview of relevant mouse models used to study breast cancer metastasis,as well as treatment strategies and clinical trials addressing BCSC-TME interactions during metastasis.Overall,this study provides valuable insights for the development of effective therapeutic strategies to reduce breast cancer metastasis.

A statistical dynamics model of the marine ecosystem and its application in Jiaozhou Bay

Models of marine ecosystem dynamics play an important role in revealing the evolution mechanisms of marine ecosystems and in forecasting their future changes. Most traditional ecological dynamics models are established based on basic physical and biological laws, and have obvious dynamic characteristics and ecological significance. However, they are not flexible enough for the variability of environment conditions and ecological processes found in offshore marine areas, where it is often difficult to obtain parameters for the model, and the precision of the model is often low. In this paper, a new modeling method is introduced, which aims to establish an evolution model of marine ecosystems by coupling statistics with differential dynamics. Firstly, we outline the basic concept and method of inverse modeling of marine ecosystems. Then we set up a statistical dynamics model of marine ecosystems evolution according to annual ecological observation data from Jiaozhou Bay. This was done under the forcing conditions of sea surface temperature and surface irradiance and considering the state variables of phytoplankton, zooplankton and nutrients. This model is dynamic, makes the best of field observation data, and the average predicted precision can reach 90% or higher. A simpler model can be easily obtained through eliminating the terms with smaller contributions according to the weight coefficients of model differential items. The method proposed in this paper avoids the difficulties of obtaining and optimizing parameters, which exist in traditional research, and it provides a new path for research of marine ecological dynamics.

Development and Application of a Marine Ecosystem Dynamic Model

A nutrient-phytoplankton-zooplankton-detritus （NPZD） type of marine ecosystem model was developed in this study,and was further coupled to a three-dimensional primitive-equation ocean circulation model with a river discharge model and a solar radiation model to reproduce the dynamics of the low nutrition level in the Bohai Sea （BS）.The simulation results were validated by observations and it was shown that the seasonal variation in the phytoplankton biomass could be characterized by the double-peak structure,corresponding to the spring and summer blooms,respectively.It was also found that both nitrogen and phosphate declined to the lowest level after the onset of the summer bloom,since the large amounts of nutrients were exhausted by phytoplankton for photosynthesis,and the concentrations of nutrients could resume in winter after a series of the biogeochemical-physical processes.By calculating the nitrogen/phosphorus （N/P） ratio,it is easy to see that the phytoplankton dynamics is nitrogen-limited as a whole in BS,though the phosphorus limitation may occur in the Yellow River （YR） Estuary where the input of riverine nitrogen is much more than that of phosphate.

Numerical study on spatially varying control parameters of a marine ecosystem dynamical model with adjoint method

Based on the simulation of a marine ecosystem dynamical model in the Bohai Sea, the Yellow Sea and the East China Sea, chlorophyll data are assimilated to study the spatially varying control parameters （CPs） by using the adjoint method. In this study, the CPs at some grid points are selected as the independent CPs, while the CPs at other grid points can be obtained through linear interpolation with the independent CPs. The independent CPs are uniformly selected from each 30′ × 30′area, and we confirm that the optimal influence radius is 1.2° by a twin experiment. In the following experiments, when only the maximum growth rate of phytoplankton （Vm） is estimated by two given types of spatially varying CPs, the mean relative errors of Vm are 1.22% and 0.94% while the decrease rates of the mean error of chlorophyll in the surface are 94.6% and 95.8%, respectively. When the other four CPs are estimated respectively, the results are also satisfactory, which indicates that the adjoint method has a strong ability of optimizing the prescribed CP with spatial variations. However, when all these five most important CPs are estimated simultaneously, the collocation of the changing trend of each parameter influences the estimation results remarkably. Only when the collocation of the changing trend of each parameter is consistent with the ecological mechanisms which influence the growth of the phytoplankton in marine ecosystem, could the five most important CPs be estimated more accurately.

Research on stability and Hopf bifurcation of marine ecosystem dynamics models

The predictability of marine ecosystem dynamics models is one of the most vital factors to limit their practical applications, of which the stability is the fundamental condition. In order to discuss the stability and Hopf bifurcation of marine ecosystem dynamics models, an approach based on a theorem termed dimension reduction was proposed and further applied in the mass-conservative nutrient-phytoplankton-zooplankton-detritus（NPZD） model in this paper. Results showed that the nonsingular equilibrium point of NPZD model was analytically stable in use of the dimension reduction theorem and the Hopf bifurcation might occur when model parameters changed along the threshold values. The analytical results of the NPZD model were further verified by numerical simulation in this study. It can be concluded that this approach based on the dimension reduction theorem is well applicable to the theoretical analysis of a kind of stability problems and Hopf bifurcation of massconservative systems.

Forward modeling of marine DC resistivity method for a layered anisotropic earth

Since the ocean bottom is a sedimentary environment wherein stratification is well developed, the use of an anisotropic model is best for studying its geology. Beginning with Maxwell＇s equations for an anisotropic model, we introduce scalar potentials based on the divergence-free characteristic of the electric and magnetic （EM） fields. We then continue the EM fields down into the deep earth and upward into the seawater and couple them at the ocean bottom to the transmitting source. By studying both the DC apparent resistivity curves and their polar plots, we can resolve the anisotropy of the ocean bottom. Forward modeling of a high-resistivity thin layer in an anisotropic half-space demonstrates that the marine DC resistivity method in shallow water is very sensitive to the resistive reservoir but is not influenced by airwaves. As such, it is very suitable for oil and gas exploration in shallowwater areas but, to date, most modeling algorithms for studying marine DC resistivity are based on isotropic models. In this paper, we investigate one-dimensional anisotropic forward modeling for marine DC resistivity method, prove the algorithm to have high accuracy, and thus provide a theoretical basis for 2D and 3D forward modeling.

Spatio-temporal Evolution of Marine Fishery Industry Ecosystem Vulnerability in the Bohai Rim Region

The building of the ocean power strategy and the implementation of the blue agriculture plan urgently need to strengthen the sustainable development of marine fishery.Taking vulnerability as the starting point, this paper constructs the vulnerability index system of marine fishery industry ecosystem from the aspects of sensitivity and response capacity, and combines the entropy method with the Topsis to comprehensively analyze the spatio-temporal evolution characteristics of vulnerability of marine fishery industry ecosystem in the Bohai Rim Region from 2001 to 2015.The results show that: 1) In the time dimension, from 2001 to 2015, the vulnerability of the marine fishery industry ecosystem in the Bohai Rim Region shows a fluctuant and degressive trend;2) In the spatial dimension, the spatial distribution of the marine fishery industry ecosystem vulnerability in the Bohai Rim Region presents the gradient characteristics which shows high vulnerability in the east and low vulnerability in the west.According to the evolution track of the system’s vulnerability level, the vulnerability of the marine fishery industry ecosystem is divided into ‘declining’ and ‘stable’ types of evolutionary structures;3) The development of marine fishery in the Bohai Rim Region needs to be derived from the marine fishery’s ecological environment and the industrial development mode and structure, which can improve the marine environment remediation efforts, optimize the marine fishery industry structure, vigorously focus on pelagic fishery, and enhance the introduction of marine fishery’s science and technology talents, etc.Then, the marine fishery’s development in the Bohai Rim Region will be moving in the green, circular and sustainable direction.

Studies on the role of marine bacteria in the upwelling ecosystem——Ⅰ.Bacterial biomass in the upwelling regions

-Six cruises were carried out off the south bank of Fujian - Taiwan during the period of December 21, 1987 to November 15, 1988 to estimate the contribution of bacterial biomass carbon (BBC) to the totai particulate organic pools using epifluorescent microscopic technique. The results show that the standing crop of bacteria fluctuated from 0. 95 to 66. 60 mg /m3 (dry weight). Upwelling phenomena appeared in the region around Nanpeng Island in summer while in the region of Waixie in all seasons. The average value of BBC was 27. 60(±6. 08)mg/m3and 21. 32 (±2. 34) mg/m3 respectively. The seasonal and spatial distribution is discussed in relation to environmental factors as well as upwelling phenomena. The role of bacteria in the flow of material and energy in the upwelling ecosystem is emphasized.

SIMPLE ECOSYSTEM MODEL OF THE CENTRAL PART OF THE EAST CHINA SEA IN SPRING

This paper’s simple ecological model to simulate the ecosystem variation and the vertical carbon flux in the central part of the East China Sea in spring, inter-reated the phytoplankton, zooplankton,autotrophic and heterotrophic bacterioplankton, nitrate, and dissolved organic carbon (DOC) in a run lasting 90 days. Except for DOC, because of poor observation precision,the major seasonal features of the vertical distribution for these components can be simulated by this model. The results show that spring bloom is just a short period of 1-2 weeks and that deposit carbon flux at the bottom interface is about 200 mg /m2 ·d in the first 20 days and then reaches its maximum of 1500mg/m2·d about 2 months later after the spring bloom.

Development of a modified Mooney-Rivlin constitutive model for rubber to investigate the effects of aging and marine corrosion on seismic isolated bearings

In this study, aging and marine corrosion tests of a large number of rubber material and rubber bearings have been carried out. The constitutive Mooney-Rivlin model parameters for a rubber isolated bearing have been determined. By applying the least-square method to the experimental data, the relationships between the aging time and the marine corrosion time with the constants in the constitutive model for a rubber beating have been derived. Next, the Mooney-Rivlin model has been modified accordingly. Further, using the modified Mooney-Rivlin model and the Abaqus software, the performance of the rubber isolated bearings has been simulated. The simulation results have been compared to the experimental results so as to verify the accuracy of the modified model. The comparison shows that the maximum errors for the vertical and horizontal stiffnesses are 16.8% and 0.49%, respectively. Since these errors are considered acceptable, the accuracy of the modified constitutive model can be considered verified. The results of this study can provide theoretical support for the performance study on rubber isolated bearings under the complex ocean environment and the life-cycle performance evaluation of bridges and other offshore structures.

A spatial-explicit dynamic vegetation model that couples carbon,water,and nitrogen processes for arid and semiarid ecosystems

Arid and semiarid ecosystems, or dryland, are important to global biogeochemical cycles. Dryland＇s community structure and vegetation dynamics as well as biogeochemical cycles are sensitive to changes in climate and atmospheric composition. Vegetation dynamic models has been applied in global change studies, but the com- plex interactions among the carbon （C）, water, and nitrogen （N） cycles have not been adequately addressed in the current models. In this study, a process-based vegetation dynamic model was developed to study the responses of dryland ecosystems to environmental changes, emphasizing on the interactions among the C, water, and N proc- esses. To address the interactions between the C and water processes, it not only considers the effects of annual precipitation on vegetation distribution and soil moisture on organic matter （SOM） decomposition, but also explicitly models root competition for water and the water compensation processes. To address the interactions between C and N processes, it models the soil inorganic mater processes, such as N mineralization/immobilization, denitrifica- tion/nitrification, and N leaching, as well as the root competition for soil N. The model was parameterized for major plant functional types and evaluated against field observations.

Modeling Marine Stratocumulus with a Detailed Microphysical Scheme

A one-dimensional 3rd-order turbulence closure model with size-resolved microphysics and radiative transfer has been developed for investigating aerosol and cloud interactions of the stratocumulus-topped marine boundary layer. A new method is presented for coupling between the dynamical model and the microphysical model. This scheme allows the liquid water related correlations to be directly calculated rather than parameterized. On 21 April 2001, a marine stratocumulus was observed by the Caesar aircraft over the west Pacific Rim south of Japan during the 2001 APEX/ACE-Asia field measurements. This cloud is simulated by the model we present here. The model results show that the general features of the stratocumulus-topped marine boundary layer predicted by the model are in agreement with the measurements. A new onboard cloud condensation nuclei (CCN) counter provides not only total CCN number concentration (as the traditional CCN counters do at a certain supersaturation) but also the CCN size distribution information. Using these CCN data, model responses to different CCN initial concentrations are examined. The model results are consistent with both observations and expectations. The numerical results show that the cloud microphysical properties are changed fundamentally by different initial CCN concentrations but the cloud liquid water content does not differ significantly. Different initial CCN loadings have large impacts on the evolution of cloud microstructure and radiation transfer while they have a modest effect on thermodynamics. Increased CCN concentration leads to significant decrease of cloud effective radius.

Quantitative model of trophic interactions in Beibu Gulf ecosystem in the northern South China Sea

A mass-balanced model was constructed to determine the flow-energy in a community of fishes and invertebrates in the Beibu Gulf, northern South China Sea using Ecopath and Ecosim software. Input parameters were taken from the literature, except for the biomass of fish groups which was obtained from trawl surveys during October 1997 to May 1999 in the study area. The model consisted of 16 functional groups （boxes）, including one marine mammal and seabirds, each representing organisms with a similar role in the food web, and only covered the main trophic flow in the Beibu Gulf ecosystem. The results showed that the food web of Beibu Gulf was dominated by the detrital path and benthic invertebrates played a significant role in transferring energy from the detritus to higher trophic levels; phytoplankton was a primary producer and most utilized as a food source. Fractional trophic levels ranged from 1.0 to 4.08 with marine mammals occupying the highest trophic level. Using network analysis, the system network was mapped into a linear food chain and six discrete trophic levels were found with a mean transfer efficiency of 16.7% from the detritus, 16.2% from the primary producer within the ecosystem. The biomass density of the commercially utilized species estimated by the model is 8.46 t/km^2, only O. 48% of the net primary production.

Marine Mobile Wireless Channel Modeling Based on Improved Spatial Partitioning Ray Tracing

In 5G era,it is expected to achieve wireless network coverage including offshore areas.Modeling of marine wireless channels is the basis of constructing a marine communication system.In this paper,a communication scene between an unmanned aerial vehicle(UAV)and a boat is simulated to study the marine wireless channel.Firstly,an improved spatial partitioning ray tracing algorithm is proposed to track the propagation path of electromagnetic waves at sea surface.Secondly,a mobile channel is simulated and modeled based on the track results.Finally,a loss measurement is carried out in the coastal waters based on the simple wireless channel loss measuring platform,and a path loss propagation model is built.Then we compare the actual measurement data with the simulation results and find that the two are have good consistency,which further verifies the reliability of the simulation.

Integrating ecosystem services evaluation and landscape pattern analysis into urban planning based on scenario prediction and regression model

Urban planning has become a widely concern for minimizing the negative effects of urban expansion on terrestrial ecosystems. We developed an interdisciplinary modeling framework to evaluate the effectiveness and shortcomings of urban expansion management strategies. A three-step method was applied to Yinchuan Plain in the northwestern of China, including(1)analyzing the relationship between landscape pattern and ecosystem service values through mathematical statistics;(2) predicting landscape pattern and ecosystem services change under different scenarios based on cellular automaton model(SLEUTH-3r model); and(3) designing and validating optimized scenario through integrating historical analysis experiments and future multi-comparison suggestions. Results have suggested that landscape composition and configuration can significantly affect regional ecosystem service values, especially the connectivity and shape of landscape. Compact urban growth policy and medium environment protection policy are the appropriate setting for urban expansion plan. Optimization validation of the combined designed scenario implied the reliability of this method. Our results highlighted the significance of integrating application of landscape pattern analysis, ecosystem service value evaluation,model simulation and multi-scenario prediction in urban planning.

Biotic communities of the marine ecosystem in Meizhou Bay

The current situation of biotic communities in Meizhou Bay is presented in this paper.The species composition,seasonal variation,and distribution of phytoplankton,zooplankton, red tide organisms,fishes,and benthos in Meizhou Bay were investigated,and the content of chlorophyll a and primary production and their seasonal variation were also determined.The water quality of Meizhou Bay was monitored by measuring the density of Escherichia coli. Results reveal that there is a great variety of species in Meizhou Bay and the water in Meizhou Bay is oligotrophic.But the individual numbers of various organisms are very low, especially those of algae.Moreover,there are more than 40 species of red tide organisms and there exist opportunities of red tides between May and November.All these demand cautious be taken in the future development of this area although it has great environment capacity.