林草湿荒地生态系统综合监测方法探讨

林草湿荒地生态系统作为地球生态系统不可或缺的组成部分,对维护生物多样性及全球气候稳定具有关键作用。本文深入探讨了林草湿荒地生态系统的综合监测方法。首先,强调了该系统对长期、精细化监测的迫切需求,并阐述了其重要性。随后,提出了一种综合监测框架,该框架集成了遥感监测、现场观测与生态模型模拟等多种技术手段,实现了对物种多样性、生物量及气候因素等关键生态参数的全面监测。研究结果显示,该方法不仅能精准捕捉林草湿荒地生态系统的动态变化,还能有效预测潜在的生态问题,为生态保护与恢复策略的制定提供了坚实的科学依据。本文的研究成果对于科学家和决策者深入理解林草湿荒地生态系统,制定科学合理的保护政策,具有重要的理论指导意义和实际应用价值。

Simulation logging experiment and interpretation model of array production logging measurements in a horizontal well

The distributions of local velocity and local phase holdup along the radial direction of pipes are complicated because of gravity differentiation,and the distribution of fluid velocity fi eld changes along the gravity direction in horizontal wells.Therefore,measuring the mixture flow and water holdup is difficult,resulting in poor interpretation accuracy of the production logging output profile.In this paper,oil–water two-phase flow dynamic simulation logging experiments in horizontal oil–water two-phase fl ow simulation wells were conducted using the Multiple Array Production Suite,which comprises a capacitance array tool(CAT)and a spinner array tool(SAT),and then the response characteristics of SAT and CAT in diff erent fl ow rates and water cut production conditions were studied.According to the response characteristics of CAT in diff erent water holdup ranges,interpolation imaging along the wellbore section determines the water holdup distribution,and then,the oil–water two-phase velocity fi eld in the fl ow section was reconstructed on the basis of the fl ow section water holdup distribution and the logging value of SAT and combined with the rheological equation of viscous fl uid,and the calculation method of the oil–water partial phase fl ow rate in the fl ow section was proposed.This new approach was applied in the experiment data calculations,and the results are basically consistent with the experimental data.The total fl ow rate and water holdup from the calculation are in agreement with the set values in the experiment,suggesting that the method has high accuracy.

River Flow Control on the Phytoplankton Dynamics of Chesapeake Bay

Recent observations support an emerging paradigm that climate variability dominates nutrient enrichment in costal eco-systems, which can explain seasonal and inter-annual variability of phytoplankton community composition, biomass (Chl-a), and primary production (PP). In this paper, we combined observation and modeling to investigate the regulation of phytoplankton dynamics in Chesapeake Bay. The year we chose is 1996 that has high river runoff and is usually called a 'wet year'. A 3-D physical-biogeochemical model based on ROMS was developed to simulate the seasonal cycle and the regional distributions of phytoplankton biomass and primary production in Chesapeake Bay. Based on the model results, NO3 presents a strong contrast to the river nitrate load during spring and the highest concentration in the bay reaches around 80 mmol Nm-3 . Compared with the normal year, phytoplankton bloom in spring of 1996 appears in lower latitudes with a higher concentration. Quantitative comparison between the modeled and observed seasonal averaged dissolved inorganic nitrogen concentrations shows that the model produces reliable results. The correlation coefficient r2 for all quantities exceeds 0.95, and the skill parameter for the four seasons is all above 0.95.

Inverted Simulations Demonstrating Strong Ecological Fallacies in Cohort Studies

We start with a description of the statistical inferential framework and the duality between observed data and the true state of nature that underlies it. We demonstrate here that the usual testing of dueling hypotheses and the acceptance of one and the rejection of the other is a framework which can often be faulty when such inferences are applied to individual subjects. This follows from noting that the statistical inferential framework is predominantly based on conclusions drawn for aggregates and noting that what is true in the aggregate frequently does not hold for individuals, an ecological fallacy. Such a fallacy is usually seen as problematic when each data record represents aggregate statistics for counties or districts and not data for individuals. Here we demonstrate strong ecological fallacies even when using subject data. Inverted simulations, of trials rightly sized to detect meaningful differences, yielding a statistically significant p-value of 0.000001 （1 in a million） and associated with clinically meaningful differences between a hypothetical new therapy and a standard therapy, had a proportion of instances of subjects with standard therapy effect better than new therapy effects close to 30%. A ―winner take all‖ choice between two hypotheses may not be supported by statistically significant differences based on stochastic data. We also argue the incorrectness across many individuals of other summaries such as correlations, density estimates, standard deviations and predictions based on machine learning models. Despite artifacts we support the use of prospective clinical trials and careful unbiased model building as necessary first steps. In health care, high touch personalized care based on patient level data will remain relevant even as we adopt more high tech data-intensive personalized therapeutic strategies based on aggregates.

Farmland Abandonment Research Progress: Influencing Factors and Simulation Model

Farmland abandonment is a global problem and considered one of the most important areas in land use change research. Farmland abandonment research currently focuses on understanding the factors that affect farmland abandonment and developing scientific models to simulate farmland abandonment. The study reviewed the natural and political factors driving farmland abandonment and summarized the main models for farmland abandonment simulation together with their advantages and disadvantages. We discuss the main ecological effects of farmland abandonment and propose farmland abandonment research directions. The study found that:(1) the influence of labor cost change and ageing labor force on farmland abandonment needs further investigation,(2) simulation models for farmland abandonment must include the decision-making mechanism of individual farmers and focus on macro large-scale abandonment prediction models, and(3) the influence of farmland abandonment on landscape culture must be investigated in detail.

COMPLEX ECO-ECONOMY SYSTEM

In the past there were a lot of researches on the topic of economic growth. Nevertheless, the environment has been a bit abstracted by standard economics. Scarce natural resources and our choices to protect them or exploit them jointly determine the economic and environmental systems. In this paper we describe a model with a particular focus on the relationship among income, pollution, and non-renewable resources. We want to combine both economic and environmental sectors. The system dynamics approach is used in analyzing these complex relationships. This paper gives an insight into the possibilities for replacing non-renewable resources with more renewable ones. Next, we present the simulation runs of the model that are conducted with the help of existing system dynamics modeling tools. Only the relationships simulated so far between the variables ought to be put under yet more cautious examination.

Species Abundance Distribution Patterns of a Toona ciliata Community in Xingdoushan Nature Reserve

With the goal of model fitting species abundance distribution patterns of the tree,shrub and herb layers of the natural Toona ciliata community in Xingdoushan Nature Reserve,Enshi Autonomous Prefecture,Hubei Province,we used the data collected from the field survey and employed different ecological niche models.The models tested were the broken stick model(BSM),the overlapping niche model(ONM)and the niche preemption model(NPM),as well as three statistic models,the log-series distribution model(LSD),the log-normal distribution model(LND)and the Weibull distribution model(WDM).To determine the fitted model most suitable to each layer,the fitting effects were judged by criteria of the lowest value of Akaike Information Criterion(AIC),Chi-square and the K-S values with no significant difference(P>0.05)between the theoretical predictions and observed species abundance distribution values.The result showed:(1)The fitting suitability and goodness of fit of the tree,shrub and herb layers by using the three ecological niche models were ranked as:NPM>BSM>ONM.Of the three statistical models,by accepting the fitting results of the three layers,WDM was the best fitting model,followed by LND.By rejecting the fitting tests of the herb layer,LSD had the worst fitting effect.The goodness of the statistical models was ranked as:WDM>LND>LSD.In general,the statistical models had better fitting results than the ecological models.(2)T.ciliata was the dominant species of the tree layer.The species richness and diversity of the herb layer were much higher than those of either the tree layer or the shrub layer.The species richness and diversity of the shrub layer were slightly higher than those of the tree layer.The community evenness accorded to the following order:herb>shrub>tree.Considering the fitting results of the different layers,different ecological niche models or statistical models with optimal goodness of fit and ecological significance can be given priority to in studying the species abundance distribution patterns of T.ciliata communities.