斜坡稳定性的二级模糊推断

根据对斜坡稳定性影响的大小,选取了七个主要因于,引用了山西明水河流域几个斜坡样点实测数据．应用模糊近似推论方法及信息分配原理,对斜坡稳定性进行了单因子灰色隶属度分析及综合二级模糊近似推论,该方法克服了传统单因子评价的弊端,能比较真实地反映实际,为布设护坡工程提供了理论依据。     

完全均匀混合质量平衡水质模型在滇池中的应用

介绍了完全均匀混合假设下以质量平衡为基础的湖泊水质模型,运用滇池的实测数据对模型进行了参数率定、验证,给出了模型在滇池水质预测中的应用实测,最后讨论了模型的几个假设条件对滇池的适应性。实例研究表明,该模型可适用于滇池水质有机污染长期浓度预测。      

Approaches and terminology for causal analysis in land systems science

Research into land and social-ecological systems science could benefit from improved clarity in the terminology used for causal analysis and a structured way to make causal inferences. Here I identify two aspects of causality, i.e. causal effects and causal mechanisms, and discuss explanation in historical sciences. I then propose definitions for the major terms used for causal relations, including driver, (spatial) determinant, location and contextual factor, proximate and underlying factors. Finally, I discuss the contribution of various operational approaches, including time series and counterfactual approaches for assessing causal effects and process-tracing approaches for establishing causal mechanisms. Having a coherent concept of causality, agreeing on a precise vocabulary and harnessing our tools with the clear purpose of establishing both causal effects and causal mechanisms should strengthen causal explanations for single cases, for drawing policy-relevant lessons and for theoretical development in relation to land and, more broadly, social-ecological systems processes.     

Simulation of long-term nutrient removal in a full-scale closed-loop bioreactor for sewage treatment: an example of Bayesian inference

In this study, the performance of nitrogen and phosphorus removal in a full-scale closed-loop bioreactor (oxidation ditch) system was simulated using the ASM2d model. Routine data describing the process for two years were compiled for calibration and validation. To overcome the identifiability problem, the classic Bayesian inference approach was utilized for parameter estimation. The calibrated model could describe the long-term trend of nutrient removal and short-term variations of the process performance, showing that the Bayesian method was a reliable and useful tool for the parameter estimation of the activated sludge models. The anoxic phosphate uptake by polyphosphate accumulating organisms (PAO) contributed 71.2% of the total Poly-P storage, which reveals the dominance of denitrifying phosphorus removal process under the oxygen limiting conditions. It was found that 58.7% of the anoxic Poly-P storage and denitrification by PAO in the reactor was achieved in the aerated compartment, implying that the PAO’s anoxic activity was significantly stimulated by the low dissolved oxygen (DO) level in this compartment due to the oxygen gradient caused by brush aerator.     

Estimating dyad association probability under imperfect and heterogeneous detection

In animal behaviour studies, association indices estimate the proportion of time two individuals (i.e. a dyad) spend in association. In terms of dyads, all association indices can be interpreted as estimators of the probability that a dyad is associated. However, traditional indices rely on the assumptions that the probability to detect a particular individual (p) is either approximately one and/or homogeneous between associated and not associated individuals. Based on marked individuals we develop a likelihood based model to estimate the probability a dyad is associated (ψ) accounting for p < 1 and possibly varying between associated and not associated individuals. The proposed likelihood based model allows for both individual and dyadic missing observations. In addition, the model can easily be extended to incorporate covariate information for modeling p and ψ. A simulation study showed that the likelihood based model approach yield reasonably unbiased estimates, even for low and heterogeneous individual detection probabilities, while, in contrast, traditional indices showed moderate to strong biases. The application of the proposed approach is illustrated using a real data set collected from a population of Commerson's dolphin (Cephalorhynchus commersonii) in Patagonia Argentina. Finally, we discuss possible extensions of the proposed model and its applicability in animal behaviour and ecological studies.     

Inverse calculation approaches for source determination in hazardous chemical releases

Source determination is vital in decision making and emergency planning involving hazardous chemical releases. This work was concentrated on inverse calculation approaches for source determination as well as current trends and future perspectives. In this paper, these different approaches are reviewed by dividing them into two categories: probability modeling methods and optimization modeling methods. The traits of these approaches are comparatively analyzed. Then it is shown how these approaches behave when applied to practical cases, and their feasibility, applicability, stability, and limitation in determining the location and strength are presented. It is argued that when experimenting with potential terrorist attacks involving hazardous chemical releases, observation points should be around the main line of the downwind direction when the source is known; while the uniform distribution of observation points is an efficient solution for unknown incidents. Probability modeling methods are demonstrated to be insufficient during emergency responses due to their lacking of enough prior information of unknown parameters, while optimization modeling methods are efficient and become a new trend in source determination. Findings reflect an urgent need for the development of high-accuracy detectors and further research of data transmission techniques in order to ensure the validity of these approaches.     

Studying ecological communities from a neutral standpoint: A review of models’ structure and parameter estimation

Neutral models provide an alternative to niche-based assembly rules of ecological communities by assuming that communities’ properties are shaped by the stochastic interplay between ecological drift, migration and speciation. The recent and ongoing interest about neutral assumptions has produced many developments on the theoretical side, with nevertheless limited echoes in terms of analyses of real-world data. The present review paper aims to help bridge the widening gap between modellers and field ecologists through two objectives. First, to provide a multi-criteria typology of the main neutral models, including those from population genetics that have not yet been transposed to ecology, by considering how the fundamental processes of ecological drift, speciation and migration are modelled and, specifically, how space is taken into account. Second, to review methods recently proposed to estimate models parameters from field data, a point that should be mastered to allow for broader applications.     

A Bayesian approach to multi-source forest area estimation

In efforts such as land use change monitoring, carbon budgeting, and forecasting ecological conditions and timber supply, there is increasing demand for regional and national data layers depicting forest cover. These data layers must permit small area estimates of forest area and, most importantly, provide associated error estimates. This paper presents a model-based approach for coupling mid-resolution satellite imagery with plot-based forest inventory data to produce estimates of probability of forest and associated error at the pixel-level. The proposed Bayesian hierarchical model provides access to each pixel’s posterior predictive distribution allowing for a highly flexible analysis of pixel and multi-pixel areas of interest. The paper presents a trial using multiple dates of Landsat imagery and USDA Forest Service Forest Inventory and Analysis plot data. The results describe the spatial dependence structure within the trial site, provide pixel and multi-pixel summaries of probability of forest land use, and explore discretization schemes of the posterior predictive distributions to forest and non-forest classes. Model prediction results of a holdout set analysis suggest the proposed model provides high classification accuracy, 88%, for the trial site.

Extinction rate of discovered and undiscovered plants in Singapore

Extinction is a key issue in the assessment of global biodiversity. However, many extinction rate measures do not account for species that went extinct before they could be discovered. The highly developed island city–state of Singapore has one of the best-documented tropical floras in the world. This allowed us to estimate the total rate of floristic extinctions in Singapore since 1822 after accounting for sampling effort and crypto extinctions by collating herbaria records. Our database comprised 34,224 specimens from 2076 native species, of which 464 species (22%) were considered nationally extinct. We assumed that undiscovered species had the same annual per-species extinction rates as discovered species and that no undiscovered species remained extant. With classical and Bayesian algorithms, we estimated that 304 (95% confidence interval, 213–414) and 412 (95% credible interval, 313–534) additional species went extinct before they could be discovered, respectively; corresponding total extinction rate estimates were 32% and 35% (range 30–38%). We detected violations of our 2 assumptions that could cause our extinction estimates, particularly the absolute numbers, to be biased downward. Thus, our estimates should be treated as lower bounds. Our results illustrate the possible magnitudes of plant extirpations that can be expected in the tropics as development continues.     

Development of methods for establishing nutrient criteria in lakes and reservoirs: A review

Nutrient criteria provide a scientific foundation for the comprehensive evaluation, prevention,control and management of water eutrophication. In this review, the literature was examined to systematically evaluate the benefits, drawbacks, and applications of statistical analysis,paleolimnological reconstruction, stressor-response model, and model inference approaches for nutrient criteria determination. The developments and challenges in the determination of nutrient criteria in lakes and reservoirs are presented. Reference lakes can reflect the original states of lakes, but reference sites are often unavailable. Using the paleolimnological reconstruction method, it is often difficult to reconstruct the historical nutrient conditions of shallow lakes in which the sediments are easily disturbed. The model inference approach requires sufficient data to identify the appropriate equations and characterize a waterbody or group of waterbodies, thereby increasing the difficulty of establishing nutrient criteria. The stressor-response model is a potential development direction for nutrient criteria determination, and the mechanisms of stressor-response models should be studied further. Based on studies of the relationships among water ecological criteria, eutrophication, nutrient criteria and plankton, methods for determining nutrient criteria should be closely integrated with water management requirements.