Convexity in projection matrices: Projection to a calibration problem

Convexity, as a fundamental property of sets and functions defined on convex sets, plays an important role in many mathematical and applied disciplines, including extremal and optimal-control problems. We prove the set of all feasible projection matrices in a general class of matrix models for stage-structured population dynamics to be convex and the dominant eigenvalue (λ₁) of any projection 2 × 2 matrix to be either a convex, or a concave function on a simplex of the matrix first-row entries (i.e., stage-specific reproduction rates). The latter is also conjectured for the general n × n case. Though looking far from practical needs of matrix population models, this mathematical result has appeared to be quite useful in solving a practical problem to calibrate the projection matrix, i.e., to estimate all the stage-specific vital rates, from empirical data. The data from monitoring of individual life histories of marked plants on permanent sample plots during successive years enable direct calculation of the stage-specific survival and ontogenetic transition rates, but the rates of reproduction do remain uncertain as far as the parent plants can hardly be determined for the (not yet marked!) recruitment.     

Improved strategies for coverage estimation by using replicated line-intercept sampling

Coverage, i.e., the area covered by the target attribute in the study region, is a key parameter in many surveys. Coverage estimation is usually performed by adopting a replicated protocol based on line-intercept sampling coupled with a suitable linear homogeneous estimator. Since coverage is a parameter which may be interestingly represented as the integral of a suitable function, improved Monte Carlo strategies for implementing the replicated protocol are introduced in order to achieve estimators with small variance rates. In addition, new specific theoretical results on Monte Carlo integration methods are given to deal with the integrand functions arising in the special coverage estimation setting.

多波段激光防护塑料的研制

本文以PMMA为基质制备了多波段激光防护塑料样品,对其性能进行了测试,该样品对YAG激光有很好的防护作用,达到实用要求。     

An integrated optimization and simulation approach for air pollution control under uncertainty in open-pit metal mine

Air Pollution Control model is developed for open-pit metal mines. Model will aid decision makers to select a cost-effective solution. Open-pit metal mines contribute toward air pollution and without effective control techniques manifests the risk of violation of environmental guidelines. This paper establishes a stochastic approach to conceptualize the air pollution control model to attain a sustainable solution. The model is formulated for decision makers to select the least costly treatment method using linear programming with a defined objective function and multi-constraints. Furthermore, an integrated fuzzy based risk assessment approach is applied to examine uncertainties and evaluate an ambient air quality systematically. The applicability of the optimized model is explored through an open-pit metal mine case study, in North America. This method also incorporates the meteorological data as input to accommodate the local conditions. The uncertainties in the inputs, and predicted concentration are accomplished by probabilistic analysis using Monte Carlo simulation method. The output results are obtained to select the cost-effective pollution control technologies for PM_2.5, PM₁₀, NO_x, SO₂ and greenhouse gases. The risk level is divided into three types (loose, medium and strict) using a triangular fuzzy membership approach based on different environmental guidelines. Fuzzy logic is then used to identify environmental risk through stochastic simulated cumulative distribution functions of pollutant concentration. Thus, an integrated modeling approach can be used as a decision tool for decision makers to select the cost-effective technology to control air pollution.     

南方红壤典型水土流失区植被覆盖度变化及其生态效应评估——以福建省长汀县为例

南方红壤典型水土流失区--福建省长汀县曾因生态破坏导致严重的水土流失.经过多年以植树为主的生态修复,该县生态面貌有了明显的改观.论文首先采用线性光谱混合分析模型计算植被覆盖度,并在此原始模型的基础上提出了对地形阴影进行修正的方法来获取植被覆盖度.精度验证表明,在线性光谱混合分析模型中加入山地指数(NDMVI)波段能够削弱地形阴影问题,提高植被覆盖度反演精度.在此基础上利用多时相遥感影像分析了长汀2001-2013 年植被覆盖度的时空变化,并利用遥感生态指数(RSEI)定量评价了长汀水土流失生态修复的效果.结果表明,经过13 a 的水土流失治理,长汀的植被覆盖度有了明显的升高,从2001 年的75.1%上升到2013 年的86.5%.RSEI 生态指数值也随之上升,生态等级为优良的面积比例从85.83%增加到90.59%,反映了长汀县生态质量整体有了明显的提高.植被的生态效应定量研究表明,长汀县的植被覆盖度每增加10%,RSEI 生态指数值至少提高10%,植被覆盖度的生态提升效应显著.     

Adapting empirical equations to Lake Kinneret data by using three calibration methods

This paper examines whether the relationships between a number of characteristic limnological variables (suspended particulate matter, turbidity, Secchi depth, light attenuation, and chlorophyll a) determined for temperate lakes are consistent with the relationships found in Mediterranean lakes such as Lake Kinneret. We found that the use of published relationships between lake variables may lead to erroneous results when applied indiscriminately to other lake types.     

The effect of species response form on species distribution model prediction and inference

Ecological theory and current evidence support the validity of various species response curves according to a variety of environmental gradients. Various methods have been developed for building species distribution models but it is not well known how these methods perform under various assumptions about the form of the underlying species response. It is also not well known how spatial correlation in species occurrence affects model performance. These effects were investigated by applying an environmental envelope method (BIOCLIM) and three regression-based methods: logistic regression (LR), generalized additive modelling (GAM), and classification and regression tree (CART) to simulated species occurrence data. Each simulated species was constructed as a sum of responses with varying weights. Three basic species response curves were assumed: Gaussian (bell-shaped), Beta (skew) and linear. The two non-linear responses conform to standard ecological niche theory. All three responses were applied in turn to three simulated environmental variables, each with varying degrees of spatial autocorrelation. GAM produced the most consistent model performance over all forms of simulated species response. BIOCLIM and CART were inclined to underrate the performance of variables with a linear response. BIOCLIM was less sensitive to data density. LR was susceptible to model misspecification. The use of a linear function in LR underestimated the performance of variables with non-linear species response and contributed to increased spatial autocorrelation in model residuals. Omission of important environmental variables with non-linear species response also contributed to increased spatial autocorrelation in model residuals. Adding a spatial autocovariate term to the LR model (autologistic model) reduced the spatial autocorrelation and improved model performance, but did not correct the misidentification of the dominant environmental determinant. This is to be expected since the autologistic approach was designed primarily for prediction and not for inference. Given that various forms of species response to environmental determinants arise commonly in nature: (1) higher order functions should always be tested when applying LR in modelling species distribution; (2) spatial autocorrelation in species distribution model residuals can indicate that environmental determinants with non-linear response are missing from the model; and (3) deficiencies in LR model performance due to model misspecification can be addressed by adding a spatial autocovariate to the model, but care should be taken when interpreting the coefficients of the model parameters.     

Response surface models for the formation of PCDD and PCDF in a pilot plant combustion of MSW

Experimental data on PCDD and PCDF emissions in raw gases from municipal solid waste combustion in a pilot plant were processed by Response Surface models to gain information on process parameter values which minimize both the total PCDD/PCDF concentrations and those of a selected congener group.     

Initial repercussions and hydroelectric developments in the French upper rhone valley: A lesson for predictive scenarios propositions

The authors demonstrate the difficulties inherent in predicting vegetation changes in floodplains affected by hydroelectric developments. The results are based on phytoecological studies in the Rhone River valley between Geneva and Lyon. The study is based in a 200-km stretch of river where the floodplain can attain 10 km in width. Vegetation is described for the area prior to the construction of four dams and compared with the situations 8 yr later. Research methods include systematic sampling of geomorphological, soils, and floristic factors; collection of a data base of spatial information; and large-scale vegetation mapping.