Will Evolving Climate Conditions Increase the Risk of Floods of the Large U.S.‐Canada Transboundary Richelieu River Basin?

In spring 2011, an unprecedented flood hit the complex eastern United States (U.S.)–Canada transboundary Lake Champlain–Richelieu River (LCRR) Basin, destructing properties and inducing negative impacts on agriculture and fish habitats. The damages, covered by the Governments of Canada and the U.S., were estimated to C$90M. This natural disaster motivated the study of mitigation measures to prevent such disasters from reoccurring. When evaluating flood risks, long‐term evolving climate change should be taken into account to adopt mitigation measures that will remain relevant in the future. To assess the impacts of climate change on flood risks of the LCRR basin, three bias‐corrected multi‐resolution ensembles of climate projections for two greenhouse gas concentration scenarios were used to force a state‐of‐the‐art, high‐resolution, distributed hydrological model. The analysis of the hydrological simulations indicates that the 20‐year return period flood (corresponding to a medium flood) should decrease between 8% and 35% for the end of the 21st Century (2070–2099) time horizon and for the high‐emission scenario representative concentration pathway (RCP) 8.5. The reduction in flood risks is explained by a decrease in snow accumulation and an increase in evapotranspiration expected with the future warming of the region. Nevertheless, due to the large climate inter‐annual variability, short‐term flood probabilities should remain similar to those experienced in the recent past.     

Bridging gaps in demographic analysis with phylogenetic imputation

Phylogenetically informed imputation methods have rarely been applied to estimate missing values in demographic data but may be a powerful tool for reconstructing vital rates of survival, maturation, and fecundity for species of conservation concern. Imputed vital rates could be used to parameterize demographic models to explore how populations respond when vital rates are perturbed. We used standardized vital rate estimates for 50 bird species to assess the use of phylogenetic imputation to fill gaps in demographic data. We calculated imputation accuracy for vital rates of focal species excluded from the data set either singly or in combination and with and without phylogeny, body mass, and life-history trait data. We used imputed vital rates to calculate demographic metrics, including generation time, to validate the use of imputation in demographic analyses. Covariance among vital rates and other trait data provided a strong basis to guide imputation of missing vital rates in birds, even in the absence of phylogenetic information. Mean NRMSE for null and phylogenetic models differed by <0.01 except when no vital rates were available or for vital rates with high phylogenetic signal (Pagel's λ > 0.8). In these cases, including body mass and life-history trait data compensated for lack of phylogenetic information: mean normalized root mean square error (NRMSE) for null and phylogenetic models differed by <0.01 for adult survival and <0.04 for maturation rate. Estimates of demographic metrics were sensitive to the accuracy of imputed vital rates. For example, mean error in generation time doubled in response to inaccurate estimates of maturation time. Accurate demographic data and metrics, such as generation time, are needed to inform conservation planning processes, for example through International Union for Conservation of Nature Red List assessments and population viability analysis. Imputed vital rates could be useful in this context but, as for any estimated model parameters, awareness of the sensitivities of demographic model outputs to the imputed vital rates is essential.     

3MRA风险模型在铬渣整治项目制定过程中的应用

选用美国环境保护署现行废物风险评价模型(3MRA)对某铬渣整治项目进行环境风险评价.模拟了治理前后区域内环境风险情况.分析了污染物暴露途径及危害对象.通过模型对该项目预定处置方法可行性进行了验证.模拟结果显示,在95%受保护对象、95%置信水平条件下,铬渣堆存区域存在显著的环境风险,周边居民致癌风险在10-4数量级,水域生态风险危害商数>1.而在对铬渣进行解毒填埋处置后,环境风险将有效降低,验证了此项目处置方法的可行性.     

黑龙江省粮食生产的时空格局及动因分析

采用空间自相关、聚类分析和多元回归模型等方法,论文探讨了2000 年以来黑龙江省粮食生产的时空动态及其主要影响因素.结果表明:① 黑龙江省粮食生产规模持续扩大,其中,大豆播种面积及其占农作物总播种面积的比重均经历了“上升-下降”的波动过程,玉米和水稻播种面积不断扩大,但其占农作物播种面积的比重分别在2009 和2011 年超过大豆;② 黑龙江省粮食生产具有一定的空间相关性,大豆空间集聚最显著,玉米次之,水稻最不明显;③ 粮食生产区域化和专门化态势增强,松嫩平原北部及大小兴安岭地区、松嫩平原东南部和三江平原北部分别形成了以大豆、玉米和水稻为主的粮食生产类型区;④ 多元回归分析表明,农业投入、经济环境、技术水平、市场因素是影响黑龙江省粮食生产及其结构时空变化的主要因素.     

呼伦贝尔典型草原区植物生长旺季地上干物质量估算的地面光谱模型

为促进地面高光谱遥感在草地估产方面的应用,采用美国ASD公司生产的Fieldspec 3光谱仪,于2009年7月下旬在呼伦贝尔典型草原区进行了高光谱遥感地面观测试验. 运用单变量线性、非线性和逐步回归分析方法,建立植物生长旺季归一化植被指数(NDVI)与地上干物质量(ANPP)间的地面光谱模型. 结果表明,基于判定系数(R2)判断,线性函数和指数函数拟合较理想,R2分别达到0.729 5和0.720 3. 误差分析表明,标准误差(SE)最大的是对数函数,其SE为24.82 g/m2;最小的是幂函数,其SE为22.63 g/m2. 平均误差系数(MEC)最大的是对数函数,其MEC为0.249 7;指数函数最小,其MEC为0.193 2. 综合分析后,选用一元线性回归方程作为呼伦贝尔典型草原区的植物生长旺季最优地面光谱模型:ANPP406.08NDVI-101.64,其R2为0.729 5,SE为23.61 g/m2,MEC为0.220　9,P<0.001.      

Toxicokinetic-toxicodynamic modelling in an individual based context—Consequences of parameter variability

Toxicokinetic-toxicodynamic (TKTD) models simulate the time-course of toxicant concentration in the organism and toxicity at the level of the organism. A link between TKTD models that simulate survival and individual based models for populations (IBMs) is proposed which allows TKTD parameters to vary between individuals. The TKTD-IBM predicts different survival in response to toxicants when TKTD parameters vary amongst individuals compared to the survival predicted with fixed TKTD parameters. The model with fixed parameters represents the concept of stochastic death whereas the model with variable parameters behaves, at least partly, according to the individual tolerance distribution concept. The whole set of TKTD parameters of an individual can be interpreted as constituting “individual tolerance”.     

Adding rigor to ecological network models by evaluating a set of pre-balance diagnostics: A plea for PREBAL

The widespread use of ecological network models (e.g., Ecopath, Econetwrk, and related energy budget models) has been laudable for several reasons, chief of which is providing an easy-to-use set of modeling tools that can present an ecosystem context for improved understanding and management of living marine resources (LMR). Yet the ease-of-use of these models has led to two challenges. First, the veritable explosion of the use and application of these network models has resulted in recognition that the content and use of such models has spanned a range of quality. Second, as these models and their application have become more widespread, they are increasingly being used in a LMR management context. Thus review panels and other evaluators of these models would benefit from a set of rigorous and standard criteria from which the basis for all network models and related applications for any given system (i.e., the initial, static energy budget) can be evaluated. To this end, as one suggestion for improving network models in general, here I propose a series of pre-balance (PREBAL) diagnostics. These PREBAL diagnostics can be done, now, in simple spreadsheets before any balancing or tuning is executed. Examples of these PREBAL diagnostics include biomasses, biomass ratios, vital rates, vital rate ratios, total production, and total removals (and slopes thereof) across the taxa and trophic levels in any given energy budget. I assert that there are some general ecological and fishery principles that can be used in conjunction with PREBAL diagnostics to identify issues of model structure and data quality before balancing and dynamic applications are executed. I humbly present this PREBAL information as a simple yet general approach that could be easily implemented, could be considered for further incorporation into these model packages, and as such would ultimately result in a straightforward way to evaluate (and perhaps identify areas for improving) initial conditions in food web modeling efforts.     

Generation time and the maximum growth rate for populations with age-specific fecundities and unknown juvenile survival

In age-classified population models where all parameters are known, the generation time and growth rate are calculated in a straightforward manner. For many populations, some parameters, such as juvenile survival, are difficult to estimate accurately. In a simplified population model where fecundity and survival are constant from the onset of breeding, it is known that generation time may be calculated given only adult survival, age at first reproduction, and the population growth rate. However, the assumption of constant fecundity from the onset of breeding does not hold for many populations. An extended population model allows calculation of generation time with the additional knowledge of the ratio of age-specific fecundities compared to a maximum fecundity rate. When these relative fecundities are unknown, an ad hoc adjustment to the simplified model performs well.When the study population is in an ideal environment, the optimal generation time and maximum growth rate are linked, and both may be approximated knowing only adult survival, age at first reproduction, and the relative fecundities. The maximum growth rate has important conservation implications, and calculating it correctly is therefore important. Improper use of the simplified population model to calculate the maximum growth rate, combined with a simple decision rule, leads to an average overharvest of 36%, and >60% for three of six bird species studied, compared to the full population model. By comparison, using the approximation from the extended or adjusted models results in average overharvests of only 8% (extended model) and 5% (adjusted model), and <50% for all six species (either model).     

环境模型与GIS的集成技术研究

首先介绍了环境模型发展现状,重点论述了环境模型与GIS集成的必要性和优势;环境模型与GIS集成的方式、集成系统的体系结构以及它们各自的优缺点,最后以福建省海岸带环境决策支持系统为例具体介绍了环境模型与GIS的集成,并对环境模型与GIS集成未来发展提出了几点看法。     

Mathematical modelling and experimental validation of solar drying of mushrooms

This article presents two mathematical models for drying mushrooms considering the shrinkage effect. Both the models consider the physical changes of mushrooms during drying using the diffusion equation. A convective term is presented in the first model while, in the second model, the effective diffusion co-efficient is employed. Although the diffusion co-efficient is mainly dependent on the water content of the mushrooms, both models are suitable for analyzing the drying process. Moreover, in this study it has been demonstrated that both models are equivalent. The Genetic Algorithmic process was used to estimate the parameter values in different conditions. The information regarding the moisture content and the thickness evaluation taken from the models shows the best fit with the experimental data. The mathematical models developed to simulate the drying curve of mushroom have been evaluated and compared.