Soil drying in a tropical forest: Three distinct environments controlled by gap size

Soil water and temperature regimes in the tropical moist forest on Barro Colorado Island, Panama, were simulated directly from meteorological data using the model SWEAT. Separate field observations from root-exclusion, litter-removal and control treatments in one small and one large forest gap were used for calibration and validation. After irrigating all treatments to field capacity, soil matric potential and temperature were measured over 17 days at four depths ≤50 mm using the filter-paper technique and bead thermistors. Understorey environments were also simulated under the same initial conditions. The results suggest that three distinct scenarios, controlled by gap size, describe how the above- and below-ground processes controlling soil drying are coupled: (1) in the large gap, root water extraction by surrounding trees is negligible so soil drying is dominated by evaporation from the soil surface. Soil temperature is dominated by direct solar heating and cooling due to evaporation. (2) In the small gap, root water extraction dominates soil drying with soil evaporation playing a minor role. Soil temperature is still dominated by direct sunlight with some cooling due to evaporation. (3) In the understorey, root water extraction dominates soil drying. Soil temperature is dominated by heat conduction from deep soil layers with some evaporation and sensible heat transfer. The contrasting soil drying regimes imposed by variation in canopy structure enhance micro-environmental heterogeneity and the scope for differential germination and seedling establishment in coexisting tropical tree species.     

Integrating selected ecological effects of mixed European beech–Norway spruce stands in bioeconomic modelling

The simplicity of many bioeconomic models has been criticised several times, due to their lack of realism resulting from a deterministic nature and a single-species focus. In this context it was interesting to test the financial sensitivity of bioeconomic modelling against fairly well documented ecological effects in mixed forests. For this purpose our study linked existing results of ecological research with bioeconomic modelling. The presented methodological approach could not only show the importance of considering ecological effects in bioeconomic models; it in fact enabled prioritising ecological research from a financial point of view.In a first step, the possible influence of the tree species mixture on forest stand resistance, productivity and timber quality was derived from existing studies. In a second step, the available Monte Carlo simulations for Norway spruce (Picea abies [L.] Karst.) and European beech (Fagus sylvatica L.), simulated under site conditions and risks typical of southern Germany, were extended by the mentioned ecological effects and then evaluated from a financial perspective.The results showed a clear influence of all tested ecological effects on the financial indicators, financial risk and return. While testing each ecological effect separately, an increased resistance against wind, snow and insect attacks had the greatest influence on financial risk and return. It over-proportionally enhanced the financial return while simultaneously the financial risk was reduced. In contrast, a degraded timber quality could eliminate the positive effect of risk compensation in mixed forests almost completely. The least influence on the financial indicators finally showed a changed volume growth in mixed forests.A combination of the separately tested ecological effects (increased resistance, changed volume growth and decreased timber quality), between both tree species, underlined the dominating importance of the stand resistance. The integration of ecological effects, induced by interdependent tree species, in our bioeconomic model resulted in significantly lower financial risk than ignoring these effects. Moreover, the financial return of mixed stand variants with a proportion of Norway spruce greater than 60% even exceeded that of the most profitable pure stand.In conclusion this paper clearly confirmed that ignoring ecological effects in bioeconomic models could lead to seriously biased financial results. While a changed volume growth proved rather to be of minor importance for European beech/Norway spruce stands, tree resistance and timber quality may change the financial results significantly.     

Uncertainties in integrated assessment modelling of abatement strategies: illustrations with the ASAM model

Following the signing of the Second Sulphur Protocol in 1994 under the 1979 Convention on Long-range Transboundary Air Pollution, preparations are now underway for a new multi-pollutant multi-effects protocol, under the auspices of the United Nations Economic Commission for Europe (UN ECE). A number of scientific models have been used to provide policy makers involved in these preparations with sound scientific information. These include the Abatement Strategies Assessment Model (ASAM). ASAM has recently been extended to cover abatement strategies for NH₃ and NOx as well as SO₂, in order to address the amelioration of acidification and eutrophication in the ECE region. It is important to be able to demonstrate that the scientific information provided to policy makers is robust to uncertainties, and hence there is a need for a thorough sensitivity analysis. In this study ASAM is used to demonstrate a large degree of robustness of derived abatement strategies to uncertainties in critical loads, meteorological data and cost information. This is based on a comparison of strategies at the same overall abatement cost. Systematic changes in data are shown to influence model results more profoundly than random changes.     

饱和带有机污染物的厌氧反硝化微生物降解

以卤代烃和芳香烃为代表,通过室内实验模拟饱和带厌氧反硝化环境,对地下饱和带中有机污染物的厌氧反硝化可生物降解性,降解机理,降解动力学方程等进行了研究。实验结果表明,芳香烃较卤代烃易被微生物降解,在有低学葡萄糖存在时有 机物的最大生物降解速率Ｃ６Ｈ６：Ｌｍａｘ＝１７ｍｇ／（ｍ＾２．ｄ）,Ｃ７Ｈ８：Ｌｍａｘ＝４６ｍｇ／（ｍ＾２．ｄ）,ＣＣｌ４;Ｌｍａｘ＝７ｍｇ／（ｍ＾２．ｄ）,ＣＨＣｌ３：Ｌｍａｘ＝６     

对金州沿海地区地下水中氯离子与硬度相关关系的研究

根据1991～2002年大连市金州沿海地区地下水中硬度与氯离子的检测结果,对硬度 氯离子浓度进行一元线性回归,回归方程为y=2.1975x-3.1072,经相关系数和回归线的显著性检验,此方程有99%的可信度。     

甘肃省迭部县居民森林生态环境支付意愿影响因素分析

公众的生态环境认知水平及支付意愿对森林生态环境保护具有重要的影响和作用.根据甘肃省迭部县居民的291份有效调查问卷,采用描述性统计方法和结构方程模型对森林生态环境支付意愿的影响因素进行了分析.结果表明:①居民对生态环境服务价值的认知、对生态环境补偿的认知、对生态环境保护的预期收益、居民个人资金技术因素、外部环境因素与居民森林生态环境支付意愿之间存在正相关关系,且影响显著,其中影响程度最大的是外部环境因素,标准相关系数为0.830,解释效果良好,影响程度最小的是资金技术因素,相关系数仅为0.283.②多群组结构方程模型研究结果显示,男性居民的森林生态环境支付意愿主要受对森林生态环境认知程度的影响,女性更容易受外部环境因素的影响.不同年龄段的居民在森林生态环境服务价值认知、资金技术因素和外部环境因素方面存在差异性.不同教育程度居民之间的差异主要体现在对森林生态环境服务价值的认知和对森林生态环境补偿的认知上.③性别、年龄、教育程度等因素对生态环境服务价值认知、预期收益等有显著影响,且不同因素的影响程度存在差异.研究显示,对森林生态环境支付意愿影响因素分析反映了环境支付意愿的普适性问题,研究结果可为生态资源和环境管理等提供参考.      

Effect of lifestyle changes and consumption patterns on environmental impact: a comparison study of Pakistan and China

Increased economic development and industrialization put strain on environment, hence causing pollution and destroying ecosystem. Generally, many different factors affect the environment. These factors include GHG emissions, deforestation, and others. These are all related to human activities on Earth. Other factors that affect environment include population, consumption patterns, and changing life styles of people due to increased income. This study involves the comparison analysis of Pakistan and China on the basis of environmental impact caused by some major driving factors. China is the second largest CO₂ emitter in the world with a population of 1.37 billion in 2016 and the second largest economy in the world. Pakistan is ranked as 40th on the basis of nominal GDP. Both the countries observed noticeable growth in economic development for over 55 years, i.e. 1960–2016. This study identifies how population, affluence, consumption, and emissions as the major factors affect environmental pollution and use ImPACT equation, or I = PACT, to calculate the environmental impact and to determine which factors affect the environment the most. The study suggests that the people of both China and Pakistan have experienced increased income for the past 50 years and this increase has led to the changes in their lifestyles, from suitable clothing and quality food to comfortable living and increased energy consumption, thus affecting environment.     

新体制下我国基层防震减灾工作研究——以天津市为例

为了深入分析和研究新体制下我国基层防震减灾工作的具体思路,采用文献检索、实地调研、对比分析等方法,对以天津市为代表的基层防震减灾工作机构的改革现状、工作特点和存在问题等进行分析研究,并结合工作实际,提出新体制下基层防震减灾工作管理体系框架,并有针对性地提出具体工作建议,研究成果对进一步加强应急管理新体制下的地震基层工作具有一定的实践指导意义。     

基于STAMP-ISM的铁路危险品运输系统风险-事故分析方法*

为预防铁路危险品运输系统事故的发生,采用STAMP-ISM模型分析铁路危险品运输系统风险-事故。首先,利用STAMP模型详细分析事故,得到控制结构的相关安全约束、不充分控制行为及产生原因,以及系统的安全动态变化;其次,采用ISM分析事故致因因素之间的关联关系并划分层级;最后,基于STAMP和ISM分析结果提出系统改进方案。以我国一起匿名夹带事故为背景进行案例研究,结果表明,ISM模型的加入可深入挖掘事故因素间的相互关系,为事故致因因素重要度划分层级,分析结果及建议更具针对性。     

PyLUR: Efficient software for land use regression modeling the spatial distribution of air pollutants using GDAL/OGR library in Python

• PyLUR comprises four modules for developing and applying a LUR model. • It considers both conventional and novel potential predictor variables. • GDAL/OGR libraries are used to do spatial analysis in the modeling and prediction. • Developed on Python platform, PyLUR is rather efficient in data processing. Land use regression (LUR) models have been widely used in air pollution modeling. This regression-based approach estimates the ambient pollutant concentrations at un-sampled points of interest by considering the relationship between ambient concentrations and several predictor variables selected from the surrounding environment. Although conceptually quite simple, its successful implementation requires detailed knowledge of the area, expertise in GIS, statistics, and programming skills, which makes this modeling approach relatively inaccessible to novice users. In this contribution, we present a LUR modeling and pollution-mapping software named PyLUR. It uses GDAL/OGR libraries based on the Python platform and can build a LUR model and generate pollutant concentration maps efficiently. This self-developed software comprises four modules: a potential predictor variable generation module, a regression modeling module, a model validation module, and a prediction and mapping module. The performance of the newly developed PyLUR is compared to an existing LUR modeling software called RLUR (with similar functions implemented on R language platform) in terms of model accuracy, processing efficiency and software stability. The results show that PyLUR out-performs RLUR for modeling in the Bradford and Auckland case studies examined. Furthermore, PyLUR is much more efficient in data processing and it has a capability to handle detailed GIS input data.