Comparison of sensitivity analysis techniques: A case study with the rice model WARM

The considerable complexity often included in biophysical models leads to the need of specifying a large number of parameters and inputs, which are available with various levels of uncertainty. Also, models may behave counter-intuitively, particularly when there are nonlinearities in multiple input-output relationships. Quantitative knowledge of the sensitivity of models to changes in their parameters is hence a prerequisite for operational use of models. This can be achieved using sensitivity analysis (SA) via methods which differ for specific characteristics, including computational resources required to perform the analysis. Running SA on biophysical models across several contexts requires flexible and computationally efficient SA approaches, which must be able to account also for possible interactions among parameters. A number of SA experiments were performed on a crop model for the simulation of rice growth (Water Accounting Rice Model, WARM) in Northern Italy. SAs were carried out using the Morris method, three regression-based methods (Latin hypercube sampling, random and Quasi-Random, LpTau), and two methods based on variance decomposition: Extended Fourier Amplitude Sensitivity Test (E-FAST) and Sobol’, with the latter adopted as benchmark. Aboveground biomass at physiological maturity was selected as reference output to facilitate the comparison of alternative SA methods. Rankings of crop parameters (from the most to the least relevant) were generated according to sensitivity experiments using different SA methods and alternate parameterizations for each method, and calculating the top-down coefficient of concordance (TDCC) as measure of agreement between rankings. With few exceptions, significant TDCC values were obtained both for different parameterizations within each method and for the comparison of each method to the Sobol’ one. The substantial stability observed in the rankings seem to indicate that, for a crop model of average complexity such as WARM, resource intensive SA methods could not be needed to identify most relevant parameters. In fact, the simplest among the SA methods used (i.e., Morris method) produced results comparable to those obtained by methods more computationally expensive.     

Predicting a ‘tree change’ in Australia's tropical savannas: Combining different types of models to understand complex ecosystem behaviour

In this study, key ecological modelling limitations of a process-based simulation model and a Bayesian network were reduced by combining the two approaches. We demonstrate the combined modelling approach with a case study investigating increases in woody vegetation density in northern Australia's tropical savannas. We found that by utilising the strengths of a simulation model and a Bayesian network we could both forecast future change in woody vegetation density and diagnose the reasons for current vegetation states. The local conditions of climate, soil characteristics and the starting population of trees were found to be more important in explaining the likelihood of change in woody vegetation density compared to management practices such as grazing pressure and fire regimes. We conclude that combining the strengths of a process and BN model allowed us to produce a simple model that utilised the ability of the process model to simulate ecosystem processes in detail and over long time periods, and the ability of the BN to capture uncertainty in ecosystem response and to conduct scenario, sensitivity and diagnostic analysis. The overall result was a model that has the potential to provide land managers with a better understanding of the behaviour of a complex ecosystem than simply utilising either modelling approach in isolation.     

Evaluation of Heritage Trees for Conservation and Management in Guangzhou City (China)

The recent fast pace of urbanization in China and other developing countries has exerted pressure on urban trees, which constitute a key urban environmental asset. The most outstanding trees should be treated as natural-cum-cultural heritage. Guangzhou Citys growth has threatened its rich urban-tree endowment, a diversified assemblage of 200,000 trees represented by 254 species and located in three major habitats: roadside, park, and institutional grounds. Mainly based on age and performance, 348 trees were officially designated as heritage specimens. They were evaluated in the field for tree dimensions, habitat, performance, and landscape contribution, to establish enhanced conservation and management strategies. With only 25 species, heritage trees were dominated by five cultivated natives and encompass some of the citys rare species; some common urban-forest species were not represented. Older districts and roadside habitats, despite their compact town plan and limited growing space, had the largest tree dimensions and largest share of heritage trees. Many heritage trees were large with long life expectancy and the potential for biomass expansion, and had pivotal cityscape impacts where they occur. Old neighborhoods, traditional haven for the arborescent treasure, are being changed by construction activities and periodic typhoon and windstorm damages. Increasing development density could degrade the heritage trees and their growing space, and reduce tree quality and life span. Upgrading the statutory-administrative systems and arboricultural care can enhance long-term survival of the precious natural-cum-cultural heritage. The experience of Guangzhou in identifying and preserving its high-quality urban trees can provide management strategies for other cities.     

银杏叶中有效成分的提取

通过使用不同溶剂比较了两种装置提取银杏叶中有效成分的优缺点。结果表明，简易装置所用时间较短、收率较高且操作简单方便；利用95％乙醇作为提取剂在使用简易装置时，银杏叶粗提物得率最高。     

西藏色季拉山公路沿线PAHs分布、来源及风险

分别于2017年3月和12月沿色季拉山318国道采集表层土和冷杉（Abies Mill.）样品,测定了多环芳烃（PAHs）的含量.表层土和冷杉叶中∑₁₆PAHs的含量范围分别为30.21~366.94ng/g dw和39.53~236.42ng/g dw,组成以低环（2、3环）为主.通过特征单体比值法和主成分分析法分析表明,色季拉山PAHs主要来源于化石燃料和生物质的燃烧,同时也受到车辆石油泄漏和大气远距离传输的影响;通过反向气团轨迹判断,色季拉山PAHs大气传输污染主要来自于印度次大陆.色季拉山公路沿线土壤中PAHs的终生致癌风险值均低于1×10^-6,说明对当地居民的致癌风险较小.     

珠三角某垃圾焚烧厂周边植物叶片汞含量空间格局影响因素影响因素

为研究珠三角某城市生活垃圾焚烧厂周边汞污染空间格局及影响因素,于2014年1月,采集了马占相思、荔枝和芒萁等优势种的叶片样品192份,并同步采集相应表层土壤样品64份,采用冷原子吸收法测定样品总汞含量,并运用ADMS模型对2013年大气汞年均浓度进行模拟,分析了植物叶片汞含量与土壤和大气汞浓度之间的关系。结果表明,植物叶片的汞含量范围为0.0029~0.1741 mg·kg-1,荔枝叶片汞含量最高,为(0.0766±0.0395)mg·kg-1,其次为芒萁((0.0599±0.0370)mg·kg-1)和马占相思((0.0556±0.0396)mg·kg-1)。植物叶片汞含量与土壤汞含量无显著相关性,而受风向和距污染源的距离影响显著,与ADMS模拟的大气年均汞浓度存在显著相关性。研究表明,植物叶片汞含量变化与烟气扩散浓度的空间分异格局基本吻合,叶片对大气中汞的吸收在植物与环境的汞交换中占据主导地位,对叶片的生物监测可以反映城市生活垃圾焚烧厂汞排放对生态环境的实际影响。     

生物对铀的吸附研究

研究榕树叶、啤酒酵母菌、大肠杆菌在不同pH值、吸附时间t和不同初始浓度的铀下吸附的规律,进行了实验室吸附模拟实验,绘制出吸附等温线,并由吸附等温线Freundlich曲线求出相应参数。初步对榕树叶、啤酒酵母菌、大肠杆菌对铀的吸附能力进行评价:大肠杆菌对铀酰离子吸附强度强于啤酒酵母菌和榕树叶的吸附强度;而榕树叶的吸附强度优于啤酒酵母菌铀酰离子的吸附强度。     

Optimal hardwood tree planting and forest reclamation policy on reclaimed surface mine lands in the Appalachian coal region

We study the optimal hardwood tree planting decision on reclaimed surface coal mines in the Appalachian region using a mine operator-focused, expected cost model that recognizes costs of preparing the site for tree planting, unit costs of planting seedlings, and opportunity costs of reforestation treatments and the performance bond. We also consider the possibility of failed initial attempts by incorporating the probability of reforestation success, based on empirical seedling ,survival rates and regulated tree survival standards, as well as fixed and unit costs of returning for additional planting. Optimal planting levels from 319 to 780 trees per acre and expected costs from $1049 to $2338 were found using simulations over a range of unit planting costs, fixed costs of replanting, tree survival standards, and interest rates. Further simulations compared optimal planting across un-weathered gray sandstone and weathered brown sandstone substrate materials, finding gray sandstone to be associated with lower expected costs. We conclude that optimal planting density and expected reforestation cost are sensitive to economic parameters, regulations, and planting substrate materials; and those policies influencing these factors may have substantial impact on reforestation outcomes and the choice of post-mining land use by mine operators. Our study provides a framework for understanding forest reclamation decisions that incorporates incentives faced by the mine operators who develop and implement the plans for mine reclamation, including forestry.     

上海市公园绿地树叶对大气重金属污染的磁学响应

为探究城市公园绿地树叶对大气重金属污染的磁学响应,按照上海市年均主导风设置纵横两个采样断面,采集城郊区公园绿地中广泛分布的香樟树叶,进行岩石磁学和重金属元素分析.结果表明,样品磁性矿物以亚铁磁性矿物为主导,磁性颗粒物的含量和粒径由典型工业区沿冬季风方向逐级递减.对叶片进行超声清洗后磁化率下降63%~90%,即样品的磁性特征主要取决于叶表附尘.树叶重金属元素Fe、Mn、Zn、Cu、Cr、V、Pb含量与磁参数显著相关(0.442≤R≤0.799,P0.05),说明城市公园绿地树叶磁参数可以作为大气重金属污染的替代指标.运用多元统计分析方法表明,研究区树叶磁性矿物及重金属含量主要受工业活动和交通道路污染的复合影响.     

榕树叶对铀吸附的研究

为探讨榕树叶对铀的吸附特性 ,考察 pH、吸附时间、含重金属溶液浓度对吸附能力的影响 ,绘制出吸附等温线 ,并求出Langmuir曲线和Freundlich曲线相应方程 .结果表明 :榕树叶在pH =3 ,吸附时间t=2 0min时吸附铀的能力最高 .重金属离子浓度越高 ,榕树叶的吸附量越高。