Predicting tree species presence and basal area in Utah: A comparison of stochastic gradient boosting,generalized additive models,and tree-based methods

Many efforts are underway to produce broad-scale forest attribute maps by modelling forest class and structure variables collected in forest inventories as functions of satellite-based and biophysical information. Typically, variants of classification and regression trees implemented in Rulequest's^© See5 and Cubist (for binary and continuous responses, respectively) are the tools of choice in many of these applications. These tools are widely used in large remote sensing applications, but are not easily interpretable, do not have ties with survey estimation methods, and use proprietary unpublished algorithms. Consequently, three alternative modelling techniques were compared for mapping presence and basal area of 13 species located in the mountain ranges of Utah, USA. The modelling techniques compared included the widely used See5/Cubist, generalized additive models (GAMs), and stochastic gradient boosting (SGB). Model performance was evaluated using independent test data sets. Evaluation criteria for mapping species presence included specificity, sensitivity, Kappa, and area under the curve (AUC). Evaluation criteria for the continuous basal area variables included correlation and relative mean squared error. For predicting species presence (setting thresholds to maximize Kappa), SGB had higher values for the majority of the species for specificity and Kappa, while GAMs had higher values for the majority of the species for sensitivity. In evaluating resultant AUC values, GAM and/or SGB models had significantly better results than the See5 models where significant differences could be detected between models. For nine out of 13 species, basal area prediction results for all modelling techniques were poor (correlations less than 0.5 and relative mean squared errors greater than 0.8), but SGB provided the most stable predictions in these instances. SGB and Cubist performed equally well for modelling basal area for three species with moderate prediction success, while all three modelling tools produced comparably good predictions (correlation of 0.68 and relative mean squared error of 0.56) for one species.     

建筑环境的生命周期分析

生命周期思想是解决环境与社会问题的一种整体性方法.这种方法是可持续建筑概念的关键.LCA(生命周期分析,或者生命周期评价)是将生命周期思想应用于建筑和建造业的一种重要工具.LCA可以提供有关物质和能源流动的重要信息.由于它很难应用于建筑物本身,所以关注的焦点越业越集中在对建筑环境实施更全面的分析上.通过LCA获得的知识最好是作为综合设计方法的一部分进行应用.在大多数项目中,如果不把LCA与数量调查或者能源模拟等其他手段结合起来就无法获得完整的LCA.将LCA应用于政策制定和需要优先考虑的问题依地区和经济条件而有所不同.     

印染行业清洁生产技术

论述了目前印染行业水污染的现状及原因，指出调整产业结构、应用新工艺、大力提倡节约用水、清沽生产将是印染行业实现可持续发展的必由之路。     

Above- and below-ground methane fluxes and methanotrophic activity in a landfill-cover soil

Landfills are a major anthropogenic source of the greenhouse gas methane (CH(4)). However, much of the CH(4) produced during the anaerobic degradation of organic waste is consumed by methanotrophic microorganisms during passage through the landfill-cover soil. On a section of a closed landfill near Liestal, Switzerland, we performed experiments to compare CH(4) fluxes obtained by different methods at or above the cover-soil surface with below-ground fluxes, and to link methanotrophic activity to estimates of CH(4) ingress (loading) from the waste body at selected locations. Fluxes of CH(4) into or out of the cover soil were quantified by eddy-covariance and static flux-chamber measurements. In addition, CH(4) concentrations at the soil surface were monitored using a field-portable FID detector. Near-surface CH(4) fluxes and CH(4) loading were estimated from soil-gas concentration profiles in conjunction with radon measurements, and gas push-pull tests (GPPTs) were performed to quantify rates of microbial CH(4) oxidation. Eddy-covariance measurements yielded by far the largest and probably most representative estimates of overall CH(4) emissions from the test section (daily mean up to ～91,500μmolm(-2)d(-1)), whereas flux-chamber measurements and CH(4) concentration profiles indicated that at the majority of locations the cover soil was a net sink for atmospheric CH(4) (uptake up to -380μmolm(-2)d(-1)) during the experimental period. Methane concentration profiles also indicated strong variability in CH(4) loading over short distances in the cover soil, while potential methanotrophic activity derived from GPPTs was high (v(max)～13mmolL(-1)(soil air)h(-1)) at a location with substantial CH(4) loading. Our results provide a basis to assess spatial and temporal variability of CH(4) dynamics in the complex terrain of a landfill-cover soil.     

建筑环境的生命周期分析

生命周期思想是解决环境与社会问题的一种整体性方法.这种方法是可持续建筑概念的关键.LCA(生命周期分析,或者生命周期评价)是将生命周期思想应用于建筑和建造业的一种重要工具.LCA可以提供有关物质和能源流动的重要信息.由于它很难应用于建筑物本身,所以关注的焦点越业越集中在对建筑环境实施更全面的分析上.通过LCA获得的知识最好是作为综合设计方法的一部分进行应用.在大多数项目中,如果不把LCA与数量调查或者能源模拟等其他手段结合起来就无法获得完整的LCA.将LCA应用于政策制定和需要优先考虑的问题依地区和经济条件而有所不同.     

Interactive effects of plant species diversity and elevated CO2 on soil biota and nutrient cycling

Terrestrial ecosystems consist of mutually dependent producer and decomposer subsystems, but not much is known on how their interactions are modified by plant diversity and elevated atmospheric CO2 concentrations. Factorially manipulating grassland plant species diversity and atmospheric CO2 concentrations for five years, we tested whether high diversity or elevated CO2 sustain larger or more active soil communities, affect soil aggregation, water dynamics, or nutrient cycling, and whether plant diversity and elevated CO2 interact. Nitrogen (N) and phosphorus (P) pools, symbiotic N2 fixation, plant litter quality, soil moisture, soil physical structure, soil nematode, collembola and acari communities, soil microbial biomass and microflora community structure (phospholipid fatty acid [PLFA] profiles), soil enzyme activities, and rates of C fluxes to soils were measured. No increases in soil C fluxes or the biomass, number, or activity of soil organisms were detected at high plant diversity; soil H2O and aggregation remained unaltered. Elevated CO2 affected the ecosystem primarily by improving plant and soil water status by reducing leaf conductance, whereas changes in C cycling appeared to be of subordinate importance. Slowed-down soil drying cycles resulted in lower soil aggregation under elevated CO2. Collembola benefited from extra soil moisture under elevated CO2, whereas other faunal groups did not respond. Diversity effects and interactions with elevated CO2 may have been absent because soil responses were mainly driven by community-level processes such as rates of organic C input and water use; these drivers were not changed by plant diversity manipulations, possibly because our species diversity gradient did not extend below five species and because functional type composition remained unaltered. Our findings demonstrate that global change can affect soil aggregation, and we advocate that soil aggregation should be considered as a dynamic property that may respond to environmental changes and feed back on other ecosystem functions.     

Natural forest regrowth as a proxy variable for agricultural land abandonment in the Swiss mountains: a spatial statistical model based on geophysical and socio-economic variables

In many European mountain regions, natural forest regrowth on abandoned agricultural land and the related consequences for the environment are issues of increasing concern. We developed a spatial statistical model based on multiple geophysical and socio-economic variables to investigate the pattern of natural forest regrowth in the Swiss mountain area between the 1980s and 1990s. Results show that forest regrowth occurred primarily in areas with low temperature sum, intermediate steepness and soil stoniness as well as close to forest edges and relatively close to roads. Model results suggest that regions with weak labor markets are favored in terms of land abandonment and forest regrowth. We could not find an effect of population change on land abandonment and forest regrowth. Therefore, we conclude that decision makers should consider non-linearities in the pattern of forest regrowth and the fact that labor markets have an effect on land abandonment and forest regrowth when designing measures to prevent agricultural land abandonment and natural forest regrowth in the Swiss mountains.     

应用时间-活动模式估计儿童个体NOx暴露水平

将时间-活动模式与微环境空气污染物监测相结合估计儿童个体NO_x暴露水平. 分别在北京和青岛两市各选择3所学校监测校园环境污染物,并在每个学校选择10名儿童监测其家庭居室空气中ρ(NO_x)及个体24 h NO_x暴露水平,同时收集其时间-活动信息,采用时间-活动模式估计儿童的个体暴露水平. 交通工具中的NO_x暴露水平可通过校门口空气中ρ(NO_x)和交通工具的污染水平系数(λ)估计.结果表明:利用时间-活动模式模拟的儿童个体24 h NO_x暴露水平为0.041 mg/m3,与调整后的个体暴露实测水平相关性较好(R0.785,P<0.01),差值为(-0.002　6±0.013　0) mg/m3,二者的差异无统计学意义 (t0.139,P>0.05).表明采用时间-活动模式与微环境空气质量监测结果相结合方法估计的儿童NO_x暴露水平与个体实际暴露水平一致.