Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.     

Methodological convergence as an issue within environmental cognition research

Two perspectives in the analysis of pointing and mapping tasks as the measure of representations of the large-scale environment are examined. These two perspectives are: (1) an individual difference approach; and (2) a cognitive representational approach. Convergence between methods assessing the same geographical/spatial knowledge is necessary as evidence for the existence of unified cognitive-spatial representations of the environment.Three sets of analyses interrelate performance on pointing and mapping tasks. In the first analysis, a confirmatory factor analytic model is applied to short tests of pointing and mapping accuracy to determine whether one or two factors are needed to account for covariation between the tests. In the second analysis, covariation among errors in pointing and mapping of specific locations is partitioned into general and specific method factors using the Schmid-Leiman procedure. In the third analysis, pointing errors for identical locations within the mapping and pointing tasks are directly compared on the basis of directional errors.The three analyses indicate that: (1) tests of pointing and mapping measure highly related abilities; (2) the targets used in pointing and mapping tasks are of differential importance in identifying general and specific method factors; and (3) there is little or no direct correspondence between directional errors made in pointing tasks and those occurring in mapping tasks for the same locations.When results of the three analyses are examined in relationship to criteria for convergence of pointing and mapping tasks, little evidence is found to suggest that directional errors in these tasks arise from a unified mental representation of the geographical environment. However, substantial predictable individual differences are apparent for both tasks.     

2004～2009年我国典型陆地生态系统地下水硝态氮评价

利用中国生态系统研究网络（CERN）2004～2009年31个典型陆地生态系统38个浅层地下水井硝态氮（NO 3--N）的监测数据,评价我国典型陆地生态系统地下水NO 3--N污染状况.结果表明,农田（4.85 mg.L-1±0.42 mg.L-1）、绿洲农田（3.72mg.L-1±0.42 mg.L-1）、城市（3....     

Ecological indicators of global climate change: A research framework

Large-scale environmental research efforts are conducted under frameworks that provide a common basis for evaluating research in many diverse fields. Such frameworks should be subjected to critical review to determine if they meet crucial expectations. In the case of the US Global Change Research Program, we perceive that most research follows a framework that we define as the predictive model framework. We believe this framework is insufficient for resolving the unprecedented predicaments posed by global change. We recommend a complementary framework, the system response framework, which directs research toward useful indicators of change rather than precise predictions. We further argue that, even if research is complementary and effective under the two frameworks, conclusive results prior to decisions should not be expected. The burden of proof must itself be a continuing topic of open discourse and inquiry.     

The optimal time path of clean energy R&D policy when patents have finite lifetime

We study the optimal time path for clean energy innovation policy. In a model with emission reduction through clean energy deployment, and with R&D increasing the overall productivity of clean energy, we describe optimal R&D policies jointly with emission pricing policies. We find that while emission prices can be set at the Pigouvian level independently of innovation policy, the optimal level of R&D subsidies and patent lifetime change with the stages of the climate problem. In the early stages of clean energy development, innovators find it more difficult to capture the social value of their innovations. Thus, for a given finite patent lifetime, optimal clean energy R&D subsidies are initially high, but then fall over time. Alternatively, if research subsidies are kept constant, the optimal patent lifetime should initially be long and fall over time.     

Path forward: Emerging issues and challenges

The NIOSH Construction Program worked with industry stakeholders to develop a National Occupational Safety and Health Construction Agenda to target future research and activities. The Program and its partners are also cognizant that new developments can emerge over time and that research can play an important role in helping to understand and address these emerging issues. Examples of emerging issues relevant to construction safety and health are described. These include: (a) climate change and energy considerations; (b) green construction developments and opportunities; (c) new materials; (d) changes in industry structure and practice; (e) workforce developments and disparities; (f) injury underreporting and cost and risk shifting; and (g) increased interest in addressing root causes. Responding to emerging issues while maintaining a focus on fundamental longstanding issues represents an ongoing challenge for researchers and industry organizations. Additional research to understand the diffusion and adoption of research by the industry is also needed. Research accomplished to date provides a strong foundation for addressing future industry needs and trends.     

沈阳市环保科技成果产业化工作进展与展望

总结了沈阳市几年来环保科技成果产业化工作的成绩和经验,提出了有效推进环保科技成果转化的建议及对策。     

科技支撑美丽中国建设的进展和展望

自党的十八大提出美丽中国建设目标以来,为发挥好科技支撑作用,国家组织开展了一系列关于资源、生态和环境等领域的科技计划,有效支撑了美丽中国建设的理论探索、生态环境保护修复和生态文明体制建设决策支持等方面的科技需求。本文在梳理过去十年国际及发达国家生态环境领域科技研发布局情况,以及我国相关领域科技研发计划和推进情况的基础上,重点介绍了中国科学院“美丽中国生态文明建设科技工程”战略性先导科技专项（A类）的主要研发内容及取得的阶段进展,并基于现状与期望分析,辨识有关领域科技前沿动态与发展趋势,提出关于下一步科技发展方向的建议,以期为党的二十大之后科技推进美丽中国建设的方向提供参考。     

污水处理技术的研究与发展

随着经济的快速增长以及人口数量的增多,越来越多的生活及工业废水被排出,进入污水处理系统。污水的成分十分复杂,处理不当会对环境造成严重污染,影响到人们的居住环境安全。因此,要想保障人们的居住安全,就必须要针对污水处理技术展开研究,改进污水处理方法,为污水处理系统提供技术支持,为创建更好的居住环境而努力。     

环境监测对环境治理的促进性作用探讨

本文首先概述了环境监测的内容;其次分析了环境监测对环境治理的促进性作用;最后探讨了应用环境监测进一步提升环境治理水平的对策。