磁化处理对水体的复氧速率及生物效应影响的研究

通过试验证明，磁化处理不仅可引起水体物理、化学性质的异常变化，而且还强烈影响水体的生物性质（刺激藻类生长、抑止异养菌数等）。磁化处理引起藻类生产力显著提高的特殊生物效应，对加速水体的复氧能力，提高自净效率，有着重要的意义。     

土地生产潜力的计算方法

本文通过对国外土地生产潜力计算方法的评述,展示了这一领域的研究前沿和发展动态,提出了今后的努力方向。     

Regional assessment of climate change impacts on maize productivity and associated production risk in Switzerland

A simple model of yield was used along with climate scenarios to assess the impact of climate change on grain maize productivity and associated economic risk in Switzerland. In a first application, changes in the precipitation regime alone were shown to affect the distribution of yield considerably, with shifts not only in the mean but also in the standard deviation and the skewness. Production risk was found to respond more markedly to changes in the long-term mean than in the inter-annual variability of seasonal precipitation amounts. In a further application, yield projections were generated with respect to a full climate scenario, with the emission pathway as specified in the IPCC A2 scenario. Anticipation of the sowing date was found to reduce the negative impact of climate change on yield stability, but was not sufficient to ensure average productivity levels comparable to those observed at present. We argued that this was caused by the reduction in the duration of the growing season, which had a stronger impact than suggested by previous studies. Assuming no change in price relations, the results also revealed a strong increase in production risk with climate change, with more than a doubling in the probability of yield falling short of a critical threshold as compared to today’s situation.     

Prospering Revolution of Resource Efficiency in Northeast Industrial Area in China

Despite its strong advantages in resource, technology and human resource, China＇s Northeast Industrial Area is also experiencing problems of unreasonable industrial structure, environmental pollution, and the degradation of ecological condition, etc., which prevent this area from achieving a sustainable devel- opment. Through analyzing the resource problem, the present paper proposed a strategy of circular economy for the prosperity of this are, discussed the theories of circular economy and resource recycling, and finally concluded that improving resource productivity is at the core of circular economy.     

Response of tree growth to a changing climate in boreal central Canada: A comparison of empirical,process-based,and hybrid modelling approaches

The impact of 2 × CO₂ driven climate change on radial growth of boreal tree species Pinus banksiana Lamb., Populus tremuloides Michx. and Picea mariana (Mill.) BSP growing in the Duck Mountain Provincial Forest of Manitoba (DMPF), Canada, is simulated using empirical and process-based model approaches. First, empirical relationships between growth and climate are developed. Stepwise multiple-regression models are conducted between tree-ring growth increments (TRGI) and monthly drought, precipitation and temperature series. Predictive skills are tested using a calibration–verification scheme. The established relationships are then transferred to climates driven by 1× and 2 × CO₂ scenarios using outputs from the Canadian second-generation coupled global climate model. Second, empirical results are contrasted with process-based projections of net primary productivity allocated to stem development (NPP_s). At the finest scale, a leaf-level model of photosynthesis is used to simulate canopy properties per species and their interaction with the variability in radiation, temperature and vapour pressure deficit. Then, a top-down plot-level model of forest productivity is used to simulate landscape-level productivity by capturing the between-stand variability in forest cover. Results show that the predicted TRGI from the empirical models account for up to 56.3% of the variance in the observed TRGI over the period 1912–1999. Under a 2 × CO₂ scenario, the predicted impact of climate change is a radial growth decline for all three species under study. However, projections obtained from the process-based model suggest that an increasing growing season length in a changing climate could counteract and potentially overwhelm the negative influence of increased drought stress. The divergence between TRGI and NPP_s simulations likely resulted, among others, from assumptions about soil water holding capacity and from calibration of variables affecting gross primary productivity. An attempt was therefore made to bridge the gap between the two modelling approaches by using physiological variables as TRGI predictors. Results obtained in this manner are similar to those obtained using climate variables, and suggest that the positive effect of increasing growing season length would be counteracted by increasing summer temperatures. Notwithstanding uncertainties in these simulations (CO₂ fertilization effect, feedback from disturbance regimes, phenology of species, and uncertainties in future CO₂ emissions), a decrease in forest productivity with climate change should be considered as a plausible scenario in sustainable forest management planning of the DMPF.     

Modification of an ecosystem model for filling medium-sized gaps in tower-based estimates of net ecosystem productivity

Gap filling of flux data is necessary to assist with periodic interruptions in the measurement data stream. The gap-filling model (GFM), first described in Xing et al. [Xing, Z., Bourque, C.P.-A., Meng, F.-R., Zha, T.-S., Cox, R.M., Swift, E., 2007. A simple net ecosystem productivity model for gap filling of tower-based fluxes: an extension of Landsberg's equation with modifications to the light interception term. Ecol. Model. 206, 250–262], was modified to account for the day-to-day control of net ecosystem productivity (NEP) by incorporating air and soil temperature as new controlling variables in the calculation of NEP. To account for the multiple-phase influences of air and soil temperature on plant growth we model ecosystem respiration as a function of soil and canopy respiration. The paper presents model development in an incremental fashion in order to quantify the contribution of individual model enhancements to the prediction of NEP during periods when air and soil temperature variations are important.     

Aging and demographic plasticity in response to experimental age structures in honeybees (<Emphasis Type="Italic">Apis mellifera</Emphasis> L)

Honeybee colonies are highly integrated functional units characterized by a pronounced division of labor. Division of labor among workers is mainly age-based, with younger individuals focusing on in-hive tasks and older workers performing the more hazardous foraging activities. Thus, experimental disruption of the age composition of the worker hive population is expected to have profound consequences for colony function. Adaptive demography theory predicts that the natural hive age composition represents a colony-level adaptation and thus results in optimal hive performance. Alternatively, the hive age composition may be an epiphenomenon, resulting from individual life history optimization. We addressed these predictions by comparing individual worker longevity and brood production in hives that were composed of a single-age cohort, two distinct age cohorts, and hives that had a continuous, natural age distribution. Four experimental replicates showed that colonies with a natural age composition did not consistently have a higher life expectancy and/or brood production than the single-cohort or double-cohort hives. Instead, a complex interplay of age structure, environmental conditions, colony size, brood production, and individual mortality emerged. A general tradeoff between worker life expectancy and colony productivity was apparent, and the transition from in-hive tasks to foraging was the most significant predictor of worker lifespan irrespective of the colony age structure. We conclude that the natural age structure of honeybee hives is not a colony-level adaptation. Furthermore, our results show that honeybees exhibit pronounced demographic plasticity in addition to behavioral plasticity to react to demographic disturbances of their societies.     

2000~2010年中国资源产出率测算

在中国实际管理需求的基础上,构建了中国经济系统物质流分析(Chinese Economy-wide Material Flow Analysis - CEW-MFA)模型,对传统经济系统物质流分析工具进行了补充和拓展.在该模型的基础上将中国的RP定义为一组4个指标:直接物质投入(DMI)/GDP、本地物质消耗(DMC)/GDP、物质总循环量(CR)/(CR+DMI)与CR/固体废物总产生量(TG).测算了2000~2010年时间段的物质流及RP指标,并对其中的资源经济产出效率进行了国际比较.结果表明,中国现阶段的物质代谢总量高,2010年国家的DMI接近120亿t,DMC超过107亿t.中国资源的经济产出效率与主要发达国家相比仍有较大差距.2010年的GDP/DMI与GDP/DMC分别为2260,2512元/t.循环物质总量有较大幅度的增长,综合利用率CRR(1)与CRR(2)总体保持上升趋势.CRR(1)从2000年的16%升至2010年的23%,CRR(2)由46.8%升至54.1%.     

我国城镇污水处理厂运行效率评价

污水处理厂运行效率的定量评价是当前污水处理行业管理需要解决的问题,效率研究将有助于政府制订合理政策以促进污水处理厂的发展. 基于全要素生产框架,采用DEA(数据包络分析)方法构建了污水处理厂运行效率评价模型,以固定资产总额、年运行费用、污水处理人员数和年耗电量为投入变量,以污水年处理量、BOD₅和氨氮削减量为产出变量,对2013年我国74座排放标准为一级A且处理工艺相同的城镇污水处理厂作为样本进行效率评价,基于评价结果,对运行效率和污水厂处理规模之间的关系进行检验,并对样本的投入冗余和产出不足情况进行定量分析. 结果显示:有20个样本的运行效率达到相对最优,可以成为其余效率不足样本今后改进的标杆;有10个样本纯技术效率有效但规模效率无效,需要改进其规模;85.2%的DEA无效样本规模报酬为递增状态,表明我国污水处理行业整体上处于规模收益递增的发展阶段;通过KW(Kruskal-Wallis)检验发现,样本污水处理厂具有规模效应,规模越大的运行效率越高;54个DEA无效样本存在不同程度的投入冗余和产出不足,冗余率或不足率较高的样本是今后进行效率改进的重点对象.      

Spatial impacts of climate factors on regional agricultural and forestry biomass resources in north-eastern province of China

The dynamics of agricultural and forestry biomass are highly sensitive to climate change, particularly in high latitude regions. Heilongjiang Province was selected as research area in North-east China. We explored the trend of regional climate warming and distribution feature of biomass resources, and then analyzed on the spatial relationship between climate factors and biomass resources. Net primary productivity (NPP) is one of the key indicators of vegetation productivity, and was simulated as base data to calculate the distribution of agricultural and forestry biomass. The results show that temperatures rose by up to 0.37°C/10a from 1961 to 2013. Spatially, the variation of agricultural biomass per unit area changed from -1.93 to 5.85 t·km^–2·a^–1 during 2000–2013. More than 85% of farmland areas showed a positive relationship between agricultural biomass and precipitation. The results suggest that precipitation exerts an overwhelming climate influence on agricultural biomass. The mean density of forestry biomass varied from 10 to 30 t·km^–2. Temperature had a significant negative effect on forestry biomass in Lesser Khingan and northern Changbai Mountain, because increased temperature leads to decreased Rubisco activity and increased respiration in these areas. Precipitation had a significant positive relationship with forestry biomass in south-western Changbai Mountain, because this area had a warmer climate and stress from insufficient precipitation may induce xylem cavitation. Understanding the effects of climate factors on regional biomass resources is of great significance in improving environmental management and promoting sustainable development of further biomass resource use.

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