华西雨屏区不同密度巨桉人工林土壤呼吸特征

从2008-03至2009-02,采用闭合动态法(LI-6400-09)对华西雨屏区不同密度中龄巨桉人工林土壤呼吸进行了研究。结果表明:①该林分土壤呼吸具有明显的季节动态,各密度林分土壤呼吸速率最高值均出现在7月份,最低出现在1月,且密度为883株·hm^-2(1.5 m×8 m)的巨桉林土壤呼吸速率最大,2 222株·hm^-2(1.5 m×3 m)的最小;②2008年4、7、10月土壤呼吸速率24 h平均值均表现为883株·hm^-2> 1 333株·hm^-2> 2 222株·hm^-2,且7月>4月>10月;③土壤微生物生物量碳氮、土壤有机质含量和10 cm根系生物量都表现出相同的趋势,即林分密度越小,土壤微生物生物量碳氮越高,草本植物越多,根系生物量越大,有机质含量越多;④温度是巨桉林土壤呼吸变异的主导因子,土壤呼吸速率与土壤温度和湿度的双因素模型优于单因素模型,两者共同解释了土壤呼吸速率月动态的78.3%~91.5%;⑤各密度林分土壤呼吸Q₁₀值随巨桉林分密度增大而降低,大小顺序为3.65(883株·hm^-2)>2.60(1 333株·hm^-2)>2.55(2 222株·hm^-2)。     

Mining and social development: Refocusing community investment using multi-criteria decision analysis

This paper addresses the question: How can mining companies assess social investment projects so that projects create value for the company and communities in which they operate? Mining companies are still wrestling with the limits of their responsibility in relation to social development even though they accept the business case for community investment at a general level. Fully aware of the practical hazards involved in taking an active role in facilitating local development, companies increasingly avoid methods that are overly paternalistic or assume the functions of the national or local governments. Gaining senior management's commitment to long-term social projects, which are characterised by uncertainty and complexity, is made easier if projects are shown to benefit the site's strategic goals. Case study research on large global mining companies, including interviews with social investment decision makers, has assisted in developing a Social Investment Decision Analysis Tool (SIDAT), a decision model for evaluating social projects. Multi-criteria decision analysis techniques integrating business planning processes with social impact assessment have proved useful in assisting mining companies think beyond seeking reputational benefits, to how they can meet their business goals and contribute to sustainable development.     

Natural resource abundance in Nigeria: From dependence to development

There are several strategies open to an economy in its attempt to attain sustainable economic development depending on its historical background and resource endowment. One of such is the resource-led strategy. Nigeria is superabundantly rich in crude oil and has reaped billions of petrodollars. However, the country seems to be facing the problem of successfully translating this huge oil wealth into sustainable development. This paper employs the vector error-correction methodology in examining the long-run impact of the huge oil wealth accruing to Nigeria on its economic development. Indicators such as per capita GDP (PGDP), household consumption, infrastructural development (electricity), and agricultural and manufacturing output growth rates are examined. The results suggest a significant positive long-run impact of per capita oil revenue on per capita household consumption and electricity generation, while a negative relationship is established for GDP, agriculture and manufacturing. Even for those variables with negative relationship at current period, there exist positive relationships at subsequent lags. Thus, oil revenue, if properly managed and invested, could be effectively used to induce oil-led development in Nigeria provided the current inhibitions of corruption, lack of transparency, accountability and fairness in its use and distribution are removed.     

Financial and economic factors affecting the lignite prices in Turkey: An analysis of Soma and Can lignites

Using a simultaneous equation econometric model based on yearly data between 1997 and 2006 for the Aegean Lignite Enterprise this study examines factors that affect the lignite price in Turkey. The Aegean Lignite Enterprise produces and sells the lignite of Soma and Can and their data reflect the general Turkish situation. The results suggest that (1) lignite prices sold to the industry increase (decrease) depending on the decrease (increase) in the industrial production and (2) total electricity production and electricity price are the most important factors that potential investors and related persons have to take into consideration for the pricing of lignite in the thermal power plant market.     

Is corporate social responsibility possible in the mining sector? Evidence from Catalan companies

This paper examines the role and diffusion of corporate social responsibility (CSR) management, especially in relation with the adoption of other management systems, in small and medium sized companies in the surface mining industry in Catalonia (Spain). Specifically, it identifies the most salient CSR practices, procedures and metrics and the profiles of companies more prone to adopt them. To fulfill this aim, a survey has been conducted. Results show that mining companies are familiar with CSR practices, but there is not much formalization of procedures and measurement systems of CSR yet. Results show that the majority of socially responsible practices are related to environmental issues and therefore there is a relation between CSR and the application of environmental management systems. The analysis reveals that the management of CSR activities improves with the diffusion of knowledge on CSR practices. A second survey collected the opinion of professional associations in the sector. Respondents indicate that an improvement in CSR management will lead to a better global competitive position.     

How can public–private partnerships contribute to security and human rights policy and practice in the extractive industries? A case study of The Democratic Republic of Congo (DRC)

Across sub-Saharan Africa, the presence of foreign large-scale mining companies is increasing. This is in part a result of depleting resources in countries such as Canada, United States and Australia, and in part from a more favorable national mine investment climate in several mineral-rich African countries. Their increased presence raises important questions around the potential role and function of Corporate Social Responsibility (CSR) in the sector. In post-conflict and/or fragile states, CSR has further implications for conflict and risk mitigation strategies to ensure the protection of human rights. One CSR approach increasingly being considered is the public–private partnership, whereby companies, public donors, and development agencies leverage their relationships for mutual benefit. There is merit in exploring its function in post-conflict fragile states, where socio-economic needs are high and the capacity of the state to respond to a variety of mine governance challenges is limited. Two case studies from the Democratic Republic of Congo (DRC) are presented, and their policy implications, discussed.     

The macroeconomic determinants of volatility in precious metals markets

This paper models the monthly price volatilities of four precious metals (gold, silver, platinum and palladium prices) and investigates the macroeconomic determinants (business cycle, monetary environment and financial market sentiment) of these volatilities. Gold volatility is shown to be explained by monetary variables, but this is not true for silver. Overall, there is limited evidence that the same macroeconomic factors jointly influence the volatility processes of the four precious metal price series, although there is evidence of volatility feedback between the precious metals. These results are consistent with the view that precious metals are too distinct to be considered a single asset class, or represented by a single index. This finding is of importance for portfolio managers and investors.     

The evolution of the Canadian mining industry: The role of regulatory punctuation

In this study, we analyze the evolution of Canada's mining industry from 1929 to 2006, focussing on the determinants of the number of firms in the industry and why this number changed over that period. Most empirical studies of industry evolution have focused on manufacturing industries that share similar structural characteristics. Perhaps because of this, extant models of industry evolution tend to ignore industry-specific and national-specific factors that can cause atypical trajectories, that is, heterogeneous industry evolution. Initial inspection of the Canadian mining industry shows that it is atypical in that it exhibits “negative skew” over time in the number of firms rather than the typical “positive skew.” We review two dominant theoretical approaches to industry evolution: the density-dependence theory and variants of industrial organization economics. We also consider possible sources of industry evolution heterogeneity, focussing particularly on “regulatory punctuation”. Using Canadian mining data, we find that the traditional models do not fully explain the changes in population size in Canada's mining industry. As a result, we introduce a number of hybrid models. The results from these hybrid models suggest that Canadian-specific regulatory punctuations, particularly the introduction of significant new taxes, environmental legislation, and incentives have shaped the trajectory of mining firm participation.     

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis.     

Determination of Q1, an unknown organochlorine contaminant, in human milk, Antarctic air, and further environmental samples

Q1, an organochlorine component with the molecular formula C(9)H(3)Cl(7)N(2) and of unknown origin was recently identified in seal blubber samples from the Namibian coast (southwest of Africa) and the Antarctic. In these samples, Q1 was more abundant than PCBs and on the level of DDT residues. Furthermore, Q1 was more abundant in seals from the Antarctic than the Arctic. To prove this assumption, gas chromatography-electron-capture negative ion mass spectrometry (GC/ECNI-MS), which is sensitive and selective for Q1, allowed for screening of traces of Q1 even in samples with particularly high levels of other organochlorine contaminants. Q1 was isolated by high-performance liquid chromatography (HPLC) from a skua liver sample. A 1:1 mixture with trans-nonachlor in electron-capture detectors (ECDs) was used to determine the relative response factor with ECNI-MS. The ECNI-MS response of Q1 turned out to be 4.5 times higher than that of trans-nonachlor in an ECD. With GC/ECNI-MS in the selected ion-monitoring mode, four Antarctic and four Arctic air samples were investigated for the presence of Q1. In the Antarctic air samples, Q1 levels ranged from 0.7 to 0.9 fg/m(3). In Arctic air samples, however, Q1 was below the detection limit (<0.06 fg/m(3) or 60 ag/m(3)). We also report on high Q1 levels in selected human milk samples (12-230 microg/kg lipid) and, therefore, suggested that the unknown Q1 is an environmental compound whose origin and distribution should be investigated in detail. Our data confirm that Q1 is a bioaccumulative natural organochlorine product. Detection of a highly chlorinated natural organochlorine compound in air and human milk is novel.