One of the most documented effects of human activity on our environment is the reduction of stratospheric ozone resulting in an increase of biologically harmful ultraviolet (UV) radiation. In a less predictable manner, UV radiation incident at the surface of the earth is expected to be further modified in the future as a result of altered cloud condition, atmospheric aerosol concentration, and snow cover. Although UV radiation comprises only a small fraction of the total solar radiation that is incident at the earth’s surface, it has the greatest energy per unit wavelength and, thus, the greatest potential to damage the biosphere. Recent investigations have highlighted numerous ways that UV radiation could potentially affect a variety of ecological processes, including nutrient cycling and the terrestrial carbon cycle. The objectives of the following literature review are to summarize and synthesize the available information relevant to the effects of UV radiation and other climate change factors on the terrestrial carbon balance in an effort to highlight current gaps in knowledge and future research directions for UV radiation research.
Environmental geochemistry of high arsenic groundwater at Hetao plain was studied on the basis of geochemical survey of the groundwater and a core sediment. Arsenic concentration in groundwater samples varies from 76 to 1093 μg/L. The high arsenic groundwater mostly appears to be weakly alkaline. The concentrations of
Samples of groundwater were collected from 17 sites in the Jianghan plain in July 2007. Sixteen phthalate esters (PAEs) were detected in samples collected by using solid-phase extraction (SPE)-gas chromatography (GC). The results show that there were one or several PAEs in all the samples, and the concentrations of total PAEs ranged from 80.12 to 1882.18 ng/L. Four PAEs, i.e. di-iso-butyl phthalate (DIBP), di-n-butyl phthalate (DBP), bis (2-ethoxyethyl) phthalate (BEEP) and di (2-ethylhexyl) phthalate DEHP) were the dominant species. Among these, DIBP, DBP and DEHP concentrations were closely related to the water supply from the Yangtze River, Hanjiang River and Honghu Lake. However, the distribution of BEEP was irregular, which may be due to the application of some kind of products containing BEEP in the related areas. PAE distribution was irrelevant to the electrical conductivity and sample depth.
Snow bacterial abundance and diversity at the Guoqu Glacier and the East Rongbuk Glacier located in the central and southern Tibetan Pateau were investigated using a 16S rRNA gene clone library and flow cytometry approach. Bacterial abundance was observed to show seasonal variation, with different patterns, at the two glaciers. High bacterial abundance occurs during the monsoon season at the East Rongbuk Glacier and during the non-monsoon season at the Guoqu Glacier. Seasonal variation in abundance is caused by the snow bacterial growth at the East Rongbuk Glacier, but by bacterial input from the dust at the Guoqu Glacier. Under the influence of various atmospheric circulations and temperature, bacterial diversity varies seasonally at different degrees. Seasonal variation in bacterial diversity is more distinct at the Guoqu Glacier than at the East Rongbuk Glacier. Bacterial diversity at the two glaciers exhibits different responses to various environmental conditions. More bacteria at the Guoqu Glacier are connected with those from a soil environment, while more bacteria affiliated with a marine environment occur at the East Rongbuk Glacier.
The comparison of the fatty acids between aerobic anoxygenic phototrophic bacteria (AAPB) and their phylogenetic relatives has been a fascinating but yet enigmatic topic, enhancing our understanding of physiological variations between these evolutionarily related microorganisms. Two strains of marine bacteria, both phylogenetically falling into
The stable carbon isotope composition in surface soil organic matter (
The urban fringe, which can be seen as a special form of regional ecosystem with a spatial transition from urban to rural areas, has strong heterogeneity and is a typical ecologically sensitive area. The expansion of cities and the landscape effect of the changes have attracted wide attention. The primary aim of this study is to obtain an understanding of the spatial patterns of landscape conversion and the corresponding environmental sustainability. With the help of GIS and Fragstats software, the changes of landscape patterns before and after town planning were compared in An-Ding town of Beijing, of which the sustainability was also revealed based on the ecological footprint using social and economic statistic data. The results showed that the landscape pattern changed greatly during its conversion from several villages to a small town and the landscape fragmentation increased due to road construction. Meanwhile, human disturbance increased with the constructed land extension. For the gap between the ecological footprint and the biological capacity, An-Ding town ran an ecological deficit at that period, which means it was unsustainable. However, the environmental sustainability decreased after planning due to the degraded green land and forest. The results suggested that ecological management should be strengthened during the town planning period.
Biomass can indicate plant growth status, so it is an important index for plant growth monitoring. This paper focused on the methodology of estimating the winter wheat biomass based on hyperspectral field data, including the LANDSAT TM and EOS MODIS images. In order to develop the method of retrieving the wheat biomass from remote sensed data, routine field measurements were initiated during periods when the LANDSAT satellite passed over the study region. In the course of the experiment, five LANDSAT TM images were acquired respectively at early erecting stage, jointing stage, earring stage, flowering stage and grain-filling stage of the winter wheat, and the wheat biomass was measured at each stage. Based on the TM and MODIS images, spectral indices such as NDVI, RDVI, EVI, MSAVI, SIPI and NDWI were calculated. At the same time, the hyperspectral field data was used to compute the normalized difference in spectral indices, red-edge parameters, spectral absorption, and reflection feature parameters. Then the correlation coefficients between the wheat biomass and spectral parameters of the experiment sites were computed. According to the correlation coefficients, the optimal spectral parameters for estimating the wheat biomass were determined. The best-fitting method was employed to build the relationship models between the wheat biomass and the optimal spectral parameters. Finally, the models were used to estimate the wheat biomass based on the TM and MODIS data. The maximum RMSE of estimated biomass was 66.403 g/m2.