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Forest soil respiration (SR) has become a vital issue in global change ecology because of its critical role in global warming processes. However, SR remains the least understood component of the terrestrial carbon cycle because of its high spatial-temporal variability, inaccessibility of the soil substrate, and the high cost of measurement equipment. This study investigated the spatial and temporal variations of SR in six temperate and subtropical forest sites in eastern China. Seasonal variations of SR, the relationship between SR and soil temperature (ST) and volumetric water content (SW) were analyzed. Mean monthly SR varied seasonally and peaked in summer. SR varied temporally with ST (R² = 0.43∼0.79) in different sites and varied spatially with latitude (R² = 0.68). The responses of SR to the changes of SW varied across different sites and forest types. Their relationships were simulated by piecewise functions in the north three sites. The modules of ST and SW showed that ST is the dominant environmental factor in regulating seasonal dynamics of SR. This study is the first to examine the temporal and spatial variations of SR using a consistent method in situ in temperate and subtropical forests in eastern China. The results provide a scientific basis for accurately assessing future soil CO₂ efflux as a result of climate changes, and aid predictions of the changes of forest SR.
Ground-level sulphur dioxide is one of the air pollutants of high concern as a typical indicator of urban air quality. To inform decisions regarding, for instance, the protection of public health from elevated SO₂ levels in the city of Balikesir, an understanding of spatial-temporal variance of SO₂ patterns is necessary. Therefore, the aim of this study is to locate sample points, characterize distribution patterns, perform the probability map, and map SO₂ distributions by means of spatial information sciences. In this work, the data were compiled from 48 sampling sites using passive sampling on 10-17 March 2010 (in winter) and on 13-20 August 2010 (in summer). The estimations of SO₂ levels at unsampled locations were carried out with the inverse distance weighted method. Finally, locations exceeding the Turkish Air Quality Standard threshold value were determined in the Balikesir by use of geostatistical algorithms (Indicator kriging). The capability of the methods to predict air quality data in an area with multiple land-use types and pollution sources were then discussed. The results of the passive sampling study show that the winter and summer average concentrations are 32.79 µg/m³ and 28.27 µg/m³ for SO₂, respectively. It is expected that where industrial activity is not excessively important, traffic and domestic heating systems are the main source of SO₂ precursors. Moreover, using Indicator Kriging, results show that there are multiple hotspots for SO₂ concentrations and they are strongly correlated to the locations of industrial plants, traffic, and domestic heating systems in Balikesir.
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