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Soil heterotrophic respiration is a major flux of CO2 between terrestrial ecosystems and the atmosphere.It is defined as the sum of carbon releases as gaseous products in the microbial decomposition of soil carbon pool.Soil heterotrophic respiration plays a critical role in regulating the global carbon cycle and is potentially sensitive to climate changes in the future.The alpine area of southwestern China is one of the most sensitive areas to climate change.Therefore,it is of great importance to investigate the response of soil heterotrophic respiration to climate in this region for evaluating the contribution of regional carbon cycle to global climate changes. A process-based biogeochemical model CEVSA(Carbon Exchange between Vegetation,Soil,and the Atmosphere) was used to estimate the temporal and spatial variations of soil heterotrophic respiration(HR) in alpine area of southwestern China during the period from 1954 to 2010.We conducted CEVSA model with observation-based data sets of climate(ten days mean value of temperature,precipitation,relative humidity,and cloudiness),atmospheric CO2 concentration,and soil and vegetation distribution at a spatial resolution of 0.1°.Using the climate,vegetation and soil data,firstly,we ran the model with the average climate data from 1954 to 2010 until an ecological equilibrium was reached,then conducted dynamic simulations with climate data at a time-step of ten days from 1954 to 2010.Also,the correlation coefficients between soil HR and climate variables were calculated to analyze the response of soil heterotrophic respiration to climate change.To achieve the results,various kinds of computer software were used,such as ANUSPLIN4.1,Fortran 90,Arcgis 9.3,SPSS18.0.The results showed that:(1) The mean values of soil HR density was 422 g C · m-2 · a-1 during the period of 1954—2010 in alpine area of southwestern China.The soil HR showed a decreasing trend from southeast to northwest and had significant positive correlation with both annual mean temperature(r = 0.721,P 0.01) and annual total precipitation(r = 0.564,P 0.01).(2)Total annual soil HR showed an increasing trend with the rate of 0.710 Tg C/a(P0.05),and varied between 197 and 251 Tg C/a.The increasing rate was 1.621,1.496 and 1.055 g C · m-2 · a-2 in grassland,evergreen coniferous forest and evergreen broad-leaved forest(P0.01),which were three main vegetation types in alpine area of southwestern China,respectively.(3) Annual variation of soil HR was mainly influenced by temperature.The temperature sensitivity of soil HR(Q10) in the high-elevation northwestern areas was higher than that in the low-elevation southeastern areas,and it is 2.35,2.34 and 1.93 in grassland,evergreen coniferous forest and evergreen broad-leaved forest in this area,respectively. Soil heterotrophic respiration is an extremely complex process involving a variety of biological and non-biological factors.Climate and vegetation changed with topography and high space heterogeneity existed in alpine area of southwestern China.For these reasons,we suggest that the model resolution should be improved and validation of the simulation result should be strengthened in future to reduce uncertainty.

The research on the impact of rainfall on soil respiration is significant to predict accurately the carbon balance of terrestrial ecosystems under future climate change.It is consensus that a certain degree of drought would suppress soil respiration,as well as the processes of water,carbon and nitrogen would be excited after re-watering by precipitation or irrigation.However,some research showed the suppression of soil respiration by precipitation.As a disturbance factor,the effect of precipitation on soil respiration is complex because of different vegetation and soil type in different regions.It is necessary to reveal the impact of rainfall amount,intensity and duration on soil respiration under different soil water content,as well to make clear the turning point of suppression or excitation of soil respiration in different regions.In a maize cropland located at eastern Loess Plateau,soil respiration and its components was measured continuously around 3 rainfall incidents based on in situ observation technique,and the impact of rainfall on soil respiration and its components was analyzed. The study was conducted in Shouyang county,Shanxi Province.It is a semi-humid area.The seasonal variation of precipitation is large,about 70% of annual amount occurs from June to September.In the field of maize cropland,soil respiration and its components were measured continuously by LI-8150 Soil CO2 Flux System.Soil respiration was divided into microbial respiration and root respiration respectively based on root exclude method.Each treatment was repeated twice,and there were 4 observation fields in total. There were 3 rainfalls recorded during July and August,and we analyzed the variation of soil respiration and its components before and after the 3 rainfalls.The results showed that rainfall suppressed the soil CO2 efflux obviously under high soil water content.When soil volumetric water content was higher than 21.2%,20.7% and 21.8%,respectively,soil respiration,microbial respiration and root respiration decreased obviously with the increase of soil water content,and the sensitivity of soil respiration to soil temperature also decreased.The variation of soil respiration and its components were influenced by both soil temperature and moisture.The amount and duration of rainfall and soil water content before rainfall decided the intensity and duration of response to precipitation.The temperature sensitivity of soil respiration and its components were different with each other.The temperature sensitivity of microbial respiration was the highest,Q10 was 5.14,and the second highest was soil respiration with Q10 3.86.The temperature sensitivity of root respiration was the lowest,and Q10 was 3.24.The ratio of root respiration to soil respiration increased after rainfall because the different sensitivity of respiration to temperature and moisture.Two factor model,including soil temperature and soil water content,was able to evaluate the response of soil respiration and microbial respiration to the variation of environmental factors in the maize ecosystem.

There are various types of ecosystems and complex landform in alpine area of southwestern China,which make it very sensitive to global climate change.Quantifying the spatial and temporal variation of terrestrial ecosystem carbon sink in this place requires a detailed understanding of carbon exchange between vegetation,soil,and the atmosphere.A process-based biogeochemical model CEVSA(Carbon Exchange between Vegetation,Soil,and the Atmosphere) was used to estimate temporal and spatial variations of net ecosystem production(NEP) in alpine area of southwestern China from 1954 to 2010.In this study,the set of independent environmental variables to run the model consisted of climate(ten days mean value of temperature,precipitation,relative humidity,cloudiness),atmospheric CO2 concentration,soil and vegetation types at a spatial resolution of 0.1°.We first ran CEVSA model with average climate data during the period 1954—2010 until an ecological equilibrium was reached,then made dynamic simulations from 1954 to 2010 with transient changes in climate at a time-step of ten days.To achieve the results,various kinds of computer software were applied,such as ANUSPLIN4.1,Arcgis9.3,SPSS18.0,Fortran 90.The results showed:(1)The mean value of NEP was 29.7 g C · m-2 · a-1 during the period 1954—2010 in alpine area of southwestern China,with higher NEP in the evergreen needle-leaved and evergreen broadleaved tree cover at low altitude and lower NEP in herbaceous cover at high altitude of study area.(2) Annual total NEP ranged from-8.36 to 29.4 Tg C/a with a mean value of 15.4 Tg C/a.NEP showed a statistically significant decreasing trend with a reduction rate of 0.187 Tg C/a(P0.05) during the period 1954—2010 and the significant decreasing area of NEP accounted for 35.2%(P0.05).The decreasing trend was highly significant in herbaceous cover(-0.526 g C · m-2 · a-2,P0.01) and evergreen needle-leaved tree cover(-0.691 g C · m-2 · a-2,P0.01).(3)Annual total NEP was significantly negatively correlated with annual mean temperature(AMT)(r=-0.454,P0.01) and positively correlated with annual total precipitation(ATP)(r=0.708,P0.01).The negative correlation(P0.05) of annual NEP and AMT existed in 60.3% of the study region while the positive correlation(P0.05) of annual NEP with ATP existed in 52.1% of the study region,respectively.Herbaceous cover and evergreen needle-leaved tree cover as the two main vegetation types in study area were both correlated negatively with AMT(r=-0.603,P0.01;r=-0.485,P0.01) and positively with ATP(r=0.554,P0.01;r=0.749,P0.01),reaching an extremely remarkable level.(4)Alpine area of southwestern China acted as a carbon sink,however,a small fraction of terrestrial ecosystems here shifted from carbon sinks into carbon sources in recent 20 years,for that the NPP(net primary production) growth rate was less than that of the soil HR(heterotrophic respiration).These estimates indicate that the carbon sequestration capacity in alpine area of southwestern China was weakened by the ongoing climate change.

Model predictions can be improved by parameter estimation from measurements. It was assumed that measurement errors of net ecosystem exchange (NEE) of CO2 follow a normal distribution. However, recent studies have shown that errors in eddy covariance measurements closely follow a double exponential distribution. In this paper, we compared effects of different distributions of measurement errors of NEE data on parameter estimation. NEE measurements in the Changbaishan forest were assimilated into a process-based terrestrial ecosystem model. We used the Markov chain Monte Carlo method to derive probability density functions of estimated parameters. Our results showed that modeled annual total gross primary production (GPP) and ecosystem respiration (Re) using the normal error distribution were higher than those using the double exponential distribution by 61–86 gC m−2 a−1 and 107–116 gC m−2 a−1, respectively. As a result, modeled annual sum of NEE using the normal error distribution was lower by 29–47 gC m−2 a−1 than that using the double exponential error distribution. Especially, modeled daily NEE based on the normal distribution underestimated the strong carbon sink in the Changbaishan forest in the growing season. We concluded that types of measurement error distributions and corresponding cost functions can substantially influence the estimation of parameters and carbon fluxes.

Locating in the Tarim Basin of Xinjiang, china, the Taklamakan Desert is an important replacement district of China oil industry development. In the Taklamakan Desert, climate is extreme arid, and rainfall quantity is below 50mm.Though groundwater is plentiful, mineral content is higher. During the course of oil field base construction, with the exploitation of desert oil and natural gas resource we get success in planting and vegetable growing in use of highly saline water at the rate of 4 to 5 g/1. Highly saline water mainly contains Cl− and So4 2−. The water shows a little alkaline (PH7–8). Greening plant selected includes sand-fixation shrubs, flowers and turf plants. The kinds of vegetable include tomato, celery, spinach and so on. Plants provide a material basis for almost 3000 (sometimes even 5000) oil works in desert oil field base to improve ecology environment. Meanwhile, it also provides fresh vegetable. Green plants offer living and inhabitation environment for other animals, too. In past there were only 35 kinds of wildlife (including insect). At present there are 57 kinds of animals. The quantity of microorganism as decomposer in vegetation systems also adds thousands of times.