Junxia Yan

Vegetation net primary productivity and its response to climate change during 2001-2008 in the Tibetan Plateau

Alpine ecosystems are highly sensitive to global climate changes. The Tibetan Plateau is one of the areas that are most sensitive to global climate change. Increases in temperature and changes in precipitation can impact the plateaus ecosystem productivity. Net primary productivity (NPP) is one of the most important factors in the carbon cycle of terrestrial ecosystems. In this paper, a light-use-efficiency model was used to estimate the net primary productivity in the Tibetan Plateau. The model is based on a 1-km×1-km-resolution map of vegetation type, multi-temporal 500-m-resolution MODIS data and daily meteorological data. The spatial distribution pattern and dynamic change of the annual NPP from 2001 to 2008 are analyzed. Then, we analyzed the response of the NPP to temperature and precipitation changes. The results show that the mean annual NPP of alpine ecosystems in the Tibetan Plateau is equal to 0.472 Pg C and that the NPP exhibits significant seasonal and interannual variation due to the combined effects of temperature and precipitation changes. Finally, to analyze the effect of temperature and precipitation on the inter-annual change of the NPP, the correlation coefficient between temperature, precipitation and the NPP was computed. It was found that the relations among air temperature, precipitation and the NPP in the Tibetan Plateau region are different. The annual average temperature increase had a significantly positive effect on the vegetation NPP (R(2)=0.83). In contrast, the annual precipitation changes had a weakly negative effect on the vegetation NPP (R(2)=0.373).

Succession of plant and soil microbial communities with restoration of abandoned land in the Loess Plateau, China

PurposeThere have been a number of studies on the succession of vegetation; however, the succession of soil microbes and the collaborative relationships between microbes and vegetation during land restoration remain poorly understood. The objectives of this study were to characterize soil microbial succession and to explore the collaborative mechanisms between microbes and vegetation during the restoration of abandoned land through quantitative ecology methods.Materials and methodsThe present research was carried out in the succession of a 5-year abandoned land and its conversion to Hippophae rhamnoides shrubs, Larix principis-rupprechtii plantation, and a naturally regenerated forest (mixed forest). Soil bacterial, archaeal and fungal characteristics were tested by real-time quantitative PCR assays and terminal restriction fragment length polymorphism. The richness, diversity, and evenness indices were employed to analyze plant and microbial communities’ structure. The stability of plant and microbial communities was tested using Spearman’s rank correlation. The relationships between the regeneration scenarios and environmental factors were determined through canonical correspondence analysis.Results and discussionThe aboveground biomass was significantly different among the sites. Soil bacterial, archaeal, and fungal rRNA gene abundances did not increase significantly with increasing soil organic carbon content. There were higher correlation coefficients between plant and total microbial communities on the richness, diversity, and evenness indices and ratios of positive to negative association compared to ones between plant and individual bacteria, archaea, and fungi. Soil bulk density, clay, pH, and litter were the primary significant environmental factors affecting the structure of plant and microbial communities. The positive relationships between plant and soil bacteria, fungi, and total microbe communities, as well as the negative relationships between plant and archaea, were demonstrated.ConclusionsThe results suggested that plants promote the growth of soil bacteria and fungi during the process of community succession on a small scale; however, plants inhibit the growth of soil archaea.

Effects of Different Regeneration Scenarios and Fertilizer Treatments on Soil Microbial Ecology in Reclaimed Opencast Mining Areas on the Loess Plateau, China

The soil microbial community in reclaimed mining areas is fundamental to vegetative establishment. However, how this community responds to different regeneration scenarios and fertilizer treatments is poorly understood. This research evaluated plant and soil microbial communities from different regeneration scenarios and different fertilizer treatments. Regeneration scenarios significantly influenced soil bacterial, archaeal, and fungal rDNA abundance. The ratios of fungi to bacteria or archaea were increased with fertilizer application. The diversity of both plants and microbes was lowest in Lotus corniculatus grasslands. Regeneration scenario, fertilizer treatment, and their interaction influenced soil microbial richness, diversity and evenness indices. Labile carbon pool 2 was a significant factor affected plant and microbe communities in July, suggesting that plants and microbes may be competing for nutrients. The higher ratios of positive to negative association were found in soil bacteria and total microbe than in archaea and fungi. Stronger clustering of microbial communities from the same regeneration scenario indicated that the vegetative composition of regeneration site may have a greater influence on soil microbial communities than fertilizer treatment.

Labile and Recalcitrant Organic Matter and Microbial Communities in Soil After Conversion of Abandoned Lands in the Loess Plateau, China

To control serious soil erosion in the Loess Plateau of China, many areas are subjected to afforestation and subsequent shifts in the pool of soil organic matter. In this study, we investigated changes of labile and recalcitrant carbon (C) and nitrogen (N) pools, inorganic N, and microbial populations in environments of 5-year abandoned land, Hippophae rhamnoides shrubs, Larix principis-rupprechtii plantation, and a naturally regenerated forest. Soil general physicochemical and microbial characteristics were improved significantly in 30-year restoration compared with 5-year abandoned land. At the soil surface, the highest levels of C, N, and microbes were observed in mixed forest and the lowest on abandoned land in most conditions. Vegetation types, soil depth, and sampling date as well as their interaction produced significant influences on soil properties. Soil characteristics tested in this study indicated that the natural regeneration of forests may be a better restoration method than pure shrub and tree plantations.

Physicochemical and microbiological assessment of soil quality on a chronosequence of a mine reclamation site: Soil quality of mine reclamation

Assessment of the activity of the soil microbial community is essential to evaluate the success of reclamation. The purpose of this study was to investigate the effect of reclamation on soil physiochemical, biological and microbial community properties. Soil samples were collected from 12 post-mining sites with different lengths of time since reclamation (2, 3, 5, 6, 7, 9, 11, 16, 19, 21, 23 and 26 years) at Pingshuo surface coal mine, China. Our results indicated soil organic and labile carbon, nitrogen, enzyme activities, microbial functional diversity, bacterial, archaeal and fungal abundances and taxonomic diversity improved with increasing time since reclamation. Soil pH and bulk density declined with increasing time after reclamation. Redundancy analysis revealed the importance of soil pH in microbial metabolic structure and bacterial genetic assemblages, and soil organic carbon in fungal genetic assemblages. The mine soil quality index (MSQI) was positively correlated with time since reclamation, and reclamation could be considered satisfactory at the 19-year site with an MSQI >0.5. Soil enzyme activities were strongly correlated with microbial abundance. Our overall findings indicated that nutrition, microbial abundance and functional diversity of the soil ecosystem improved after reclamation.

Soil Respiration Characteristics in Three Shrublands along an Elevation Gradient in a Semiarid Loess Plateau Mountain Area

ABSTRACT Shrub is one of the major vegetation types distributed mostly in the mountainous area in China, and its vegetation carbon storage is approximately one-third of both forests and grasslands. It is essential to investigate how soil temperature (Ts) and soil water content (Ws) affect soil respiration (Rs) in this ecosystem. The purpose of this study was to understand the correlations of Rs with Ts, Ws, and other factors in the shrubs. In the current study, Rs was characterized in three shrublands (hereafter, shrub 1, shrub 2, and shrub 3, respectively) located in different elevations over a 4-year period at a biweekly interval in the eastern Loess Plateau (Shanxi province) of China. Our results showed that the trend of seasonal change of Rs was controlled mainly by Ts and Ws. The measured mean Rs over 4 years was 3.64 ± 2.83 (mean ± S.D.), 2.69 ± 2.05, and 4.41 ± 3.28 μmol carbon dioxide (CO2) m−2 s−1 for shrubs 1, 2, and 3, respectively, exhibiting an increase trend with elevation increment. Over the season, Rs illustrated a significant change depending on the variation of Ts and Ws, with larger values appearing in summer when both Ts and Ws were high, and smaller values in winter or in summer whenever Ws was low. An exponential model (Rs = a e bTs) fitted well the relation between Rs and Ts for shrub 3, whereas linear (Rs = a Ws + b) and power (Rs = a Ws b) models of Rs to Ws fitted well for shrub 1. This indicated that at a lower elevation, Ws had a greater effect on Rs than that at a higher elevation. The reverse trend was true between Rs and Ts, i.e., at a higher elevation Ts had a greater effect on Rs than that at a lower elevation. The calculated Q10 values of 1.61, 3.03, and 3.73 for shrubs 1, 2, and 3 increased to 2.25, 3.63, and 4.07, respectively (when the data in low Ws conditions were excluded from the analysis), showing that Q10 increased with elevation increment. Furthermore, three two-variable models, one linear (Rs = a (Ts Ws) + b), and two nonlinear (Rs = a Ts b Ws c and Rs = a ebTs Ws c), were also well developed to predict the dependency of Rs on both Ts and Ws. Our research results might have important implications for the estimation of soil carbon emissions of the shrublands in this region.

Response of soil respiration to temperature and soil moisture: Effects of different vegetation types on a small scale in the eastern Loess Plateau of China

Soil respiration is affected by vegetation and environmental conditions. The purpose of this study was to investigate the effect of vegetation type on soil respiration, temperature and water content, and their correlations on a small scale. We measured soil respiration rate (Rs) over a 3-year period at biweekly intervals in three plots in the eastern Loess Plateau of China, with the same soil texture but different vegetation types: pine forest, grassland, and shrub land. Simultaneously, soil temperature (Ts) at 10 cm depth and soil water content (Ws) within 10 cm depth were measured. The seasonal course of Rs and Ts showed a similar temporal variation in the three plots, with higher values in summer and autumn and lower values in winter and spring. No significant differences (P>0.05) were found between plots, except for Ws. The mean cumulative release of CO2 efflux from March to December was 962.5, 1027.5, and 1166.5 g C m− 2 a− 1 for plots 1, 2, and 3, respectively, with no significant difference between plots. The fitted exponential equations of Rs versus Ts from the 3-year data-set were significant (P < 0.05) with an R2 of 0.72, 0.64, and 0.72 for plots 1, 2, and 3, respectively. The calculated Q10 from the parameters of the fitted equation was 3.57, 3.52, and 3.61, and the R10 was 2.36, 2.03, and 2.37 μmol CO2 m− 2 s− 1 for plots 1, 2, and 3, respectively. Compared with the Ts, the correlations between Rs and Ws were not significant for the three plots. However, if the Ts was above 10°C, then their correlation was significant, and Ws had an impact on Rs. Four combined regression equations including two variables of Ts and Ws could be well established to model correlations between Rs and both Ts and Ws. Our study demonstrated that the exponential and power model fitted best and no significant different correlations of combined equations existed between the three plots. These results show that vegetation type had little impact on Rs, Ts, Ws, and their correlations, as well as on related parameters such as Q10 and R10. Therefore, while doing Rs research in a horizontal patchy vegetation conditions on a small area, the sampling location of measurements should focus on vertical dominant vegetation and ignore patch vegetation so as to reduce field work load.

Can Canopy Radiometric Temperature Be Used as an Alternate of Air Temperature to Predict Ecosystem Carbon Fluxes

Net ecosystem carbon dioxide (CO₂) exchange (NEE) and ecosystem respiration (R_eco) were determined in an alfalfa (Medicago sativa L) crop in Taiyuan basin, Shanxi province of China, using the closed chamber technique. Gross primary production (GPP) was calculated as the sum of NEE and R_eco. The results showed that the coefficients of determination (r²) of the GPP and NEE with canopy radiometric temperature (T_c) were significantly higher than those with air temperature (T_a) on diurnal scales. The R_eco was closely correlated to both Ta and Tc on all measurement dates on a diurnal scale. The coefficients of determination (r²) values between R_eco and T_s were lower than those between R_eco and both T_a and T_c on diurnal scale. Those results suggest that at the plot scale T_c is a better predict factor for ecosystem carbon fluxes estimate than both T_a and T_s are. Those results give us some implications for linking remotely sensed infrared temperature of canopy to ecosystem carbon flux estimate.

Application of the land surface temperature from MODIS in the estimation of gross primary productivity for a subtropical pinus plantation in southern China

In this study, the land surface temperature (LST) from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor which was chosen as one scalar temperature directly modifying light use efficiency (LUE), together with the 8-day composited MODIS data and the site measurements of photosynthetically active radiation (PAR) of a subtropical evergreen coniferous forest ecosystem in southern China during 2005–2006 are used to estimate the seasonal variations of gross primary production (GPP) with the Production Efficiency Model (PEM). To investigate the possibility of LST instead of atmospheric temperature (T<inf>a</inf>) in the PEM model to estimate the GPP values, the LST predicted GPP (GPP<inf>LST</inf>) and T<inf>a</inf> predicted GPP (GPP<inf>air</inf>) are used to compare the GPP values observed from eddy covariance measurements (GPP<inf>obs</inf>). It was found that the coefficient of determination of the fitted exponential equations between the GPP<inf>obs</inf> and the T<inf>a</inf>(r² = 0.89) was slightly higher than that between the GPP<inf>obs</inf> and the LST(r² = 0.80), and both variables could explain above 80 % variations of the GPP<inf>obs</inf> in this area. Both the GPP<inf>LST</inf> and GPP<inf>air</inf> agreed well with the observed GPP<inf>obs</inf>.There was a very strong linear relation between GPP<inf>LST</inf> and GPP<inf>air</inf> (r² = 0.99), and they both were highly correlated with the GPP<inf>obs</inf> (r² = 0.91 and 0.91, respectively). The annual total GPP<inf>LST</inf> and GPP<inf>air</inf> values (1630.6 and 1598.6 g C m⁻² for 2005; 1740.2 and 1660.8 g C m⁻² for 2006, respectively) were slightly lower than the GPP<inf>obs</inf> (1646.8 and 1867.4 g C m⁻², respectively), and the error of the predicted GPP from LST (0.98% and 6.8% for 2005 and 2006, respectively) was smaller than the predicted GPP from T<inf>a</inf> (2.9% and 11.1% for 2005 and 2006, respectively) for the whole year data. These results demonstrate that the LST can be potentially used to estimate GPP instead of T<inf>a</inf>.