Soil carbon redistribution is an important process in the terrestrial carbon cycle. This study describes a new index, soil carbon redistribution (SCR) index, that can be used to assess long-term soil carbon redistribution at a large watershed scale. The new index is based on the theoretical preconditions that soil carbon redistribution is mainly controlled by vegetation type, precipitation, topography/slope, and soil carbon concentration. The Haihe River Basin served as an example for this analysis. The SCR index was calculated, and a GIS-based map shows its spatial patterns. The results suggested that soil carbon was usually prone to being carried away from mountainous regions with natural vegetation, while it was prone to deposition in the plain and plateau regions with cultivated vegetation. The methods in the paper offer a tool that can be used to quantify the potential risk where soil carbon is prone to being carried away and deposited in a large watershed.
Warming, watering and elevated atmospheric CO?-concentration effects have been extensively studied separately; however, their combined impact on plants is not well understood. In the current research, we examined plant growth and physiological responses of three dominant species from the Eurasian Steppe with different functional traits to a combination of elevated CO?, high temperature, and four simulated precipitation patterns. Elevated CO? stimulated plant growth by 10.8-41.7 % for a C? leguminous shrub, Caragana microphylla, and by 33.2-52.3 % for a C? grass, Stipa grandis, across all temperature and watering treatments. Elevated CO?, however, did not affect plant biomass of a C? grass, Cleistogenes squarrosa, under normal or increased precipitation, whereas a 20.0-69.7 % stimulation of growth occurred with elevated CO? under drought conditions. Plant growth was enhanced in the C? shrub and the C? grass by warming under normal precipitation, but declined drastically with severe drought. The effects of elevated CO? on leaf traits, biomass allocation and photosynthetic potential were remarkably species-dependent. Suppression of photosynthetic activity, and enhancement of cell peroxidation by a combination of warming and severe drought, were partly alleviated by elevated CO?. The relationships between plant functional traits and physiological activities and their responses to climate change were discussed. The present results suggested that the response to CO? enrichment may strongly depend on the response of specific species under varying patterns of precipitation, with or without warming, highlighting that individual species and multifactor dependencies must be considered in a projection of terrestrial ecosystem response to climatic change.
Gross Primary Production (GPP) is the largest flux in the global carbon cycle. However, large uncertainties in current global estimations persist. In this study, we examined the performance of a process-based model (Integrated BIosphere Simulator, IBIS) at 62 eddy covariance sites around the world. Our results indicated that the IBIS model explained 60% of the observed variation in daily GPP at all validation sites. Comparison with a satellite-based vegetation model (Eddy Covariance-Light Use Efficiency, EC-LUE) revealed that the IBIS simulations yielded comparable GPP results as the EC-LUE model. Global mean GPP estimated by the IBIS model was 107.50±1.37 Pg C year-1 (mean value ± standard deviation) across the vegetated area for the period 2000-2006, consistent with the results of the EC-LUE model (109.39±1.48 Pg C year-1). To evaluate the uncertainty introduced by the parameter Vcmax, which represents the maximum photosynthetic capacity, we inversed Vcmax using Markov Chain-Monte Carlo (MCMC) procedures. Using the inversed Vcmax values, the simulated global GPP increased by 16.5 Pg C year-1, indicating that IBIS model is sensitive to Vcmax, and large uncertainty exists in model parameterization.
The regression tree method is used to upscale evapotranspiration (ET) measurements at eddy-covariance (EC) towers to the grassland ecosystems over the Dryland East Asia (DEA). The regression tree model was driven by satellite and meteorology datasets, and explained 82% and 76% of the variations of ET observations in the calibration and validation datasets, respectively. The annual ET estimates ranged from 222.6 to 269.1 mm yr(-1) over the DEA region with an average of 245.8 mm yr(-1) from 1982 through 2009. Ecosystem ET showed decreased trends over 61% of the DEA region during this period, especially in most regions of Mongolia and eastern Inner Mongolia due to decreased precipitation. The increased ET occurred primarily in the western and southern DEA region. Over the entire study area, water balance (the difference between precipitation and ecosystem ET) decreased substantially during the summer and growing season. Precipitation reduction was an important cause for the severe water deficits. The drying trend occurring in the grassland ecosystems of the DEA region can exert profound impacts on a variety of terrestrial ecosystem processes and functions.
Although some studies have indicated that climate changes can affect Pinus koraiensis mixed forest, the responses of composition and structure of Pinus koraiensis mixed forests to climatic changes are unknown and the key climatic factors controlling the composition and structure of Pinus koraiensis mixed forest are uncertain.
Arid grassland ecosystems have significant interannual variation in carbon exchange; however, it is unclear how environmental factors influence carbon exchange in different hydrological years. In this study, the eddy covariance technique was used to investigate the seasonal and interannual variability of CO? flux over a temperate desert steppe in Inner Mongolia, China from 2008 to 2010. The amounts and times of precipitation varied significantly throughout the study period. The precipitation in 2009 (186.4 mm) was close to the long-term average (183.9±47.6 mm), while the precipitation in 2008 (136.3 mm) and 2010 (141.3 mm) was approximately a quarter below the long-term average. The temperate desert steppe showed carbon neutrality for atmospheric CO? throughout the study period, with a net ecosystem carbon dioxide exchange (NEE) of -7.2, -22.9, and 26.0 g C m?² yr?¹ in 2008, 2009, and 2010, not significantly different from zero. The ecosystem gained more carbon in 2009 compared to other two relatively dry years, while there was significant difference in carbon uptake between 2008 and 2010, although both years recorded similar annual precipitation. The results suggest that summer precipitation is a key factor determining annual NEE. The apparent quantum yield and saturation value of NEE (NEE(sat)) and the temperature sensitivity coefficient of ecosystem respiration (R(eco)) exhibited significant variations. The values of NEE(sat) were -2.6, -2.9, and -1.4 µmol CO? m?² s?¹ in 2008, 2009, and 2010, respectively. Drought suppressed both the gross primary production (GPP) and R(eco), and the drought sensitivity of GPP was greater than that of R(eco). The soil water content sensitivity of GPP was high during the dry year of 2008 with limited soil moisture availability. Our results suggest the carbon balance of this temperate desert steppe was not only sensitive to total annual precipitation, but also to its seasonal distribution.
Grazing is one of the main grassland disturbances in China, and it is essential to quantitatively evaluate the effects of different grazing intensities on grassland production for grassland carbon budget and sustainable use.
To better understand how warming, increased precipitation and their interactions influence community structure and composition, a field experiment simulating hydrothermal interactions was conducted at an annual forb dominated desert steppe in northern China over 2 years. Increased precipitation increased species richness while warming significantly decreased species richness, and their effects were additive rather than interactive. Although interannual variations in weather conditions may have a major affect on plant community composition on short term experiments, warming and precipitation treatments affected individual species and functional group composition. Warming caused C4 grasses such as Cleistogenes squarrosa to increase while increased precipitation caused the proportions of non-perennial C3 plants like Artemisia capillaris to decrease and perennial C4 plants to increase.
Many theoretical researches predicted that the larch species would decrease drastically in China under future climatic changes. However, responses of the structural and compositional changes of Gmelin larch (Larix gmelinii var. gmelinii) forests to climatic changes have rarely been reported.
Changing water condition represents a dramatic impact on global terrestrial ecosystem productivity, mainly by limiting plant functions, including growth and photosynthesis, particularly in arid and semiarid areas. However, responses of the potential photosynthetic capacity to soil water status in a wide range of soil moisture levels, and determination of their thresholds are poorly understood. This study examined the response patterns of plant photosynthetic capacity and their thresholds to a soil moisture gradient in a perennial rhizome grass, Leymus chinensis, and a perennial bunchgrass, Stipa grandis, both dominant in the Eurasian Steppe.
Plants would be more vulnerable to water stress and thereafter rewatering or a cycled water environmental change, which occur more frequently under climatic change conditions in terms of the prediction scenarios. Effects of water stress on plants alone have been well-documented in many reports. However, the combined responses to drought and rewatering and its mechanism are relatively scant. As we known, plant growth, photosynthesis and stomatal aperture may be limited under water deficit, which would be regulated by physical and chemical signals. Under severe drought, while peroxidation may be provoked, the relevant antioxidant metabolism would be involved to annihilate the damage of reactive oxygen species. As rewatering, the recoveries of plant growth and photosynthesis would appear immediately through growing new plant parts, re-opening the stomata, and decreasing peroxidation; the recovery extents (reversely: pre-drought limitation) due to rewatering strongly depend on pre-drought intensity, duration and species. Understanding how plants response to episodic drought and watering pulse and the underlying mechanism is remarkably helpful to implement vegetation management practices in climatic changing.
Although the relationship between grassland productivity and soil water status has been extensively researched, the responses of plant growth and photosynthetic physiological processes to long-term drought and rewatering are not fully understood. Here, the perennial grass (Leymus chinensis), predominantly distributed in the Euro-Asia steppe, was used as an experimental plant for an irrigation manipulation experiment involving five soil moisture levels [75-80, 60-75, 50-60, 35-50, and 25-35% of soil relative water content (SRWC), i.e. the ratio between present soil moisture and field capacity] to examine the effects of soil drought and rewatering on plant biomass, relative growth rate (RGR), and photosynthetic potential. The recovery of plant biomass following rewatering was lower for the plants that had experienced previous drought compared with the controls; the extent of recovery was proportional to the intensity of soil drought. However, the plant RGR, leaf photosynthesis, and light use potential were markedly stimulated by the previous drought, depending on drought intensity, whereas stomatal conductance (g(s)) achieved only partial recovery. The results indicated that g(s) may be responsible for regulating actual photosynthetic efficiency. It is assumed that the new plant growth and photosynthetic potential enhanced by pre-drought following rewatering may try to overcompensate the great loss of the plants net primary production due to the pre-drought effect. The present results highlight the episodic effects of drought on grass growth and photosynthesis. This study will assist in understanding how degraded ecosystems can potentially cope with climate change.
Vegetation light use efficiency (LUE) is a key parameter of Production Efficiency Models (PEMs) for simulating gross primary production (GPP) of vegetation, from regional to global scales. Previous studies suggest that grasslands have the largest inter-site variation of LUE and controlling factors of grassland LUE differ from those of other biomes, since grasslands are usually water-limited ecosystems. Combining eddy covariance flux data with the fraction of photosynthetically active radiation absorbed by the plant canopy from MODIS, we report LUE on a typical steppe and a desert steppe in Inner Mongolia, northern China. Results show that both annual average LUE and maximum LUE were higher on the desert steppe (0.51 and 1.13 g C MJ(-1)) than on the typical steppe (0.34 and 0.88 g C MJ(-1)), despite the higher GPP of the latter. Water availability was the primary limiting factor of LUE at both sites. Evaporative fraction (EF) or the ratio of actual evapotranspiration to potential evapotranspiration (AET/PET) can explain 50-70% of seasonal LUE variations at both sites. However, the slope of linear regression between LUE and EF (or AET/PET) differed significantly between the two sites. LUE increased with the diffuse radiation ratio on the typical steppe; however, such a trend was not found for the desert steppe. Our results suggest that a biome-dependent LUE(max) is inappropriate, because of the large inter-site difference of LUE(max) within the biome. EF could be a promising down-regulator on grassland LUE for PEMs, but there may be a site-specific relationship between LUE and EF.
Related JoVE Video
Journal of Visualized Experiments
What is Visualize?
JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.
How does it work?
We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.
Video X seems to be unrelated to Abstract Y...
In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.