Yinyin Wang

Bio: Yinyin Wang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Steppe & Vegetation. The author has an hindex of 3, co-authored 3 publications receiving 42 citations.

Prediction of aboveground grassland biomass on the Loess Plateau, China, using a random forest algorithm

Abstract: Grasslands are an important component of terrestrial ecosystems that play a crucial role in the carbon cycle and climate change. In this study, we collected aboveground biomass (AGB) data from 223 grassland quadrats distributed across the Loess Plateau from 2011 to 2013 and predicted the spatial distribution of the grassland AGB at a 100-m resolution from both meteorological station and remote sensing data (TM and MODIS) using a Random Forest (RF) algorithm. The results showed that the predicted grassland AGB on the Loess Plateau decreased from east to west. Vegetation indexes were positively correlated with grassland AGB, and the normalized difference vegetation index (NDVI) acquired from TM data was the most important predictive factor. Tussock and shrub tussock had the highest AGB, and desert steppe had the lowest. Rainfall higher than 400 m might have benefitted the grassland AGB. Compared with those obtained for the bagging, mboost and the support vector machine (SVM) models, higher values for the mean Pearson coefficient (R) and the symmetric index of agreement (λ) were obtained for the RF model, indicating that this RF model could reasonably estimate the grassland AGB (65.01%) on the Loess Plateau.

Large scale soil organic carbon mapping based on multivariate modelling: the case of grasslands on the Loess Plateau

Abstract: The Loess Plateau is considered one of the world's typical regions with severe soil erosion. Grasslands are widely distributed on the Loess Plateau, accounting for approximately 40% of the total area. Soil organic carbon (SOC) plays an important role in the terrestrial carbon (C) cycle in this region. We compiled more than 1000 measurements of plant biomass and SOC content derived from 223 field studies of grasslands on the Loess Plateau. Combined with meteorological factors (precipitation and air temperature) and the photosynthetically active radiation factor (FPAR), the topsoil SOC contents of grasslands were predicted using the random forest (RF) regression algorithm. Predicted grassland SOC content (1.70 ~ 40.34 g kg-1) decreased from the southeast to the northwest of the Loess Plateau, with approximately 1/5 of the grassland exhibiting values lower than 4 g kg-1. Observed SOC content was positively correlated with observed plant biomass, and for predicted values, this correlation was strong in the desert steppe and the steppe desert of rocky mountains. Air temperature was the most important factor affecting SOC contents in the RF model. Moreover, the residual error of observations and predictions increased as the grazing intensity varied from none to very severe in the temperate desert steppe, and this RF model may not performed well in plains. The use of the RF model for SOC prediction in Loess Plateau grasslands provides a reference for C storage studies in arid and semi-arid regions, and AGB and temperature should receive more attention due to increasing C sequestration.

Estimates of carbon storage in grassland ecosystems on the Loess Plateau

Abstract: Grassland ecosystems play an important role in the carbon (C) balance of arid and semi–arid regions. These ecosystems provide C for grass growth and soil microbial activities and represent one of the main sources of atmospheric C. In this study, we estimated the C density and storage of 223 sampling sites in grassland ecosystems on the Loess Plateau using elevation, vegetation indexes, precipitation, air temperature, day and night land surface temperature (LSTd and LSTn, respectively), evapotranspiration (ET), percent tree cover and the non–vegetated area to build decision regression tree and generalized linear regression models (GLMs). The results showed that the C density decreased from south to north and ranged from 0.22 to 29.29 kg C/m2. The average amount of C stored in the ecosystems was 1.46 Pg. The typical steppe and forest steppe stored the most C, and the steppe desert stored the least. The soil (0–1 m) stored most of the organic C, accounting for > 90%, and the belowground biomass (BGB) contained > 3 times the amount of C as the aboveground biomass (AGB). This study provides reference information for the loss of C and associated mitigation strategies on the Loess Plateau.

Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009

Abstract: Terrestrial net primary production (NPP) quantifies the amount of atmospheric carbon fixed by plants and accumulated as biomass. Previous studies have shown that climate constraints were relaxing with increasing temperature and solar radiation, allowing an upward trend in NPP from 1982 through 1999. The past decade (2000 to 2009) has been the warmest since instrumental measurements began, which could imply continued increases in NPP; however, our estimates suggest a reduction in the global NPP of 0.55 petagrams of carbon. Large-scale droughts have reduced regional NPP, and a drying trend in the Southern Hemisphere has decreased NPP in that area, counteracting the increased NPP over the Northern Hemisphere. A continued decline in NPP would not only weaken the terrestrial carbon sink, but it would also intensify future competition between food demand and proposed biofuel production.

Agricultural Soil Erosion and Global Carbon Cycle: Controversy over?

Abstract: Recent research on the contribution of soil erosion on agricultural land to atmospheric carbon dioxide (CO2) emphasizes either the contribution of soil organic matter (SOM) mineralization during transport as source for atmospheric CO2, or the deep burial of SOM-rich sediment in agricultural landscapes as a sink. The contribution of either process is subject to a controversial debate. In this letter, we present preliminary results on our research on interrill carbon (C) erosion, SOM transport by rill erosion and the stationarity of C erosion during the Holocene. None of those issues has been incorporated comprehensively and with global coverage in the debate on the role of C erosion in the global C cycle. Therefore, we argue that only an eco-geomorphologic perspective on organic C movement through landscapes can reconcile the two positions. Copyright © 2009 John Wiley & Sons, Ltd.

Remote Sensing of Grassland Production and Management—A Review

Abstract: Grasslands cover one third of the earth’s terrestrial surface and are mainly used for livestock production. The usage type, use intensity and condition of grasslands are often unclear. Remote sensing enables the analysis of grassland production and management on large spatial scales and with high temporal resolution. Despite growing numbers of studies in the field, remote sensing applications in grassland biomes are underrepresented in literature and less streamlined compared to other vegetation types. By reviewing articles within research on satellite-based remote sensing of grassland production traits and management, we describe and evaluate methods and results and reveal spatial and temporal patterns of existing work. In addition, we highlight research gaps and suggest research opportunities. The focus is on managed grasslands and pastures and special emphasize is given to the assessment of studies on grazing intensity and mowing detection based on earth observation data. Grazing and mowing highly influence the production and ecology of grassland and are major grassland management types. In total, 253 research articles were reviewed. The majority of these studies focused on grassland production traits and only 80 articles were about grassland management and use intensity. While the remote sensing-based analysis of grassland production heavily relied on empirical relationships between ground-truth and satellite data or radiation transfer models, the used methods to detect and investigate grassland management differed. In addition, this review identified that studies on grassland production traits with satellite data often lacked including spatial management information into the analyses. Studies focusing on grassland management and use intensity mostly investigated rather small study areas with homogeneous intensity levels among the grassland parcels. Combining grassland production estimations with management information, while accounting for the variability among grasslands, is recommended to facilitate the development of large-scale continuous monitoring and remote sensing grassland products, which have been rare thus far.