A new spectral index to detect Poaceae grass abundance in Mongolian grasslands

The objectives of the present study were to develop a new index based on remotely-sensed data for detecting the abundance of grasses in the family Poaceae, which has a high palatability for livestock in Mongolia, and to map the distribution of these grasses in the semi-arid Mongolian steppes. We measured ground-based spectral reflectance of pure plant leaves – including Poaceae grasses – and soils, as well as in-situ in the Mongolian grasslands. The hyper-spectral data, taken by a spectroradiometer, were converted into four multi-spectral bands (i.e., blue, green, red, and NIR) to simulate satellite-based imagery data. In order to magnify the characteristics of the spectral signal of Poaceae, NGBDI (Normalized Green-Blue Difference Index), NGRDI (Normalized Green-Red Difference Index), NDVI (Normalized Difference Vegetation Index), NNBDI (Normalized NIR-Blue Difference Index) were calculated from the four multi-spectral reflectance values. Poaceae Abundance Index (PAI) was derived by combining these four normalized difference indices. PAI was found out to be a good indicator to discriminate Poaceae grass from the other plant spectral data.     

Spatiotemporal variations in litter mass and their relationships with climate in temperate grassland: A case study from Xilingol grassland,Inner Mongolia (China)

Clarifying spatiotemporal variations of litter mass and their relationships with climate factors will advance our understanding of ecosystem structure and functioning in grasslands. Our objective is to investigate the spatiotemporal variations of litter mass in the growing season and their relationships with precipitation and temperature in the Xilingol grassland using MOD09A1 data. With widely used STI (simple tillage index), we firstly estimated the litter mass of Xilingol grassland in the growing season from 2000 to 2014. Then we investigated the variations of litter mass in the growing season at regional and site scales. We further explored the spatiotemporal relationships between litter mass and precipitation and temperature at both scales. The litter mass increased with increasing mean annual precipitation and decreasing mean annual temperature at regional scale. The variations of litter mass at given sites followed quadratic function curves in the growing season, and litter mass generally attained maximums between August 1 and September 1. Positive spatial relationship was observed between litter mass variations and precipitation, and negative spatial relationship was found between litter mass variations and temperature in the growing season. There was no significant relationship between inter-annual variations of litter mass and precipitation and temperature at given sites. Results illustrate that precipitation and temperature are important drivers in shaping ecosystem functioning as reflected in litter mass at regional scale in the Xilingol grassland. Our findings also suggest the action of distinct mechanism in controlling litter mass variations at regional and sites scales.