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The present study compared the abilities of the spectral vegetation indices (VI) of Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors in accurately detecting seasonal vegetation changes (phenology) with regard to forage quantity and quality. The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were computed with a 10-day maximum value composite from April 1 to October 31, 2002. The study sites included four meadow steppes and six typical steppes in the Xilingol steppe area of central Inner Mongolia, China. Comparisons of the MODIS-NDVI and AVHRR-NDVI profiles revealed that the MODIS-NDVI temporal profile had a higher fidelity. The dynamic range of the MODIS-NDVI was then analyzed and its sensitivity in discriminating between vegetation differences was evaluated in sparsely and densely vegetated areas. Estimations of the live, dead standing, total biomass and crude protein (CP) concentration and standing CP were obtained using AVHRR-NDVI (1.1 km pixels), MODIS-NDVI and -EVI (500 m pixels). Regression analysis revealed that the MODIS-VI showed a good coefficient of determination ( R 2 = 0.77-0.83) with regard to estimations of the total and live biomass. Furthermore, the MODIS-EVI was a good predictor of standing CP ( R 2 = 0.74) compared with AVHRR ( R 2 = 0.53). These results suggest that the MODIS-VI can reliably detect the phenology and forage quantity and quality of grassland steppe areas.

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A study was conducted to determine the potential suitability of Terra/MODIS imagery for monitoring short-term phenological changes in forage conditions in a semi-arid region. The study sites included four meadow steppes and six typical steppes in the Xilingol steppe in central Inner Mongolia, China. The live biomass, dead standing biomass, total biomass, crude protein (CP) concentration and standing CP were estimated from early April to late October using the Enhanced Vegetation Index (EVI) values from Terra imagery (500 m pixels). Applying regression models, the EVI accounted for 80% of the variation in live biomass, 42% of the dead biomass, 77% of the total biomass, 11% of the CP concentration and 74% of the standing CP. MODIS/EVI is superior to AVHRR/NDVI when estimating forage quantity. Applying these results, the seasonal changes in live biomass and the standing CP could be described in the selected four sites with different degrees of grazing intensity. Generally, the increase in grazing intensity tended to decrease live biomass and standing CP. It was suggested that the EVI obtained from Terra imagery was an available predictor of the forage condition as measured by live biomass and standing CP. The MODIS/EVI values could provide information on the suitable timing of cutting for hay-making and nutritive value to range managers.

A new regression analysis was proposed to evaluate the degree of spatial heterogeneity for individual species comprising a plant grassland community. The weighted average of the heterogeneity value of all the species comprising the community provides a measure of community‐level heterogeneity. A field survey was carried out, as an example, in order to analyze the spatial heterogeneity of a pasture with grazing cows, using 100 quadrats 50 cm × 50 cm, each of which was divided into four smaller quadrats 25 cm × 25 cm, on a 50 m long line‐transect. The frequency of occurrence for all the species in each small quadrat was recorded. The regression associated with the ratio of the theoretical and observed variances of occurence counts was used to analyse the frequency distribution of species in a pasture community. A good fit to the regression for the whole community was obtained. These results indicate that (i) each species in the example was distributed more heterogeneously than a random pattern; and (ii) the regression could well describe the spatial heterogeneity of the grassland plant community. In most of the observed species, spatial heterogeneity is often characterized by species‐specific propagation traits and the architecture of plant bodies. Thus, the spatial patterns of a grassland community can be evaluated in detail by this power‐law approach. This measure is suitable for field surveys and comparative studies of grassland communities, and for other plant communities that are generally short in height.