Quantitative monitoring of grazing intensity in the temperate meadow steppe based on remote sensing data

ABSTRACT

Grazing intensity (GI) is difficult to measure accurately because of the diversity of grazing livestock, their mobility in the grazing space and the uncertainty of grazing times. Thus, GI monitoring is often only qualitative, while quantitative monitoring is scarce. In this study, models correlating GI, the normalized difference vegetation index (NDVI) and aboveground biomass (AGB) were established based on a controlled GI experiment. The GI derived from NDVI was evaluated using the GI derived from AGB samples, under the principle that AGB is similar for the same GI in the same grassland type. The results showed that the appropriate time to build the model in the study area was from July to August, when there was a negative correlation between GI and NDVI. The simulated GI derived from NDVI was similar to GI derived from AGB, and the R² (coefficient of determination) values for fresh weight and dry weight were 0.3770 and 0.4292, respectively; the root mean square error (RMSE) were 0.2302 and 0.1953 animal units (AU) ha⁻¹ (1 AU = 500 kg of adult cattle); and the relative error from −20% to 20% accounted for 62.07% and 72.41% of the total samples. Most of the study area was under heavy grazing according to monitoring results from 2010 to 2016, except for a few pastures with rational utilization (0.23 AU ha⁻¹ – 0.46 AU ha⁻¹), and continuous heavy grazing often occurred for many years without rest grazing.

Acknowledgments

We are grateful to many colleagues at the Hulunber Grassland Ecosystem Observation and Research Station, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences and Agricultural University of Hebei, for their assistance with field observations and sample collection.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was funded by the following projects: National Natural Science Foundation of China (41471093); National Key Research and Development Program of China (2016YFC0500608); Public Sector Projects in the Ministry of Agriculture (201303060); Special Funding for Modern Agricultural Technology Systems from the Chinese Ministry of Agriculture (CARS-34); Research Funds for Central Non-profit Scientific Institution (No.1610132016033; No.1610132016027).