Using Remote Sensing Data and Species–Environmental Matching Model to Predict the Potential Distribution of Grassland Rodents in the Northern China

An increase in grassland rodent pests China has seriously affected ecological environments and the development of husbandry. Here, we used remote sensing data a species–environmental matching model to predict potential spatial distribution five major pest species (Microtus, Citellus, Myospalax, Meriones, Ochotona) northern China, examined how predicted suitability area depends on environmental variables. The results were consistent significant, better than random, close optimal. Meriones Microtus had largest areas High Suitability Moderate with regard conditions. combination analysis showed that for 66% total area, conditions suitable just one species, while two three kinds rodents accounted 31% 3%, respectively. Altitude, land surface temperature winter (November, December, February) summer (May, June, July), vegetation cover (July, August), precipitation from spring (April, May, June) determined rodents. Our findings provide powerful useful methodological tool tracking future management measures ensure environment security.