Long-term prediction of grassland production for five temporal patterns of precipitation during the growing season of plants based on a system model in Xilingol, Inner Mongolia, China

We proposed a method to conveniently predict seasonal changes in aboveground grassland biomass in Xilingol, Inner Mongola, China, by herders and their cooperative. First, we formed five precipitation patterns with different meteorological characteristics during the plant growing season (March 16–October 15) using data accumulated for 55 years since 1953 at the Xilinghot Meteorological Observatory based on cluster analysis. Second, we applied the improved Xilingol Grassland Ecosystem Model to each of the five precipitation patterns and the 55-year grand mean of the patterns. The time-dependent aboveground biomass simulation showed different shapes among the six meteorological patterns, in particular a pattern formed by 13 drought years that produced the lowest aboveground biomass during the entire plant growing season. At the beginning of grazing season, herders and/or their cooperatives can choose one of the six patterns based on the long- and medium-term meteorological prediction officially announced by the meteorological observatory to predict temporal changes in aboveground biomass during a growing season of grassland plants. As the drought pattern years will come statistically once in four years in the Xilingol area according to our study, maintaining an appropriate stocking density is important to avoid economic loss to herders and degradation of the grassland ecosystem. Thus, a decision for grassland utilization based on our model choice will play a key role to maintain a stable income and to avoid overgrazing and to conserve grassland vegetation.