An improved phenology model for monitoring green-up date variation in Leymus chinensis steppe in Inner Mongolia during 1962–2017

Abstract

Phenology is an important indicator of the biological responses to climate change, and previous studies have reported divergent phenological responses of grasslands in Inner Mongolia from the analyses of in-situ measurements and satellite observations; thus, robust phenology models are required to understand and simulate the relationship between ecosystems and climate change. However, phenology models for natural grasslands in which heating accumulation, chilling requirements, precipitation effects and other climate factors are introduced at the same time are relatively deficient; as a result, the accuracy of the herbaceous plant phenology model and its universality across different species and regions are restricted. We proposed an improved phenology model (unified model combined with precipitation driving, UMPD) that reflects the combined effect of temperature and precipitation at the forcing unit level. Green-up evaluation based on satellite observations shows that the UMPD phenology model achieves better accuracy than previous models (RMSE < 10 days), and the simulated spatial distribution of green-up date change is more consistent with the ground observation, which means that the inclusion of the precipitation driving effect in the temperature-based phenology model improves model applicability at a regional scale and under complex climatic conditions. Based on the UMPD model and its parameters, spatial and temporal changes in green-up dates for Leymus chinensis steppe in Inner Mongolia from 1962 to 2017 were simulated, and the results showed an overall advancing trend with obvious spatial differences and complex stage characteristics. We demonstrate the feasibility of combining temperature and precipitation driving effects to develop and refine phenology models, and the improved model provides wide potential for characterizing the spatiotemporal patterns of grassland green-up date variations.