Precipitation-mediated responses of plant biomass production and allocation to changing soil pH in semiarid grasslands

Biomass and its allocation are crucial to understand carbon cycling. Climate change and human disturbance potentially alter soil pH, but it remains unclear how biomass production and its partitioning respond to altered soil pH. Here, we investigated how changing soil pH (acidification and alkalization) affected above- and belowground biomass production and allocation (hereafter AB, BB and BB/AB, respectively) at nine sites representing desert, typical, and meadow grasslands with increasing precipitation across a 1500-km transect in Inner Mongolia, China. The results showed that soil acidification reduced AB in typical and meadow grasslands, whereas soil alkalization reduced AB in desert and typical grasslands. Changing soil pH did not affect BB in desert or typical grasslands, but reduced BB in meadow grasslands. Altered soil pH negatively impacted species richness, Shannon-Wiener diversity, and dominant species biomass across all grasslands. BB/AB was increased by soil acidification and alkalization along the study transect. Soil C, N and C:N ratio were not affected by changing soil pH in three types of grasslands. Response ratios of AB, BB/AB and dominant species biomass were positively correlated with precipitation under altered soil pH, whereas response ratios of BB were negatively correlated with precipitation under soil alkalization. Variance partitioning analysis showed that the response of biomass and its allocation to altered soil pH were mainly explained by community composition but not soil fertility. Structural equation model analysis demonstrated that precipitation mediated the responses of biomass distribution to soil pH changes in semi-arid grasslands mainly via altering the response of dominant species. Our results indicate that dry grasslands with low productivity and precipitation generally allocate more C to belowground than wet grasslands regardless of pH change. These findings can improve our predictions of carbon dynamics in grassland ecosystems under climate change.