Warming suppresses grassland recovery in biomass but not in community composition after grazing exclusion in a Mongolian grassland.

We conducted a 4-year temperature manipulation experiment in a Mongolian grassland to examine the effect of daytime and nighttime warming on grassland recovery after grazing exclusion. After constructing a livestock exclusion fence in the grassland, we established daytime and daytime-and-nighttime warming treatments within the fenced area by a combination of open-top chambers (OTC) and electric heaters. We measured the numbers of plants and aboveground biomass by species after recording percentage vegetation cover every summer for three warming treatments inside the fence-non-warming, daytime warming, and daytime-and-nighttime warming-and for the grassland outside of the fence.

Aridity-dependent shifts in biodiversity-stability relationships but not in underlying mechanisms.

Climate change will affect the way biodiversity influences the stability of plant communities. Although biodiversity, associated species asynchrony, and species stability could enhance community stability, the understanding of potential nonlinear shifts in the biodiversity-stability relationship across a wide range of aridity (measured as the aridity index, the precipitation/potential evapotranspiration ratio) gradients and the underlying mechanisms remain limited. Using an 8-year dataset from 687 sites in Mongolia, which included 5496 records of vegetation and productivity, we found that the temporal stability of plant communities decreased more rapidly in more arid areas than in less arid areas.

Dryland sensitivity to climate change and variability using nonlinear dynamics.

Primary productivity response to climatic drivers varies temporally, indicating state-dependent interactions between climate and productivity. Previous studies primarily employed equation-based approaches to clarify this relationship, ignoring the state-dependent nature of ecological dynamics. Here, using 40 y of climate and productivity data from 48 grassland sites across Mongolia, we applied an equation-free, nonlinear time-series analysis to reveal sensitivity patterns of productivity to climate change and variability and clarify underlying mechanisms.