Project description:We measured transcriptional profiles of individuals of Andropogon gerardii, a C4 grass native to North American grasslands, in a field experiment in which both temperature and precipitation have been manipulated to simulate key aspects of forecasted climate change.
Project description:We measured transcriptional profiles of individuals of Andropogon gerardii and Sorghastrum nutans, two C4 grass species native to North American grasslands, in a field experiment in which both temperature and precipitation have been manipulated to simulate key aspects of forecasted climate change.
Project description:Precipitation change is often associated with climate warming, but its effects on soil microbial community assembly remain relatively underexplored. Traditionally, it is thought that increasing the magnitude of environmental changes will increase the importance of deterministic processes in community assembly. Here, while ±30% precipitation promoted deterministic processes in the assembly of soil prokaryotic community during a five-year semiarid grassland experiment, ±60% precipitation increased the importance of stochastic processes like random birth/death, countering to conventional thinking. Similarly, analysis of a multifactorial experiment showed that +54% precipitation stimulated a random bacterial birth process while other environmental change factors did not. In addition, the increased taxonomic stochasticity under ±60% precipitation translated into functional stochasticity at the gene, protein, and enzyme levels. Our results revealed the distinctive mechanism and critical role of precipitation in determining microbial assemblages, demonstrating the need to integrate microbial taxonomic information to better predict their functional responses to precipitation changes.
Project description:We measured transcriptional profiles of individuals of Andropogon gerardii and Sorghastrum nutans, two C4 grass species native to North American grasslands, in a field experiment in which both temperature and precipitation have been manipulated to simulate key aspects of forecasted climate change. 99 samples were analyzed.
