2021 ESA Annual Meeting (August 2 - 6)

Above- and below-ground connectivity: Revisiting questions of stability in a constructed old field

On Demand
Elizabeth A. O'Brien, University of Michigan;
Background/Question/Methods

Multiple global change drivers are altering the structure and function of ecosystems. Here, we use a large-scale multi-factor global change experiment to test how the direct and interactive effects of elevated atmospheric CO2, warming, and shifting precipitation alter the stability of a constructed grassland ecosystem. In 2002, we established an open top chamber experiment in a factorial design with treatments of ambient or elevated (+300 ppm) CO2 concentration, ambient or elevated (+3 °C) air temperature, and high or low precipitation inputs. We monitored a variety of ecosystem properties including cover, ANPP, BNPP, and root standing stock. Previous studies show soil moisture was a prominent ecosystem control factor both above and below-ground through direct and indirect influence: soil moisture affected seedling establishment, foliar cover, species diversity, evenness and richness, increased potential asymbiotic N2 fixation, and was more important than elevated CO2 as a control on soil carbon dynamics. We revisited below-ground root production and standing stock data paired with aboveground foliar cover data from the OCCAM experiment to test if the additive climate change treatments affected above- and below-ground stability differentially. We hypothesized higher below-ground stability than aboveground.

Results/Conclusions

While plant community composition shifts resulted in decreased aboveground biodiversity, a strong predictor for ecosystem stability, preliminary analyses on root data do not reveal changes in root biomass to soil moisture, which drove plant community composition changes. Warming appears to increase root standing crop across years, but there are few interactive effects of the treatments. It is important to continue to analyze the complex dynamics between multiple climate factors to predict future climate scenarios.