PS 14-166 - Integrating invasive grasses into carbon cycle projections: Cogongrass spread in southern pine forests

Monday, August 7, 2017
Exhibit Hall, Oregon Convention Center
Tempest McCabe, Earth and Environment, Boston University, Allston, MA, S. Luke Flory, Agronomy Department, University of Florida, Gainesville, FL and Michael C. Dietze, Earth and Environment, Boston University, Boston, MA
Background/Question/Methods

Southern pine forests are the largest source of US timber and play an important role in the biogeochemical cycle, but are subjected to numerous plant invaders. Imperata cylindrica ( cogongrass) is a particularly noxious invader of southern pine forests because it is widespread and aggressive, and can reduce forest productivity and biodiversity. Cogongrass is more likely to invade with fire and disturbance, two factors likely to increase with climate change. To better manage the increasing threat of invasive grasses such as cogongrass, we need to simultaneously project invader population size and their impacts on forest productivity, biogeochemistry, and fire under future climate and management scenarios. As a first step toward integrating invasive grasses into dynamic vegetation models we used the Predictive Ecosystem Analyzer (PEcAn) to develop parameterization based on a hierarchical meta-analysis of cogongrass trait data. Next, we performed an uncertainty analysis within the Ecosystem Demography 2 (ED2) model to identify gaps in knowledge that could be reduced through targeted field measurements. Finally, we produced initial stand ensemble projections under RCP4.5 of forest and cogongrass dynamics.

Results/Conclusions

The initial attempt at cogongrass parameterization of PEcAn demonstrated that not all of the required ecophysiological and demographic traits of this species have yet been measured. Existing data is most available for leaf-level economic and photosynthetic traits, but more limited for belowground allocation, turnover, survival, dispersal, and recruitment. Uncertainty analyses demonstrated that not all of these unmeasured traits were equally important, with cogongrass particularly sensitive to low-light survival. Initial analyses were done without fire disturbance, which we suspect under reports the importance of belowground allocation and fire mortality. Projections under moderate climate change but no fire or management suggest a general increase in cogongrass abundance in response to warmer, drier conditions, but with southern pine forests better able to take advantage of elevated CO2 than the C4 cogongrass. This suggests that even without fire-related feedbacks the southern pine forest is at risk of cogongrass invasion.