Assessing earth system model predictions of C4 grass cover in North America: From the glacial era to the end of this century. Issue 2 (25th November 2018)

• Record Type: Journal Article
• Authors: Still, Christopher J.; Cotton, Jennifer M.; Griffith, Daniel M.
• Editors: Gillespie, Thomas
• Is Part Of: Global ecology & biogeography. Volume 28:Issue 2(2019)
• Page Start: 145
• Page End: 157
• Publication Date: 2018-11-25
• Subjects: C4 grasses -- CMIP5 -- DGVM -- earth system model -- grassland -- plant functional type; Ecology -- Periodicals; Biogeography -- Periodicals; Biodiversity -- Periodicals; Macroevolution -- Periodicals; 577
• DOI: 10.1111/geb.12830
• Languages: English
• ISSNs: 1466-822X

Abstract

Abstract: Aim: C4 grasses are distinct from C3 grasses, because C4 grasses respond in a different manner to light, temperature, CO2 and nitrogen and often have higher resource‐use efficiencies. C3 and C4 grasses are typically represented in earth system models (ESMs) by different plant functional types (PFTs). The ability of ESMs to capture C4 grass biogeography and ecology across differing time periods is important to assess, given the crucial role they play in ecosystems and their divergent responses to global change. Location: North America. Time periods: Last Glacial Maximum (LGM), historical modern period ( ca . 1850) and end of this century. Major taxa studied: C4 grasses. Methods: Proxy data representing relative cover and productivity of C4 grasses were collated, including carbon isotope ratios of soil carbon and animal grazer tissue, and vegetation plot data in undisturbed grasslands. We selected available model predictions of C4 PFT percentage cover. Models were compared against one another and assessed against proxy data at key time points: the LGM, the historical modern period before widespread grassland conversion to agriculture, and the end of this century. Results: We highlight large differences among model predictions of percentage C4 grass cover across North America: all pairwise combinations have correlations < .5, and most are < .2. Models also do not capture spatial patterns of the percentage C4 grass cover from proxy data, during either the LGM or the historical modern period. Models generally under‐predict percentage C4 grass cover, particularly during the historical modern period. Main conclusions: Earth system models do not accurately represent the biogeography of C4 grasses across a range of time‐scales, and their outputs do not agree with one another. We suggest model improvements to represent this crucial functional type better, including more collection and greater integration of C3 and C4 grass trait data, explicit representations of tree–grass competition for water, and a greater focus on disturbance ecology.