Preprints
https://doi.org/10.5194/bg-2021-54
https://doi.org/10.5194/bg-2021-54

  23 Mar 2021

23 Mar 2021

Review status: this preprint is currently under review for the journal BG.

Capturing functional strategies and compositional dynamics in vegetation demographic models

Polly Buotte1, Charles Koven2, Chonggang Xu3, Jacquelyn Shuman4, Michael Goulden5, Samuel Levis6, Jessica Katz1, Junyan Ding2, Wu Ma3, Zachary Robbins7, and Lara Kueppers1 Polly Buotte et al.
  • 1Energy and Resources Group, University of California Berkeley, Berkeley, CA, United States
  • 2Climate and Ecosystem Sciences Division, Lawrence-Berkeley National Laboratory, Berkeley, CA, United States
  • 3Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM, United States
  • 4Climate and Global Dynamics, Terrestrial Sciences Section, National Center for Atmospheric Research, Boulder, CO, United States
  • 5Department of Earth System Science, University of California Irvine, Irvine, CA, United States
  • 6SLevis Consulting, LLC, Oceanside, CA, United States
  • 7Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, United States

Abstract. Plant community composition influences carbon, water and energy fluxes at regional to global scales. Composition is a dynamic property of ecosystems, arising from complex feedbacks among the environment, disturbance, and plant physiology. Vegetation demographic models (VDMs) allow investigation of the effects of changing climate and disturbance regimes on vegetation composition and fluxes. Such investigation requires that the models can accurately resolve these feedbacks to simulate realistic composition. Vegetation in VDMs is composed of plant functional types (PFTs), which are specified according to plant traits. Defining PFTs is challenging due to large variability in trait observations within and between plant types and a lack of understanding of model sensitivity to these traits. Here we present an approach for developing PFT parameterizations that are connected to the underlying ecological processes determining forest composition in the mixed-conifer forest of the Sierra Nevada Mountains of California, USA. We constrain multiple relative trait values between PFTs, as opposed to randomly sampling within the range of observations. An ensemble of PFT parameterizations are then filtered based on emergent forest properties meeting observation-based ecological criteria under alternate disturbance scenarios. A small ensemble of alternate PFT parameterizations is identified that produces plausible forest composition, and demonstrates variability in response to disturbance frequency and regional environmental variation. Retaining multiple PFT parameterizations allows us to quantify the uncertainty in forest responses due to variability in trait observations. Vegetation composition is a key emergent outcome from VDMs and our methodology provides a foundation for robust PFT parameterization across ecosystems.

Polly Buotte et al.

Status: open (until 08 May 2021)

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Polly Buotte et al.

Data sets

Data in support of capturing functional strategies and compositional dynamics in vegetation demographic models Polly C. Buotte https://datadryad.org/stash/share/ipqeTSD9BmH6_SO-tONnnRkaOWCnI6fssv5TS0FieiI

Polly Buotte et al.

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Short summary
We present an approach for ensuring the definitions of plant types in dynamic vegetation models are connected to the underlying ecological processes controlling community composition. Our approach can be applied regionally or globally. Robust resolution of community composition will allow us to use these models to address important questions related to future climate and management effects on plant community composition, structure, carbon storage, and feedbacks within the Earth system.
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