Preprints
https://doi.org/10.5194/bg-2022-65
https://doi.org/10.5194/bg-2022-65
28 Mar 2022
 | 28 Mar 2022
Status: a revised version of this preprint was accepted for the journal BG and is expected to appear here in due course.

Exploring the impacts of unprecedented climate extremes on forest ecosystems: hypotheses to guide modeling and experimental studies

Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig

Abstract. Climatic extreme events are expected to occur more frequently in the future, increasing the likelihood of unprecedented climate extremes (UCEs), or record-breaking events. UCEs, such as extreme heatwaves and droughts, substantially affect ecosystem stability and carbon cycling by increasing plant mortality and delaying ecosystem recovery. Quantitative knowledge of such effects is limited due to the paucity of experiments focusing on extreme climatic events beyond the range of historical experience. Here, we use two dynamic vegetation demographic models (VDMs), ED2 and LPJ-GUESS, to investigate the hypothesis that ecosystem responses to UCEs (e.g., unprecedented droughts) differ qualitatively from ecosystem responses to milder extremes, as a result of non-linear ecosystem responses. Additionally, we explore how unprecedented droughts in combination with increasing atmospheric CO2 and/or temperature may affect ecosystem stability and carbon cycling. We explored these questions using simulations of pre-drought and post-drought conditions at well-studied forest sites in Australia and Costa Rica. Both models produced nonlinear responses to UCEs. Due to the two models having different but plausible representations of processes and interactions, they diverge in sensitivity of biomass loss due to drought duration or intensity, and differ between each site. Biomass losses are most sensitive to drought duration in ED2, but to drought intensity in LPJ-GUESS. Elevated atmospheric CO2 concentrations (eCO2) alone did not completely buffer the ecosystems from carbon losses during UCEs in the majority of our simulations. Our findings highlight contrasting differences in process formulations and uncertainties in models, notably related to availability in plant carbohydrate storage and the diversity of plant hydraulic schemes, in projecting potential ecosystem responses to UCEs. The different hypotheses of plant responses to UCEs existing in models reflect knowledge gaps, which should be tested with targeted field experiments. This iterative modeling-experimental framework would help improve predictions of terrestrial ecosystem responses and climate feedbacks.

Jennifer A. Holm et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2022-65', Anonymous Referee #1, 06 Jun 2022
    • AC1: 'Reply on RC1', Jennifer A. Holm, 31 Jul 2022
      • AC3: 'Reply on AC1', Jennifer A. Holm, 05 Jan 2023
  • RC2: 'Comment on bg-2022-65', Anonymous Referee #2, 17 Jun 2022
    • AC2: 'Reply on RC2', Jennifer A. Holm, 31 Jul 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2022-65', Anonymous Referee #1, 06 Jun 2022
    • AC1: 'Reply on RC1', Jennifer A. Holm, 31 Jul 2022
      • AC3: 'Reply on AC1', Jennifer A. Holm, 05 Jan 2023
  • RC2: 'Comment on bg-2022-65', Anonymous Referee #2, 17 Jun 2022
    • AC2: 'Reply on RC2', Jennifer A. Holm, 31 Jul 2022

Jennifer A. Holm et al.

Jennifer A. Holm et al.

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Latest update: 20 Apr 2023
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Short summary
Unprecedented climate extremes (UCEs) are expected to have dramatic impacts for ecosystems. We examine extreme droughts with rising CO2 and temperatures using two dynamic vegetation models, to assess ecological processes to measure, and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explored specific plant responses that reflect knowledge gaps.
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