2025
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Field-based Canopy Gradients in Leaf Respiration Improve Modeled Canopy Structure
Field-based Canopy Gradients in Leaf Respiration Improve Modeled Canopy Structure
By updating model assumptions to align with field observations, scientists reduced bias in simulated forest dynamics.
The Science
Around half of all carbon that plants take up through photosynthesis is released back to the atmosphere by plant respiration. Despite its importance as a major component of the carbon cycle, most Earth system models represent plant respiration very simply. Scientists from the Next Generation Ecosystem Experiments Tropics project updated assumptions in the DOE’s earth system model about how respiration changes from sunlit leaves at the top of the canopy to shaded leaves deep in the forest understory based on measurements from a field site in Panama. Global simulations with the updated model were a better match to observations of forest structure.
The Impact
Leaf area index, a measure of the amount of leaf area in the forest canopy per unit ground area, is an important forest attribute, driving exchanges of carbon, water and energy between the land and atmosphere through impacts on photosynthesis and evapotranspiration. By updating model assumptions based on field observations, scientists were able to improve modelled leaf area index. This will further our understanding of the role of forests in the Earth system over the coming decades.
Summary
When field scientists from the NGEE-Tropics project found that vertical gradients in leaf respiration differed from model assumptions, scientists from the modelling team responded by updating the ELM-FATES model to align with observations. When respiration has a steeper canopy gradient and is lower in the understory, leaves deeper in the canopy remain in positive carbon balance, with more carbon taken up by photosynthesis than is used in leaf construction and respiration. As a result, plants grow more leaves, which increases simulated rates of photosynthesis and evapotranspiration. The updated parameterization of ELM-FATES led to an increased number of understory plants, and higher leaf area index, both of which improved alignment of simulations with ground and satellite observations.
Contact
Jessica Needham
Lawrence Berkeley National Laboratory
jfneedham@lbl.govFunding
This research was supported as part of the Next Generation Ecosystem Experiments-Tropics, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research and as part of the Energy Exascale Earth System Model (E3SM) project, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research Earth Systems Model Development Program area of Earth and Environmental System Modeling. LBNL is managed and operated by the Regents of the University of California under prime contract number DEAC02-05CH11231. R.F. also acknowledges support of the EU Horizon2020 under grant agreement 101003536 (ESM 2025).
Publications
For each publication, link to the publication’s record in DOE Pages in OSTI (https://www.osti.gov/pages/) in the title of the article. This is now required for all research funded by DOE. The researcher submitting the highlight will need to first submit the accepted manuscript of the journal article(s) to the DOE Office of Scientific and Technical Information (OSTI) via the DOE Energy Link System (E-Link). If the researcher is a financial assistance awardee, they can submit a completed DOE Announcement Notice (AN) 241.3 by going to: https://www.osti.gov/elink-2413. In the case of lab researchers, they will need to consult with their lab’s STI Manager for more information about submission. A listing of STI Managers can be found here: https://www.osti.gov/stip/stimanagers#stimanagers.
Needham, J. F., et al, “Vertical Canopy Gradients of Respiration Drive Plant Carbon Budgets and Leaf Area Index.” New Phytologist, (2025). [DOI: 10.1111/NPH.20423]
Lamour, J., et al. “The Effect of the Vertical Gradients of Photosynthetic Parameters on the CO2 Assimilation and Transpiration of a Panamanian Tropical Forest.” New Phytologist 238 (6), 2345–62 (2023). https://doi.org/10.1111/nph.18901.
2024
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Increased occurrence of large-scale windthrows across the Amazon basin
The Science
Windthrows, the uprooting or breaking of trees by winds, in the Amazon are produced by downdrafts associated with strong convective storms. They are a major natural disturbance that can influence the structure, carbon balance and species composition of forests. Our results document an approximately four-fold increase in large (≥30 ha) windthrows during the analyze period (1985 to 2020). Overall, we detected no changes in the size distribution or severity of windthrows over the past 35 years., except for an increase in very large events (>500 ha) since 1990. Thus, it is the number of events that has increased.
The Impact
Given predictions of increased storm severity with global warming, the number of windthrows are also predicted to increase. This is likely to make wind disturbance an important mode of tree mortality, especially if large trees become more vulnerable to snapping and uprooting as a consequence of other emerging disturbances.
Summary
Convective storms with strong downdrafts create windthrows—areas of snapped and uprooted trees—that locally alter forest structure, composition, and carbon balance. Using Landsat imagery from consecutive years, we documented the temporal and spatial variation of large windthrows (≥30 hectares) across the Amazon basin between 1985 and 2020. Over the 33-year period, we identified 3,179 large windthrows. Windthrow density was highest in central and western Amazon regions, with ~33% of all events occurring within ~3% of the monitored area. In these “hotspot” regions, return intervals for large windthrows at the same location span centuries to millennia, while in the rest of the Amazon, return intervals exceed 10,000 years. Our data show a nearly fourfold increase in the number of windthrows and affected area, from 78 events (6,900 ha) in 1985 to 264 events (32,170 ha) in 2020, with an increase in events larger than 500 hectares after 1990. These extremely large windthrows (ranging from >500 ha to 2,543 ha) drive interannual variation in median (84 ± 5.2 ha; ±95% CI) and mean (147 ± 13 ha) windthrow area. However, we found no significant temporal trends in the size distribution of windthrows over time.
Contact
Robinson Negron-Juarez
Lawrence Berkeley National Laboratory
robionson.inj@lbl.govFunding
J.D.U.M. has been supported by the Max Planck Institute of Biogeochemistry, the German Academic Exchange Service (DAAD). D.M.M. and S.T. are supported by the ATTO Project funded by the German Federal Ministry of Education and Research (BMBF, contracts 01LB1001A and 01LK1602A), the Brazilian Ministério da Ciência, Tecnologia e Inovação(MCTI/FINEP contract 01.11.01248.00) and the Max Planck Society. S.T. and J.D.U.M also acknowledge support from the Balzan Foundation. R.N.J. is supported by the Next Generation Ecosystem Experiments-Tropics, and the Office of Science’s Regional and Global Model Analysis of the US Department of Energy, Agreement Grant DE-AC02-05CH11231, and Reducing Uncertainties in Biogeochemical Interactions through Synthesis Computation Scientific Focus Area (RUBISCO SFA). M.V.P has been supported by Forest Data Connect of the National University of the Peruvian Amazon
Publication
Urquiza-Muñoz J, Trumbore S, Negron-Juarez R, Feng Y, Brenning A, Vasquez-Parana M, Marra D. Increased occurrence of large-scale windthrow across the Amazon basin, AGU Advances, 2024. DOI: http://dx.doi.org/10.1029/2023AV001030
2016
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Predicting biomass of complex central Amazonian forests
The hyper-diversity of tropical forests makes it difficult to predict their aboveground biomass levels based on biomass models that generalize across species. In a recent study, researchers employed a virtual forest approach using extensive field data to estimate biomass levels in the central Amazon. Due to the highly heterogenous nature of old-growth forests in structure and species composition, this study found that generic global or pantropical biomass estimation models can lead to strong biases.
PI Contacts
Robinson Negron-Juarez, robinson.inj@lbl.gov
Jeffrey Q. Chambers, jchambers@lbl.govPublication
Magnabosco Marra, D., et al. “Predicting biomass of hyperdiverse and structurally complex central Amazonian forests: A virtual approach using extensive field data.” Biogeosciences 13, 1553–70 (2016). [DOI:10.5194/bg-13-1553-2016]. (Reference link)