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Novick KA, Keenan TF, Anderegg WRL, Normile CP, Runkle BRK, Oldfield EE, Shrestha G, Baldocchi DD, Evans MEK, Randerson JT, Sanderman J, Torn MS, Trugman AT, Williams CA. We need a solid scientific basis for nature-based climate solutions in the United States. Proc Natl Acad Sci U S A 2024; 121:e2318505121. [PMID: 38536749 PMCID: PMC10998553 DOI: 10.1073/pnas.2318505121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2024] Open
Affiliation(s)
- Kimberly A. Novick
- O’Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN47405
| | - Trevor F. Keenan
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA94720
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA94720
| | - William R. L. Anderegg
- Wilkes Center for Climate Science and Policy, University of Utah, Salt Lake City, UT84112
- School of Biological Sciences, University of Utah, Salt Lake City, UT84112
| | | | - Benjamin R. K. Runkle
- Department of Biological & Agricultural Engineering, University of Arkansas, Fayetteville, AR72701
| | | | | | - Dennis D. Baldocchi
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA94720
| | | | - James T. Randerson
- Department of Earth System Science, University of California, Irvine, CA92697
| | | | - Margaret S. Torn
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA94720
- Energy and Resources Group, University of California, Berkeley, CA94720
| | - Anna T. Trugman
- Department of Geography University of California, Santa Barbara, CA93106
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2
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Wei J, von Arx G, Fan Z, Ibrom A, Mund M, Knohl A, Peters RL, Babst F. Drought alters aboveground biomass production efficiency: Insights from two European beech forests. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 919:170726. [PMID: 38331275 DOI: 10.1016/j.scitotenv.2024.170726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 02/03/2024] [Accepted: 02/03/2024] [Indexed: 02/10/2024]
Abstract
The fraction of photosynthetically assimilated carbon that trees allocate to long-lasting woody biomass pools (biomass production efficiency - BPE), is a key metric of the forest carbon balance. Its apparent simplicity belies the complex interplay between underlying processes of photosynthesis, respiration, litter and fruit production, and tree growth that respond differently to climate variability. Whereas the magnitude of BPE has been routinely quantified in ecological studies, its temporal dynamics and responses to extreme events such as drought remain less well understood. Here, we combine long-term records of aboveground carbon increment (ACI) obtained from tree rings with stand-level gross primary productivity (GPP) from eddy covariance (EC) records to empirically quantify aboveground BPE (= ACI/GPP) and its interannual variability in two European beech forests (Hainich, DE-Hai, Germany; Sorø, DK-Sor, Denmark). We found significant negative correlations between BPE and a daily-resolved drought index at both sites, indicating that woody growth is de-prioritized under water limitation. During identified extreme years, early-season drought reduced same-year BPE by 29 % (Hainich, 2011), 31 % (Sorø, 2006), and 14 % (Sorø, 2013). By contrast, the 2003 late-summer drought resulted in a 17 % reduction of post-drought year BPE at Hainich. Across the entire EC period, the daily-to-seasonal drought response of BPE resembled that of ACI, rather than that of GPP. This indicates that BPE follows sink dynamics more closely than source dynamics, which appear to be decoupled given the distinctive climate response patterns of GPP and ACI. Based on our observations, we caution against estimating the magnitude and variability of the carbon sink in European beech (and likely other temperate forests) based on carbon fluxes alone. We also encourage comparable studies at other long-term EC measurement sites from different ecosystems to further constrain the BPE response to rare climatic events.
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Affiliation(s)
- Jingshu Wei
- School of Natural Resources and the Environment, University of Arizona, 1064 E Lowell Street, Tucson, AZ 85721, USA; Swiss Federal Institute for Forest Snow and Landscape Research WSL, Zuercherstrasse 111, CH-8903 Birmensdorf, Switzerland; CAS Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun Town, Mengla County, Yunnan Province 666303, China.
| | - Georg von Arx
- Swiss Federal Institute for Forest Snow and Landscape Research WSL, Zuercherstrasse 111, CH-8903 Birmensdorf, Switzerland; Oeschger Centre for Climate Change Research, University of Bern, Hochschulstrasse 4, CH-3012 Bern, Switzerland
| | - Zexin Fan
- CAS Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun Town, Mengla County, Yunnan Province 666303, China
| | - Andreas Ibrom
- Biosystems Division, Risø National Laboratory for Sustainable Energy, Technical University of Denmark, Denmark
| | - Martina Mund
- Forestry Research and Competence Centre Gotha, Jägerstraße1, D-99867 Gotha, Germany
| | - Alexander Knohl
- Bioclimatology, University of Göttingen, Büsgenweg 2, D-37077 Göttingen, Germany
| | - Richard L Peters
- Environmental Sciences - Botany, University of Basel, Schönbeinstrasse 6, Basel CH-4056, Switzerland
| | - Flurin Babst
- School of Natural Resources and the Environment, University of Arizona, 1064 E Lowell Street, Tucson, AZ 85721, USA; Laboratory of Tree-Ring Research, University of Arizona, 1215 E Lowell Street, Tucson, AZ 85721, USA
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3
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Ellis PW, Page AM, Wood S, Fargione J, Masuda YJ, Carrasco Denney V, Moore C, Kroeger T, Griscom B, Sanderman J, Atleo T, Cortez R, Leavitt S, Cook-Patton SC. The principles of natural climate solutions. Nat Commun 2024; 15:547. [PMID: 38263156 PMCID: PMC10805724 DOI: 10.1038/s41467-023-44425-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 12/13/2023] [Indexed: 01/25/2024] Open
Abstract
Natural climate solutions can mitigate climate change in the near-term, during a climate-critical window. Yet, persistent misunderstandings about what constitutes a natural climate solution generate unnecessary confusion and controversy, thereby delaying critical mitigation action. Based on a review of scientific literature and best practices, we distill five foundational principles of natural climate solutions (nature-based, sustainable, climate-additional, measurable, and equitable) and fifteen operational principles for practical implementation. By adhering to these principles, practitioners can activate effective and durable natural climate solutions, enabling the rapid and wide-scale adoption necessary to meaningfully contribute to climate change mitigation.
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4
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Liu L, Zhou W, Guan K, Peng B, Xu S, Tang J, Zhu Q, Till J, Jia X, Jiang C, Wang S, Qin Z, Kong H, Grant R, Mezbahuddin S, Kumar V, Jin Z. Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems. Nat Commun 2024; 15:357. [PMID: 38191521 PMCID: PMC10774286 DOI: 10.1038/s41467-023-43860-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Accepted: 11/22/2023] [Indexed: 01/10/2024] Open
Abstract
Accurate and cost-effective quantification of the carbon cycle for agroecosystems at decision-relevant scales is critical to mitigating climate change and ensuring sustainable food production. However, conventional process-based or data-driven modeling approaches alone have large prediction uncertainties due to the complex biogeochemical processes to model and the lack of observations to constrain many key state and flux variables. Here we propose a Knowledge-Guided Machine Learning (KGML) framework that addresses the above challenges by integrating knowledge embedded in a process-based model, high-resolution remote sensing observations, and machine learning (ML) techniques. Using the U.S. Corn Belt as a testbed, we demonstrate that KGML can outperform conventional process-based and black-box ML models in quantifying carbon cycle dynamics. Our high-resolution approach quantitatively reveals 86% more spatial detail of soil organic carbon changes than conventional coarse-resolution approaches. Moreover, we outline a protocol for improving KGML via various paths, which can be generalized to develop hybrid models to better predict complex earth system dynamics.
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Affiliation(s)
- Licheng Liu
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN, 55108, USA
| | - Wang Zhou
- Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Kaiyu Guan
- Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
- Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - Bin Peng
- Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Shaoming Xu
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Jinyun Tang
- Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Qing Zhu
- Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Jessica Till
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN, 55108, USA
| | - Xiaowei Jia
- Department of Computer Science, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Chongya Jiang
- Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Sheng Wang
- Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Agroecology, Aarhus University, 4200, Slagelse, Denmark
| | - Ziqi Qin
- Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Hui Kong
- Humphrey School of Public Affairs, University of Minnesota, Twin Cities, MN, 55455, USA
| | - Robert Grant
- Department of Renewable Resources, University of Alberta, Edmonton, AB, T6G2E3, Canada
| | - Symon Mezbahuddin
- Department of Renewable Resources, University of Alberta, Edmonton, AB, T6G2E3, Canada
- Environmental Knowledge and Prediction Branch, Alberta Environment and Protected Areas, Edmonton, AB, T5K 2J6, Canada
| | - Vipin Kumar
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Zhenong Jin
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN, 55108, USA.
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5
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Chu H, Christianson DS, Cheah YW, Pastorello G, O'Brien F, Geden J, Ngo ST, Hollowgrass R, Leibowitz K, Beekwilder NF, Sandesh M, Dengel S, Chan SW, Santos A, Delwiche K, Yi K, Buechner C, Baldocchi D, Papale D, Keenan TF, Biraud SC, Agarwal DA, Torn MS. AmeriFlux BASE data pipeline to support network growth and data sharing. Sci Data 2023; 10:614. [PMID: 37696825 PMCID: PMC10495345 DOI: 10.1038/s41597-023-02531-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 08/31/2023] [Indexed: 09/13/2023] Open
Abstract
AmeriFlux is a network of research sites that measure carbon, water, and energy fluxes between ecosystems and the atmosphere using the eddy covariance technique to study a variety of Earth science questions. AmeriFlux's diversity of ecosystems, instruments, and data-processing routines create challenges for data standardization, quality assurance, and sharing across the network. To address these challenges, the AmeriFlux Management Project (AMP) designed and implemented the BASE data-processing pipeline. The pipeline begins with data uploaded by the site teams, followed by the AMP team's quality assurance and quality control (QA/QC), ingestion of site metadata, and publication of the BASE data product. The semi-automated pipeline enables us to keep pace with the rapid growth of the network. As of 2022, the AmeriFlux BASE data product contains 3,130 site years of data from 444 sites, with standardized units and variable names of more than 60 common variables, representing the largest long-term data repository for flux-met data in the world. The standardized, quality-ensured data product facilitates multisite comparisons, model evaluations, and data syntheses.
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Affiliation(s)
- Housen Chu
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
| | | | - You-Wei Cheah
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Gilberto Pastorello
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Fianna O'Brien
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Joshua Geden
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Sy-Toan Ngo
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Rachel Hollowgrass
- Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, 94720, USA
| | | | - Norman F Beekwilder
- Department of Computer Science, University of Virginia, Charlottesville, VA, 22903, USA
| | - Megha Sandesh
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Sigrid Dengel
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Stephen W Chan
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - André Santos
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Kyle Delwiche
- Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Koong Yi
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Christin Buechner
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Dennis Baldocchi
- Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Dario Papale
- DIBAF, University of Tuscia, Viterbo, 01100, Italy
- Euro-Mediterranean Center on Climate Change CMCC IAFES, Viterbo, 01100, Italy
| | - Trevor F Keenan
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
- Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Sébastien C Biraud
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Deborah A Agarwal
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Margaret S Torn
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
- Energy and Resources Group, University of California Berkeley, Berkeley, CA, 94720, USA
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6
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Desai AR, Murphy BA, Wiesner S, Thom J, Butterworth BJ, Koupaei‐Abyazani N, Muttaqin A, Paleri S, Talib A, Turner J, Mineau J, Merrelli A, Stoy P, Davis K. Drivers of Decadal Carbon Fluxes Across Temperate Ecosystems. JOURNAL OF GEOPHYSICAL RESEARCH. BIOGEOSCIENCES 2022; 127:e2022JG007014. [PMID: 37502709 PMCID: PMC10369927 DOI: 10.1029/2022jg007014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 11/18/2022] [Accepted: 11/21/2022] [Indexed: 07/29/2023]
Abstract
Long-running eddy covariance flux towers provide insights into how the terrestrial carbon cycle operates over multiple timescales. Here, we evaluated variation in net ecosystem exchange (NEE) of carbon dioxide (CO2) across the Chequamegon Ecosystem-Atmosphere Study AmeriFlux core site cluster in the upper Great Lakes region of the USA from 1997 to 2020. The tower network included two mature hardwood forests with differing management regimes (US-WCr and US-Syv), two fen wetlands with varying levels of canopy sheltering and vegetation (US-Los and US-ALQ), and a very tall (400 m) landscape-level tower (US-PFa). Together, they provided over 70 site-years of observations. The 19-tower Chequamegon Heterogenous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 campaign centered around US-PFa provided additional information on the spatial variation of NEE. Decadal variability was present in all long-term sites, but cross-site coherence in interannual NEE in the earlier part of the record became weaker with time as non-climatic factors such as local disturbances likely dominated flux time series. Average decadal NEE at the tall tower transitioned from carbon source to sink to near neutral over 24 years. Respiration had a greater effect than photosynthesis on driving variations in NEE at all sites. Declining snowfall offset potential increases in assimilation from warmer springs, as less-insulated soils delayed start of spring green-up. Higher CO2 increased maximum net assimilation parameters but not total gross primary productivity. Stand-scale sites were larger net sinks than the landscape tower. Clustered, long-term carbon flux observations provide value for understanding the diverse links between carbon and climate and the challenges of upscaling these responses across space.
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Affiliation(s)
- Ankur R. Desai
- Department of Atmospheric and Oceanic SciencesUniversity of Wisconsin–MadisonMadisonWIUSA
| | - Bailey A. Murphy
- Department of Atmospheric and Oceanic SciencesUniversity of Wisconsin–MadisonMadisonWIUSA
| | - Susanne Wiesner
- Department of Plant and Earth ScienceUniversity of Wisconsin–River FallsRiver FallsWIUSA
| | - Jonathan Thom
- Space Science and Engineering CenterUniversity of Wisconsin–MadisonMadisonWIUSA
| | - Brian J. Butterworth
- Cooperative Institute for Research in Environmental SciencesCU BoulderBoulderCOUSA
- NOAA Physical Sciences LaboratoryBoulderCOUSA
| | | | - Andi Muttaqin
- Department of Atmospheric and Oceanic SciencesUniversity of Wisconsin–MadisonMadisonWIUSA
| | - Sreenath Paleri
- Department of Atmospheric and Oceanic SciencesUniversity of Wisconsin–MadisonMadisonWIUSA
| | - Ammara Talib
- Department of Civil and Environmental EngineeringUniversity of Wisconsin–MadisonMadisonWIUSA
| | - Jess Turner
- Freshwater & Marine SciencesUniversity of Wisconsin–MadisonMadisonWIUSA
| | - James Mineau
- Department of Atmospheric and Oceanic SciencesUniversity of Wisconsin–MadisonMadisonWIUSA
| | - Aronne Merrelli
- Department of Climate and Space Sciences and EngineeringUniversity of MichiganAnn ArborMIUSA
| | - Paul Stoy
- Department of Plant and Earth ScienceUniversity of Wisconsin–River FallsRiver FallsWIUSA
| | - Ken Davis
- Department of MeteorologyPennsylvania State UniversityUniversity ParkPAUSA
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