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Quan Q, He N, Zhang R, Wang J, Luo Y, Ma F, Pan J, Wang R, Liu C, Zhang J, Wang Y, Song B, Li Z, Zhou Q, Yu G, Niu S. Plant height as an indicator for alpine carbon sequestration and ecosystem response to warming. NATURE PLANTS 2024; 10:890-900. [PMID: 38755277 PMCID: PMC11208140 DOI: 10.1038/s41477-024-01705-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Accepted: 04/19/2024] [Indexed: 05/18/2024]
Abstract
Growing evidence indicates that plant community structure and traits have changed under climate warming, especially in cold or high-elevation regions. However, the impact of these warming-induced changes on ecosystem carbon sequestration remains unclear. Using a warming experiment on the high-elevation Qinghai-Tibetan Plateau, we found that warming not only increased plant species height but also altered species composition, collectively resulting in a taller plant community associated with increased net ecosystem productivity (NEP). Along a 1,500 km transect on the Plateau, taller plant community promoted NEP and soil carbon through associated chlorophyll content and other photosynthetic traits at the community level. Overall, plant community height as a dominant trait is associated with species composition and regulates ecosystem C sequestration in the high-elevation biome. This trait-based association provides new insights into predicting the direction, magnitude and sensitivity of ecosystem C fluxes in response to climate warming.
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Affiliation(s)
- Quan Quan
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, PR China
- Department of Environment and Resources, University of Chinese Academy of Sciences, Beijing, PR China
- School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
| | - Nianpeng He
- Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northeast Forestry University, Harbin, PR China
| | - Ruiyang Zhang
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, PR China
| | - Jinsong Wang
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, PR China
| | - Yiqi Luo
- School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
| | - Fangfang Ma
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, PR China
- Department of Environment and Resources, University of Chinese Academy of Sciences, Beijing, PR China
| | - Junxiao Pan
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, PR China
| | - Ruomeng Wang
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, PR China
- Department of Environment and Resources, University of Chinese Academy of Sciences, Beijing, PR China
| | - Congcong Liu
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, PR China
- Department of Environment and Resources, University of Chinese Academy of Sciences, Beijing, PR China
| | - Jiahui Zhang
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, PR China
- Department of Environment and Resources, University of Chinese Academy of Sciences, Beijing, PR China
| | - Yiheng Wang
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, PR China
- Department of Environment and Resources, University of Chinese Academy of Sciences, Beijing, PR China
| | - Bing Song
- School of Resources and Environmental Engineering, Ludong University, Yantai, PR China
| | - Zhaolei Li
- College of Resources and Environment, Southwest University, Chongqing, PR China
| | - Qingping Zhou
- Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, PR China
| | - Guirui Yu
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, PR China
- Department of Environment and Resources, University of Chinese Academy of Sciences, Beijing, PR China
| | - Shuli Niu
- Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, PR China.
- Department of Environment and Resources, University of Chinese Academy of Sciences, Beijing, PR China.
- Sichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, PR China.
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2
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Cusack DF, Christoffersen B, Smith-Martin CM, Andersen KM, Cordeiro AL, Fleischer K, Wright SJ, Guerrero-Ramírez NR, Lugli LF, McCulloch LA, Sanchez-Julia M, Batterman SA, Dallstream C, Fortunel C, Toro L, Fuchslueger L, Wong MY, Yaffar D, Fisher JB, Arnaud M, Dietterich LH, Addo-Danso SD, Valverde-Barrantes OJ, Weemstra M, Ng JC, Norby RJ. Toward a coordinated understanding of hydro-biogeochemical root functions in tropical forests for application in vegetation models. THE NEW PHYTOLOGIST 2024; 242:351-371. [PMID: 38416367 DOI: 10.1111/nph.19561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 01/10/2024] [Indexed: 02/29/2024]
Abstract
Tropical forest root characteristics and resource acquisition strategies are underrepresented in vegetation and global models, hampering the prediction of forest-climate feedbacks for these carbon-rich ecosystems. Lowland tropical forests often have globally unique combinations of high taxonomic and functional biodiversity, rainfall seasonality, and strongly weathered infertile soils, giving rise to distinct patterns in root traits and functions compared with higher latitude ecosystems. We provide a roadmap for integrating recent advances in our understanding of tropical forest belowground function into vegetation models, focusing on water and nutrient acquisition. We offer comparisons of recent advances in empirical and model understanding of root characteristics that represent important functional processes in tropical forests. We focus on: (1) fine-root strategies for soil resource exploration, (2) coupling and trade-offs in fine-root water vs nutrient acquisition, and (3) aboveground-belowground linkages in plant resource acquisition and use. We suggest avenues for representing these extremely diverse plant communities in computationally manageable and ecologically meaningful groups in models for linked aboveground-belowground hydro-nutrient functions. Tropical forests are undergoing warming, shifting rainfall regimes, and exacerbation of soil nutrient scarcity caused by elevated atmospheric CO2. The accurate model representation of tropical forest functions is crucial for understanding the interactions of this biome with the climate.
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Affiliation(s)
- Daniela F Cusack
- Department of Ecosystem Science and Sustainability, Warner College of Natural Resources, Colorado State University, 1231 Libbie Coy Way, A104, Fort Collins, CO, 80523-1476, USA
- Smithsonian Tropical Research Institute, Apartado, Balboa, 0843-03092, Panama
| | - Bradley Christoffersen
- School of Integrative Biological and Chemical Sciences, The University of Texas Rio Grande Valley, Edinburg, TX, 78539, USA
| | - Chris M Smith-Martin
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, MN, 55108, USA
| | | | - Amanda L Cordeiro
- Department of Ecosystem Science and Sustainability, Warner College of Natural Resources, Colorado State University, 1231 Libbie Coy Way, A104, Fort Collins, CO, 80523-1476, USA
- Smithsonian Tropical Research Institute, Apartado, Balboa, 0843-03092, Panama
| | - Katrin Fleischer
- Department Biogeochemical Signals, Max-Planck-Institute for Biogeochemistry, Hans-Knöll-Straße 10, Jena, 07745, Germany
| | - S Joseph Wright
- Smithsonian Tropical Research Institute, Apartado, Balboa, 0843-03092, Panama
| | - Nathaly R Guerrero-Ramírez
- Silviculture and Forest Ecology of Temperate Zones, Faculty of Forest Sciences and Forest Ecology, University of Göttingen, Gottingen, 37077, Germany
- Centre of Biodiversity and Sustainable Land Use (CBL), University of Göttingen, Gottingen, 37077, Germany
| | - Laynara F Lugli
- School of Life Sciences, Technical University of Munich, Freising, 85354, Germany
| | - Lindsay A McCulloch
- Department of Organismic and Evolutionary Biology, Harvard University, 26 Oxford St., Cambridge, MA, 02138, USA
- National Center for Atmospheric Research, National Oceanographic and Atmospheric Agency, 1850 Table Mesa Dr., Boulder, CO, 80305, USA
| | - Mareli Sanchez-Julia
- Department of Ecology and Evolutionary Biology, Tulane University, New Orleans, LA, 70118, USA
| | - Sarah A Batterman
- Smithsonian Tropical Research Institute, Apartado, Balboa, 0843-03092, Panama
- Cary Institute of Ecosystem Studies, Millbrook, NY, 12545, USA
- School of Geography, University of Leeds, Leeds, LS2 9JT, UK
| | - Caroline Dallstream
- Department of Biology, McGill University, 1205 Av. du Docteur-Penfield, Montreal, QC, H3A 1B1, Canada
| | - Claire Fortunel
- AMAP (Botanique et Modélisation de l'Architecture des Plantes et des Végétations), Université de Montpellier, CIRAD, CNRS, INRAE, IRD, Montpellier, 34398, France
| | - Laura Toro
- Yale Applied Science Synthesis Program, The Forest School at the Yale School of the Environment, Yale University, New Haven, CT, 06511, USA
| | - Lucia Fuchslueger
- Centre for Microbiology and Environmental Systems Science, University of Vienna, Vienna, 1030, Austria
| | - Michelle Y Wong
- Cary Institute of Ecosystem Studies, Millbrook, NY, 12545, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, 06511, USA
| | - Daniela Yaffar
- Functional Forest Ecology, Universität Hamburg, Barsbüttel, 22885, Germany
| | - Joshua B Fisher
- Schmid College of Science and Technology, Chapman University, 1 University Drive, Orange, CA, 92866, USA
| | - Marie Arnaud
- Institute of Ecology and Environmental Sciences (IEES), UMR 7618, CNRS-Sorbonne University-INRAE-UPEC-IRD, Paris, 75005, France
- School of Geography, Earth and Environmental Sciences & BIFOR, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Lee H Dietterich
- Department of Ecosystem Science and Sustainability, Warner College of Natural Resources, Colorado State University, 1231 Libbie Coy Way, A104, Fort Collins, CO, 80523-1476, USA
- U.S. Army Engineer Research and Development Center, Environmental Laboratory, Vicksburg, MS, 39180, USA
- Department of Biology, Haverford College, Haverford, PA, 19003, USA
| | - Shalom D Addo-Danso
- Forests and Climate Change Division, CSIR-Forestry Research Institute of Ghana, P.O Box UP 63 KNUST, Kumasi, Ghana
| | - Oscar J Valverde-Barrantes
- Department of Biological Sciences, International Center for Tropical Biodiversity, Florida International University, Miami, FL, 33199, USA
| | - Monique Weemstra
- Department of Biological Sciences, International Center for Tropical Biodiversity, Florida International University, Miami, FL, 33199, USA
| | - Jing Cheng Ng
- Nanyang Technological University, Singapore, 639798, Singapore
| | - Richard J Norby
- Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN, 37996, USA
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3
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Baca Cabrera JC, Vanderborght J, Couvreur V, Behrend D, Gaiser T, Nguyen TH, Lobet G. Root hydraulic properties: An exploration of their variability across scales. PLANT DIRECT 2024; 8:e582. [PMID: 38590783 PMCID: PMC10999368 DOI: 10.1002/pld3.582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 02/26/2024] [Accepted: 03/05/2024] [Indexed: 04/10/2024]
Abstract
Root hydraulic properties are key physiological traits that determine the capacity of root systems to take up water, at a specific evaporative demand. They can strongly vary among species, cultivars or even within the same genotype, but a systematic analysis of their variation across plant functional types (PFTs) is still missing. Here, we reviewed published empirical studies on root hydraulic properties at the segment-, individual root-, or root system scale and determined its variability and the main factors contributing to it. This corresponded to a total of 241 published studies, comprising 213 species, including woody and herbaceous vegetation. We observed an extremely large range of variation (of orders of magnitude) in root hydraulic properties, but this was not caused by systematic differences among PFTs. Rather, the (combined) effect of factors such as root system age, driving force used for measurement, or stress treatments shaped the results. We found a significant decrease in root hydraulic properties under stress conditions (drought and aquaporin inhibition, p < .001) and a significant effect of the driving force used for measurement (hydrostatic or osmotic gradients, p < .001). Furthermore, whole root system conductance increased significantly with root system age across several crop species (p < .01), causing very large variation in the data (>2 orders of magnitude). Interestingly, this relationship showed an asymptotic shape, with a steep increase during the first days of growth and a flattening out at later stages of development. We confirmed this dynamic through simulations using a state-of-the-art computational model of water flow in the root system for a variety of crop species, suggesting common patterns across studies and species. These findings provide better understanding of the main causes of root hydraulic properties variations observed across empirical studies. They also open the door to better representation of hydraulic processes across multiple plant functional types and at large scales. All data collected in our analysis has been aggregated into an open access database (https://roothydraulic-properties.shinyapps.io/database/), fostering scientific exchange.
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Affiliation(s)
- Juan C. Baca Cabrera
- Institute of Bio‐ and Geoscience, Agrosphere (IBG‐3)Forschungszentrum Jülich GmbHJülichGermany
| | - Jan Vanderborght
- Institute of Bio‐ and Geoscience, Agrosphere (IBG‐3)Forschungszentrum Jülich GmbHJülichGermany
| | - Valentin Couvreur
- Earth and Life InstituteUniversité catholique de LouvainLouvain‐la‐NeuveBelgium
| | - Dominik Behrend
- Institute of Crop Science and Resources ConservationUniversity of BonnBonnGermany
| | - Thomas Gaiser
- Institute of Crop Science and Resources ConservationUniversity of BonnBonnGermany
| | - Thuy Huu Nguyen
- Institute of Crop Science and Resources ConservationUniversity of BonnBonnGermany
| | - Guillaume Lobet
- Institute of Bio‐ and Geoscience, Agrosphere (IBG‐3)Forschungszentrum Jülich GmbHJülichGermany
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4
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Berner LT, Orndahl KM, Rose M, Tamstorf M, Arndal MF, Alexander HD, Humphreys ER, Loranty MM, Ludwig SM, Nyman J, Juutinen S, Aurela M, Happonen K, Mikola J, Mack MC, Vankoughnett MR, Iversen CM, Salmon VG, Yang D, Kumar J, Grogan P, Danby RK, Scott NA, Olofsson J, Siewert MB, Deschamps L, Lévesque E, Maire V, Morneault A, Gauthier G, Gignac C, Boudreau S, Gaspard A, Kholodov A, Bret-Harte MS, Greaves HE, Walker D, Gregory FM, Michelsen A, Kumpula T, Villoslada M, Ylänne H, Luoto M, Virtanen T, Forbes BC, Hölzel N, Epstein H, Heim RJ, Bunn A, Holmes RM, Hung JKY, Natali SM, Virkkala AM, Goetz SJ. The Arctic Plant Aboveground Biomass Synthesis Dataset. Sci Data 2024; 11:305. [PMID: 38509110 PMCID: PMC10954756 DOI: 10.1038/s41597-024-03139-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 03/14/2024] [Indexed: 03/22/2024] Open
Abstract
Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m-2) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.
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Affiliation(s)
- Logan T Berner
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, USA.
| | - Kathleen M Orndahl
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, USA
| | - Melissa Rose
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, USA
| | - Mikkel Tamstorf
- Department of Ecoscience, Aarhus University, Aarhus, Denmark
| | - Marie F Arndal
- Department of Ecoscience, Aarhus University, Aarhus, Denmark
| | - Heather D Alexander
- College of Forestry, Wildlife, and Environment, Auburn University, Auburn, USA
| | - Elyn R Humphreys
- Department of Geography and Environmental Studies, Carleton University, Ottawa, Canada
| | | | - Sarah M Ludwig
- Department of Earth and Environmental Sciences, Columbia University, Palisades, USA
| | - Johanna Nyman
- Jeb E. Brooks School of Public Policy, Cornell University, Ithaca, USA
| | - Sari Juutinen
- Climate System Research, Finnish Meteorological Institute, Helsinki, Finland
| | - Mika Aurela
- Finnish Meteorological Institute, Helsinki, Finland
| | | | - Juha Mikola
- Bioeconomy and Environment Unit, Natural Resources Institute Finland, Helsinki, Finland
| | - Michelle C Mack
- Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, USA
- Department of Biological Sciences, Northern Arizona University, Flagstaff, USA
| | | | - Colleen M Iversen
- Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, USA
| | - Verity G Salmon
- Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, USA
- Environmental Science Division, Oak Ridge National Laboratory, Oak Ridge, USA
| | - Dedi Yang
- Environmental Science Division, Oak Ridge National Laboratory, Oak Ridge, USA
| | - Jitendra Kumar
- Environmental Science Division, Oak Ridge National Laboratory, Oak Ridge, USA
| | - Paul Grogan
- Department of Biology, Queen's University, Kingston, Canada
| | - Ryan K Danby
- Department of Geography and Planning, Queen's University, Kingston, Canada
| | - Neal A Scott
- Department of Geography and Planning, Queen's University, Kingston, Canada
| | - Johan Olofsson
- Department of Ecology and Environmental Science, Umeå University, Umeå, Sweden
| | - Matthias B Siewert
- Department of Ecology and Environmental Science, Umeå University, Umeå, Sweden
| | - Lucas Deschamps
- Département des sciences de l'environnement, Université du Québec à Trois-Rivières, Trois-Rivières, Canada
| | - Esther Lévesque
- Département des sciences de l'environnement, Université du Québec à Trois-Rivières, Trois-Rivières, Canada
| | - Vincent Maire
- Département des sciences de l'environnement, Université du Québec à Trois-Rivières, Trois-Rivières, Canada
| | - Amélie Morneault
- Département des sciences de l'environnement, Université du Québec à Trois-Rivières, Trois-Rivières, Canada
| | - Gilles Gauthier
- Centre d'Études Nordiques, Université Laval, Québec, Canada
- Department of Biology, Université Laval, Québec, Canada
| | - Charles Gignac
- Centre d'Études Nordiques, Université Laval, Québec, Canada
- Department of Plant Science, Université Laval, Québec, Canada
| | | | - Anna Gaspard
- Department of Biology, Université Laval, Québec, Canada
| | | | | | - Heather E Greaves
- Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, USA
| | - Donald Walker
- Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, USA
| | - Fiona M Gregory
- Alberta Biodiversity Monitoring Institute, University of Alberta, Edmonton, Canada
| | - Anders Michelsen
- Department of Biology, University of Copenhagen, København, Denmark
| | - Timo Kumpula
- Department of Geographical and Historical Studies, University of Eastern Finland, Joensuu, Finland
| | - Miguel Villoslada
- Department of Geographical and Historical Studies, University of Eastern Finland, Joensuu, Finland
- Institute of Agriculture and Environmental Sciences, Estonian University of Life Sciences, Tartu, Estonia
| | - Henni Ylänne
- School of Forest Sciences, University of Eastern Finland, Joensuu, Finland
| | - Miska Luoto
- Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland
| | - Tarmo Virtanen
- Ecosystems and Environment Research Program, University of Helsinki, Helsinki, Finland
| | - Bruce C Forbes
- Arctic Centre, University of Lapland, Rovaniemi, Finland
| | - Norbert Hölzel
- Institute of Landscape Ecology, University of Münster, Münster, Germany
| | - Howard Epstein
- Department of Environmental Science, University of Virginia, Charlottesville, USA
| | - Ramona J Heim
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zürich, Switzerland
| | - Andrew Bunn
- Department of Environmental Sciences, Western Washington University, Bellingham, USA
| | | | | | | | | | - Scott J Goetz
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, USA
- Bioeconomy and Environment Unit, Natural Resources Institute Finland, Helsinki, Finland
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5
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Ge M, Korrensalo A, Laiho R, Kohl L, Lohila A, Pihlatie M, Li X, Laine AM, Anttila J, Putkinen A, Wang W, Koskinen M. Plant-mediated CH 4 exchange in wetlands: A review of mechanisms and measurement methods with implications for modelling. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 914:169662. [PMID: 38159777 DOI: 10.1016/j.scitotenv.2023.169662] [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: 07/03/2023] [Revised: 12/22/2023] [Accepted: 12/22/2023] [Indexed: 01/03/2024]
Abstract
Plant-mediated CH4 transport (PMT) is the dominant pathway through which soil-produced CH4 can escape into the atmosphere and thus plays an important role in controlling ecosystem CH4 emission. PMT is affected by abiotic and biotic factors simultaneously, and the effects of biotic factors, such as the dominant plant species and their traits, can override the effects of abiotic factors. Increasing evidence shows that plant-mediated CH4 fluxes include not only PMT, but also within-plant CH4 production and oxidation due to the detection of methanogens and methanotrophs attached to the shoots. Despite the inter-species and seasonal differences, and the probable contribution of within-plant microbes to total plant-mediated CH4 exchange (PME), current process-based ecosystem models only estimate PMT based on the bulk biomass or leaf area index of aerenchymatous plants. We highlight five knowledge gaps to which more research efforts should be devoted. First, large between-species variation, even within the same family, complicates general estimation of PMT, and calls for further work on the key dominant species in different types of wetlands. Second, the interface (rhizosphere-root, root-shoot, or leaf-atmosphere) and plant traits controlling PMT remain poorly documented, but would be required for generalizations from species to relevant functional groups. Third, the main environmental controls of PMT across species remain uncertain. Fourth, the role of within-plant CH4 production and oxidation is poorly quantified. Fifth, the simplistic description of PMT in current process models results in uncertainty and potentially high errors in predictions of the ecosystem CH4 flux. Our review suggest that flux measurements should be conducted over multiple growing seasons and be paired with trait assessment and microbial analysis, and that trait-based models should be developed. Only then we are capable to accurately estimate plant-mediated CH4 emissions, and eventually ecosystem total CH4 emissions at both regional and global scales.
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Affiliation(s)
- Mengyu Ge
- Department of Agricultural Sciences, University of Helsinki, PO Box 56, Helsinki 00014, Finland; Institute for Atmospheric and Earth System Research (INAR)/Forest Sciences, University of Helsinki, PO Box 56, Helsinki 00014, Finland.
| | - Aino Korrensalo
- Department of Environmental and Biological Sciences, University of Eastern Finland, PO Box 111, Kuopio 80101, Finland; Natural Resources Institute Finland, Latokartanonkaari 9, Helsinki 00790, Finland
| | - Raija Laiho
- Natural Resources Institute Finland, Latokartanonkaari 9, Helsinki 00790, Finland
| | - Lukas Kohl
- Department of Agricultural Sciences, University of Helsinki, PO Box 56, Helsinki 00014, Finland; Institute for Atmospheric and Earth System Research (INAR)/Forest Sciences, University of Helsinki, PO Box 56, Helsinki 00014, Finland; Department of Environmental and Biological Sciences, University of Eastern Finland, PO Box 111, Kuopio 80101, Finland
| | - Annalea Lohila
- Finnish Meteorological Institute, Erik Palménin aukio 1, Helsinki 00560, Finland
| | - Mari Pihlatie
- Department of Agricultural Sciences, University of Helsinki, PO Box 56, Helsinki 00014, Finland; Institute for Atmospheric and Earth System Research (INAR)/Forest Sciences, University of Helsinki, PO Box 56, Helsinki 00014, Finland; Department of Agricultural Sciences, Viikki Plant Science Centre (ViPS), University of Helsinki, PO Box 56, 00014 Helsinki, Finland
| | - Xuefei Li
- Institute for Atmospheric and Earth System Research (INAR)/Forest Sciences, University of Helsinki, PO Box 56, Helsinki 00014, Finland
| | - Anna M Laine
- Geological Survey of Finland, PO Box 1237, 70211 Kuopio, Finland
| | - Jani Anttila
- Natural Resources Institute Finland, Latokartanonkaari 9, Helsinki 00790, Finland
| | - Anuliina Putkinen
- Department of Agricultural Sciences, University of Helsinki, PO Box 56, Helsinki 00014, Finland; Institute for Atmospheric and Earth System Research (INAR)/Forest Sciences, University of Helsinki, PO Box 56, Helsinki 00014, Finland
| | - Weifeng Wang
- College of Biology and the Environment, Nanjing Forestry University, 210037 Nanjing, China
| | - Markku Koskinen
- Department of Agricultural Sciences, University of Helsinki, PO Box 56, Helsinki 00014, Finland; Institute for Atmospheric and Earth System Research (INAR)/Forest Sciences, University of Helsinki, PO Box 56, Helsinki 00014, Finland
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6
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Wilcox KR, Chen A, Avolio ML, Butler EE, Collins S, Fisher R, Keenan T, Kiang NY, Knapp AK, Koerner SE, Kueppers L, Liang G, Lieungh E, Loik M, Luo Y, Poulter B, Reich P, Renwick K, Smith MD, Walker A, Weng E, Komatsu KJ. Accounting for herbaceous communities in process-based models will advance our understanding of "grassy" ecosystems. GLOBAL CHANGE BIOLOGY 2023; 29:6453-6477. [PMID: 37814910 DOI: 10.1111/gcb.16950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 06/01/2023] [Indexed: 10/11/2023]
Abstract
Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process-based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.
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Affiliation(s)
- Kevin R Wilcox
- University of North Carolina Greensboro, Greensboro, North Carolina, USA
- University of Wyoming, Laramie, Wyoming, USA
| | - Anping Chen
- Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, USA
| | - Meghan L Avolio
- Earth and Planetary Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Ethan E Butler
- Department of Forest Resources, University of Minnesota, St. Paul, Minnesota, USA
| | - Scott Collins
- Department of Biology, University of New Mexico, Albuquerque, New Mexico, USA
| | - Rosie Fisher
- CICERO Centre for International Cimate Research, Forskningsparken, Oslo, Norway
| | - Trevor Keenan
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
| | - Nancy Y Kiang
- NASA Goddard Institute for Space Studies, New York, New York, USA
| | - Alan K Knapp
- Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, USA
| | - Sally E Koerner
- University of North Carolina Greensboro, Greensboro, North Carolina, USA
| | - Lara Kueppers
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
| | - Guopeng Liang
- Department of Forest Resources, University of Minnesota, St. Paul, Minnesota, USA
| | - Eva Lieungh
- Natural History Museum, University of Oslo, Oslo, Norway
| | - Michael Loik
- Department of Environmental Studies, University of California, Santa Cruz, California, USA
| | - Yiqi Luo
- School of Integrative Plant Science, Cornell University, Ithaca, New York, USA
| | - Ben Poulter
- Biospheric Sciences Lab, NASA GSFC, Greenbelt, Maryland, USA
| | - Peter Reich
- Department of Forest Resources, University of Minnesota, St. Paul, Minnesota, USA
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, New South Wales, Australia
| | | | - Melinda D Smith
- Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, USA
| | - Anthony Walker
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Ensheng Weng
- NASA Goddard Institute for Space Studies, New York, New York, USA
- Center for Climate Systems Research, Columbia University, New York, New York, USA
| | - Kimberly J Komatsu
- University of North Carolina Greensboro, Greensboro, North Carolina, USA
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7
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Liu C, Sack L, Li Y, Zhang J, Yu K, Zhang Q, He N, Yu G. Relationships of stomatal morphology to the environment across plant communities. Nat Commun 2023; 14:6629. [PMID: 37857672 PMCID: PMC10587080 DOI: 10.1038/s41467-023-42136-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 10/02/2023] [Indexed: 10/21/2023] Open
Abstract
The relationship between stomatal traits and environmental drivers across plant communities has important implications for ecosystem carbon and water fluxes, but it has remained unclear. Here, we measure the stomatal morphology of 4492 species-site combinations in 340 vegetation plots across China and calculate their community-weighted values for mean, variance, skewness, and kurtosis. We demonstrate a trade-off between stomatal density and size at the community level. The community-weighted mean and variance of stomatal density are mainly associated with precipitation, while that of stomatal size is mainly associated with temperature, and the skewness and kurtosis of stomatal traits are less related to climatic and soil variables. Beyond mean climate variables, stomatal trait moments also vary with climatic seasonality and extreme conditions. Our findings extend the knowledge of stomatal trait-environment relationships to the ecosystem scale, with applications in predicting future water and carbon cycles.
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Affiliation(s)
- Congcong Liu
- Key Laboratory of Ecology and Environment in Minority Areas (Minzu University of China), National Ethnic Affairs Commission, 100081, Beijing, China
- College of Life and Environmental Sciences, Minzu University of China, 100081, Beijing, China
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China
| | - Lawren Sack
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, 90025, USA
| | - Ying Li
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China
| | - Jiahui Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China
| | - Kailiang Yu
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, 08540, USA
| | - Qiongyu Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China
| | - Nianpeng He
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China.
- Center for Ecological Research, Northeast Forestry University, 150040, Harbin, China.
- Earth Critical Zone and Flux Research Station of Xing'an Mountains, Chinese Academy of Sciences, 165200, Daxing'anling, China.
| | - Guirui Yu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, 100049, Beijing, China
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8
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Blume-Werry G, Dorrepaal E, Keuper F, Kummu M, Wild B, Weedon JT. Arctic rooting depth distribution influences modelled carbon emissions but cannot be inferred from aboveground vegetation type. THE NEW PHYTOLOGIST 2023; 240:502-514. [PMID: 37227127 DOI: 10.1111/nph.18998] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 05/04/2023] [Indexed: 05/26/2023]
Abstract
The distribution of roots throughout the soil drives depth-dependent plant-soil interactions and ecosystem processes, particularly in arctic tundra where plant biomass, is predominantly belowground. Vegetation is usually classified from aboveground, but it is unclear whether such classifications are suitable to estimate belowground attributes and their consequences, such as rooting depth distribution and its influence on carbon cycling. We performed a meta-analysis of 55 published arctic rooting depth profiles, testing for differences both between distributions based on aboveground vegetation types (Graminoid, Wetland, Erect-shrub, and Prostrate-shrub tundra) and between 'Root Profile Types' for which we defined three representative and contrasting clusters. We further analyzed potential impacts of these different rooting depth distributions on rhizosphere priming-induced carbon losses from tundra soils. Rooting depth distribution hardly differed between aboveground vegetation types but varied between Root Profile Types. Accordingly, modelled priming-induced carbon emissions were similar between aboveground vegetation types when they were applied to the entire tundra, but ranged from 7.2 to 17.6 Pg C cumulative emissions until 2100 between individual Root Profile Types. Variations in rooting depth distribution are important for the circumpolar tundra carbon-climate feedback but can currently not be inferred adequately from aboveground vegetation type classifications.
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Affiliation(s)
- Gesche Blume-Werry
- Experimental Plant Ecology, Institute of Botany and Landscape Ecology, Greifswald University, 17487, Greifswald, Germany
- Climate Impacts Research Centre, Department of Ecology and Environmental Science, Umeå University, 981 07, Abisko, Sweden
| | - Ellen Dorrepaal
- Climate Impacts Research Centre, Department of Ecology and Environmental Science, Umeå University, 981 07, Abisko, Sweden
| | - Frida Keuper
- BioEcoAgro Joint Research Unit, INRAE, F-02000, Barenton-Bugny, France
| | - Matti Kummu
- Water and Development Research Group, Aalto University, 00076, Aalto, Finland
| | - Birgit Wild
- Department of Environmental Science, Stockholm University, 114 18, Stockholm, Sweden
- Bolin Centre for Climate Research, Stockholm University, 114 18, Stockholm, Sweden
| | - James T Weedon
- Amsterdam Institute for Life and Environment (A-LIFE), Systems Ecology Section, Vrije Universiteit Amsterdam, 1081, Amsterdam, the Netherlands
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9
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Keetz LT, Lieungh E, Karimi-Asli K, Geange SR, Gelati E, Tang H, Yilmaz YA, Aas KS, Althuizen IHJ, Bryn A, Falk S, Fisher R, Fouilloux A, Horvath P, Indrehus S, Lee H, Lombardozzi D, Parmentier FJW, Pirk N, Vandvik V, Vollsnes AV, Skarpaas O, Stordal F, Tallaksen LM. Climate-ecosystem modelling made easy: The Land Sites Platform. GLOBAL CHANGE BIOLOGY 2023; 29:4440-4452. [PMID: 37303068 DOI: 10.1111/gcb.16808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 05/03/2023] [Indexed: 06/13/2023]
Abstract
Dynamic Global Vegetation Models (DGVMs) provide a state-of-the-art process-based approach to study the complex interplay between vegetation and its physical environment. For example, they help to predict how terrestrial plants interact with climate, soils, disturbance and competition for resources. We argue that there is untapped potential for the use of DGVMs in ecological and ecophysiological research. One fundamental barrier to realize this potential is that many researchers with relevant expertize (ecology, plant physiology, soil science, etc.) lack access to the technical resources or awareness of the research potential of DGVMs. Here we present the Land Sites Platform (LSP): new software that facilitates single-site simulations with the Functionally Assembled Terrestrial Ecosystem Simulator, an advanced DGVM coupled with the Community Land Model. The LSP includes a Graphical User Interface and an Application Programming Interface, which improve the user experience and lower the technical thresholds for installing these model architectures and setting up model experiments. The software is distributed via version-controlled containers; researchers and students can run simulations directly on their personal computers or servers, with relatively low hardware requirements, and on different operating systems. Version 1.0 of the LSP supports site-level simulations. We provide input data for 20 established geo-ecological observation sites in Norway and workflows to add generic sites from public global datasets. The LSP makes standard model experiments with default data easily achievable (e.g., for educational or introductory purposes) while retaining flexibility for more advanced scientific uses. We further provide tools to visualize the model input and output, including simple examples to relate predictions to local observations. The LSP improves access to land surface and DGVM modelling as a building block of community cyberinfrastructure that may inspire new avenues for mechanistic ecosystem research across disciplines.
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Affiliation(s)
- Lasse T Keetz
- Department of Geosciences, University of Oslo, Oslo, Norway
| | - Eva Lieungh
- Natural History Museum, University of Oslo, Oslo, Norway
| | | | - Sonya R Geange
- Department of Biological Sciences, University of Bergen, Bergen, Norway
| | | | - Hui Tang
- Department of Geosciences, University of Oslo, Oslo, Norway
- Natural History Museum, University of Oslo, Oslo, Norway
- Finnish Meteorological Institute, Climate System Research, Helsinki, Finland
| | - Yeliz A Yilmaz
- Department of Geosciences, University of Oslo, Oslo, Norway
- Centre for Biogeochemistry in the Anthropocene, University of Oslo, Oslo, Norway
| | - Kjetil S Aas
- Department of Geosciences, University of Oslo, Oslo, Norway
- CICERO Center for International Climate Research, Oslo, Norway
| | - Inge H J Althuizen
- Division of Climate and Environment, NORCE Norwegian Research Centre, Bergen, Norway
| | - Anders Bryn
- Natural History Museum, University of Oslo, Oslo, Norway
- Centre for Biogeochemistry in the Anthropocene, University of Oslo, Oslo, Norway
| | - Stefanie Falk
- Department of Geography, Ludwig Maximilian University of Munich, Munich, Germany
| | - Rosie Fisher
- CICERO Center for International Climate Research, Oslo, Norway
- Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
| | | | - Peter Horvath
- Natural History Museum, University of Oslo, Oslo, Norway
| | | | - Hanna Lee
- Division of Climate and Environment, NORCE Norwegian Research Centre, Bergen, Norway
- Department of Biology, Norwegian University of Science and Technology NTNU, Trondheim, Norway
| | - Danica Lombardozzi
- Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
| | - Frans-Jan W Parmentier
- Department of Geosciences, University of Oslo, Oslo, Norway
- Centre for Biogeochemistry in the Anthropocene, University of Oslo, Oslo, Norway
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
| | - Norbert Pirk
- Department of Geosciences, University of Oslo, Oslo, Norway
| | - Vigdis Vandvik
- Department of Biological Sciences, University of Bergen, Bergen, Norway
- Bjerknes Centre for Climate Research, University of Bergen, Bergen, Norway
| | - Ane V Vollsnes
- Centre for Biogeochemistry in the Anthropocene, University of Oslo, Oslo, Norway
- Department of Biosciences, University of Oslo, Oslo, Norway
| | - Olav Skarpaas
- Natural History Museum, University of Oslo, Oslo, Norway
| | - Frode Stordal
- Department of Geosciences, University of Oslo, Oslo, Norway
- Centre for Biogeochemistry in the Anthropocene, University of Oslo, Oslo, Norway
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10
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Curasi SR, Fetcher N, Wright KS, Weldon DP, Rocha AV. Insights into the tussock growth form with model-data fusion. THE NEW PHYTOLOGIST 2023; 239:562-575. [PMID: 36653954 DOI: 10.1111/nph.18751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 01/11/2023] [Indexed: 06/15/2023]
Abstract
Some rhizomatous grass and sedge species form tussocks that impact ecosystem structure and function. Despite their importance, tussock development and size controls are poorly understood due to the decadal to centennial timescales over which tussocks form. We explored mechanisms regulating tussock development and size in a ubiquitous arctic tussock sedge (Eriophorum vaginatum) using field observations and a mass balance model coupled with a tiller population model. Model-data fusion was used to quantify parameter and prediction uncertainty, determine model sensitivity, and test hypotheses on the factors regulating tussock size. The model accurately captured the dynamics of tussock development, characteristics, and size observed in the field. Tussock growth approached maximal size within several decades, which was determined by feedbacks between the mass balance of tussock root necromass and density-dependent tillering. The model also predicted that maximal tussock size was primarily regulated by tiller root productivity and necromass bulk density and less so by tiller demography. These predictions were corroborated by field observations of tussock biomass and root characteristics. The study highlights the importance of belowground processes in regulating tussock development and size and enhances our understanding of the influence of tussocks on arctic ecosystem structure and function.
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Affiliation(s)
- Salvatore R Curasi
- Department of Biology, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Ned Fetcher
- Institute for Environmental Science and Sustainability, Wilkes University, Wilkes-Barre, PA, 18766, USA
| | - Kelseyann S Wright
- Department of Biology, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Daniel P Weldon
- Department of Biology, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Adrian V Rocha
- Department of Biology, University of Notre Dame, Notre Dame, IN, 46556, USA
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11
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Rius BF, Filho JPD, Fleischer K, Hofhansl F, Blanco CC, Rammig A, Domingues TF, Lapola DM. Higher functional diversity improves modeling of Amazon forest carbon storage. Ecol Modell 2023. [DOI: 10.1016/j.ecolmodel.2023.110323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2023]
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12
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García Criado M, Myers-Smith IH, Bjorkman AD, Normand S, Blach-Overgaard A, Thomas HJD, Eskelinen A, Happonen K, Alatalo JM, Anadon-Rosell A, Aubin I, Te Beest M, Betway-May KR, Blok D, Buras A, Cerabolini BEL, Christie K, Cornelissen JHC, Forbes BC, Frei ER, Grogan P, Hermanutz L, Hollister RD, Hudson J, Iturrate-Garcia M, Kaarlejärvi E, Kleyer M, Lamarque LJ, Lembrechts JJ, Lévesque E, Luoto M, Macek P, May JL, Prevéy JS, Schaepman-Strub G, Sheremetiev SN, Siegwart Collier L, Soudzilovskaia NA, Trant A, Venn SE, Virkkala AM. Plant traits poorly predict winner and loser shrub species in a warming tundra biome. Nat Commun 2023; 14:3837. [PMID: 37380662 DOI: 10.1038/s41467-023-39573-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 06/15/2023] [Indexed: 06/30/2023] Open
Abstract
Climate change is leading to species redistributions. In the tundra biome, shrubs are generally expanding, but not all tundra shrub species will benefit from warming. Winner and loser species, and the characteristics that may determine success or failure, have not yet been fully identified. Here, we investigate whether past abundance changes, current range sizes and projected range shifts derived from species distribution models are related to plant trait values and intraspecific trait variation. We combined 17,921 trait records with observed past and modelled future distributions from 62 tundra shrub species across three continents. We found that species with greater variation in seed mass and specific leaf area had larger projected range shifts, and projected winner species had greater seed mass values. However, trait values and variation were not consistently related to current and projected ranges, nor to past abundance change. Overall, our findings indicate that abundance change and range shifts will not lead to directional modifications in shrub trait composition, since winner and loser species share relatively similar trait spaces.
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Affiliation(s)
| | | | - Anne D Bjorkman
- Department of Biology and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
| | - Signe Normand
- Department of Biology, Aarhus University, Aarhus, Denmark
| | | | - Haydn J D Thomas
- School of GeoSciences, University of Edinburgh, Edinburgh, Scotland, UK
| | - Anu Eskelinen
- Department of Physiological Diversity, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Department of Ecology and Genetics, University of Oulu, Oulu, Finland
| | - Konsta Happonen
- Department of Biology and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Juha M Alatalo
- Environmental Science Center, Qatar University, Doha, Qatar
| | - Alba Anadon-Rosell
- CREAF, Cerdanyola del Vallès, Barcelona, Catalonia, Spain
- Institute of Botany and Landscape Ecology, University of Greifswald, Greifswald, Germany
| | - Isabelle Aubin
- Natural Resources Canada, Canadian Forest Service, Great Lakes Forestry Centre, Sault Ste Marie, ON, Canada
| | - Mariska Te Beest
- Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, the Netherlands
- Centre for African Conservation Ecology, Nelson Mandela University, Port Elizabeth, South Africa
| | | | - Daan Blok
- Dutch Research Council (NWO), The Hague, The Netherlands
| | - Allan Buras
- Land Surface-Atmosphere Interactions, School of Life Sciences Weihenstephan, Freising, Germany
| | - Bruno E L Cerabolini
- Department of Biotechnologies and Life Sciences, University of Insubria, Varese, Italy
| | - Katherine Christie
- Threatened, Endangered, and Diversity Program, Alaska Department of Fish and Game, Anchorage, USA
| | - J Hans C Cornelissen
- Section Systems Ecology, Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit, Amsterdam, The Netherlands
| | - Bruce C Forbes
- Arctic Centre, University of Lapland, Rovaniemi, Finland
| | - Esther R Frei
- WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
- Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
- Department of Geography, University of British Columbia, Vancouver, BC, Canada
- Climate Change and Extremes in Alpine Regions Research Centre CERC, Davos, Switzerland
| | - Paul Grogan
- Department of Biology, Queen's University, Kingston, Ontario, ON, Canada
| | - Luise Hermanutz
- Department of Biology, Memorial University, St. John's, NL, Canada
| | | | - James Hudson
- Government of British Columbia, Vancouver, BC, Canada
| | - Maitane Iturrate-Garcia
- Department of Chemical and Biological Metrology, Federal Institute of Metrology METAS, Bern-Wabern, Switzerland
| | - Elina Kaarlejärvi
- Research Centre for Ecological Change, Organismal and Evolutionary Biology Research Programme, University of Helsinki, Helsinki, Finland
| | - Michael Kleyer
- Institute of Biology and Environmental Sciences, University of Oldenburg, Oldenburg, Germany
| | - Laurent J Lamarque
- Département des Sciences de l'environnement et Centre d'études nordiques, Université du Québec à Trois-Rivières, Trois-Rivières, Québec, Canada
| | - Jonas J Lembrechts
- Research Group Plants and Ecosystems (PLECO), University of Antwerp, Wilrijk, Belgium
| | - Esther Lévesque
- Département des Sciences de l'environnement et Centre d'études nordiques, Université du Québec à Trois-Rivières, Trois-Rivières, Québec, Canada
| | - Miska Luoto
- Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland
| | - Petr Macek
- Institute of Hydrobiology, Biology Centre of the Czech Academy of Sciences, Ceske Budejovice, Czech Republic
| | - Jeremy L May
- Department of Biological Sciences, Florida International University, Miami, FL, USA
- Department of Biology and Environmental Science, Marietta College, Marietta, OH, USA
| | - Janet S Prevéy
- WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
- U.S. Geological Survey, Fort Collins, CO, USA
| | - Gabriela Schaepman-Strub
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | | | - Laura Siegwart Collier
- Department of Biology, Memorial University, St. John's, NL, Canada
- Terra Nova National Park, Parks Canada Agency, Glovertown, NL, Canada
| | | | - Andrew Trant
- School of Environment, Resources and Sustainability, University of Waterloo, Waterloo, ON, Canada
| | - Susanna E Venn
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Burwood, VIC, Australia
| | - Anna-Maria Virkkala
- Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland
- Woodwell Climate Research Center, Falmouth, MA, USA
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13
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LaFond-Hudson S, Sulman B. Modeling strategies and data needs for representing coastal wetland vegetation in land surface models. THE NEW PHYTOLOGIST 2023; 238:938-951. [PMID: 36683447 DOI: 10.1111/nph.18760] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 01/10/2023] [Indexed: 06/17/2023]
Abstract
Vegetated coastal ecosystems sequester carbon rapidly relative to terrestrial ecosystems. Coastal wetlands are poorly represented in land surface models, but work is underway to improve process-based, predictive modeling of these ecosystems. Here, we identify guiding questions, potential simulations, and data needs to make progress in improving representation of vegetation in terrestrial-aquatic interfaces, with a focus on coastal and estuarine ecosystems. We synthesize relevant plant traits and environmental controls on vegetation that influence carbon cycling in coastal ecosystems. We propose that models include separate plant functional types (PFTs) for mangroves, graminoid salt marshes, and succulent salt marshes to adequately represent the variation in aboveground and belowground productivity between common coastal wetland vegetation types. We also discuss the drivers and carbon storage consequences of shifts in dominant PFTs. We suggest several potential approaches to represent the diversity in vegetation tolerance and adaptations to fluctuations in salinity and water level, which drive key gradients in coastal wetland ecosystems. Finally, we discuss data needs for parameterizing and evaluating model implementations of coastal wetland vegetation types and function.
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Affiliation(s)
- Sophia LaFond-Hudson
- Environmental Sciences Division, Oak Ridge National Laboratory, 1 Bethel Valley Rd, Oak Ridge, TN, 37917, USA
| | - Benjamin Sulman
- Environmental Sciences Division, Oak Ridge National Laboratory, 1 Bethel Valley Rd, Oak Ridge, TN, 37917, USA
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14
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Famiglietti CA, Worden M, Quetin GR, Smallman TL, Dayal U, Bloom AA, Williams M, Konings AG. Global net biome CO 2 exchange predicted comparably well using parameter-environment relationships and plant functional types. GLOBAL CHANGE BIOLOGY 2023; 29:2256-2273. [PMID: 36560840 DOI: 10.1111/gcb.16574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 12/13/2022] [Indexed: 05/28/2023]
Abstract
Accurate estimation and forecasts of net biome CO2 exchange (NBE) are vital for understanding the role of terrestrial ecosystems in a changing climate. Prior efforts to improve NBE predictions have predominantly focused on increasing models' structural realism (and thus complexity), but parametric error and uncertainty are also key determinants of model skill. Here, we investigate how different parameterization assumptions propagate into NBE prediction errors across the globe, pitting the traditional plant functional type (PFT)-based approach against a novel top-down, machine learning-based "environmental filtering" (EF) approach. To do so, we simulate these contrasting methods for parameter assignment within a flexible model-data fusion framework of the terrestrial carbon cycle (CARDAMOM) at a global scale. In the PFT-based approach, model parameters from a small number of select locations are applied uniformly within regions sharing similar land cover characteristics. In the EF-based approach, a pixel's parameters are predicted based on underlying relationships with climate, soil, and canopy properties. To isolate the role of parametric from structural uncertainty in our analysis, we benchmark the resulting PFT-based and EF-based NBE predictions with estimates from CARDAMOM's Bayesian optimization approach (whereby "true" parameters consistent with a suite of data constraints are retrieved on a pixel-by-pixel basis). When considering the mean absolute error of NBE predictions across time, we find that the EF-based approach matches or outperforms the PFT-based approach at 55% of pixels-a narrow majority. However, NBE estimates from the EF-based approach are susceptible to compensation between errors in component flux predictions and predicted parameters can align poorly with the assumed "true" values. Overall, though, the EF-based approach is comparable to conventional approaches and merits further investigation to better understand and resolve these limitations. This work provides insight into the relationship between terrestrial biosphere model performance and parametric uncertainty, informing efforts to improve model parameterization via PFT-free and trait-based approaches.
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Affiliation(s)
| | - Matthew Worden
- Department of Earth System Science, Stanford University, Stanford, California, USA
| | - Gregory R Quetin
- Department of Geography, University of California at Santa Barbara, Santa Barbara, California, USA
| | - T Luke Smallman
- School of GeoSciences and National Centre for Earth Observation, University of Edinburgh, Edinburgh, UK
| | - Uma Dayal
- Department of Earth System Science, Stanford University, Stanford, California, USA
| | - A Anthony Bloom
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - Mathew Williams
- School of GeoSciences and National Centre for Earth Observation, University of Edinburgh, Edinburgh, UK
| | - Alexandra G Konings
- Department of Earth System Science, Stanford University, Stanford, California, USA
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15
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Martin MR, Kumar P, Sonnentag O, Marsh P. Thermodynamic basis for the demarcation of Arctic and alpine treelines. Sci Rep 2022; 12:12565. [PMID: 35869102 PMCID: PMC9307831 DOI: 10.1038/s41598-022-16462-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 07/11/2022] [Indexed: 11/09/2022] Open
Abstract
AbstractAt the edge of alpine and Arctic ecosystems all over the world, a transition zone exists beyond which it is either infeasible or unfavorable for trees to exist, colloquially identified as the treeline. We explore the possibility of a thermodynamic basis behind this demarcation in vegetation by considering ecosystems as open systems driven by thermodynamic advantage—defined by vegetation’s ability to dissipate heat from the earth’s surface to the air above the canopy. To deduce whether forests would be more thermodynamically advantageous than existing ecosystems beyond treelines, we construct and examine counterfactual scenarios in which trees exist beyond a treeline instead of the existing alpine meadow or Arctic tundra. Meteorological data from the Italian Alps, United States Rocky Mountains, and Western Canadian Taiga-Tundra are used as forcing for model computation of ecosystem work and temperature gradients at sites on both sides of each treeline with and without trees. Model results indicate that the alpine sites do not support trees beyond the treeline, as their presence would result in excessive CO$$_2$$
2
loss and extended periods of snowpack due to temperature inversions (i.e., positive temperature gradient from the earth surface to the atmosphere). Further, both Arctic and alpine sites exhibit negative work resulting in positive feedback between vegetation heat dissipation and temperature gradient, thereby extending the duration of temperature inversions. These conditions demonstrate thermodynamic infeasibility associated with the counterfactual scenario of trees existing beyond a treeline. Thus, we conclude that, in addition to resource constraints, a treeline is an outcome of an ecosystem’s ability to self-organize towards the most advantageous vegetation structure facilitated by thermodynamic feasibility.
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López-Blanco E, Langen PL, Williams M, Christensen JH, Boberg F, Langley K, Christensen TR. The future of tundra carbon storage in Greenland - Sensitivity to climate and plant trait changes. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 846:157385. [PMID: 35870583 DOI: 10.1016/j.scitotenv.2022.157385] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 07/02/2022] [Accepted: 07/11/2022] [Indexed: 06/15/2023]
Abstract
The continuous change in observed key indicators such as increasing nitrogen deposition, temperatures and precipitation will have marked but uncertain consequences for the ecosystem carbon (C) sink-source functioning of the Arctic. Here, we use multiple in-situ data streams measured by the Greenland Ecosystem Monitoring programme in tight connection with the Soil-Plant-Atmosphere model and climate projections from the high-resolution HIRHAM5 regional model. We apply this modelling framework with focus on two climatically different tundra sites in Greenland (Zackenberg and Kobbefjord) to assess how sensitive the net C uptake will expectedly be under warmer and wetter conditions across the 21st century and pin down the relative contribution to the overall C sink strength from climate versus plant trait variability. Our results suggest that temperatures (5-7.7 °C), total precipitation (19-110 %) and vapour pressure deficit will increase (32-36 %), while shortwave radiation will decline (6-9 %) at both sites by 2100 under the RCP8.5 scenario. Such a combined effect will, on average, intensify the net C uptake by 9-10 g C m-2 year-1 at both sites towards the end of 2100, but Zackenberg is expected to have more than twice the C sink strength capacity of Kobbefjord. Our sensitivity analysis not only reveals that plant traits are the most sensitive parameters controlling the net C exchange in both sites at the beginning and end of the century, but also that the projected increase in the net C uptake will likely be similarly influenced by future changes in climate and existing local nutrient conditions. A series of experiments forcing realistic changes in plant nitrogen status at both sites corroborates this hypothesis. This work proves the unique synergy between monitoring data and numerical models to assist robust model calibration/validation and narrow uncertainty ranges and ultimately produce more reliable C cycle projections in understudied regions such as Greenland.
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Affiliation(s)
- Efrén López-Blanco
- Department of Environment and Minerals, Greenland Institute of Natural Resources, Kivioq 2, PO Box 570, 3900 Nuuk, Greenland; Department of Ecoscience, Arctic Research Center, Aarhus University, Frederiksborgvej 399, 4000 Roskilde, Denmark.
| | - Peter L Langen
- Department of Environmental Sciences, iClimate, Aarhus University, Frederiksborgvej 399, 4000 Roskilde, Denmark
| | - Mathew Williams
- School of GeoSciences and NCEO, University of Edinburgh, Alexander Crum Brown Road, EH9 3FF Edinburgh, UK
| | - Jens Hesselbjerg Christensen
- Niels Bohr Institute, Copenhagen University, Tagensvej 16, 2200 Copenhagen, Denmark; Danish Meteorological Institute, Lyngbyvej 100, 2100 Copenhagen, Denmark; NORCE, Norwegian Research Centre AS, Bjerknes Centre for Climate Research, P.O.B 22 Nygårdstangen, 5838 Bergen, Norway
| | - Fredrik Boberg
- Danish Meteorological Institute, Lyngbyvej 100, 2100 Copenhagen, Denmark
| | - Kirsty Langley
- Asiaq, Greenland Survey, Qatserisut 8, 3900 Nuuk, Greenland
| | - Torben Røjle Christensen
- Department of Ecoscience, Arctic Research Center, Aarhus University, Frederiksborgvej 399, 4000 Roskilde, Denmark; Oulanka Research Station, Oulu University, PO Box 8000, 90014, Finland
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17
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Oehri J, Schaepman-Strub G, Kim JS, Grysko R, Kropp H, Grünberg I, Zemlianskii V, Sonnentag O, Euskirchen ES, Reji Chacko M, Muscari G, Blanken PD, Dean JF, di Sarra A, Harding RJ, Sobota I, Kutzbach L, Plekhanova E, Riihelä A, Boike J, Miller NB, Beringer J, López-Blanco E, Stoy PC, Sullivan RC, Kejna M, Parmentier FJW, Gamon JA, Mastepanov M, Wille C, Jackowicz-Korczynski M, Karger DN, Quinton WL, Putkonen J, van As D, Christensen TR, Hakuba MZ, Stone RS, Metzger S, Vandecrux B, Frost GV, Wild M, Hansen B, Meloni D, Domine F, Te Beest M, Sachs T, Kalhori A, Rocha AV, Williamson SN, Morris S, Atchley AL, Essery R, Runkle BRK, Holl D, Riihimaki LD, Iwata H, Schuur EAG, Cox CJ, Grachev AA, McFadden JP, Fausto RS, Göckede M, Ueyama M, Pirk N, de Boer G, Bret-Harte MS, Leppäranta M, Steffen K, Friborg T, Ohmura A, Edgar CW, Olofsson J, Chambers SD. Vegetation type is an important predictor of the arctic summer land surface energy budget. Nat Commun 2022; 13:6379. [PMID: 36316310 PMCID: PMC9622844 DOI: 10.1038/s41467-022-34049-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 10/11/2022] [Indexed: 11/05/2022] Open
Abstract
Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm-2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.
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Affiliation(s)
- Jacqueline Oehri
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.
- Department of Biology, McGill University, 1205 Docteur Penfield, H3A 1B1, Montreal, QC, Canada.
| | - Gabriela Schaepman-Strub
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.
| | - Jin-Soo Kim
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland
- Low-Carbon and Climate Impact Research Centre, School of Energy and Environment, City University of Hong Kong, Tat Chee Ave, Kowloon Tong, Hongkong, People's Republic of China
| | - Raleigh Grysko
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland
| | - Heather Kropp
- Environmental Studies Program, Hamilton College, 198 College Hill Rd, Clinton, NY, USA
| | - Inge Grünberg
- Permafrost Research Section, Alfred-Wegener Institute, Telegrafenberg, 14473, Potsdam, Germany
| | - Vitalii Zemlianskii
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland
| | - Oliver Sonnentag
- Département de géographie, Université de Montréal, 2900 Edouard Montpetit Blvd, Montreal, QC, H3T 1J4, Canada
| | - Eugénie S Euskirchen
- Institute of Arctic Biology, University of Alaska Fairbanks, 2140 Koyukuk Dr, Fairbanks, AK, USA
| | - Merin Reji Chacko
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland
- Institute of Terrestrial Ecosystems, ETH Zurich, CHN, Universitätstrasse 16, 8006, Zurich, Switzerland
- Land Change Science Unit, Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Zürcherstrasse 111, 8903, Birmensdorf, ZH, Switzerland
| | - Giovanni Muscari
- Istituto Nazionale di Geofisica e Vulcanologia, Via di Vigna Murata, 605, Rome, Italy
| | - Peter D Blanken
- Department of Geography, University of Colorado, Boulder, CO, USA
| | - Joshua F Dean
- School of Geographical Sciences, University of Bristol, University Rd, Bristol, UK
| | - Alcide di Sarra
- Department for Sustainability, ENEA, Via Enrico Fermi 45, Frascati, Italy
| | - Richard J Harding
- UK Centre for Ecology & Hydrology (UKCEH), MacLean Bldg, Benson Ln, Crowmarsh Gifford, Wallingford, UK
| | - Ireneusz Sobota
- Department of Hydrology and Water Management, Faculty of Earth Sciences and Spatial Management, Nicolaus Copernicus University, Lwowska, 87-100, Toruń, Poland
| | - Lars Kutzbach
- Center for Earth System Research and Sustainability (CEN), University of Hamburg, Bundesstrasse 53, 20146, Hamburg, Germany
| | - Elena Plekhanova
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland
| | - Aku Riihelä
- Finnish Meteorological Institute, Erik Palménin aukio 1, 00560, Helsinki, Finland
| | - Julia Boike
- Permafrost Research Section, Alfred-Wegener Institute, Telegrafenberg, 14473, Potsdam, Germany
- Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10117, Berlin, Germany
| | | | - Jason Beringer
- School of Agriculture and Environment, The University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009, WA, Australia
| | - Efrén López-Blanco
- Department of Environment and Minerals, Greenland Institute of Natural Resources, Kivioq 2, Nuuk, 3900, Greenland
- Department of Ecoscience, Aarhus University, Nordre Ringgade 1, 8000, Aarhus C, Denmark
| | - Paul C Stoy
- University of Wisconsin-Madison, Madison, WI, USA
| | - Ryan C Sullivan
- Environmental Science Division, Argonne National Laboratory, 9700 S Cass Ave, Lemont, IL, USA
| | - Marek Kejna
- Department of Meteorology and Climatology, Faculty of Earth Sciences and Spatial Management, Nicolaus Copernicus University, Lwowska, 87-100, Toruń, Poland
| | - Frans-Jan W Parmentier
- Center for Biogeochemistry of the Anthropocene, Department of Geosciences, University of Oslo, Sem Sælands vei 1, 0371, Oslo, Norway
- Department of Physical Geography and Ecosystem Science, Lund University, Geocentrum II, Sölvegatan 12, 223 62, Lund, Sweden
| | - John A Gamon
- University of Nebraska - Lincoln, 1400 R St, Lincoln, NE, USA
| | - Mikhail Mastepanov
- Department of Ecoscience, Aarhus University, Nordre Ringgade 1, 8000, Aarhus C, Denmark
- Oulanka Research Station, University of Oulu, Pentti Kaiteran katu 1, 90570, Oulu, Finland
| | - Christian Wille
- GFZ German Research Centre for Geosciences, Wissenschaftspark Albert Einstein, Telegrafenberg, 14473, Potsdam, Germany
| | - Marcin Jackowicz-Korczynski
- Department of Ecoscience, Aarhus University, Nordre Ringgade 1, 8000, Aarhus C, Denmark
- Department of Physical Geography and Ecosystem Science, Lund University, Geocentrum II, Sölvegatan 12, 223 62, Lund, Sweden
| | - Dirk N Karger
- Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), Zürcherstrasse 111, 8903, Birmensdorf, ZH, Switzerland
| | - William L Quinton
- Cold Regions Research Centre, Wilfrid Laurier University, 75 University Ave W, Waterloo, ON, Canada
| | - Jaakko Putkonen
- Harold Hamm School of Geology and Geological Engineering, University of North Dakota, Grand Forks, ND, USA
| | - Dirk van As
- Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Øster Voldgade 10, 1350, Copenhagen, Denmark
| | - Torben R Christensen
- Department of Ecoscience, Aarhus University, Nordre Ringgade 1, 8000, Aarhus C, Denmark
- Oulanka Research Station, University of Oulu, Pentti Kaiteran katu 1, 90570, Oulu, Finland
| | - Maria Z Hakuba
- Jet Propulsion Laboratory, CalTech, 4800, Oak Grove Dr, Pasadena, CA, USA
| | - Robert S Stone
- NOAA Global Monitoring Laboratory, 325 Broadway, Boulder, CO, USA
| | - Stefan Metzger
- National Ecological Observatory Network, Battelle, 1685 38th St #100, Boulder, CO, USA
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, 1225 W Dayton St, Madison, WI, USA
| | - Baptiste Vandecrux
- Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Øster Voldgade 10, 1350, Copenhagen, Denmark
| | - Gerald V Frost
- Alaska Biological Research, Inc, 2842, Goldstream Rd, Fairbanks, AK, USA
| | - Martin Wild
- Institute for Atmospheric and Climate Science, ETH Zurich, CHN, Universitätstrasse 16, 8006, Zurich, Switzerland
| | - Birger Hansen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Rolighedsvej 23, 1958, Frederiksberg, Denmark
| | - Daniela Meloni
- Department for Sustainability, ENEA, Lungotevere Grande Ammiraglio Thaon di Revel, 76, Rome, Italy
| | - Florent Domine
- Department of Chemistry, Université Laval, Pavillon Alexandre-Vachon, 1045 Av. de la Médecine, G1V 0A6, Québec, QC, Canada
- Takuvik Laboratory, CNRS-INSU, Département de Biologie, Université Laval, Pavillon Alexandre-Vachon, 1045 Av. de la Médecine, G1V 0A6, Québec, QC, Canada
| | - Mariska Te Beest
- Copernicus Institute of Sustainable Development, Utrecht University, Vening Meinesz Building, Princetonlaan 8a, 3584 CB, Utrecht, The Netherlands
- Centre for African Conservation Ecology, Nelson Mandela University, University Way, Summerstrand, Gqeberha, 6019, Port Elizabeth, South Africa
| | - Torsten Sachs
- GFZ German Research Centre for Geosciences, Wissenschaftspark Albert Einstein, Telegrafenberg, 14473, Potsdam, Germany
| | - Aram Kalhori
- GFZ German Research Centre for Geosciences, Wissenschaftspark Albert Einstein, Telegrafenberg, 14473, Potsdam, Germany
| | - Adrian V Rocha
- Department of Biological Sciences, University of Notre Dame, 100 Galvin Life Sciences, Notre Dame, IN, USA
| | - Scott N Williamson
- Polar Knowledge Canada, Canadian High Arctic Research Station, 1 rue Uvajuq place, CP 2150, Cambridge Bay, NU, Canada
| | - Sara Morris
- NOAA Physical Sciences Laboratory, 325 Broadway, Boulder, CO, USA
| | - Adam L Atchley
- Los Alamos National Laboratory, Bikini Atoll Rd., SM 30, Los Alamos, NM, USA
| | - Richard Essery
- School of Geosciences, University of Edinburgh, Drummond St, Edinburgh, EH8 9XP, UK
| | - Benjamin R K Runkle
- Department of Biological & Agricultural Engineering, University of Arkansas, 1164 W Maple St, Fayetteville, AR, USA
| | - David Holl
- Center for Earth System Research and Sustainability (CEN), University of Hamburg, Bundesstrasse 53, 20146, Hamburg, Germany
| | - Laura D Riihimaki
- NOAA Global Monitoring Laboratory, 325 Broadway, Boulder, CO, USA
- CIRES (Cooperative Institute for Research in Environmental Sciences), 216 UCB, University of Colorado Boulder Campus, Boulder, CO, USA
| | - Hiroki Iwata
- Department of Environmental Science, Shinshu University, 3 Chome-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan
| | - Edward A G Schuur
- Center for Ecosystem Science and Society, Northern Arizona University, S San Francisco St, Flagstaff, AZ, USA
| | | | - Andrey A Grachev
- DEVCOM Army Research Laboratory, Owen Rd, White Sands Missile Range, New Mexico, NM, USA
| | - Joseph P McFadden
- Department of Geography and Earth Research Institute, University of California Santa Barbara, 5816, Ellison Hall, Isla Vista, CA, USA
| | - Robert S Fausto
- Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Øster Voldgade 10, 1350, Copenhagen, Denmark
| | - Mathias Göckede
- Department of Biogeochemical Signals, Max Planck Institute for Biogeochemistry, Hans-Knöll-Straße 10, 07745, Jena, Germany
| | - Masahito Ueyama
- Osaka Metropolitan University, Sakai, Kita Ward, Umeda, 1 Chome-2 - 2-600, Osaka, Japan
| | - Norbert Pirk
- Department of Geosciences, University of Oslo, Sem Sælands vei 1, 0371, Oslo, Norway
| | - Gijs de Boer
- NOAA Physical Sciences Laboratory, 325 Broadway, Boulder, CO, USA
- CIRES (Cooperative Institute for Research in Environmental Sciences), 216 UCB, University of Colorado Boulder Campus, Boulder, CO, USA
- IRISS (Integrated Remote and In Situ Sensing), University of Colorado, Boulder, CO, USA
| | - M Syndonia Bret-Harte
- Institute of Arctic Biology, University of Alaska Fairbanks, 2140 Koyukuk Dr, Fairbanks, AK, USA
| | - Matti Leppäranta
- University of Helsinki, Yliopistonkatu 4, 00100, Helsinki, Finland
| | - Konrad Steffen
- Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), Zürcherstrasse 111, 8903, Birmensdorf, ZH, Switzerland
| | - Thomas Friborg
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Rolighedsvej 23, 1958, Frederiksberg, Denmark
| | - Atsumu Ohmura
- Institute for Atmospheric and Climate Science, ETH Zurich, CHN, Universitätstrasse 16, 8006, Zurich, Switzerland
| | - Colin W Edgar
- Institute of Arctic Biology, University of Alaska Fairbanks, 2140 Koyukuk Dr, Fairbanks, AK, USA
| | - Johan Olofsson
- Department of Ecology and Environmental Science, Umeå University, Linnaeus väg 4-6, 907 36, Umeå, Sweden
| | - Scott D Chambers
- ANSTO Lucas Heights, New Illawarra Rd, Lucas Heights NSW, 2234, Sydney, NSW, Australia
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18
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Braghiere RK, Fisher JB, Allen K, Brzostek E, Shi M, Yang X, Ricciuto DM, Fisher RA, Zhu Q, Phillips RP. Modeling Global Carbon Costs of Plant Nitrogen and Phosphorus Acquisition. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 2022; 14:e2022MS003204. [PMID: 36245670 PMCID: PMC9539603 DOI: 10.1029/2022ms003204] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/02/2022] [Accepted: 08/06/2022] [Indexed: 06/16/2023]
Abstract
Most Earth system models (ESMs) do not explicitly represent the carbon (C) costs of plant nutrient acquisition, which leads to uncertainty in predictions of the current and future constraints to the land C sink. We integrate a plant productivity-optimizing nitrogen (N) and phosphorus (P) acquisition model (fixation & uptake of nutrients, FUN) into the energy exascale Earth system (E3SM) land model (ELM). Global plant N and P uptake are dynamically simulated by ELM-FUN based on the C costs of nutrient acquisition from mycorrhizae, direct root uptake, retranslocation from senescing leaves, and biological N fixation. We benchmarked ELM-FUN with three classes of products: ILAMB, a remotely sensed nutrient limitation product, and CMIP6 models; we found significant improvements in C cycle variables, although the lack of more observed nutrient data prevents a comprehensive level of benchmarking. Overall, we found N and P co-limitation for 80% of land area, with the remaining 20% being either predominantly N or P limited. Globally, the new model predicts that plants invested 4.1 Pg C yr-1 to acquire 841.8 Tg N yr-1 and 48.1 Tg P yr-1 (1994-2005), leading to significant downregulation of global net primary production (NPP). Global NPP is reduced by 20% with C costs of N and 50% with C costs of NP. Modeled and observed nutrient limitation agreement increases when N and P are considered together (r 2 from 0.73 to 0.83).
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Affiliation(s)
- R. K. Braghiere
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
- Joint Institute for Regional Earth System Science and EngineeringUniversity of California Los AngelesLos AngelesCAUSA
- Division of Geological and Planetary SciencesCalifornia Institute of TechnologyPasadenaCAUSA
| | - J. B. Fisher
- Schmid College of Science and TechnologyChapman UniversityOrangeCAUSA
| | - K. Allen
- Manaaki Whenua—Landcare ResearchLincolnNew Zealand
| | - E. Brzostek
- Department of BiologyWest Virginia UniversityMorgantownWVUSA
| | - M. Shi
- Pacific Northwest National LaboratoryRichlandWAUSA
| | - X. Yang
- Environmental Sciences Division and Climate Change Science InstituteOak Ridge National LaboratoryOak RidgeTNUSA
| | - D. M. Ricciuto
- Environmental Sciences Division and Climate Change Science InstituteOak Ridge National LaboratoryOak RidgeTNUSA
| | - R. A. Fisher
- Center for International Climate ResearchOsloNorway
- Laboratoire Évolution & Diversité BiologiqueCNRS:UMRUniversité Paul SabatierToulouseFrance
| | - Q. Zhu
- Climate and Ecosystem Sciences DivisionClimate Sciences DepartmentLawrence Berkeley National LaboratoryBerkeleyCAUSA
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19
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Holopainen E, Kokkola H, Faiola C, Laakso A, Kühn T. Insect Herbivory Caused Plant Stress Emissions Increases the Negative Radiative Forcing of Aerosols. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2022; 127:e2022JD036733. [PMID: 36249538 PMCID: PMC9540253 DOI: 10.1029/2022jd036733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 06/10/2022] [Accepted: 06/22/2022] [Indexed: 06/16/2023]
Abstract
Plant stress in a changing climate is predicted to increase plant volatile organic compound (VOC) emissions and thus can affect the formed secondary organic aerosol (SOA) concentrations, which in turn affect the radiative properties of clouds and aerosol. However, global aerosol-climate models do not usually consider plant stress induced VOCs in their emission schemes. In this study, we modified the monoterpene emission factors in biogenic emission model to simulate biotic stress caused by insect herbivory on needleleaf evergreen boreal and broadleaf deciduous boreal trees and studied the consequent effects on SOA formation, aerosol-cloud interactions as well as direct radiative effects of formed SOA. Simulations were done altering the fraction of stressed and healthy trees in the latest version of ECHAM-HAMMOZ (ECHAM6.3-HAM2.3-MOZ1.0) global aerosol-climate model. Our simulations showed that increasing the extent of stress to the aforementioned tree types, substantially increased the SOA burden especially over the areas where these trees are located. This indicates that increased VOC emissions due to increasing stress enhance the SOA formation via oxidation of VOCs to low VOCs. In addition, cloud droplet number concentration at the cloud top increased with increasing extent of biotic stress. This indicates that as SOA formation increases, it further enhances the number of particles acting as cloud condensation nuclei. The increase in SOA formation also decreased both all-sky and clear-sky radiative forcing. This was due to a shift in particle size distributions that enhanced aerosol reflecting and scattering of incoming solar radiation.
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Affiliation(s)
- E. Holopainen
- Atmospheric Research Centre of Eastern FinlandFinnish Meteorological InstituteKuopioFinland
- Aerosol Physics Research GroupUniversity of Eastern FinlandKuopioFinland
| | - H. Kokkola
- Atmospheric Research Centre of Eastern FinlandFinnish Meteorological InstituteKuopioFinland
| | - C. Faiola
- Department of Ecology and Evolutionary BiologyUniversity of California IrvineIrvineCAUSA
- Department of ChemistryUniversity of California IrvineIrvineCAUSA
| | - A. Laakso
- Atmospheric Research Centre of Eastern FinlandFinnish Meteorological InstituteKuopioFinland
| | - T. Kühn
- Atmospheric Research Centre of Eastern FinlandFinnish Meteorological InstituteKuopioFinland
- Aerosol Physics Research GroupUniversity of Eastern FinlandKuopioFinland
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20
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Morales-Sánchez JÁM, Mark K, Souza JPS, Niinemets Ü. Desiccation-rehydration measurements in bryophytes: current status and future insights. JOURNAL OF EXPERIMENTAL BOTANY 2022; 73:4338-4361. [PMID: 35536655 DOI: 10.1093/jxb/erac172] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 04/27/2022] [Indexed: 06/14/2023]
Abstract
Desiccation-rehydration experiments have been employed over the years to evaluate desiccation tolerance of bryophytes (Bryophyta, Marchantiophyta, and Anthocerotophyta). Researchers have applied a spectrum of protocols to induce desiccation and subsequent rehydration, and a wide variety of techniques have been used to study desiccation-dependent changes in bryophyte molecular, cellular, physiological, and structural traits, resulting in a multifaceted assortment of information that is challenging to synthesize. We analysed 337 desiccation-rehydration studies, providing information for 351 species, to identify the most frequent methods used, analyse the advances in desiccation studies over the years, and characterize the taxonomic representation of the species assessed. We observed certain similarities across methodologies, but the degree of convergence among the experimental protocols was surprisingly low. Out of 52 bryophyte orders, 40% have not been studied, and data are lacking for multiple remote or difficult to access locations. We conclude that for quantitative interspecific comparisons of desiccation tolerance, rigorous standardization of experimental protocols and measurement techniques, and simultaneous use of an array of experimental techniques are required for a mechanistic insight into the different traits modified in response to desiccation. New studies should also aim to fill gaps in taxonomic, ecological, and spatial coverage of bryophytes.
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Affiliation(s)
- José Ángel M Morales-Sánchez
- Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Fr. R. Kreutzwaldi 5, Tartu 51006, Estonia
| | - Kristiina Mark
- Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Fr. R. Kreutzwaldi 5, Tartu 51006, Estonia
| | - João Paulo S Souza
- Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Fr. R. Kreutzwaldi 5, Tartu 51006, Estonia
| | - Ülo Niinemets
- Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Fr. R. Kreutzwaldi 5, Tartu 51006, Estonia
- Estonian Academy of Sciences, Kohtu 6, Tallinn 10130, Estonia
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21
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Beigaitė R, Tang H, Bryn A, Skarpaas O, Stordal F, Bjerke JW, Žliobaitė I. Identifying climate thresholds for dominant natural vegetation types at the global scale using machine learning: Average climate versus extremes. GLOBAL CHANGE BIOLOGY 2022; 28:3557-3579. [PMID: 35212092 PMCID: PMC9302987 DOI: 10.1111/gcb.16110] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 01/13/2022] [Indexed: 05/08/2023]
Abstract
The global distribution of vegetation is largely determined by climatic conditions and feeds back into the climate system. To predict future vegetation changes in response to climate change, it is crucial to identify and understand key patterns and processes that couple vegetation and climate. Dynamic global vegetation models (DGVMs) have been widely applied to describe the distribution of vegetation types and their future dynamics in response to climate change. As a process-based approach, it partly relies on hard-coded climate thresholds to constrain the distribution of vegetation. What thresholds to implement in DGVMs and how to replace them with more process-based descriptions remain among the major challenges. In this study, we employ machine learning using decision trees to extract large-scale relationships between the global distribution of vegetation and climatic characteristics from remotely sensed vegetation and climate data. We analyse how the dominant vegetation types are linked to climate extremes as compared to seasonally or annually averaged climatic conditions. The results show that climate extremes allow us to describe the distribution and eco-climatological space of the vegetation types more accurately than the averaged climate variables, especially those types which occupy small territories in a relatively homogeneous ecological space. Future predicted vegetation changes using both climate extremes and averaged climate variables are less prominent than that predicted by averaged climate variables and are in better agreement with those of DGVMs, further indicating the importance of climate extremes in determining geographic distributions of different vegetation types. We found that the temperature thresholds for vegetation types (e.g. grass and open shrubland) in cold environments vary with moisture conditions. The coldest daily maximum temperature (extreme cold day) is particularly important for separating many different vegetation types. These findings highlight the need for a more explicit representation of the impacts of climate extremes on vegetation in DGVMs.
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Affiliation(s)
- Rita Beigaitė
- Department of Computer ScienceUniversity of HelsinkiHelsinkiFinland
| | - Hui Tang
- Natural History MuseumUniversity of OsloOsloNorway
- Department of GeosciencesUniversity of OsloOsloNorway
| | - Anders Bryn
- Natural History MuseumUniversity of OsloOsloNorway
| | | | - Frode Stordal
- Department of GeosciencesUniversity of OsloOsloNorway
| | - Jarle W. Bjerke
- Norwegian Institute for Nature ResearchFRAM – High North Research Centre for Climate and the EnvironmentTromsøNorway
| | - Indrė Žliobaitė
- Department of Computer ScienceUniversity of HelsinkiHelsinkiFinland
- Finnish Museum of Natural HistoryUniversity of HelsinkiHelsinkiFinland
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22
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Variability in frost occurrence under climate change and consequent risk of damage to trees of western Quebec, Canada. Sci Rep 2022; 12:7220. [PMID: 35508611 PMCID: PMC9068889 DOI: 10.1038/s41598-022-11105-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 04/08/2022] [Indexed: 12/02/2022] Open
Abstract
Climate change affects timings, frequency, and intensity of frost events in northern ecosystems. However, our understanding of the impacts that frost will have on growth and survival of plants is still limited. When projecting the occurrence of frost, the internal variability and the different underlying physical formulations are two major sources of uncertainty of climate models. We use 50 climate simulations produced by a single-initial large climate ensemble and five climate simulations produced by different pairs of global and regional climate models based on the concentration pathway (RCP 8.5) over a latitudinal transect covering the temperate and boreal ecosystems of western Quebec, Canada, during 1955–2099 to provide a first-order estimate of the relative importance of these two sources of uncertainty on the occurrence of frost, i.e. when air temperature is < 0 °C, and their potential damage to trees. The variation in the date of the last spring frost was larger by 21 days (from 46 to 25 days) for the 50 climate simulations compared to the 5 different pairs of climate models. When considering these two sources of uncertainty in an eco-physiological model simulating the timings of budbreak for trees of northern environment, results show that 20% of climate simulations expect that trees will be exposed to frost even in 2090. Thus, frost damage to trees remains likely under global warming.
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23
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Lemmer M, Xu B, Strack M, Rochefort L. Reestablishment of peatland vegetation following surface levelling of decommissioned in situ oil mining infrastructures. Restor Ecol 2022. [DOI: 10.1111/rec.13714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Meike Lemmer
- Centre for Northern Studies and Centre de recherche et d'innovation des végétaux Université Laval, Département de phytologie, Pavillon Envirotron, 2480 Boulevard Hochelaga Québec G1V 0A6 QC Canada
| | - Bin Xu
- Northern Alberta Institute for Technology, Centre for Boreal Research, 8102 99 Avenue Peace River T8S 1R2 AB Canada
| | - Maria Strack
- Department of Geography and Environmental Management University of Waterloo, 200 University Avenue West, Environment 1, room 115 Waterloo N2L 3G1 ON Canada
| | - Line Rochefort
- Centre for Northern Studies and Centre de recherche et d'innovation des végétaux Université Laval, Département de phytologie, Pavillon Envirotron, 2480 Boulevard Hochelaga Québec G1V 0A6 QC Canada
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24
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Estimation of Global Cropland Gross Primary Production from Satellite Observations by Integrating Water Availability Variable in Light-Use-Efficiency Model. REMOTE SENSING 2022. [DOI: 10.3390/rs14071722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Satellite-based models have been widely used to estimate gross primary production (GPP) of terrestrial ecosystems. Although they have many advantages for mapping spatiotemporal variations of regional or global GPP, the performance in agroecosystems is relatively poor. In this study, a light-use-efficiency model for cropland GPP estimation, named EF-LUE, driven by remote sensing data, was developed by integrating evaporative fraction (EF) as limiting factor accounting for soil water availability. Model parameters were optimized first using CO2 flux measurements by eddy covariance system from flux tower sites, and the optimized parameters were further spatially extrapolated according to climate zones for global cropland GPP estimation in 2001–2019. The major forcing datasets include the fraction of absorbed photosynthetically active radiation (FAPAR) data from the Copernicus Global Land Service System (CGLS) GEOV2 dataset, EF from the ETMonitor model, and meteorological forcing variables from ERA5 data. The EF-LUE model was first evaluated at flux tower site-level, and the results suggested that the proposed EF-LUE model and the LUE model without using water availability limiting factor, both driven by flux tower meteorology data, explained 82% and 74% of the temporal variations of GPP across crop sites, respectively. The overall KGE increased from 0.73 to 0.83, NSE increased from 0.73 to 0.81, and RMSE decreased from 2.87 to 2.39 g C m−2 d−1 in the estimated GPP after integrating EF in the LUE model. These improvements may be largely attributed to parameters optimized for different climatic zones and incorporating water availability limiting factor expressed by EF into the light-use-efficiency model. At global scale, the verification by GPP measurements from cropland flux tower sites showed that GPP estimated by the EF-LUE model driven by ERA5 reanalysis meteorological data and EF from ETMonitor had overall the highest R2, KGE, and NSE and the smallest RMSE over the four existing GPP datasets (MOD17 GPP, revised EC-LUE GPP, GOSIF GPP and PML-V2 GPP). The global GPP from the EF-LUE model could capture the significant negative GPP anomalies during drought or heat-wave events, indicating its ability to express the impacts of the water stress on cropland GPP.
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25
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Wan J, Crowther TW. Uniting the scales of microbial biogeochemistry with trait‐based modeling. Funct Ecol 2022. [DOI: 10.1111/1365-2435.14035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Affiliation(s)
- Joe Wan
- Institute of Integrative Biology ETH Zürich Zürich Switzerland
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26
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Rogers A, Serbin SP, Way DA. Reducing model uncertainty of climate change impacts on high latitude carbon assimilation. GLOBAL CHANGE BIOLOGY 2022; 28:1222-1247. [PMID: 34689389 DOI: 10.1111/gcb.15958] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 09/17/2021] [Indexed: 06/13/2023]
Abstract
The Arctic-Boreal Region (ABR) has a large impact on global vegetation-atmosphere interactions and is experiencing markedly greater warming than the rest of the planet, a trend that is projected to continue with anticipated future emissions of CO2 . The ABR is a significant source of uncertainty in estimates of carbon uptake in terrestrial biosphere models such that reducing this uncertainty is critical for more accurately estimating global carbon cycling and understanding the response of the region to global change. Process representation and parameterization associated with gross primary productivity (GPP) drives a large amount of this model uncertainty, particularly within the next 50 years, where the response of existing vegetation to climate change will dominate estimates of GPP for the region. Here we review our current understanding and model representation of GPP in northern latitudes, focusing on vegetation composition, phenology, and physiology, and consider how climate change alters these three components. We highlight challenges in the ABR for predicting GPP, but also focus on the unique opportunities for advancing knowledge and model representation, particularly through the combination of remote sensing and traditional boots-on-the-ground science.
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Affiliation(s)
- Alistair Rogers
- Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, New York, USA
| | - Shawn P Serbin
- Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, New York, USA
| | - Danielle A Way
- Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, New York, USA
- Department of Biology, University of Western Ontario, London, Ontario, Canada
- Nicholas School of the Environment, Duke University, Durham, North Carolina, USA
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27
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Relative Importance of Landscape and Climate Factors to the Species Diversity of Plant Growth Forms along an East Asian Archipelago. FORESTS 2022. [DOI: 10.3390/f13020218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Previous studies on island biogeography theory have limitations in that they are mostly focused on total plant species and the landscape factors of the islands. Our study was conducted to overcome these limitations by dividing the plants into five growth forms and analyzing climate and landscape factors on inhabited islands, uninhabited islands, and overall. This was achieved using plant data from 578 islands of an archipelago in South Korea. To test the relationship between the species richness of each growth form and environmental factors, we performed ordinary least squares regressions and multi-model inference tests. The results showed that the island area had the largest influence on species richness of all growth forms in overall and uninhabited islands. Moreover, climate factors, in addition to island area, significantly affected species richness of all growth forms on inhabited islands. However, the effect and of isolation-related landscape factors (i.e., distance from the mainland and structural connectivity) were different among growth forms and island categories. Our study reveals that there are differences in the effects of environmental factors on the growth forms of plants among island categories. This suggests that biodiversity management and conservation strategies should be applied separately to different growth forms and islands.
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28
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The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model. REMOTE SENSING 2022. [DOI: 10.3390/rs14030437] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
This work tests the hypothesis that jointly assimilating satellite observations of leaf area index and surface soil moisture into a land surface model improves the estimation of land vegetation and water variables. An Ensemble Kalman Filter is used to test this hypothesis across the Contiguous United States from April 2015 to December 2018. The performance of the proposed methodology is assessed for several modeled vegetation and water variables (evapotranspiration, net ecosystem exchange, and soil moisture) in terms of random errors and anomaly correlation coefficients against a set of independent validation datasets (i.e., Global Land Evaporation Amsterdam Model, FLUXCOM, and International Soil Moisture Network). The results show that the assimilation of the leaf area index mostly improves the estimation of evapotranspiration and net ecosystem exchange, whereas the assimilation of surface soil moisture alone improves surface soil moisture content, especially in the western US, in terms of both root mean squared error and anomaly correlation coefficient. The joint assimilation of vegetation and soil moisture information combines the results of individual vegetation and soil moisture assimilations and reduces errors (and increases correlations with the reference datasets) in evapotranspiration, net ecosystem exchange, and surface soil moisture simulated by the land surface model. However, because soil moisture satellite observations only provide information on the water content in the top 5 cm of the soil column, the impact of the proposed data assimilation technique on root zone soil moisture is limited. This work moves one step forward in the direction of improving our estimation and understanding of land surface interactions using a multivariate data assimilation approach, which can be particularly useful in regions of the world where ground observations are sparse or missing altogether.
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29
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Qiu L, Yu M, Wu Y, Yao Y, Wang Z, Shi Z, Guan Y. Assessing and predicting soil carbon density in China using CMIP5 earth system models. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 799:149247. [PMID: 34358741 DOI: 10.1016/j.scitotenv.2021.149247] [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: 02/09/2021] [Revised: 05/18/2021] [Accepted: 07/21/2021] [Indexed: 06/13/2023]
Abstract
Soil carbon (SC) is a key component of the carbon cycle and plays an important role in climate change; however, quantitatively assessing SC dynamics at the regional scale remains challenging. Earth system model (ESM) that considers multiple environmental factors and spatial heterogeneity has become a powerful tool to explore carbon cycle-climate feedbacks, although the performance of the ESM is diverse and highly uncertain. Thus, identifying reliable ESMs is a prerequisite for better understanding the response of SC dynamics to human activity and climate change. The 16 ESMs that participated in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) were employed to evaluate the skill performance of SC density simulation by comparison with reference data from the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS). Although ESMs generally reflect spatial patterns with lower SC in northwest China and higher SC in southeast China, 11 of 16 ESMs underestimated the SC in China, and 5 of 16 ESMs overestimated the SC density as most ESMs had large discrepancies in capturing the SC density in the northern high latitudes of China and the Qinghai-Tibet Plateau. According to a series of model performance statistics, SC simulated by Institute Pierre Simon Laplace (IPSL) Coupled Model had a close spatial pattern with IGBP-DIS and showed higher skills for SC predictions in China relative to other CMIP5 ESMs. The multimodel ensemble average obtained by IPSL family ESMs showed that SC density exhibited increasing trends under both the RCP4.5 scenario and RCP8.5 scenario. The SC density increased slowly under RCP8.5 compared with that under RCP4.5 and even displayed a decreasing trend in the late 21st century. The findings of this study can provide a reference for identifying the shortcomings of SC predictions in China and guide SC parameterization improvement in ESMs.
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Affiliation(s)
- Linjing Qiu
- Department of Earth and Environmental Science, School of Human Settlements and Civil Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Mengzhen Yu
- Department of Earth and Environmental Science, School of Human Settlements and Civil Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Yiping Wu
- Department of Earth and Environmental Science, School of Human Settlements and Civil Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.
| | - Yingying Yao
- Department of Earth and Environmental Science, School of Human Settlements and Civil Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Zhaosheng Wang
- National Ecosystem Science Data Center, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhaoyang Shi
- Department of Earth and Environmental Science, School of Human Settlements and Civil Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Yinghui Guan
- School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
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30
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Vargas G G, Brodribb TJ, Dupuy JM, González-M R, Hulshof CM, Medvigy D, Allerton TAP, Pizano C, Salgado-Negret B, Schwartz NB, Van Bloem SJ, Waring BG, Powers JS. Beyond leaf habit: generalities in plant function across 97 tropical dry forest tree species. THE NEW PHYTOLOGIST 2021; 232:148-161. [PMID: 34171131 DOI: 10.1111/nph.17584] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 06/15/2021] [Indexed: 05/12/2023]
Abstract
Leaf habit has been hypothesized to define a linkage between the slow-fast plant economic spectrum and the drought resistance-avoidance trade-off in tropical forests ('slow-safe vs fast-risky'). However, variation in hydraulic traits as a function of leaf habit has rarely been explored for a large number of species. We sampled leaf and branch functional traits of 97 tropical dry forest tree species from four sites to investigate whether patterns of trait variation varied consistently in relation to leaf habit along the 'slow-safe vs fast-risky' trade-off. Leaf habit explained from 0% to 43.69% of individual trait variation. We found that evergreen and semi-deciduous species differed in their location along the multivariate trait ordination when compared to deciduous species. While deciduous species showed consistent trait values, evergreen species trait values varied as a function of the site. Last, trait values varied in relation to the proportion of deciduous species in the plant community. We found that leaf habit describes the strategies that define drought avoidance and plant economics in tropical trees. However, leaf habit alone does not explain patterns of trait variation, which suggests quantifying site-specific or species-specific uncertainty in trait variation as the way forward.
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Affiliation(s)
- German Vargas G
- Department of Plant and Microbial Biology, University of Minnesota, St Paul, MN, 55108, USA
| | - Tim J Brodribb
- School of Biological Sciences, University of Tasmania, Hobart, TAS, 7001, Australia
| | - Juan M Dupuy
- Centro de Investigación Científica de Yucatán, Unidad de Recursos Naturales, Calle 43 # 130 entre 32 y 34, Col. Chuburná de Hidalgo, Mérida, Yucatán, CP 97205, México
| | - Roy González-M
- Programa Ciencias de la Biodiversidad, Instituto de Investigación de Recursos Biológicos Alexander von Humboldt, Carrera #1 16-20, Bogotá, 111311, Colombia
| | - Catherine M Hulshof
- Department of Biology, Virginia Commonwealth University, Richmond, VA, 23284, USA
| | - David Medvigy
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Tristan A P Allerton
- Baruch Institute of Coastal Ecology and Forest Science, Clemson University, PO Box 596, Georgetown, SC, 29442, USA
| | - Camila Pizano
- Departamento de Biología, Universidad ICESI, Calle 18 # 122-135, Cali, 760031, Colombia
| | - Beatriz Salgado-Negret
- Departamento de Biología, Universidad Nacional de Colombia, sede Bogotá, Carrera 30 Calle 45, Bogotá, 111321, Colombia
| | - Naomi B Schwartz
- Department of Geography, University of British Columbia, Vancouver, BC, V6T 1Z2, Canada
| | - Skip J Van Bloem
- Baruch Institute of Coastal Ecology and Forest Science, Clemson University, PO Box 596, Georgetown, SC, 29442, USA
| | - Bonnie G Waring
- Department of Biology, Utah State University, Logan, UT, 84322, USA
| | - Jennifer S Powers
- Department of Plant and Microbial Biology, University of Minnesota, St Paul, MN, 55108, USA
- Department of Ecology, Evolution and Behavior, University of Minnesota, St Paul, MN, 55108, USA
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31
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Predicting Soil Respiration from Plant Productivity (NDVI) in a Sub-Arctic Tundra Ecosystem. REMOTE SENSING 2021. [DOI: 10.3390/rs13132571] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Soils represent the largest store of carbon in the biosphere with soils at high latitudes containing twice as much carbon (C) than the atmosphere. High latitude tundra vegetation communities show increases in the relative abundance and cover of deciduous shrubs which may influence net ecosystem exchange of CO2 from this C-rich ecosystem. Monitoring soil respiration (Rs) as a crucial component of the ecosystem carbon balance at regional scales is difficult given the remoteness of these ecosystems and the intensiveness of measurements that is required. Here we use direct measurements of Rs from contrasting tundra plant communities combined with direct measurements of aboveground plant productivity via Normalised Difference Vegetation Index (NDVI) to predict soil respiration across four key vegetation communities in a tundra ecosystem. Soil respiration exhibited a nonlinear relationship with NDVI (y = 0.202e3.508 x, p < 0.001). Our results further suggest that NDVI and soil temperature can help predict Rs if vegetation type is taken into consideration. We observed, however, that NDVI is not a relevant explanatory variable in the estimation of SOC in a single-study analysis.
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32
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Waring BG, De Guzman ME, Du DV, Dupuy JM, Gei M, Gutknecht J, Hulshof C, Jelinski N, Margenot AJ, Medvigy D, Pizano C, Salgado‐Negret B, Schwartz NB, Trierweiler AM, Van Bloem SJ, Vargas G. G, Powers JS. Soil biogeochemistry across Central and South American tropical dry forests. ECOL MONOGR 2021. [DOI: 10.1002/ecm.1453] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Affiliation(s)
- Bonnie G. Waring
- Department of Biology and Ecology Center Utah State University Logan Utah 84321 USA
| | - Mark E. De Guzman
- Ecology, Evolution and Behavior University of Minnesota St. Paul Minnesota 55108 USA
| | - Dan V. Du
- Department of Soil & Water Systems University of Idaho Moscow Idaho 83844 USA
| | - Juan M. Dupuy
- Unidad de Recursos Naturales Centro de Investigación Científica de Yucatán, A.C. (CICY) Calle 43 No. 130 x 32 y 34, Col. Chuburná de Hidalgo Mérida Yucatán C.P. 97205 México
| | - Maga Gei
- Ecology, Evolution and Behavior University of Minnesota St. Paul Minnesota 55108 USA
| | - Jessica Gutknecht
- Department of Soil, Water, and Climate University of Minnesota St. Paul Minnesota 55108 USA
| | - Catherine Hulshof
- Department of Biology Virginia Commonwealth University Richmond Virginia 23284 USA
| | - Nicolas Jelinski
- Department of Soil, Water, and Climate University of Minnesota St. Paul Minnesota 55108 USA
| | - Andrew J. Margenot
- Department of Crop Sciences University of Illinois Urbana‐Champaign Urbana Illinois 61801 USA
| | - David Medvigy
- Department of Biological Sciences University of Notre Dame Notre Dame Indiana 46556 USA
| | - Camila Pizano
- Departamento de Ciencias Biológicas Universidad Icesi Calle 18 # 122‐135 Cali Colombia
| | - Beatriz Salgado‐Negret
- Departamento de Biología Universidad Nacional de Colombia, sede Bogotá Carrera 30 Calle 45 Bogotá Colombia
| | - Naomi B. Schwartz
- Department of Geography University of British Columbia 1984 West Mall Vancouver British Columbia V6T 1Z2 Canada
| | | | - Skip J. Van Bloem
- Baruch Institute of Coastal Ecology and Forest Science Clemson University Georgetown South Carolina 29634 USA
| | - German Vargas G.
- Department of Plant and Microbial Biology University of Minnesota St. Paul Minnesota 55108 USA
| | - Jennifer S. Powers
- Ecology, Evolution and Behavior University of Minnesota St. Paul Minnesota 55108 USA
- Department of Plant and Microbial Biology University of Minnesota St. Paul Minnesota 55108 USA
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33
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Kemppinen J, Niittynen P, le Roux PC, Momberg M, Happonen K, Aalto J, Rautakoski H, Enquist BJ, Vandvik V, Halbritter AH, Maitner B, Luoto M. Consistent trait-environment relationships within and across tundra plant communities. Nat Ecol Evol 2021; 5:458-467. [PMID: 33633373 DOI: 10.1038/s41559-021-01396-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 01/19/2021] [Indexed: 01/31/2023]
Abstract
A fundamental assumption in trait-based ecology is that relationships between traits and environmental conditions are globally consistent. We use field-quantified microclimate and soil data to explore if trait-environment relationships are generalizable across plant communities and spatial scales. We collected data from 6,720 plots and 217 species across four distinct tundra regions from both hemispheres. We combined these data with over 76,000 database trait records to relate local plant community trait composition to broad gradients of key environmental drivers: soil moisture, soil temperature, soil pH and potential solar radiation. Results revealed strong, consistent trait-environment relationships across Arctic and Antarctic regions. This indicates that the detected relationships are transferable between tundra plant communities also when fine-scale environmental heterogeneity is accounted for, and that variation in local conditions heavily influences both structural and leaf economic traits. Our results strengthen the biological and mechanistic basis for climate change impact predictions of vulnerable high-latitude ecosystems.
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Affiliation(s)
| | | | | | - Mia Momberg
- University of Pretoria, Pretoria, South Africa
| | | | - Juha Aalto
- Finnish Meteorological Institute, Helsinki, Finland
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34
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A research framework for projecting ecosystem change in highly diverse tropical mountain ecosystems. Oecologia 2021; 195:589-600. [PMID: 33515062 PMCID: PMC7940296 DOI: 10.1007/s00442-021-04852-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 01/05/2021] [Indexed: 12/28/2022]
Abstract
Tropical mountain ecosystems are threatened by climate and land-use changes. Their diversity and complexity make projections how they respond to environmental changes challenging. A suitable way are trait-based approaches, by distinguishing between response traits that determine the resistance of species to environmental changes and effect traits that are relevant for species' interactions, biotic processes, and ecosystem functions. The combination of those approaches with land surface models (LSM) linking the functional community composition to ecosystem functions provides new ways to project the response of ecosystems to environmental changes. With the interdisciplinary project RESPECT, we propose a research framework that uses a trait-based response-effect-framework (REF) to quantify relationships between abiotic conditions, the diversity of functional traits in communities, and associated biotic processes, informing a biodiversity-LSM. We apply the framework to a megadiverse tropical mountain forest. We use a plot design along an elevation and a land-use gradient to collect data on abiotic drivers, functional traits, and biotic processes. We integrate these data to build the biodiversity-LSM and illustrate how to test the model. REF results show that aboveground biomass production is not directly related to changing climatic conditions, but indirectly through associated changes in functional traits. Herbivory is directly related to changing abiotic conditions. The biodiversity-LSM informed by local functional trait and soil data improved the simulation of biomass production substantially. We conclude that local data, also derived from previous projects (platform Ecuador), are key elements of the research framework. We specify essential datasets to apply this framework to other mountain ecosystems.
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35
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Anderson CG, Bond-Lamberty B, Stegen JC. Active layer depth and soil properties impact specific leaf area variation and ecosystem productivity in a boreal forest. PLoS One 2021; 15:e0232506. [PMID: 33382711 PMCID: PMC7775069 DOI: 10.1371/journal.pone.0232506] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 11/09/2020] [Indexed: 11/25/2022] Open
Abstract
Specific leaf area (SLA, leaf area per unit dry mass) is a key canopy structural characteristic, a measure of photosynthetic capacity, and an important input into many terrestrial process models. Although many studies have examined SLA variation, relatively few data exist from high latitude, climate-sensitive permafrost regions. We measured SLA and soil and topographic properties across a boreal forest permafrost transition, in which dominant tree species changed as permafrost deepened from 54 to >150 cm over 75 m hillslope transects in Caribou-Poker Creeks Research Watershed, Alaska. We characterized both linear and threshold relationships between topographic and edaphic variables and SLA and developed a conceptual model of these relationships. We found that the depth of the soil active layer above permafrost was significantly and positively correlated with SLA for both coniferous and deciduous boreal tree species. Intraspecific SLA variation was associated with a fivefold increase in net primary production, suggesting that changes in active layer depth due to permafrost thaw could strongly influence ecosystem productivity. While this is an exploratory study to begin understanding SLA variation in a non-contiguous permafrost system, our results indicate the need for more extensive evaluation across larger spatial domains. These empirical relationships and associated uncertainty can be incorporated into ecosystem models that use dynamic traits, improving our ability to predict ecosystem-level carbon cycling responses to ongoing climate change.
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Affiliation(s)
- Carolyn G. Anderson
- Pacific Northwest National Laboratory, Richland, Washington, United States of America
- * E-mail:
| | - Ben Bond-Lamberty
- Pacific Northwest National Laboratory, Joint Global Change Research Institute, College Park, Maryland, United States of America
| | - James C. Stegen
- Pacific Northwest National Laboratory, Richland, Washington, United States of America
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36
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Gustafson EJ, Miranda BR, Shvidenko AZ, Sturtevant BR. Simulating Growth and Competition on Wet and Waterlogged Soils in a Forest Landscape Model. Front Ecol Evol 2020. [DOI: 10.3389/fevo.2020.598775] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Changes in CO2 concentration and climate are likely to alter disturbance regimes and competitive outcomes among tree species, which ultimately can result in shifts of species and biome boundaries. Such changes are already evident in high latitude forests, where waterlogged soils produced by topography, surficial geology, and permafrost are an important driver of forest dynamics. Predicting such effects under the novel conditions of the future requires models with direct and mechanistic links of abiotic drivers to growth and competition. We enhanced such a forest landscape model (PnET-Succession in LANDIS-II) to allow simulation of waterlogged soils and their effects on tree growth and competition. We formally tested how these modifications alter water balance on wetland and permafrost sites, and their effect on tree growth and competition. We applied the model to evaluate its promise for mechanistically simulating species range expansion and contraction under climate change across a latitudinal gradient in Siberian Russia. We found that higher emissions scenarios permitted range expansions that were quicker and allowed a greater diversity of invading species, especially at the highest latitudes, and that disturbance hastened range shifts by overcoming the natural inertia of established ecological communities. The primary driver of range advances to the north was altered hydrology related to thawing permafrost, followed by temperature effects on growth. Range contractions from the south (extirpations) were slower and less tied to emissions or latitude, and were driven by inability to compete with invaders, or disturbance. An important non-intuitive result was that some extant species were killed off by extreme cold events projected under climate change as greater weather extremes occurred over the next 30 years, and this had important effects on subsequent successional trajectories. The mechanistic linkages between climate and soil water dynamics in this forest landscape model produced tight links between climate inputs, physiology of vegetation, and soils at a monthly time step. The updated modeling system can produce high quality projections of climate impacts on forest species range shifts by accounting for the interacting effects of CO2 concentration, climate (including longer growing seasons), seed dispersal, disturbance, and soil hydrologic properties.
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37
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Jiang C, Ryu Y, Wang H, Keenan TF. An optimality-based model explains seasonal variation in C3 plant photosynthetic capacity. GLOBAL CHANGE BIOLOGY 2020; 26:6493-6510. [PMID: 32654330 DOI: 10.1111/gcb.15276] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 05/18/2020] [Indexed: 06/11/2023]
Abstract
The maximum rate of carboxylation (Vcmax ) is an essential leaf trait determining the photosynthetic capacity of plants. Existing approaches for estimating Vcmax at large scale mainly rely on empirical relationships with proxies such as leaf nitrogen/chlorophyll content or hyperspectral reflectance, or on complicated inverse models from gross primary production or solar-induced fluorescence. A novel mechanistic approach based on the assumption that plants optimize resource investment coordinating with environment and growth has been shown to accurately predict C3 plant Vcmax based on mean growing season environmental conditions. However, the ability of optimality theory to explain seasonal variation in Vcmax has not been fully investigated. Here, we adapt an optimality-based model to simulate daily Vcmax,25C (Vcmax at a standardized temperature of 25°C) by incorporating the effects of antecedent environment, which affects current plant functioning, and dynamic light absorption, which coordinates with plant functioning. We then use seasonal Vcmax,25C field measurements from 10 sites across diverse ecosystems to evaluate model performance. Overall, the model explains about 83% of the seasonal variation in C3 plant Vcmax,25C across the 10 sites, with a medium root mean square error of 12.3 μmol m-2 s-1 , which suggests that seasonal changes in Vcmax,25C are consistent with optimal plant function. We show that failing to account for acclimation to antecedent environment or coordination with dynamic light absorption dramatically decreases estimation accuracy. Our results show that optimality-based approach can accurately reproduce seasonal variation in canopy photosynthetic potential, and suggest that incorporating such theory into next-generation trait-based terrestrial biosphere models would improve predictions of global photosynthesis.
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Affiliation(s)
- Chongya Jiang
- Department of Landscape Architecture and Rural Systems Engineering, Seoul National University, Seoul, Korea
| | - Youngryel Ryu
- Department of Landscape Architecture and Rural Systems Engineering, Seoul National University, Seoul, Korea
| | - Han Wang
- Department of Earth System Science, Tsinghua University, Beijing, China
| | - Trevor F Keenan
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Department of Environmental Science, Policy and Management, UC Berkeley, Berkeley, CA, USA
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38
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A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra. REMOTE SENSING 2020. [DOI: 10.3390/rs12162638] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Changes in vegetation distribution, structure, and function can modify the canopy properties of terrestrial ecosystems, with potential consequences for regional and global climate feedbacks. In the Arctic, climate is warming twice as fast as compared to the global average (known as ‘Arctic amplification’), likely having stronger impacts on arctic tundra vegetation. In order to quantify these changes and assess their impacts on ecosystem structure and function, methods are needed to accurately characterize the canopy properties of tundra vegetation types. However, commonly used ground-based measurements are limited in spatial and temporal coverage, and differentiating low-lying tundra plant species is challenging with coarse-resolution satellite remote sensing. The collection and processing of multi-sensor data from unoccupied aerial systems (UASs) has the potential to fill the gap between ground-based and satellite observations. To address the critical need for such data in the Arctic, we developed a cost-effective multi-sensor UAS (the ‘Osprey’) using off-the-shelf instrumentation. The Osprey simultaneously produces high-resolution optical, thermal, and structural images, as well as collecting point-based hyperspectral measurements, over vegetation canopies. In this paper, we describe the setup and deployment of the Osprey system in the Arctic to a tundra study site located in the Seward Peninsula, Alaska. We present a case study demonstrating the processing and application of Osprey data products for characterizing the key biophysical properties of tundra vegetation canopies. In this study, plant functional types (PFTs) representative of arctic tundra ecosystems were mapped with an overall accuracy of 87.4%. The Osprey image products identified significant differences in canopy-scale greenness, canopy height, and surface temperature among PFTs, with deciduous low to tall shrubs having the lowest canopy temperatures while non-vascular lichens had the warmest. The analysis of our hyperspectral data showed that variation in the fractional cover of deciduous low to tall shrubs was effectively characterized by Osprey reflectance measurements across the range of visible to near-infrared wavelengths. Therefore, the development and deployment of the Osprey UAS, as a state-of-the-art methodology, has the potential to be widely used for characterizing tundra vegetation composition and canopy properties to improve our understanding of ecosystem dynamics in the Arctic, and to address scale issues between ground-based and airborne/satellite observations.
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39
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Pace R, Liberati D, Sconocchia P, De Angelis P. Lead transfer into the vegetation layer growing naturally in a Pb-contaminated site. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2020; 42:2321-2329. [PMID: 31598822 DOI: 10.1007/s10653-019-00429-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Accepted: 09/23/2019] [Indexed: 06/10/2023]
Abstract
The lead was one of the main elements in the glazes used to colour ceramic tiles. Due to its presence, ceramic sludge has been a source of environmental pollution since this dangerous waste has been often spread into the soil without any measures of pollution control. These contaminated sites are often located close to industrial sites in the peri-urban areas, thus representing a considerable hazard to the human and ecosystem health. In this study, we investigated the lead transfer into the vegetation layer (Phragmites australis, Salix alba and Sambucus nigra) growing naturally along a Pb-contaminated ditch bank. The analysis showed a different lead accumulation among the species and their plant tissues. Salix trees were not affected by the Pb contamination, possibly because their roots mainly develop below the contaminated deposit. Differently, Sambucus accumulated high concentrations of lead in all plant tissues and fruits, representing a potential source of biomagnification. Phragmites accumulated large amounts of lead in the rhizomes and, considering its homogeneous distribution on the site, was used to map the contamination. Analysing the Pb concentration within plant tissues, we got at the same time information about the spread, the history of the contamination and the relative risks. Finally, we discussed the role of natural recolonizing plants for the soil pollution mitigation and their capacity on decreasing soil erosion and water run-off.
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Affiliation(s)
- Rocco Pace
- Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research - Atmospheric Environmental Research (IMK-IFU), Kreuzeckbahnstraße 19, 82467, Garmisch-Partenkirchen, Germany.
| | - Dario Liberati
- Department for Innovation in Biological, Agro-food and Forest Systems (DIBAF), University of Tuscia, Via San Camillo de Lellis s.n.c., 01100, Viterbo, Italy
| | - Paolo Sconocchia
- Department for Innovation in Biological, Agro-food and Forest Systems (DIBAF), University of Tuscia, Via San Camillo de Lellis s.n.c., 01100, Viterbo, Italy
- Regional Agency for Environmental Protection of Umbria (ARPA Umbria), Via Carlo Alberto Dalla Chiesa 32, 05100, Terni, Italy
| | - Paolo De Angelis
- Department for Innovation in Biological, Agro-food and Forest Systems (DIBAF), University of Tuscia, Via San Camillo de Lellis s.n.c., 01100, Viterbo, Italy
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40
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Chen X, Sun J, Wang M, Lyu M, Niklas KJ, Michaletz ST, Zhong Q, Cheng D. The Leaf Economics Spectrum Constrains Phenotypic Plasticity Across a Light Gradient. FRONTIERS IN PLANT SCIENCE 2020; 11:735. [PMID: 32595665 PMCID: PMC7300261 DOI: 10.3389/fpls.2020.00735] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Accepted: 05/07/2020] [Indexed: 05/30/2023]
Abstract
The leaf economics spectrum (LES) characterizes multivariate correlations that confine the global diversity of leaf functional traits onto a single axis of variation. Although LES is well established for traits of sun leaves, it is unclear how well LES characterizes the diversity of traits for shade leaves. Here, we evaluate LES using the sun and shade leaves of 75 woody species sampled at the extremes of a within-canopy light gradient in a subtropical forest. Shading significantly decreased the mean values of LMA and the rates of photosynthesis and dark respiration, but had no discernable effect on nitrogen and phosphorus content. Sun and shade leaves manifested the same relationships among N mass, P mass, A mass, and R mass (i.e., the slopes of log-log scaling relations of LES traits did not differ between sun and shade leaves). However, the difference between the normalization constants of shade and sun leaves was correlated with functional trait plasticity. Although the generality of this finding should be evaluated further using larger datasets comprising more phylogenetically diverse taxa and biomes, these findings support a unified LES across shade as well as sun leaves.
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Affiliation(s)
- Xiaoping Chen
- Fujian Provincial Key Laboratory of Plant Ecophysiology, Fujian Normal University, Fuzhou, China
- Key Laboratory of Humid Subtropical Eco-geographical Process, Ministry of Education, Fuzhou, China
| | - Jun Sun
- Fujian Provincial Key Laboratory of Plant Ecophysiology, Fujian Normal University, Fuzhou, China
| | - Mantang Wang
- School of City and Architecture Engineering, Zaozhuang University, Zaozhuang, China
| | - Min Lyu
- Fujian Provincial Key Laboratory of Plant Ecophysiology, Fujian Normal University, Fuzhou, China
| | - Karl J. Niklas
- Plant Biology Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, United States
| | - Sean T. Michaletz
- Department of Botany and Biodiversity Research Centre, University of British Columbia, Vancouver, BC, Canada
| | - Quanlin Zhong
- Fujian Provincial Key Laboratory of Plant Ecophysiology, Fujian Normal University, Fuzhou, China
| | - Dongliang Cheng
- Fujian Provincial Key Laboratory of Plant Ecophysiology, Fujian Normal University, Fuzhou, China
- Key Laboratory of Humid Subtropical Eco-geographical Process, Ministry of Education, Fuzhou, China
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41
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Oke TA, Turetsky MR. Evaluating
Sphagnum
traits in the context of resource economics and optimal partitioning theories. OIKOS 2020. [DOI: 10.1111/oik.07195] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Tobi A. Oke
- Marine Science Inst., The Univ. of Texas Austin 750 Channel View Drive Port Aransas TX 78373 USA
| | - Merritt R. Turetsky
- Inst. of Arctic and Alpine Research, Univ. of Colorado Boulder, Boulder, CO, USA, and: Dept of Integrative Biology, Univ. of Guelph Guelph ON Canada
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42
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Do Herbaceous Species Functional Groups Have a Uniform Pattern along an Elevation Gradient? The Case of a Semi-Arid Savanna Grasslands in Southern Ethiopia. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17082817. [PMID: 32325881 PMCID: PMC7216250 DOI: 10.3390/ijerph17082817] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 04/14/2020] [Accepted: 04/15/2020] [Indexed: 11/16/2022]
Abstract
Knowledge of the total (overall) and individual herbaceous vegetation species relating to a distinctive site might help in the development of management strategies for a large number of threatened herbaceous species. This paper assesses the total and functional group herbaceous biomass, species richness, evenness, and diversity at four elevation classes in Borana rangelands of arid thorn bush savanna grasslands in Southern Ethiopia. At each elevation class, a grid of 20 × 20 m main plot was placed, and individual herbaceous species samples were collected randomly from five 1 m2 quadrants within the main plot. Using a single-factor analysis of variance (ANOVA), the effects of four elevation classes were considered on whole-vegetation, grasses, graminoid, and forb species diversity, evenness, richness, and biomass. A total of 49 herbaceous species were recorded. Of the total identified herbaceous species, three grass species and two graminoid species were found across all studied elevation classes, but the forb species did not overlap along the studied elevation classes. The total richness, diversity, and evenness of herbaceous species were considerable and significant along elevation classes. The grass, graminoid, and forb species richness, diversity, and evenness responded differently, and the functional group of species may be a good indicator of the community processes of grassland across elevation classes. The contribution of forb richness to the total richness was more pronounced than grass and graminoid, which indicates the shift of savanna grassland to grazing tolerant herbaceous species. The results suggest that the pooled data analysis of herbaceous vegetation community structure and biomass could obscure complicate trends of the functional group at elevation classes and for managing herbaceous species in savanna grasslands, the management models should focus on the functional group species composition, community structure, and biomass.
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43
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Shiklomanov AN, Cowdery EM, Bahn M, Byun C, Jansen S, Kramer K, Minden V, Niinemets Ü, Onoda Y, Soudzilovskaia NA, Dietze MC. Does the leaf economic spectrum hold within plant functional types? A Bayesian multivariate trait meta-analysis. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2020; 30:e02064. [PMID: 31872519 DOI: 10.1002/eap.2064] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 11/01/2019] [Accepted: 11/13/2019] [Indexed: 05/25/2023]
Abstract
The leaf economic spectrum is a widely studied axis of plant trait variability that defines a trade-off between leaf longevity and productivity. While this has been investigated at the global scale, where it is robust, and at local scales, where deviations from it are common, it has received less attention at the intermediate scale of plant functional types (PFTs). We investigated whether global leaf economic relationships are also present within the scale of plant functional types (PFTs) commonly used by Earth System models, and the extent to which this global-PFT hierarchy can be used to constrain trait estimates. We developed a hierarchical multivariate Bayesian model that assumes separate means and covariance structures within and across PFTs and fit this model to seven leaf traits from the TRY database related to leaf longevity, morphology, biochemistry, and photosynthetic metabolism. Although patterns of trait covariation were generally consistent with the leaf economic spectrum, we found three approximate tiers to this consistency. Relationships among morphological and biochemical traits (specific leaf area [SLA], N, P) were the most robust within and across PFTs, suggesting that covariation in these traits is driven by universal leaf construction trade-offs and stoichiometry. Relationships among metabolic traits (dark respiration [Rd ], maximum RuBisCo carboxylation rate [Vc,max ], maximum electron transport rate [Jmax ]) were slightly less consistent, reflecting in part their much sparser sampling (especially for high-latitude PFTs), but also pointing to more flexible plasticity in plant metabolistm. Finally, relationships involving leaf lifespan were the least consistent, indicating that leaf economic relationships related to leaf lifespan are dominated by across-PFT differences and that within-PFT variation in leaf lifespan is more complex and idiosyncratic. Across all traits, this covariance was an important source of information, as evidenced by the improved imputation accuracy and reduced predictive uncertainty in multivariate models compared to univariate models. Ultimately, our study reaffirms the value of studying not just individual traits but the multivariate trait space and the utility of hierarchical modeling for studying the scale dependence of trait relationships.
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Affiliation(s)
- Alexey N Shiklomanov
- Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, Maryland, 20740, USA
| | - Elizabeth M Cowdery
- Department of Earth & Environment, Boston University, 685 Commonwealth Avenue Boston, Massachusetts, 02215, USA
| | - Michael Bahn
- Institute of Ecology, University of Innsbruck, Innsbruck, 6020, Austria
| | - Chaeho Byun
- School of Civil and Environmental Engineering, Yonsei University, Seoul, 03722, Korea
| | - Steven Jansen
- Institute of Systematic Botany and Ecology, Ulm University, Albert-Einstein-Allee 11, Ulm, 89081, Germany
| | - Koen Kramer
- Department of Vegetation, Forest, and Landscape Ecology, Wageningen Environmental Research and Wageningen University, P.O. Box 6708, Droevendaalsesteeg 4, Wageningen, The Netherlands
| | - Vanessa Minden
- Institute for Biology and Environmental Sciences, Carl von Ossietzky-University of Oldenburg, Carl von Ossietzky Strasse 9-11, Oldenburg, 26129, Germany
- Department of Biology, Ecology and Evolution, Vrije Universiteit Brussel, Pleinlaan 2, Brussels, 1050, Belgium
| | - Ülo Niinemets
- Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Kreutzwaldi 1, Tartu, 51014, Estonia
| | - Yusuke Onoda
- Graduate School of Agriculture, Kyoto University, Kyoto, 605-8503, Japan
| | - Nadejda A Soudzilovskaia
- Conservation Biology Department, Institute of Environmental Sciences, Leiden University, Rapenburg 70, 2311, EZ Leiden, The Netherlands
| | - Michael C Dietze
- Department of Earth & Environment, Boston University, 685 Commonwealth Avenue Boston, Massachusetts, 02215, USA
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44
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Thomas HJD, Bjorkman AD, Myers-Smith IH, Elmendorf SC, Kattge J, Diaz S, Vellend M, Blok D, Cornelissen JHC, Forbes BC, Henry GHR, Hollister RD, Normand S, Prevéy JS, Rixen C, Schaepman-Strub G, Wilmking M, Wipf S, Cornwell WK, Beck PSA, Georges D, Goetz SJ, Guay KC, Rüger N, Soudzilovskaia NA, Spasojevic MJ, Alatalo JM, Alexander HD, Anadon-Rosell A, Angers-Blondin S, Te Beest M, Berner LT, Björk RG, Buchwal A, Buras A, Carbognani M, Christie KS, Collier LS, Cooper EJ, Elberling B, Eskelinen A, Frei ER, Grau O, Grogan P, Hallinger M, Heijmans MMPD, Hermanutz L, Hudson JMG, Johnstone JF, Hülber K, Iturrate-Garcia M, Iversen CM, Jaroszynska F, Kaarlejarvi E, Kulonen A, Lamarque LJ, Lantz TC, Lévesque E, Little CJ, Michelsen A, Milbau A, Nabe-Nielsen J, Nielsen SS, Ninot JM, Oberbauer SF, Olofsson J, Onipchenko VG, Petraglia A, Rumpf SB, Shetti R, Speed JDM, Suding KN, Tape KD, Tomaselli M, Trant AJ, Treier UA, Tremblay M, Venn SE, Vowles T, Weijers S, Wookey PA, Zamin TJ, Bahn M, Blonder B, van Bodegom PM, Bond-Lamberty B, Campetella G, Cerabolini BEL, Chapin FS, Craine JM, Dainese M, Green WA, Jansen S, Kleyer M, Manning P, Niinemets Ü, Onoda Y, Ozinga WA, Peñuelas J, Poschlod P, Reich PB, Sandel B, Schamp BS, Sheremetiev SN, de Vries FT. Global plant trait relationships extend to the climatic extremes of the tundra biome. Nat Commun 2020; 11:1351. [PMID: 32165619 PMCID: PMC7067758 DOI: 10.1038/s41467-020-15014-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Accepted: 02/11/2020] [Indexed: 11/09/2022] Open
Abstract
The majority of variation in six traits critical to the growth, survival and reproduction of plant species is thought to be organised along just two dimensions, corresponding to strategies of plant size and resource acquisition. However, it is unknown whether global plant trait relationships extend to climatic extremes, and if these interspecific relationships are confounded by trait variation within species. We test whether trait relationships extend to the cold extremes of life on Earth using the largest database of tundra plant traits yet compiled. We show that tundra plants demonstrate remarkably similar resource economic traits, but not size traits, compared to global distributions, and exhibit the same two dimensions of trait variation. Three quarters of trait variation occurs among species, mirroring global estimates of interspecific trait variation. Plant trait relationships are thus generalizable to the edge of global trait-space, informing prediction of plant community change in a warming world.
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Affiliation(s)
- H J D Thomas
- School of Geosciences, University of Edinburgh, Edinburgh, EH9 3FF, Scotland, UK.
| | - A D Bjorkman
- School of Geosciences, University of Edinburgh, Edinburgh, EH9 3FF, Scotland, UK
- Department of Biological and Environmental Sciences, University of Gothenburg, Medicinaregatan 18, 40530, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, Carl Skottsbergs gata 22B, 41319, Gothenburg, Sweden
| | - I H Myers-Smith
- School of Geosciences, University of Edinburgh, Edinburgh, EH9 3FF, Scotland, UK
| | - S C Elmendorf
- Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO, 80309-0450, USA
| | - J Kattge
- Max Planck Institute for Biogeochemistry, 07701, Jena, Germany
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Deutscher Platz 5e, 04103, Leipzig, Germany
| | - S Diaz
- Instituto Multidisciplinario de Biología Vegetal (IMBIV), CONICET, Av.Velez Sarsfield 299, Cordoba, Argentina
- FCEFyN, Universidad Nacional de Córdoba, Av. Vélez Sarsfield 299, X5000JJC, Córdoba, Argentina
| | - M Vellend
- Département de Biologie, Université de Sherbrooke, 2500, boul. de l'Université Sherbrooke, Québec, J1K 2R1, Canada
| | - D Blok
- Dutch Research Council, (NWO), Postbus 93460, 2509 AL, Den Haag, The Netherlands
| | - J H C Cornelissen
- Systems Ecology, Department of Ecological Science, Vrije Universiteit, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands
| | - B C Forbes
- Arctic Centre, University of Lapland, 96101, Rovaniemi, Finland
| | - G H R Henry
- Department of Geography, University of British Columbia, 1984 West Mall, Vancouver, V6T 1Z2, Canada
| | - R D Hollister
- Biology Department, Grand Valley State University, 1 Campus Drive, 3300a Kindschi Hall of Science, Allendale, Michigan, USA
| | - S Normand
- Department of Biology, Aarhus University, Ny Munkegade 114-116, DK-8000, Aarhus C, Denmark
| | - J S Prevéy
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, CO, 80526, USA
- WSL Institute for Snow and Avalanche Research SLF, Flüelastrasse 11, 7260, Davos Dorf, Switzerland
| | - C Rixen
- WSL Institute for Snow and Avalanche Research SLF, Flüelastrasse 11, 7260, Davos Dorf, Switzerland
| | - G Schaepman-Strub
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland
| | - M Wilmking
- Institute of Botany and Landscape Ecology, Greifswald University, Soldmannstraße 15, 17487, Greifswald, Germany
| | - S Wipf
- WSL Institute for Snow and Avalanche Research SLF, Flüelastrasse 11, 7260, Davos Dorf, Switzerland
- Swiss National Park, Runatsch 124, Chastè Planta-Wildenberg, 7530, Zernez, Switzerland
| | - W K Cornwell
- Ecology and Evolution Research Centre, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW, 2052, Australia
| | - P S A Beck
- European Commission, Joint Research Centre, Via Enrico Fermi, 2749, Ispra, 21027, Italy
| | - D Georges
- School of Geosciences, University of Edinburgh, Edinburgh, EH9 3FF, Scotland, UK
- International Agency for Research in Cancer, 150 Cours Albert Thomas, 69372, Lyon, France
| | - S J Goetz
- School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, 1295S Knoles Dr, AZ, 86011, USA
| | - K C Guay
- Bigelow Laboratory for Ocean Sciences, 60 Bigelow Dr, East Boothbay, Maine, 04544, USA
| | - N Rüger
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Deutscher Platz 5e, 04103, Leipzig, Germany
- Smithsonian Tropical Research Institute, Luis Clement Avenue, Bldg. 401 Tupper, Balboa Ancón, Panama
| | - N A Soudzilovskaia
- Environmental Biology Department, Institute of Environmental Sciences, Leiden University, 2300 RA, Leiden, The Netherlands
| | - M J Spasojevic
- Department of Evolution, Ecology, and Organismal Biology, University of California Riverside, Life Sciences Building, Eucalyptus Dr #2710, Riverside, CA, 92521, USA
| | - J M Alatalo
- Department of Biological and Environmental Sciences, College of Arts and Sciences, Qatar University, P.O. Box 2713, Doha, Qatar
- Environmental Science Center, Qatar University, Doha, Qatar
| | - H D Alexander
- Department of Forestry, Forest and Wildlife Research Center, Mississippi State University, Mississippi, MS, 39762, USA
| | - A Anadon-Rosell
- Institute of Botany and Landscape Ecology, Greifswald University, Soldmannstraße 15, 17487, Greifswald, Germany
- Department of Evolutionary Biology, Ecology and Environmental Sciences, University of Barcelona, Diagonal, 643, 08028, Barcelona, Spain
- Biodiversity Research Institute, University of Barcelona, Av. Diagonal, 645, 08028, Barcelona, Spain
| | - S Angers-Blondin
- School of Geosciences, University of Edinburgh, Edinburgh, EH9 3FF, Scotland, UK
| | - M Te Beest
- Environmental Sciences, Copernicus Institute of Sustainable Development, Utrecht University, Heidelberglaan 8, 3584 CS, Utrecht, The Netherlands
- Department of Ecology and Environmental Science Umeå University, SE-901 87, Umeå, Sweden
| | - L T Berner
- School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, 1295S Knoles Dr, AZ, 86011, USA
| | - R G Björk
- Department of Earth Sciences, University of Gothenburg, 405 30, Gothenburg, Sweden
- Gothenburg Global Biodiversity Centre, SE-405 30, Gothenburg, Sweden
| | - A Buchwal
- Adam Mickiewicz University, Institute of Geoecology and Geoinformation, B. Krygowskiego 10, 61-680, Poznan, Poland
- University of Alaska Anchorage, 3211 Providence Dr, Anchorage, AK, 99508, USA
| | - A Buras
- Land Surface-Atmosphere Interactions, Technische Universität München, Hans-Carl-von-Carlowitz Platz 2, 85354, Freising, Germany
| | - M Carbognani
- Deptartment of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 11/a, 43124, Parma, Italy
| | - K S Christie
- Alaska Department of Fish and Game, 333 Raspberry Rd, Anchorage, AK, 99518, USA
| | - L S Collier
- Department of Biology, Memorial University, St. John's, Newfoundland and Labrador, A1C 5S7, Canada
| | - E J Cooper
- Deptartment of Arctic and Marine Biology, Faculty of Bioscences Fisheries and Economics, UiT-The Arctic University of Norway, Tromsø, Norway
| | - B Elberling
- Center for Permafrost (CENPERM), Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, DK-1350, Copenhagen K, Denmark
| | - A Eskelinen
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Deutscher Platz 5e, 04103, Leipzig, Germany
- Department of Physiological Diversity, Helmholtz Centre for Environmental Research-UFZ, Deutscher Platz 5e, 04103, Leipzig, Germany
- Department of Ecology and Genetics, University of Oulu, Pentti Kaiteran katu 1, Linnanmaa, Oulu, Finland
| | - E R Frei
- Department of Geography, University of British Columbia, 1984 West Mall, Vancouver, V6T 1Z2, Canada
- Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
| | - O Grau
- CSIC, Global Ecology Unit CREAF-CSIC-UAB, 08193 Cerdanyola del Vallès Bellaterra, Catalonia, Spain
- CREAF, 08193 Cerdanyola del Vallès, Catalonia, Spain
- Cirad, UMR EcoFoG (AgroParisTech, CNRS, Inra, Univ Antilles, Univ Guyane), Campus Agronomique, 97310, Kourou, French Guiana
| | - P Grogan
- Department of Biology, Queen's University, Biosciences Complex, 116 Barrie St., Kingston, ON, K7L 3N6, Canada
| | - M Hallinger
- Biology Department, Swedish Agricultural University (SLU), SE-750 07, Uppsala, Sweden
| | - M M P D Heijmans
- Plant Ecology and Nature Conservation Group, Wageningen University and Research, 6700 AA, Wageningen, The Netherlands
| | - L Hermanutz
- Department of Biology, Memorial University, St. John's, Newfoundland and Labrador, A1C 5S7, Canada
| | - J M G Hudson
- British Columbia Public Service, Vancouver, Canada
| | - J F Johnstone
- Department of Biology, University of Saskatchewan, Saskatoon, SK, S7N 5E2, Canada
| | - K Hülber
- Department of Botany and Biodiversity Research, University of Vienna, Rennweg 14, 1030, Vienna, Austria
| | - M Iturrate-Garcia
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland
| | - C M Iversen
- Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN, 37831-6134, USA
| | - F Jaroszynska
- WSL Institute for Snow and Avalanche Research SLF, Flüelastrasse 11, 7260, Davos Dorf, Switzerland
- Department of Biological Sciences and Bjerknes Centre for Climate Research, University of Bergen, N-5020, Bergen, Norway
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, AB24 3FX, Scotland, UK
| | - E Kaarlejarvi
- Biodiversity Research Institute, University of Barcelona, Av. Diagonal, 645, 08028, Barcelona, Spain
- Department of Biology, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050, Elsene, Brussles, Belgium
- Organismal and Evolutionary Biology Research Programme, University of Helsinki, PO Box, 65, FI-00014, Helsinki, Finland
| | - A Kulonen
- WSL Institute for Snow and Avalanche Research SLF, Flüelastrasse 11, 7260, Davos Dorf, Switzerland
| | - L J Lamarque
- Département des Sciences de l'environnement et Centre d'études nordiques, Université du Québec à Trois-Rivières, 3351, boul. des Forges, Québec, Canada
| | - T C Lantz
- School of Environmental Studies, University of Victoria, David Turpin Building, B243, Victoria, BC, Canada
| | - E Lévesque
- Département des Sciences de l'environnement et Centre d'études nordiques, Université du Québec à Trois-Rivières, 3351, boul. des Forges, Québec, Canada
| | - C J Little
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland
- Department of Aquatic Ecology, Eawag, the Swiss Federal Institute for Aquatic Science and Technology, Überlandstrasse 133, CH-8600, Duebendorf, Switzerland
| | - A Michelsen
- Center for Permafrost (CENPERM), Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, DK-1350, Copenhagen K, Denmark
- Department of Biology, University of Copenhagen, Terrestrial Ecology Section, Universitetsparken 15, DK-2100, Copenhagen Ø, Denmark
| | - A Milbau
- Research Institute for Nature and Forest (INBO), Havenlaan 88 bus 73, 1000, Brussels, Belgium
| | - J Nabe-Nielsen
- Department of Bioscience, Aarhus University, Frederiksborgvej 399, 4000, Roskilde, Denmark
| | - S S Nielsen
- Department of Biology, Aarhus University, Ny Munkegade 114-116, DK-8000, Aarhus C, Denmark
| | - J M Ninot
- Department of Evolutionary Biology, Ecology and Environmental Sciences, University of Barcelona, Diagonal, 643, 08028, Barcelona, Spain
- Biodiversity Research Institute, University of Barcelona, Av. Diagonal, 645, 08028, Barcelona, Spain
| | - S F Oberbauer
- Department of Biological Sciences, Florida International University, 11200S.W. 8th Street, Miami, FL, 33199, USA
| | - J Olofsson
- Department of Ecology and Environmental Science Umeå University, SE-901 87, Umeå, Sweden
| | - V G Onipchenko
- Department of Ecology and Plant Geography, Moscow State Lomonosov University, 119234, Moscow, 1-12 Leninskie Gory, Russia
| | - A Petraglia
- Deptartment of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 11/a, 43124, Parma, Italy
| | - S B Rumpf
- Department of Botany and Biodiversity Research, University of Vienna, Rennweg 14, 1030, Vienna, Austria
- Department of Ecology and Evolution, University of Lausanne, Bâtiment Biophore, Quartier UNIL-Sorge, 1015, Lausanne, Switzerland
| | - R Shetti
- Institute of Botany and Landscape Ecology, Greifswald University, Soldmannstraße 15, 17487, Greifswald, Germany
| | - J D M Speed
- Department of Natural History, NTNU University Museum, Norwegian University of Science and Technology, NO-7491, Trondheim, Norway
| | - K N Suding
- Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO, 80309-0450, USA
| | - K D Tape
- Institute of Northern Engineering, University of Alaska, Engineering Learning and Innovation Facility (ELIF), Suite 240, 1764 Tanana Loop, Fairbanks, AK, 99775-5910, USA
| | - M Tomaselli
- Deptartment of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 11/a, 43124, Parma, Italy
| | - A J Trant
- School of Environment, Resources and Sustainability, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
| | - U A Treier
- Department of Biology, Aarhus University, Ny Munkegade 114-116, DK-8000, Aarhus C, Denmark
| | - M Tremblay
- Département des Sciences de l'environnement et Centre d'études nordiques, Université du Québec à Trois-Rivières, 3351, boul. des Forges, Québec, Canada
| | - S E Venn
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, 75 Pigdons Rd, Waurn Ponds Victoria, 3216, Australia
| | - T Vowles
- Department of Earth Sciences, University of Gothenburg, 405 30, Gothenburg, Sweden
| | - S Weijers
- Department of Geography, University of Bonn, Meckenheimer Allee 166, D-53115, Bonn, Germany
| | - P A Wookey
- Biological and Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling, FK9 4LA, Scotland, UK
| | - T J Zamin
- Department of Biology, Queen's University, Biosciences Complex, 116 Barrie St., Kingston, ON, K7L 3N6, Canada
| | - M Bahn
- Department of Ecology, University of Innsbruck, Innrain 52, 6020, Innsbruck, Austria
| | - B Blonder
- Environmental Change Institute, School of Geography and the Environment, University of Oxford, 3 South Parks Road, Oxford, OX1 3QY, UK
- Rocky Mountain Biological Laboratory, 8000 Co Rd 317, Crested Butte, CO, 81224, USA
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, 94706, USA
| | - P M van Bodegom
- Environmental Biology Department, Institute of Environmental Sciences, Leiden University, 2300 RA, Leiden, The Netherlands
| | - B Bond-Lamberty
- Pacific Northwest National Laboratory, Joint Global Change Research Institute, 5825 University Research Ct, College Park, MD, 20740, USA
| | - G Campetella
- School of Biosciences and Veterinary Medicine-Plant Diversity and Ecosystems Management Unit, Univeristy of Camerino, Via Gentile III Da Varano, 62032, Camerino, Italy
| | - B E L Cerabolini
- DBSV-University of Insubria, Via Dunant, 3, 21100, Varese, Italy
| | - F S Chapin
- Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK, 99775, USA
| | - J M Craine
- Jonah Ventures, 1600 Range Street Suite 201, Boulder, CO, 80301, USA
| | - M Dainese
- Department of Animal Ecology and Tropical Biology, University of Würzburg, Am Hubland, 97074, Würzburg, Germany
- Institute for Alpine Environment, EURAC Research, Viale Druso, 1, 39100, Bolzano, Italy
| | - W A Green
- Department of Organismic and Evolutionary Biology, Harvard University, 52 Oxford Street, Cambridge, MA, 02138, USA
| | - S Jansen
- Institute of Systematic Botany and Ecology, Ulm University, Albert-Einstein-Allee 11, D-89081, Ulm, Germany
| | - M Kleyer
- Institute of Biology and Environmental Sciences, University of Oldenburg, Carl-von-Ossietzky-Strasse 9-11, 26129, Oldenburg, Germany
| | - P Manning
- Senckenberg Biodiversity and Climate Research Centre, 60325, Frankfurt, Germany
| | - Ü Niinemets
- Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Fr.R.Kreutzwaldi 1, 51006, Tartu, Estonia
| | - Y Onoda
- Graduate School of Agriculture, Kyoto University, Sakyo-ku, Kyoto, 606-8502, Japan
| | - W A Ozinga
- Vegetation, Forest and Landscape Ecology, Wageningen University and Research, P.O. Box 47, NL-6700 AA, Wageningen, The Netherlands
| | - J Peñuelas
- CSIC, Global Ecology Unit CREAF-CSIC-UAB, 08193 Cerdanyola del Vallès Bellaterra, Catalonia, Spain
- CREAF, 08193 Cerdanyola del Vallès, Catalonia, Spain
| | - P Poschlod
- Ecology and Conservation Biology, Institute of Plant Sciences, University of Regensburg, Regensburg, Germany
| | - P B Reich
- Department of Forest Resources, University of Minnesota, 115 Green Hall, 1530 Cleveland Ave. N., St. Paul, MN, 55108, USA
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, 2751, Australia
| | - B Sandel
- Department of Biology, Santa Clara University, 500 El Camino Real, Santa Clara, CA, 95053, USA
| | - B S Schamp
- Department of Biology, Algoma University, 1520 Queen Street East, Sault Ste., Marie, ON, P6A 2G4, Canada
| | - S N Sheremetiev
- Komarov Botanical Institute, Professor Popova Street, 2, St Petersburg, Russia
| | - F T de Vries
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Postbus 94240, 1090 GE, Amsterdam, Netherlands
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45
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Lavergne A, Voelker S, Csank A, Graven H, de Boer HJ, Daux V, Robertson I, Dorado-Liñán I, Martínez-Sancho E, Battipaglia G, Bloomfield KJ, Still CJ, Meinzer FC, Dawson TE, Julio Camarero J, Clisby R, Fang Y, Menzel A, Keen RM, Roden JS, Prentice IC. Historical changes in the stomatal limitation of photosynthesis: empirical support for an optimality principle. THE NEW PHYTOLOGIST 2020; 225:2484-2497. [PMID: 31696932 DOI: 10.1111/nph.16314] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Accepted: 10/31/2019] [Indexed: 05/08/2023]
Abstract
The ratio of leaf internal (ci ) to ambient (ca ) partial pressure of CO2 , defined here as χ, is an index of adjustments in both leaf stomatal conductance and photosynthetic rate to environmental conditions. Measurements and proxies of this ratio can be used to constrain vegetation model uncertainties for predicting terrestrial carbon uptake and water use. We test a theory based on the least-cost optimality hypothesis for modelling historical changes in χ over the 1951-2014 period, across different tree species and environmental conditions, as reconstructed from stable carbon isotopic measurements across a global network of 103 absolutely dated tree-ring chronologies. The theory predicts optimal χ as a function of air temperature, vapour pressure deficit, ca and atmospheric pressure. The theoretical model predicts 39% of the variance in χ values across sites and years, but underestimates the intersite variability in the reconstructed χ trends, resulting in only 8% of the variance in χ trends across years explained by the model. Overall, our results support theoretical predictions that variations in χ are tightly regulated by the four environmental drivers. They also suggest that explicitly accounting for the effects of plant-available soil water and other site-specific characteristics might improve the predictions.
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Affiliation(s)
- Aliénor Lavergne
- Department of Life Sciences, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot, SL5 7PY, UK
- Department of Physics, Imperial College London, Exhibition Road, London, SW7 2AZ, UK
| | - Steve Voelker
- Department of Environmental and Forest Biology, SUNY College of Environmental Science and Forestry, Syracuse, NY, 13210, USA
| | - Adam Csank
- Department of Geography, University of Nevada-Reno, 1664 N. Virginia St, Reno, NV, 89557, USA
| | - Heather Graven
- Department of Physics, Imperial College London, Exhibition Road, London, SW7 2AZ, UK
- Grantham Institute - Climate Change and the Environment, Imperial College London, Exhibition Road, London, SW7 2AZ, UK
| | - Hugo J de Boer
- Department of Environmental Sciences, Utrecht University, 3584 CB, Utrecht, the Netherlands
| | - Valérie Daux
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, 91191, Gif-sur-Yvette, France
| | - Iain Robertson
- Department of Geography, Swansea University, Swansea, SA2 8PP, UK
| | - Isabel Dorado-Liñán
- Forest Genetics and Ecophysiology Research Group, Technical University of Madrid, Madrid, 28040, Spain
| | - Elisabet Martínez-Sancho
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, Birmensdorf, 8903, Switzerland
| | - Giovanna Battipaglia
- Department of Environmental, Biological and Pharmaceutical Sciences and Technologies, University of Campania "L. Vanvitelli", Via Vivaldi, 81100, Caserta, Italy
| | - Keith J Bloomfield
- Department of Life Sciences, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot, SL5 7PY, UK
| | - Christopher J Still
- Department of Forest Ecosystems & Society, Oregon State University, Corvallis, OR, 97331-5704, USA
| | - Frederick C Meinzer
- USDA Forest Service, Pacific Northwest Research Station, Corvallis, OR, 97331-8550, USA
| | - Todd E Dawson
- Department of Integrative Biology, University of California - Berkeley, Berkeley, CA, 94720-3200, USA
| | - J Julio Camarero
- Instituto Pirenaico de Ecología (IPE-CSIC), E-50192, Zaragoza, Spain
| | - Rory Clisby
- Department of Geography, Swansea University, Swansea, SA2 8PP, UK
| | - Yunting Fang
- Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China
| | - Annette Menzel
- Ecoclimatology, Department of Ecology and Ecosystem Management, Technical University of Munich, 85354, Freising, Germany
| | - Rachel M Keen
- Division of Biology, Kansas State University, Manhattan, KS, 66506, USA
| | - John S Roden
- Department of Biology, Southern Oregon University, Ashland, OR, 97520, USA
| | - I Colin Prentice
- Department of Life Sciences, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot, SL5 7PY, UK
- Grantham Institute - Climate Change and the Environment, Imperial College London, Exhibition Road, London, SW7 2AZ, UK
- Department of Biological Sciences, Macquarie University, North Ryde, NSW, 2109, Australia
- Department of Earth System Science, Tsinghua University, Beijing, 100084, China
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46
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Han T, Zhu G, Ma J, Wang S, Zhang K, Liu X, Ma T, Shang S, Huang C. Sensitivity analysis and estimation using a hierarchical Bayesian method for the parameters of the FvCB biochemical photosynthetic model. PHOTOSYNTHESIS RESEARCH 2020; 143:45-66. [PMID: 31659624 DOI: 10.1007/s11120-019-00684-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Accepted: 10/14/2019] [Indexed: 06/10/2023]
Abstract
Photosynthesis is a major process included in land surface models. Accurately estimating the parameters of the photosynthetic sub-models can greatly improve the ability of these models to accurately simulate the carbon cycle of terrestrial ecosystems. Here, we used a hierarchical Bayesian approach to fit the Farquhar-von Caemmerer-Berry model, which is based on the biochemistry of photosynthesis using 236 curves for the relationship between net CO2 assimilation and changes in the intercellular CO2 concentration. An advantage of the hierarchical Bayesian algorithm is that parameters can be estimated at multiple levels (plant, species, plant functional type, and population level) simultaneously. The parameters of the hierarchical strategy were based on the results of a sensitivity analysis. The Michaelis-Menten constant (Kc25), enthalpies of activation (EJ and EV), and two optical parameters (θ and α) demonstrated considerable variation at different levels, which suggests that this variation cannot be ignored. The maximum electron transport rate (Jmax25), maximum rate of Rubisco activity (Vcmax25), and dark respiration in the light (Rd25) were higher for broad-leaved plants than for needle-leaved plants. Comparison of the model's simulated outputs with observed data showed strong and significant positive correlations, particularly when the model was parameterized at the plant level. In summary, our study is the first effort to combine sensitivity analysis and hierarchical Bayesian parameter estimation. The resulting realistic parameter distributions for the four levels provide a reference for current and future land surface models. Furthermore, the observed variation in the parameters will require attention when using photosynthetic parameters in future models.
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Affiliation(s)
- Tuo Han
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), Lanzhou University, Tianshui Road 222, Lanzhou, 730000, Gansu, People's Republic of China
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China
| | - Gaofeng Zhu
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), Lanzhou University, Tianshui Road 222, Lanzhou, 730000, Gansu, People's Republic of China.
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China.
| | - Jinzhu Ma
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), Lanzhou University, Tianshui Road 222, Lanzhou, 730000, Gansu, People's Republic of China
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China
| | - Shangtao Wang
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), Lanzhou University, Tianshui Road 222, Lanzhou, 730000, Gansu, People's Republic of China
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China
| | - Kun Zhang
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), Lanzhou University, Tianshui Road 222, Lanzhou, 730000, Gansu, People's Republic of China
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China
| | - Xiaowen Liu
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), Lanzhou University, Tianshui Road 222, Lanzhou, 730000, Gansu, People's Republic of China
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China
| | - Ting Ma
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), Lanzhou University, Tianshui Road 222, Lanzhou, 730000, Gansu, People's Republic of China
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China
| | - Shasha Shang
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), Lanzhou University, Tianshui Road 222, Lanzhou, 730000, Gansu, People's Republic of China
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China
| | - Chunlin Huang
- Key Laboratory of Remote Sensing of Gansu Province, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, 730000, China
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47
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Serbin SP, Wu J, Ely KS, Kruger EL, Townsend PA, Meng R, Wolfe BT, Chlus A, Wang Z, Rogers A. From the Arctic to the tropics: multibiome prediction of leaf mass per area using leaf reflectance. THE NEW PHYTOLOGIST 2019; 224:1557-1568. [PMID: 31418863 DOI: 10.1111/nph.16123] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Accepted: 07/28/2019] [Indexed: 06/10/2023]
Abstract
Leaf mass per area (LMA) is a key plant trait, reflecting tradeoffs between leaf photosynthetic function, longevity, and structural investment. Capturing spatial and temporal variability in LMA has been a long-standing goal of ecological research and is an essential component for advancing Earth system models. Despite the substantial variation in LMA within and across Earth's biomes, an efficient, globally generalizable approach to predict LMA is still lacking. We explored the capacity to predict LMA from leaf spectra across much of the global LMA trait space, with values ranging from 17 to 393 g m-2 . Our dataset contained leaves from a wide range of biomes from the high Arctic to the tropics, included broad- and needleleaf species, and upper- and lower-canopy (i.e. sun and shade) growth environments. Here we demonstrate the capacity to rapidly estimate LMA using only spectral measurements across a wide range of species, leaf age and canopy position from diverse biomes. Our model captures LMA variability with high accuracy and low error (R2 = 0.89; root mean square error (RMSE) = 15.45 g m-2 ). Our finding highlights the fact that the leaf economics spectrum is mirrored by the leaf optical spectrum, paving the way for this technology to predict the diversity of LMA in ecosystems across global biomes.
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Affiliation(s)
- Shawn P Serbin
- Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973, USA
| | - Jin Wu
- Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973, USA
- School of Biological Sciences, The University of Hong Kong, Pokfulam, Hong Kong
| | - Kim S Ely
- Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973, USA
| | - Eric L Kruger
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Philip A Townsend
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Ran Meng
- Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973, USA
- College of Natural Resources and Environment, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Brett T Wolfe
- Smithsonian Tropical Research Institute, Apartado, 0843-03092, Balboa, Panama
- School of Renewable Natural Resources, Louisiana State University, Baton Rouge, LA, USA
| | - Adam Chlus
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Zhihui Wang
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Alistair Rogers
- Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973, USA
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48
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Salmon VG, Breen AL, Kumar J, Lara MJ, Thornton PE, Wullschleger SD, Iversen CM. Alder Distribution and Expansion Across a Tundra Hillslope: Implications for Local N Cycling. FRONTIERS IN PLANT SCIENCE 2019; 10:1099. [PMID: 31681340 PMCID: PMC6807776 DOI: 10.3389/fpls.2019.01099] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 08/09/2019] [Indexed: 05/14/2023]
Abstract
Increases in the availability of nitrogen (N) may have consequences for plant growth and nutrient cycling in N-limited tundra plant communities. We investigated the impact alder (Alnus viridis spp. fruticosa), an N-fixing deciduous shrub, has on tundra N cycling at a hillslope located on Alaska's Seward Peninsula. We quantified N fixation using 15N2 incubations within two distinct alder communities at this site: alder shrublands located on well-drained, rocky outcroppings in the uplands and alder savannas located in water tracks along the moist toeslope of the hill. Annual N fixation rates in alder shrublands were 1.95 ± 0.68 g N m-2 year-1, leading to elevated N levels in adjacent soils and plants. Alder savannas had lower N fixation rates (0.53 ± 0.19 g N m-2 year-1), perhaps due to low phosphorus availability and poor drainage in these highly organic soil profiles underlain by permafrost. In addition to supporting higher rates of N fixation, tall-statured alder shrublands had different foliar traits than relatively short-statured alder in savannas, providing an opportunity to link N fixation to remotely-sensed variables. We were able to generate a map of the alder shrubland distribution at this site using a multi-sensor fusion approach. The change in alder shrubland distribution through time was also determined from historic aerial and satellite imagery. Analysis of historic imagery showed that the area of alder shrublands at this site has increased by 40% from 1956 to 2014. We estimate this increase in alder shrublands was associated with a 22% increase in N fixation. Our results suggest that expansion of alder shrublands has the potential to substantially alter N cycling, increase plant productivity, and redistribute C storage in upland tundra regions. An improved understanding of the consequences of N fixation within N-limited tundra plant communities will therefore be crucial for predicting the biogeochemistry of these warming ecosystems.
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Affiliation(s)
- Verity G. Salmon
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Amy L. Breen
- International Arctic Research Center, University of Alaska, Fairbanks, AK, United States
| | - Jitendra Kumar
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Mark J. Lara
- Department of Plant Biology, University of Illinois, Urbana, IL, United States
- Department of Geography, University of Illinois, Urbana, IL, United States
| | - Peter E. Thornton
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Stan D. Wullschleger
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Colleen M. Iversen
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, United States
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49
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Robson TM, Aphalo PJ. Transmission of ultraviolet, visible and near-infrared solar radiation to plants within a seasonal snow pack. Photochem Photobiol Sci 2019; 18:1963-1971. [PMID: 31342042 DOI: 10.1039/c9pp00197b] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Sunlight is strongly attenuated by the snowpack, causing irradiance to decrease exponentially with depth. The strength of attenuation is wavelength dependent across the spectrum. Changes in received irradiance and its spectral composition are used by plants as cues for the timing of phenology, and it is known that at shallow depths in the snowpack there is sufficient light for plants to photosynthesize if conditions are otherwise favourable. The spectral composition of solar radiation under snow in the visible region was already determined in the 1970s using scanning spectroradiometers, but spectral attenuation within the ultraviolet region (UV-B 280-315 nm, UV-A 315-400 nm) has not been well characterised because it is difficult to measure. We measured vertical transects of spectral irradiance (290-900 nm) transmitted through a settled seasonal snowpack. The peak transmission of radiation was in the UV-A region in the upper centimetres of the snowpack and transmittance generally declined at longer wavelengths. Given the known action spectra of plant photoreceptors, these results illustrate the possibility that changing UV-A : visible and red : far-red radiation ratios under the snowpack may serve as spectral cues for plants; potentially priming plants for the less stable environment they experience following snowmelt. Array spectrometers open opportunities for rapid and continuous measurement of irradiance in challenging environments, e.g. beneath the snowpack, and capturing changing light conditions for plants. Future research is needed to couple the spectral transmittance of snowpacks differing in their longevity and crystal structure with measurements of the perception and response to radiation by plants under snow.
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Affiliation(s)
- T Matthew Robson
- Organismal and Evolutionary Biology (OEB), Viikki Plant Science Centre (ViPS), P.O. Box 65, Faculty of Biological and Environmental Science, 00014, University of Helsinki, Finland.
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Jensen AM, Warren JM, King AW, Ricciuto DM, Hanson PJ, Wullschleger SD. Simulated projections of boreal forest peatland ecosystem productivity are sensitive to observed seasonality in leaf physiology†. TREE PHYSIOLOGY 2019; 39:556-572. [PMID: 30668859 DOI: 10.1093/treephys/tpy140] [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: 08/03/2018] [Revised: 01/11/2018] [Accepted: 12/07/2018] [Indexed: 06/09/2023]
Abstract
We quantified seasonal CO2 assimilation capacities for seven dominant vascular species in a wet boreal forest peatland then applied data to a land surface model parametrized to the site (ELM-SPRUCE) to test if seasonality in photosynthetic parameters results in differences in simulated plant responses to elevated CO2 and temperature. We collected seasonal leaf-level gas exchange, nutrient content and stand allometric data from the field-layer community (i.e., Maianthemum trifolium (L.) Sloboda), understory shrubs (Rhododendron groenlandicum (Oeder) Kron and Judd, Chamaedaphne calyculata (L.) Moench., Kalmia polifolia Wangenh. and Vaccinium angustifolium Alton.) and overstory trees (Picea mariana (Mill.) B.S.P. and Larix laricina (Du Roi) K. Koch). We found significant interspecific seasonal differences in specific leaf area, nitrogen content (by area; Na) and photosynthetic parameters (i.e., maximum rates of Rubisco carboxylation (Vcmax25°C), electron transport (Jmax25°C) and dark respiration (Rd25°C)), but minimal correlation between foliar Na and Vcmax25°C, Jmax25°C or Rd25°C, which illustrates that nitrogen alone is not a good correlate for physiological processes such as Rubisco activity that can change seasonally in this system. ELM-SPRUCE was sensitive to the introduction of observed interspecific seasonality in Vcmax25°C, Jmax25°C and Rd25°C, leading to simulated enhancement of net primary production (NPP) using seasonally dynamic parameters as compared with use of static parameters. This pattern was particularly pronounced under simulations with higher temperature and elevated CO2, suggesting a key hypothesis to address with future empirical or observational studies as climate changes. Inclusion of species-specific seasonal photosynthetic parameters should improve estimates of boreal ecosystem-level NPP, especially if impacts of seasonal physiological ontogeny can be separated from seasonal thermal acclimation.
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Affiliation(s)
- Anna M Jensen
- Climate Change Science Institute & Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Jeffrey M Warren
- Climate Change Science Institute & Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Anthony W King
- Climate Change Science Institute & Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Daniel M Ricciuto
- Climate Change Science Institute & Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Paul J Hanson
- Climate Change Science Institute & Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Stan D Wullschleger
- Climate Change Science Institute & Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
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