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Dusenge ME, Warren JM, Reich PB, Ward EJ, Murphy BK, Stefanski A, Bermudez R, Cruz M, McLennan DA, King AW, Montgomery RA, Hanson PJ, Way DA. Photosynthetic capacity in middle-aged larch and spruce acclimates independently to experimental warming and elevated CO 2. PLANT, CELL & ENVIRONMENT 2024. [PMID: 39101396 DOI: 10.1111/pce.15068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Accepted: 07/18/2024] [Indexed: 08/06/2024]
Abstract
Photosynthetic acclimation to both warming and elevated CO2 of boreal trees remains a key uncertainty in modelling the response of photosynthesis to future climates. We investigated the impact of increased growth temperature and elevated CO2 on photosynthetic capacity (Vcmax and Jmax) in mature trees of two North American boreal conifers, tamarack and black spruce. We show that Vcmax and Jmax at a standard temperature of 25°C did not change with warming, while Vcmax and Jmax at their thermal optima (Topt) and growth temperature (Tg) increased. Moreover, Vcmax and Jmax at either 25°C, Topt or Tg decreased with elevated CO2. The Jmax/Vcmax ratio decreased with warming when assessed at both Topt and Tg but did not significantly vary at 25°C. The Jmax/Vcmax increased with elevated CO2 at either reference temperature. We found no significant interaction between warming and elevated CO2 on all traits. If this lack of interaction between warming and elevated CO2 on the Vcmax, Jmax and Jmax/Vcmax ratio is a general trend, it would have significant implications for improving photosynthesis representation in vegetation models. However, future research is required to investigate the widespread nature of this response in a larger number of species and biomes.
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Affiliation(s)
- Mirindi Eric Dusenge
- Department of Biology, Mount Allison University, Sackville, New Brunswick, Canada
- Department of Biology, The University of Western Ontario, London, Ontario, Canada
| | - Jeffrey M Warren
- Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Peter B Reich
- Institute for Global Change Biology, and School for the Environment and Sustainability, University of Michigan, Ann Arbor, Michigan, USA
- Department of Forest Resources, University of Minnesota, Saint Paul, Minnesota, USA
- Hawkesbury Institute for the Environment, University of Western Sydney, Penrith, New South Wales, Australia
| | - Eric J Ward
- Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, USA
| | - Bridget K Murphy
- Department of Biology, The University of Western Ontario, London, Ontario, Canada
- Department of Biology, University of Toronto Mississauga, Mississauga, Ontario, Canada
- Graduate Program in Cell and Systems Biology, University of Toronto, Toronto, Ontario, Canada
| | - Artur Stefanski
- Department of Forest Resources, University of Minnesota, Saint Paul, Minnesota, USA
| | - Raimundo Bermudez
- Department of Forest Resources, University of Minnesota, Saint Paul, Minnesota, USA
| | - Marisol Cruz
- Departamento de Ciencias Biologicas, Universidad de Los Andes, Bogota, Colombia
| | - David A McLennan
- Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Anthony W King
- Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Rebecca A Montgomery
- Department of Forest Resources, University of Minnesota, Saint Paul, Minnesota, USA
| | - Paul J Hanson
- Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Danielle A Way
- Department of Biology, The University of Western Ontario, London, Ontario, Canada
- Division of Plant Sciences, Research School of Biology, The Australian National University, Canberra, Australia
- Nicholas School of the Environment, Duke University, Durham, North Carolina, USA
- Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, New York, USA
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2
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Wang R, Springer KR, Gamon JA. Confounding effects of snow cover on remotely sensed vegetation indices of evergreen and deciduous trees: An experimental study. GLOBAL CHANGE BIOLOGY 2023; 29:6120-6138. [PMID: 37589597 DOI: 10.1111/gcb.16916] [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: 01/19/2023] [Revised: 07/06/2023] [Accepted: 07/07/2023] [Indexed: 08/18/2023]
Abstract
Located at northern latitudes and subject to large seasonal temperature fluctuations, boreal forests are sensitive to the changing climate, with evidence for both increasing and decreasing productivity, depending upon conditions. Optical remote sensing of vegetation indices based on spectral reflectance offers a means of monitoring vegetation photosynthetic activity and provides a powerful tool for observing how boreal forests respond to changing environmental conditions. Reflectance-based remotely sensed optical signals at northern latitude or high-altitude regions are readily confounded by snow coverage, hampering applications of satellite-based vegetation indices in tracking vegetation productivity at large scales. Unraveling the effects of snow can be challenging from satellite data, particularly when validation data are lacking. In this study, we established an experimental system in Alberta, Canada including six boreal tree species, both evergreen and deciduous, to evaluate the confounding effects of snow on three vegetation indices: the normalized difference vegetation index (NDVI), the photochemical reflectance index (PRI), and the chlorophyll/carotenoid index (CCI), all used in tracking vegetation productivity for boreal forests. Our results revealed substantial impacts of snow on canopy reflectance and vegetation indices, expressed as increased albedo, decreased NDVI values and increased PRI and CCI values. These effects varied among species and functional groups (evergreen and deciduous) and different vegetation indices were affected differently, indicating contradictory, confounding effects of snow on these indices. In addition to snow effects, we evaluated the contribution of deciduous trees to vegetation indices in mixed stands of evergreen and deciduous species, which contribute to the observed relationship between greenness-based indices and ecosystem productivity of many evergreen-dominated forests that contain a deciduous component. Our results demonstrate confounding and interacting effects of snow and vegetation type on vegetation indices and illustrate the importance of explicitly considering snow effects in any global-scale photosynthesis monitoring efforts using remotely sensed vegetation indices.
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Affiliation(s)
- Ran Wang
- School of Natural Resources, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Kyle R Springer
- Department of Biological and Environmental Sciences, Concordia University of Edmonton, Edmonton, Alberta, Canada
| | - John A Gamon
- School of Natural Resources, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
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3
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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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Kuai L, Parazoo NC, Shi M, Miller CE, Baker I, Bloom AA, Bowman K, Lee M, Zeng Z, Commane R, Montzka SA, Berry J, Sweeney C, Miller JB, Yung YL. Quantifying Northern High Latitude Gross Primary Productivity (GPP) Using Carbonyl Sulfide (OCS). GLOBAL BIOGEOCHEMICAL CYCLES 2022; 36:e2021GB007216. [PMID: 36590828 PMCID: PMC9787914 DOI: 10.1029/2021gb007216] [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: 10/14/2021] [Revised: 07/21/2022] [Accepted: 08/08/2022] [Indexed: 06/17/2023]
Abstract
The northern high latitude (NHL, 40°N to 90°N) is where the second peak region of gross primary productivity (GPP) other than the tropics. The summer NHL GPP is about 80% of the tropical peak, but both regions are still highly uncertain (Norton et al. 2019, https://doi.org/10.5194/bg-16-3069-2019). Carbonyl sulfide (OCS) provides an important proxy for photosynthetic carbon uptake. Here we optimize the OCS plant uptake fluxes across the NHL by fitting atmospheric concentration simulation with the GEOS-CHEM global transport model to the aircraft profiles acquired over Alaska during NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (2012-2015). We use the empirical biome-specific linear relationship between OCS plant uptake flux and GPP to derive the six plant uptake OCS fluxes from different GPP data. Such GPP-based fluxes are used to drive the concentration simulations. We evaluate the simulations against the independent observations at two ground sites of Alaska. The optimized OCS fluxes suggest the NHL plant uptake OCS flux of -247 Gg S year-1, about 25% stronger than the ensemble mean of the six GPP-based OCS fluxes. GPP-based OCS fluxes systematically underestimate the peak growing season across the NHL, while a subset of models predict early start of season in Alaska, consistent with previous studies of net ecosystem exchange. The OCS optimized GPP of 34 PgC yr-1 for NHL is also about 25% more than the ensembles mean from six GPP data. Further work is needed to fully understand the environmental and biotic drivers and quantify their rate of photosynthetic carbon uptake in Arctic ecosystems.
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Affiliation(s)
- Le Kuai
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | | | - Mingjie Shi
- Pacific Northwest National LaboratoryRichlandWAUSA
| | - Charles E. Miller
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Ian Baker
- Colorado State UniversityFort CollinsCOUSA
| | - Anthony A. Bloom
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Kevin Bowman
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Meemong Lee
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Zhao‐Cheng Zeng
- University of California Los AngelesJIFRESSELos AngelesCAUSA
| | - Roisin Commane
- Lamont‐Doherty Earth Observatory at Columbia UniversityPalisadesNYUSA
| | | | | | | | | | - Yuk L. Yung
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
- California Institute of TechnologyPasadenaCAUSA
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