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Kováč D, Novotný J, Šigut L, Ač A, Peñuelas J, Grace J, Urban O. Estimation of photosynthetic dynamics in forests from daily measured fluorescence and PRI data with adjustment for canopy shadow fraction. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 898:166386. [PMID: 37597564 DOI: 10.1016/j.scitotenv.2023.166386] [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: 06/23/2023] [Revised: 08/10/2023] [Accepted: 08/16/2023] [Indexed: 08/21/2023]
Abstract
We conducted year-long measurements of the photochemical reflectance index (PRI) and solar-induced fluorescence in the O2A oxygen band (SIFA) at a Norway spruce forest and a European beech forest to study relationships of these remote sensing variables to photosynthesis by trees in grown forest stands. Measured PRI and SIFA values were linked to changes in forest gross primary productivity (GPP) and light-use efficiency (LUE). Changes in the shadow fraction (αS) within tree crowns influenced PRI and fluorescence signals. In the spruce forest, the quantum yield of SIFA (FYSIFA) decreased around midday together with photosynthesis and GPP. Such decreases in FYSIFA were accompanied by an increase in the αS. In the beech forest, we detected an increase in FYSIFA together with a decrease in αS in the afternoon hours. The overall sensitivity of PRI to LUE was variable according to the season, presumably influenced by complex changes in photosynthetic pigments. PRI and FYSIFA showed weak correlations with canopy LUE; however, when considered together, the correlation was strengthened (R2 was 0.63 and 0.34 in spruce and beech forest, respectively). Our model predicting LUE dynamics includes a diurnal minimum of PRI and canopy αS to make allowances for seasonal changes in photosynthetic pigments and for diurnal variability of the shadow fraction in forests. The incorporation of these correcting factors allowed us to estimate LUE at R2 = 0.68 (spruce) and 0.53 (beech). The modeling equations appeared sensitive to the absorbed photosynthetically active radiation (APAR), but less sensitive to the GPP of these forests. Substituting pigments correction with introducing differential PRI (ΔPRI) into the model did not significantly improve the LUE estimation across the season. Our results show that the joint use of PRI and fluorescence improves LUE and GPP estimation accuracy in both daily and seasonal observations.
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Affiliation(s)
- Daniel Kováč
- Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, 603 00 Brno, Czech Republic.
| | - Jan Novotný
- Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, 603 00 Brno, Czech Republic
| | - Ladislav Šigut
- Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, 603 00 Brno, Czech Republic
| | - Alexander Ač
- Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, 603 00 Brno, Czech Republic
| | - Josep Peñuelas
- Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, 603 00 Brno, Czech Republic; CSIC, Global Ecology Unit CREAF-CSIC-UAB, E-08193 Bellaterra, Catalonia, Spain; CREAF, E-08193 Cerdanyola del Vallès, Catalonia, Spain
| | - John Grace
- Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, 603 00 Brno, Czech Republic; School of GeoSciences, University of Edinburgh, Crew Bldg, Kings Bldgs, Alexander Crum Brown Rd, Edinburgh EH9 3FF, UK
| | - Otmar Urban
- Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, 603 00 Brno, Czech Republic
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Euskirchen ES, Serbin SP, Carman TB, Fraterrigo JM, Genet H, Iversen CM, Salmon V, McGuire AD. Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2022; 32:e2499. [PMID: 34787932 PMCID: PMC9285828 DOI: 10.1002/eap.2499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 06/22/2021] [Accepted: 07/20/2021] [Indexed: 06/13/2023]
Abstract
As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near Utqiaġvik to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change.
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Affiliation(s)
| | - Shawn P. Serbin
- Terrestrial Ecosystem Science & Technology GroupEnvironmental Sciences DepartmentBrookhaven National LaboratoryUptonNew York11973USA
| | - Tobey B. Carman
- Institute of Arctic BiologyUniversity of Alaska FairbanksFairbanksAlaska99775USA
| | - Jennifer M. Fraterrigo
- Department of Natural Resources and Environmental SciencesUniversity of Illinois at Urbana‐ChampaignUrbanaIllinois61801USA
| | - Hélène Genet
- Institute of Arctic BiologyUniversity of Alaska FairbanksFairbanksAlaska99775USA
| | - Colleen M. Iversen
- Environmental Sciences Division and Climate Change Science InstituteOak Ridge National LaboratoryOak RidgeTennessee37831USA
| | - Verity Salmon
- Environmental Sciences Division and Climate Change Science InstituteOak Ridge National LaboratoryOak RidgeTennessee37831USA
| | - A. David McGuire
- Institute of Arctic BiologyUniversity of Alaska FairbanksFairbanksAlaska99775USA
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Meunier F, Visser MD, Shiklomanov A, Dietze MC, Guzmán Q. JA, Sanchez‐Azofeifa GA, De Deurwaerder HPT, Krishna Moorthy SM, Schnitzer SA, Marvin DC, Longo M, Liu C, Broadbent EN, Almeyda Zambrano AM, Muller‐Landau HC, Detto M, Verbeeck H. Liana optical traits increase tropical forest albedo and reduce ecosystem productivity. GLOBAL CHANGE BIOLOGY 2022; 28:227-244. [PMID: 34651375 PMCID: PMC9298317 DOI: 10.1111/gcb.15928] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/30/2021] [Accepted: 10/07/2021] [Indexed: 06/13/2023]
Abstract
Lianas are a key growth form in tropical forests. Their lack of self-supporting tissues and their vertical position on top of the canopy make them strong competitors of resources. A few pioneer studies have shown that liana optical traits differ on average from those of colocated trees. Those trait discrepancies were hypothesized to be responsible for the competitive advantage of lianas over trees. Yet, in the absence of reliable modelling tools, it is impossible to unravel their impact on the forest energy balance, light competition, and on the liana success in Neotropical forests. To bridge this gap, we performed a meta-analysis of the literature to gather all published liana leaf optical spectra, as well as all canopy spectra measured over different levels of liana infestation. We then used a Bayesian data assimilation framework applied to two radiative transfer models (RTMs) covering the leaf and canopy scales to derive tropical tree and liana trait distributions, which finally informed a full dynamic vegetation model. According to the RTMs inversion, lianas grew thinner, more horizontal leaves with lower pigment concentrations. Those traits made the lianas very efficient at light interception and significantly modified the forest energy balance and its carbon cycle. While forest albedo increased by 14% in the shortwave, light availability was reduced in the understorey (-30% of the PAR radiation) and soil temperature decreased by 0.5°C. Those liana-specific traits were also responsible for a significant reduction of tree (-19%) and ecosystem (-7%) gross primary productivity (GPP) while lianas benefited from them (their GPP increased by +27%). This study provides a novel mechanistic explanation to the increase in liana abundance, new evidence of the impact of lianas on forest functioning, and paves the way for the evaluation of the large-scale impacts of lianas on forest biogeochemical cycles.
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Affiliation(s)
- Félicien Meunier
- CAVElab—Computational and Applied Vegetation EcologyDepartment of EnvironmentGhent UniversityGhentBelgium
- Department of Earth and EnvironmentBoston UniversityBostonMassachusettsUSA
| | - Marco D. Visser
- Department of Ecology and Evolutionary BiologyPrinceton UniversityPrincetonNew JerseyUSA
- Institute of Environmental SciencesLeiden UniversityLeidenThe Netherlands
| | | | - Michael C. Dietze
- Department of Earth and EnvironmentBoston UniversityBostonMassachusettsUSA
| | - J. Antonio Guzmán Q.
- Centre for Earth Observation Sciences (CEOS)Earth and Atmospheric Sciences DepartmentUniversity of AlbertaEdmontonAlbertaCanada
| | - G. Arturo Sanchez‐Azofeifa
- Centre for Earth Observation Sciences (CEOS)Earth and Atmospheric Sciences DepartmentUniversity of AlbertaEdmontonAlbertaCanada
- Smithsonian Tropical Research InstituteBalboaPanama
| | | | - Sruthi M. Krishna Moorthy
- CAVElab—Computational and Applied Vegetation EcologyDepartment of EnvironmentGhent UniversityGhentBelgium
| | - Stefan A. Schnitzer
- Smithsonian Tropical Research InstituteBalboaPanama
- Department of Biological SciencesMarquette UniversityMilwaukeeWisconsinUSA
| | | | - Marcos Longo
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCaliforniaUSA
| | - Chang Liu
- CAVElab—Computational and Applied Vegetation EcologyDepartment of EnvironmentGhent UniversityGhentBelgium
| | - Eben N. Broadbent
- Spatial Ecology and Conservation (SPEC) Lab, School of Forest, Fisheries, and Geomatics SciencesUniversity of FloridaGainesvilleFloridaUSA
- Spatial Ecology and Conservation (SPEC) Lab, Center for Latin American StudiesUniversity of FloridaGainesvilleFloridaUSA
| | - Angelica M. Almeyda Zambrano
- Spatial Ecology and Conservation (SPEC) Lab, Center for Latin American StudiesUniversity of FloridaGainesvilleFloridaUSA
| | | | - Matteo Detto
- Department of Ecology and Evolutionary BiologyPrinceton UniversityPrincetonNew JerseyUSA
- Smithsonian Tropical Research InstituteBalboaPanama
| | - Hans Verbeeck
- CAVElab—Computational and Applied Vegetation EcologyDepartment of EnvironmentGhent UniversityGhentBelgium
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Plekhanova E, Niklaus PA, Gastellu-Etchegorry JP, Schaepman-Strub G. How does leaf functional diversity affect the light environment in forest canopies? An in-silico biodiversity experiment. Ecol Modell 2021. [DOI: 10.1016/j.ecolmodel.2020.109394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Meunier F, Verbeeck H, Cowdery B, Schnitzer SA, Smith‐Martin CM, Powers JS, Xu X, Slot M, De Deurwaerder HPT, Detto M, Bonal D, Longo M, Santiago LS, Dietze M. Unraveling the relative role of light and water competition between lianas and trees in tropical forests: A vegetation model analysis. THE JOURNAL OF ECOLOGY 2021; 109:519-540. [PMID: 33536686 PMCID: PMC7839527 DOI: 10.1111/1365-2745.13540] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Accepted: 10/16/2020] [Indexed: 05/05/2023]
Abstract
Despite their low contribution to forest carbon stocks, lianas (woody vines) play an important role in the carbon dynamics of tropical forests. As structural parasites, they hinder tree survival, growth and fecundity; hence, they negatively impact net ecosystem productivity and long-term carbon sequestration.Competition (for water and light) drives various forest processes and depends on the local abundance of resources over time. However, evaluating the relative role of resource availability on the interactions between lianas and trees from empirical observations is particularly challenging. Previous approaches have used labour-intensive and ecosystem-scale manipulation experiments, which are infeasible in most situations.We propose to circumvent this challenge by evaluating the uncertainty of water and light capture processes of a process-based vegetation model (ED2) including the liana growth form. We further developed the liana plant functional type in ED2 to mechanistically simulate water uptake and transport from roots to leaves, and start the model from prescribed initial conditions. We then used the PEcAn bioinformatics platform to constrain liana parameters and run uncertainty analyses.Baseline runs successfully reproduced ecosystem gas exchange fluxes (gross primary productivity and latent heat) and forest structural features (leaf area index, aboveground biomass) in two sites (Barro Colorado Island, Panama and Paracou, French Guiana) characterized by different rainfall regimes and levels of liana abundance.Model uncertainty analyses revealed that water limitation was the factor driving the competition between trees and lianas at the drier site (BCI), and during the relatively short dry season of the wetter site (Paracou). In young patches, light competition dominated in Paracou but alternated with water competition between the wet and the dry season on BCI according to the model simulations.The modelling workflow also identified key liana traits (photosynthetic quantum efficiency, stomatal regulation parameters, allometric relationships) and processes (water use, respiration, climbing) driving the model uncertainty. They should be considered as priorities for future data acquisition and model development to improve predictions of the carbon dynamics of liana-infested forests. Synthesis. Competition for water plays a larger role in the interaction between lianas and trees than previously hypothesized, as demonstrated by simulations from a process-based vegetation model.
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Affiliation(s)
- Félicien Meunier
- Computational and Applied Vegetation EcologyDepartment of EnvironmentGhent UniversityGhentBelgium
- Department of Earth and EnvironmentBoston UniversityBostonMAUSA
| | - Hans Verbeeck
- Computational and Applied Vegetation EcologyDepartment of EnvironmentGhent UniversityGhentBelgium
| | - Betsy Cowdery
- Department of Earth and EnvironmentBoston UniversityBostonMAUSA
| | - Stefan A. Schnitzer
- Smithsonian Tropical Research InstituteApartadoPanama
- Department of Biological SciencesMarquette UniversityMilwaukeeWIUSA
| | - Chris M. Smith‐Martin
- Department of Ecology, Evolution and Evolutionary BiologyColumbia UniversityNew YorkNYUSA
| | - Jennifer S. Powers
- Smithsonian Tropical Research InstituteApartadoPanama
- Department of Ecology, Evolution, and BehaviorUniversity of MinnesotaSt. PaulMNUSA
| | - Xiangtao Xu
- Department of Ecology and Evolutionary BiologyCornell UniversityIthacaNYUSA
| | - Martijn Slot
- Smithsonian Tropical Research InstituteApartadoPanama
| | - Hannes P. T. De Deurwaerder
- Computational and Applied Vegetation EcologyDepartment of EnvironmentGhent UniversityGhentBelgium
- Department of Ecology and Evolutionary BiologyPrinceton UniversityPrincetonNJUSA
| | - Matteo Detto
- Smithsonian Tropical Research InstituteApartadoPanama
- Department of Ecology and Evolutionary BiologyPrinceton UniversityPrincetonNJUSA
| | - Damien Bonal
- Université de LorraineAgroParisTechINRAEUMR SilvaNancyFrance
| | - Marcos Longo
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Louis S. Santiago
- Smithsonian Tropical Research InstituteApartadoPanama
- Department of Botany and Plant SciencesUniversity of CaliforniaRiversideCAUSA
| | - Michael Dietze
- Department of Earth and EnvironmentBoston UniversityBostonMAUSA
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Shiklomanov AN, Bond-Lamberty B, Atkins JW, Gough CM. Structure and parameter uncertainty in centennial projections of forest community structure and carbon cycling. GLOBAL CHANGE BIOLOGY 2020; 26:6080-6096. [PMID: 32846039 DOI: 10.1111/gcb.15164] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 04/10/2020] [Accepted: 04/30/2020] [Indexed: 06/11/2023]
Abstract
Secondary forest regrowth shapes community succession and biogeochemistry for decades, including in the Upper Great Lakes region. Vegetation models encapsulate our understanding of forest function, and whether models can reproduce multi-decadal succession patterns is an indication of our ability to predict forest responses to future change. We test the ability of a vegetation model to simulate C cycling and community composition during 100 years of forest regrowth following stand-replacing disturbance, asking (a) Which processes and parameters are most important to accurately model Upper Midwest forest succession? (b) What is the relative importance of model structure versus parameter values to these predictions? We ran ensembles of the Ecosystem Demography model v2.2 with different representations of processes important to competition for light. We compared the magnitude of structural and parameter uncertainty and assessed which sub-model-parameter combinations best reproduced observed C fluxes and community composition. On average, our simulations underestimated observed net primary productivity (NPP) and leaf area index (LAI) after 100 years and predicted complete dominance by a single plant functional type (PFT). Out of 4,000 simulations, only nine fell within the observed range of both NPP and LAI, but these predicted unrealistically complete dominance by either early hardwood or pine PFTs. A different set of seven simulations were ecologically plausible but under-predicted observed NPP and LAI. Parameter uncertainty was large; NPP and LAI ranged from ~0% to >200% of their mean value, and any PFT could become dominant. The two parameters that contributed most to uncertainty in predicted NPP were plant-soil water conductance and growth respiration, both unobservable empirical coefficients. We conclude that (a) parameter uncertainty is more important than structural uncertainty, at least for ED-2.2 in Upper Midwest forests and (b) simulating both productivity and plant community composition accurately without physically unrealistic parameters remains challenging for demographic vegetation models.
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Affiliation(s)
- Alexey N Shiklomanov
- NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA
| | - Ben Bond-Lamberty
- Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA
| | - Jeff W Atkins
- Department of Biology, Virginia Commonwealth University, Richmond, VA, USA
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