BER Research Highlights

Search Date: August 09, 2020

7 Records match the search term(s):


August 16, 2020

From the Arctic to the Tropics: Multibiome Prediction of Leaf Mass per Area Using Leaf Reflectance

Spectroscopy provides a rapid and accurate means to retrieve foliar traits.

The Science
The traditional approaches used to measure many leaf functional traits, including the amount of leaf mass per unit area (LMA) are destructive, laborious, time consuming, and expensive. On the other hand, a novel spectroscopy approach, which uses measurements of the light reflected by leaves, can be used as an alternative to rapidly and nondestructively infer these foliar traits across plants growing from the high Arctic to the tropics.

The Impact
Earth system models (ESMs) require detailed information on the structural and functional properties of leaves across global biomes to simulate vegetation responses to global change and inform policy decisions. Traditional approaches used to characterize plant properties that are key inputs for ESMs are slow and limited to small geographic areas. However, remote sensing approaches that this research enables can be used to remotely measure these traits over large areas and through time.

Summary
LMA is a key plant trait used in ecological research and climate modeling. This trait reflects fundamental tradeoffs in resource investments to leaf photosynthesis, longevity or robustness, and structure. Characterizing the within and across biome spatial and temporal variabilities in LMA has been a long-standing goal of ecological research and is an essential component for advancing ESMs. In this study, researchers from Brookhaven National Laboratory explored the capacity to predict LMA from leaf spectra across much of the global LMA trait space, with values ranging from 17 to 393 grams (g) per m2. They used leaves collected from a wide range of locations encompassing broad and needleleaf species and upper and lower canopy (i.e., sun and shade) growth environments. They demonstrated the ability to rapidly estimate LMA using only leaf reflectance data with high accuracy and low error. This finding highlights the fact that the leaf economics spectrum is mirrored by a corresponding variation in leaf optical properties, paving the way for this technology to predict the diversity of LMA, and potentially a range of other leaf traits, in ecosystems across global biomes.

Contacts
Program Manager
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Earth and Environmental Systems Sciences Division (SC-33.1)
Environmental System Science
daniel.stover@science.doe.gov

Principal Investigator
Shawn P. Serbin
Brookhaven National Laboratory
Upton, NY
sserbin@bnl.gov

Funding
This work and associated field data collection campaigns were supported by the Next-Generation Ecosystem Experiments projects (NGEE–Arctic and NGEE–Tropics), which are funded by the Terrestrial Ecosystem Science program of the Office of Biological and Environmental Research (BER) within the U.S. Department of Energy (DOE) Office of Science; the National Aeronautics and Space Administration (NASA) Earth and Space Sciences Fellowship (NNX08AV07H) to SPS; NASA Forest Functional Types (NNX12AQ28G) and HyspIRI grants (NNX12AQ28G) and National Science Foundation Macrosystems Biology grant (1638720) to PAT and ELK; and a U.S. Department of Agriculture McIntire-Stennis grant (WIS01809) to PAT and ELK.

Publication
Serbin, S. P., J. Wu, K. S. Ely, E. L. Kruger, P. A. Townsend, R. Meng, B. T. Wolfe, A. Chlus, Z. Wang, and A. Rogers. “From the Arctic to the Tropics: Multibiome prediction of leaf mass per area using leaf reflectance.” New Phytologist 224(4), 1557–68 (2019). [DOI:10.1111/nph.16123].

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Division: SC-23.1 Climate and Environmental Sciences Division, BER


April 09, 2020

The Distribution of Leaf Isoprene and Monoterpene Emissions in the Five Most Abundant Tree Types in the Amazon Basin

Widespread occurrence of photosynthesis-linked volatile isoprenoid emissions in Amazonia.

The Science
Tropical forests are acknowledged to be the largest global source of emissions of the biogenic volatile organic compounds (BVOCs) isoprene (C5H8) and monoterpenes (C10H16). Current synthesis studies suggesting that few tropical species emit isoprenoids (20% to 38%) and that those that do, do so with highly variable emission capacities, including species within the same tree genera. This apparent lack of a clear phylogenetic thread has created difficulties both in linking isoprenoid function with evolution and in developing accurate biosphere-atmosphere models. In this study, a field-portable system was developed to identify and quantify isoprene and monoterpene emissions from leaves in parallel with measuring leaf physiologies including photosynthesis and transpiration. The system will enable the characterization of carbon and energy allocation to the biosynthesis and emission of isoprenoids linked with photosynthesis and their biological and environmental sensitivities (e.g., light, temperature, and carbon dioxide). Using this system, scientists from Lawrence Berkeley National Laboratory (LBNL) conducted a systematic isoprenoid emission study across the five most abundant tree genera in the Amazon basin.

The Impact
The hyperdominant species (numbering 69) across the top five most abundant genera, which make up about 50% of all individuals in the Amazon basin, showed a high abundance of isoprenoid emitters (isoprene, 63.8%; monoterpenes, 17.4%; both isoprene and monoterpenes, 11.6%). Among the abundant genera, only Pouteria had a low frequency of isoprene-emitting species (15.8% of 19 species). In contrast, Protium, Licania, Inga, and Eschweilera were rich in isoprene-emitting species (i.e., 83.3% of 12 species, 61.1% of 18 species, 100% of 8 species, and 100% of 12 species, respectively). In every genus, species were observed with light-dependent isoprene emissions together with β-ocimene emissions. These observations demonstrate that isoprene biological function and phylogenetic relationship studies cannot be conducted without including monoterpenes. These findings support the emerging view of the evolution of isoprene synthases from ocimene synthases. The finding (i.e., 64% of species observed versus 20% suggested in the literature) improves understanding of isoprenoid function-evolution relationships and represents a base for developing more accurate Earth System Models (ESMs).

Summary
Tropical forests are acknowledged to be the largest global source of emissions from isoprene (C5H8) and monoterpenes (C10H16), with current synthesis studies suggesting that few tropical species emit isoprenoids (20% to 38%) and that those do so with highly variable emission capacities, including species within the same genera. This apparent lack of a clear phylogenetic thread has created difficulties both in linking isoprenoid function with evolution and for developing accurate biosphere-atmosphere models. In this study, LBNL scientists present a systematic emission study of “hyperdominant” tree species in the Amazon basin. Across 162 individuals distributed among 25 botanical families and 113 species, isoprenoid emissions were widespread among both early and late successional species (isoprene, 61.9% of the species; monoterpenes, 15.0%; bothisoprene and monoterpenes, 9.7%). The hyperdominant species (69) across the top five most abundant genera, which make up about 50% of all individuals in the basin, had a similar abundance of isoprenoid emitters (isoprene, 63.8%; monoterpenes, 17.4%; both, 11.6%). Among the abundant genera, only Pouteria had a low frequency of isoprene-emitting species (i.e., 15.8% of 19 species). In contrast, Protium, Licania, Inga, and Eschweilera were rich in isoprene-emitting species (i.e., 83.3% of 12 species, 61.1% of 18 species, 100% of 8 species, and 100% of 12 species, respectively). Light-response curves of individuals in each of the five genera showed light-dependent, photosynthesis-linked emission rates of isoprene and monoterpenes. Importantly, in every genus, the scientists observed species with light-dependent isoprene emissions together with monoterpenes including β-ocimene. These observations support the emerging view of the evolution of isoprene synthases from β-ocimene synthases. Study results have important implications for understanding isoprenoid function-evolution relationships and the development of more accurate ESMs.

Contacts
BER Program Manager
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Earth and Environmental Systems Sciences Division (SC-33.1)
Environmental System Science
daniel.stover@science.doe.gov

Principal Investigator
Kolby Jardine
Lawrence Berkeley National Laboratory
Berkeley, CA 94720
kjjardine@lbl.gov

Funding
This material is based on work supported as part of the Next-Generation Ecosystem Experiments (NGEE)–Tropics project funded by the Office of Biological and Environmental Research (BER), within the U.S. Department of Energy Office of Science, through Contract No. DE-AC02-05CH11231 to Lawrence Berkeley National Laboratory (LBNL) as part of DOE’s Terrestrial Ecosystem Science Program. Funding for the data analysis and manuscript preparation was provided by the DOE Office of Science Early Career Research Program under award no. FP00007421 to LBNL. Graduate student support was supported by the National Council for Scientific and Technological Development (CNPq) in Brazil. Logistical and scientific support is acknowledged by the Forest Management (MF), Climate and Environment (CLIAMB), and Large-Scale Biosphere-Atmosphere (LBA) programs at the National Institute for Amazon Research (INPA) in Brazil.

Publications
Jardine, K. J., R. F. Zorzanelli, B. O. Gilmenez, L. R de Oliveira Piva, A. Teixeira, C. G. Fontes, R. Robles, N. Higuchi, J. Q. Chambers, and S. T. Martin. “Leaf isoprene and monoterpene emission distribution across hyperdominant tree genera in the Amazon basin. Phytochemistry 175, 112366 (2020). [DOI:10.1016/j.phytochem.2020.112366].

Jardine, K., R. Zorzanelli, B. Gimenez, E. Robles, and L. Piva. “Development of a portable leaf photosynthesis and volatile organic compounds emission system.” MethodsX 7, 100880 (2020). [DOI:10.1016/j.mex.2020.100880].

Jardine, K., R. Zorzanelli, B. Gimenez, E. Robles, and L. Piva. “Leaf gas exchange and volatile isoprenoid emission dataset of hyperdominant tree genera in the Amazon forest.” Phytochemistry Data in Brief (in press).

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Data DOIs

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Division: SC-23.1 Climate and Environmental Sciences Division, BER


April 06, 2020

The Tundra Trait Team: Advancing Understanding and Model Representation of Tundra Plant Strategies

The largest database of tundra plant traits assembled to date allowed new insights into tundra plant strategies.

The Science
The Tundra Trait Team (TTT) compiled the largest ever database of key tundra plant traits to improve understanding and model representation of tundra plant strategies, trait-environment relationships, and trait variation across spatial scales.

The Impact
The TTT database serves as a foundation for several major new insights about tundra ecosystems, ranging from interactions between soil moisture and tundra plant responses to warming to the unique trait space occupied by tundra plant species growing in harsh environmental conditions that should be better represented by terrestrial biosphere models.

Summary
One of the major outcomes of the sTUNDRA working group at the German Centre for Integrative Biodiversity Research (iDiv) was the compilation of the TTT database—the largest ever compilation of key tundra plant traits (Bjorkman et al. 2018; Global Ecology and Biogeography). The TTT database contains more than 90,000 unique observations of 18 plant traits on 978 tundra species, with nearly twice as many high-latitude observations as the TRY Plant Trait Database for many key traits. Using the most commonly measured tundra plant traits in its database, the TTT developed several major new insights on tundra plant trait strategies: (1) soil moisture moderates increases in tundra plant size and altered resource acquisition strategies across space and over time in response to warming (Bjorkman et al. 2018; Nature); (2) tundra plant size characteristics, which are key drivers of tundra ecosystem function, were poorly captured by the plant functional groups traditionally used by terrestrial biosphere models (Thomas et al. 2019; GEB); and (3) tundra plants exhibit the same dimensions of plant trait variation as species around the world, but they are more constrained in the expression of size-related traits adapted for extreme environmental conditions in the tundra (Thomas et al. 2020; Nature Comm.). The most frequently measured traits in the TTT database were aboveground traits. Although the belowground trait data from Iversen et al. (“The Unseen Iceberg”; 2015) that served as the foundation for the development of the Fine-Root Ecology Database (FRED; Iversen et al. 2017; New Phytol.) were initially compiled as part of the TTT database, there simply were not enough data for global comparisons. This lack of belowground understanding of tundra plant traits has led to the development of a new international working group, the Arctic Underground, which will focus on improving global understanding and model representation of belowground tundra plant traits around the world.

Contacts
BER Program Manager
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Earth and Environmental Systems Sciences Division (SC-33.1)
Environmental System Science
daniel.stover@science.doe.gov

PrincipaI Investigator
Colleen M. Iversen
Oak Ridge National Laboratory
Oak Ridge, TN 37831
iversencm@ornl.gov

Funding
This paper is an outcome of the sTundra working group supported by the Synthesis Centre (sDiv) of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig (DFG FZT 118). Support to investigators was provided as follows: ADB by an iDiv postdoctoral fellowship and The Danish Council for Independent Research–Natural Sciences (DFF 4181-00565 to S.N.). ADB, IHM-S, HJDT, and SA-B. funded by the United Kingdom (U.K.) Natural Environment Research Council (ShrubTundra Project NE/M016323/1 to IHM-S). SN, ABO, SSN, and UAT by the Villum Foundation’s Young Investigator Programme (VKR023456 to SN) and the Carlsberg Foundation (2013-01-0825). NR by the DFG-Forschungszentrum iDiv Halle-Jena-Leipzig and Deutsche Forschungsgemeinschaft DFG (RU 1536/3-1). A. Buc. by EU-F7P INTERACT (262693) and MOBILITY PLUS (1072/MOB/2013/0). ABO additionally by the Danish Council for Independent Research–Natural Sciences (DFF 4181-00565 to SN). JMA by the Carl Tryggers stiftelse för vetenskaplig forskning. AH by the Research Council of Norway (244557/E50). BE and A. Mic. by the Danish National Research Foundation (CENPERM DNRF100). BM by the Soil Conservation Service of Iceland. ERF by the Swiss National Science Foundation (155554). BCF by the Academy of Finland (256991) and Joint Programming Initiative (JPI) Climate (291581). BJE by a National Science Foundation’s (NSF) Advancing Theory in Biology (ATB) CAREER and Macrosystems award. CMI by the Office of Biological and Environmental Research (BER), within the U.S. Department of Energy (DOE) Office of Science, as part of the Next-Generation Ecosystem Experiments (NGEE)–Arctic project. DB by The Swedish Research Council (2015-00465) and Marie Sklodowska Curie Actions co-funding (INCA 600398). EW by NSF (DEB-0415383), University of Wisconsin–Eau Claire (UWEC)–Office of Research and Sponsored Programs (ORSP), and UWEC–Blugold Commitment Differential Tuition (BCDT). GS-S and MI-G. by the University of Zurich Research Priority Program on Global Change and Biodiversity. HDA by NSF Division of Polar Programs (PLR; 1623764, 1304040). ISJ by the Icelandic Research Fund (70255021) and the University of Iceland Research Fund. JDMS by the Research Council of Norway (262064). JSP by the U.S. Fish and Wildlife Service. JCO by Klimaat voor ruimte, Dutch National Research Programme Climate changes Spatial Planning. JFJ, PG, GHRH, EL, NB-L, KAH, LSC, and TZ by the Natural Sciences and Engineering Research Council of Canada (NSERC). GHRH, NB-L., EL, LSC, and LH by ArcticNet. GHRH, NB-L, MTr, and LSC. by the Northern Scientific Training Program. GHRH, EL, and NB-L additionally by the Polar Continental Shelf Program. NB-L additionally by the Fonds de recherche du Quebec: Nature et Technologies and the Centre d’études Nordiques. JP by the European Research Council Synergy grant SyG-2013-610028 IMBALANCE-P. AA-R, OG, and JMN by the Spanish National Parks Autonomous Agency (OAPN; project 534S/2012) and European INTERACT project (262693 Transnational Access). KDT by NSF Arctic Natural Sciences (ANS)-1418123. LES and PAW by the U.K. Natural Environment Research Council Arctic Terrestrial Ecology Special Topic Programme and Arctic Programme (NE/K000284/1 to PAW). PAW additionally by the European Union Fourth Environment and Climate Framework Programme (Project Number ENV4-CT970586). MW by DFG RTG 2010. RDH by NSF. MJS and KNS by the Niwot Ridge Long-Term Ecological Research (LTER; NSF DEB-1637686). HJDT funded by a British Geological Survey’s Natural Environment Research Council (NERC) doctoral training partnership grant (NE/L002558/1). VGO by the Russian Science Foundation (14-50-00029). LB by NSF ANS (1661723). SJG by the National Aeronautics and Space Administration (NASA) Arctic-Boreal Vulnerability Experiment (ABoVE; NNX15AU03A/NNX17AE44G). BB-L as part of the Energy Exascale Earth System Model (E3SM) project of BER, within the DOE Office of Science. AE by the Academy of Finland (projects 253385 and 297191). EK was supported by Swedish Research Council (2015-00498). SDí by CONICET, FONCyT, and SECyT-UNC, Argentina. The study has been supported by the TRY initiative on plant traits (http://www.try-db.org), which is hosted at the Max Planck Institute for Biogeochemistry in Jena, Germany, and is currently supported by DIVERSITAS/Future Earth and the German iDiv Halle-Jena-Leipzig. AD and SCE thank NSF for support to receive training in Bayesian methods (grant 1145200 to N. Thompson Hobbs). The project thanks the governments, parks, field stations, and local and indigenous people for the opportunity to conduct research on their land.

Publications
Thomas, H. J. D., et al. “Global plant trait relationships extend to the climatic extremes of the tundra biome.” Nature Communications 11, 1351 (2020). [DOI:10.1038/s41467-020-15014-4].

Thomas, H. J. D., et al. “Traditional plant functional groups explain plant trait variation in economic but not size-related traits across the tundra biome.” Global Ecology and Biogeography 28(2), 78–95 (2019). [DOI:10.1111/geb.12783].

Bjorkman, A. D., et al. “Plant functional trait change across a warming tundra biome.” Nature 562(7725), 57–62 (2018). [DOI:10.1038/s41586-018-0563-7].

Bjorkman, A. D., et al. “Tundra Trait Team: A database of plant traits spanning the tundra biome.” Global Ecology and Biogeography 27(12), 1402–11 (2018). [DOI:10.1111/geb.12821].

Iversen, C. M., et al. “Viewpoints: A global fine-root ecology database to address belowground challenges in plant ecology.” New Phytologist 215(1), 15–26 (2017). [DOI:10.1111/nph.14486].

Iversen, C. M., et al. “The unseen iceberg: Plant roots in Arctic tundra” (Tansley Review). New Phytologist 205(1), 34–58 (2015). [DOI:10.1111/nph.13003].

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Topic Areas:

Division: SC-23.1 Climate and Environmental Sciences Division, BER


March 31, 2020

Leaf Reflectance Spectroscopy Captures Variation in Carboxylation Capacity Across Species, Canopy Environment, and Leaf Age in Lowland Moist Tropical Forests

Understanding the pronounced seasonal and spatial variation in leaf photosynthetic capacity.

The Science
The annual fluxes of carbon in the tropics play a critical role in regulating Earth’s climate and are highly sensitive to global change; however, the process representation of the factors regulating tropical carbon uptake and loss in Earth System Models (ESMs) is poor. Tropical photosynthesis is an especially critical process to represent accurately in ESMs, and yet very limited information is available on the spatial and temporal patterns of key parameters that regulate leaf-level photosynthesis, such as the maximum carboxylation capacity (known as Vc,max). In addition, the tropics have the highest plant diversity of any terrestrial ecosystem on Earth, making it very challenging for ESMs to capture the important variations in photosynthetic capacity and leaf age across tropical species. This study investigated the capacity to provide much richer information on spatial and seasonal variation in tropical Vc,max across a broad range of tree species, using a spectroscopic approach instead of traditional gas exchange methods.

The Impact
The seasonal and spatial variation in photosynthetic capacity of terrestrial vegetation strongly regulates seasonal to annual fluxes of carbon between the land and the atmosphere, but ESMs currently lack a detailed representation of this variation given data limitations related to the logistical and technical challenges of collecting these data using traditional approaches. However, the spectroscopic approach presented here can be used to rapidly estimate plant photosynthetic capacity across a range of tropical species, leaf phenological stage, and locations, paving the way for a broad-scale remote sensing approach capable of measuring photosynthetic properties over large areas and through time.

Summary
Traditionally, Vc,max is inferred from direct measurements of leaf photosynthetic carbon assimilation rate at saturating light and at different levels of atmospheric carbon dioxide (CO2) concentration to describe the “CO2 response curve” of a leaf, which is then used to derive the maximum carboxylation capacity, or Vc,max. This direct approach is considered the “gold standard” but is also very time consuming and can be logistically challenging in remote areas such as the tropics. Instead, Brookhaven National Laboratory (BNL) scientists participating in the Next-Generation Ecosystem Experiments (NGEE)–Tropics project explored the use of spectroscopy to estimate the Vc,max of tropical leaves using only leaf-level reflectance measurements. To do this they collected leaf age and Vc,max data and linked them with measurements of leaf reflectance from a range of species sampled from tropical forests in Panama and Brazil. These results showed that leaf spectroscopy can rapidly predict Vc,max across species with high accuracy and low error. The team also showed that combining spectroscopic models enables the construction of the Vc,max-age relationship solely from leaf reflectance, suggesting that the spectroscopy technique can capture the seasonal variability in Vc,max in the tropics, potentially providing a powerful new way to inform ESMs.

Contacts
BER Program Manager
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Earth and Environmental Systems Sciences Division (SC-33.1)
Environmental System Science
daniel.stover@science.doe.gov

PrincipaI Investigator
Shawn P. Serbin
Brookhaven National Laboratory
Upton, NY 11973
sserbin@bnl.gov

Funding
This work was supported by the Next-Generation Ecosystem Experiments (NGEE)–Tropics project, which is supported by the Office of Biological and Environmental Research, within the U.S. Department of Energy Office of Science.

Publications
Wu, J., A. Rogers, L. P. Albert, K. Ely, N. Prohaska, B. T. Wolfe, R. C. Oliveira Jr., S. R. Saleska, and S. P. Serbin. “Leaf reflectance spectroscopy captures variation in carboxylation capacity across species, canopy environment and leaf age in lowland moist tropical forests.” New Phytologist 224(2), 663–74. [DOI:10.1111/nph.16029].

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Division: SC-23.1 Climate and Environmental Sciences Division, BER


March 29, 2020

A Historical and Comparative Review of 50 Years of Root Data Collection in Puerto Rico

Knowledge gaps in fine-root data noted for future studies.

The Science
Studies and raw data on root systems in Puerto Rican tropical forests, including data from Spanish-language publications not previously published in English, were synthesized and analyzed in comparison with other tropical studies, and gaps were exposed for future studies.

The Impact
Studies including root data in Puerto Rico are representative for the tropics. However, fine-root functional trait data for tropical ecosystems have not been fully explored. This synthesis will be used to enrich root database representation for the tropics and, ultimately, to better inform Earth System Models.

Summary
Fine roots play an important role in plant nutrition, as well as in carbon, water, and nutrient cycling. Fine roots account for a third of terrestrial net primary production (NPP), and inclusion of their structure and function in global carbon models should improve predictions of ecosystem responses to climate change. Unfortunately, studies focusing on underground plant components are much less frequent than those on aboveground structure. This disparity is more marked in the tropics, where one-third of the planet’s terrestrial NPP is produced. Available tropical forest fine-root data in Puerto Rico are overrepresented considering its land cover. This Caribbean island’s biodiversity, frequency of natural disturbances, ease of access to forests, and long-term plots have created an ideal place for the study of tropical ecological processes. This literature review emphasizes 50 years of root research and patterns revealed around Puerto Rico. The data in this review were compiled from scientific publications, conference reports, and symposiums, and also include new raw data shared by some researchers. Emergent patterns for fine roots in Puerto Rico include the shallower distribution there compared to other tropical forests, the greater root:shoot ratio compared to other tropical meta-analysis, the little variation in root phosphorus concentrations among forest types, and the slow recovery of root biomass after hurricane disturbance. Because more than half the data on roots come from the wet tropical Luquillo Experimental Forest, other habitat types are underrepresented. Gaps in knowledge about fine roots in Puerto Rico’s ecosystems are noted as examples to promote and guide future studies.

Contacts
BER Program Manager
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Earth and Environmental Systems Sciences Division (SC-33.1)
Environmental System Science
daniel.stover@science.doe.gov

Principal Investigator
Richard Norby
Environmental Sciences Division and Climate Change Science Institute
Oak Ridge National Laboratory
Oak Ridge, TN 37831
norbyrj@ornl.gov

Funding
This work was supported by the Climate and Environmental Sciences Division (now Earth and Environmental Systems Sciences Division) of the Office of Biological and Environmental Research (BER), within the U.S. Department of Energy (DOE) Office of Science. Oak Ridge National Laboratory (ORNL) is managed by University of Tennessee (UT)-Battelle, LLC, for DOE under Contract No. DE-AC05-00OR22725.

Publication
Yaffar, D., and R. J. Norby. “A historical and comparative review of 50 years of root data collection in Puerto Rico.” Biotropica 98(2985), 283–97 (2020). DOI:10.1111/btp.12771].

Topic Areas:

Division: SC-23.1 Climate and Environmental Sciences Division, BER


February 14, 2020

Soil “Breathes Out” More CO2 During Warmer Temperatures When Near Large Trees

Tree presence impacts how soils respond to temperature change in coastal forests.

The Science
Soil respiration—the flow of carbon dioxide (CO2) from the soil surface to the atmosphere—is one of the largest carbon fluxes in the terrestrial biosphere. A recent U.S. Department of Energy (DOE)–funded study, conducted in a coastal deciduous forest, investigated the role of tree presence and temperature on soil respiration. Results found soils closer to trees were more sensitive to temperature changes and had higher CO2 emissions. These findings suggest that heterotrophs, such as trees, are more sensitive to temperature changes than autotrophs, like microbes.

The Impact
Monitoring greenhouse gas exchange between trees and soil sheds light on the resilience of coastal soil systems during changing environmental conditions. Soil respiration is influenced by soil temperature, moisture, and the presence of plant roots. Disturbances such as sea level rise, increased extreme weather events, and climate change can have lasting impacts on the global carbon cycle and coastal forest ecosystems. Specifically, these findings could have implications on soil functions and interactions at the ecosystem -scale, helping inform large-scale climate models.

Summary
Led by Stephanie Pennington and Ben Bond-Lamberty of Pacific Northwest National Laboratory, the research team examined soil respiration in a Maryland coastal forest ecosystem over one year. The goal was to determine if and how soil CO2 emissions varied based on proximity to trees, during different seasons and during drier conditions. Soil respiration increased under a number of conditions, including in the presence of trees, during the growing season versus the dormant season, and with greater moisture. The team measured CO2 soil respiration, along with size and species of each tree within a 15-meter radius at nine sites. Researchers found that soils closer to large numbers of larger trees were more sensitive to temperature changes—and had higher CO2 emissions—than soils farther from tree trunks. In their recently published paper in Biogeosciences, the researchers discuss the variable nature of soil respiration, particularly in relation to carbon exchange in coastal forests that are vulnerable to sea level rise and extreme weather events.

Contacts
BER Program Manager
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Earth and Environmental Systems Sciences Division (SC-33.1)
Environmental System Science
daniel.stover@science.doe.gov

PrincipaI Investigators
Stephanie Pennington
Pacific Northwest National Laboratory
Richland, WA 99354
stephanie.pennington@pnnl.gov

Ben Bond-Lamberty
Pacific Northwest National Laboratory
Richland, WA 99354
bondlamberty@pnnl.gov

Funding
This research is part of the ongoing initiative called Predicting Ecosystem Resilience through Multiscale and Integrative Science (PREMIS) at Pacific Northwest National Laboratory (PNNL), a multiprogram national laboratory operated by Battelle for the U.S. Department of Energy (DOE) under Contract No. DE-AC05-76RL01830. PREMIS is supported by the Office of Biological and Environmental Research (BER), within the DOE Office of Science. This project was conducted under PNNL’s Laboratory Directed Research and Development Program. The research was also supported by the Smithsonian Environmental Research Center in Maryland.

Publication
Pennington, S. C., N. G. McDowell, J. P. Megonigal, J. C. Stegen, and B. Bond-Lamberty. “Localized basal area affects soil respiration temperature sensitivity in a coastal deciduous forest.” Biogeosciences 17(3), 771–80 (2020). [DOI:10.5194/bg-17-771-2020].

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Topic Areas:

Division: SC-23.1 Climate and Environmental Sciences Division, BER


January 22, 2020

TRY: A Freely Available Global Plant Trait Database

Resource provides unprecedented coverage of plant morphological, anatomical, physiological, biochemical, and phenological characteristics.

The Science
TRY is a plant trait database with nearly 12 million records describing how plant form and function vary across the globe; all of the data in TRY are now freely available for download by the broader scientific community at try-db.org. These data inform the understanding of ecosystem water, carbon, and nutrient cycling, now and in response to changing environmental conditions.

The Impact
Data in the TRY plant trait database have been downloaded and utilized by more than 200 publications, ranging from Landscape and Urban Planning to Geoscientific Model Development; these publications have been cited more than 10,000 times and have improved the understanding of topics ranging from climate change to plant functional diversity.

Summary
Plant traits—morphological, anatomical, physiological, biochemical and phenological characteristics—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties. Plant trait data underpin research ranging from evolutionary biology, community and functional ecology, and biodiversity conservation, to ecosystem and landscape management, restoration, biogeography, and Earth system modeling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. In particular, the Fine-Root Ecology Database (FRED), supported by the U.S. Department of Energy’s (DOE) Office of Biological and Environmental Research (BER), has contributed 700 new root traits to the TRY database. TRY now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, TRY also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. Despite unprecedented data coverage, reducing data gaps and biases in the TRY database remains a key challenge and requires collaboration with other initiatives such as FRED.

Contacts
BER Program Manager
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Earth and Environmental Systems Sciences Division (SC-33.1)
Environmental System Science
daniel.stover@science.doe.gov

Principal Investigator
Colleen M. Iversen
Oak Ridge National Laboratory
Oak Ridge, TN
iversencm@ornl.gov

Funding
The project is supported by the Max Planck Institute for Biogeochemistry; Max Planck Society; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig; International Programme of Biodiversity Science (DIVERSITAS); International Geosphere-Biosphere Programme (IGBP); Future Earth; French Foundation for Biodiversity Research (FRB); de Groupement d'Intérêt Scientifique (GIS) Climat, Environnement et Société, France; United Kingdom Natural Environment Research Council (NERC); AXA Research Fund; and the Terrestrial Ecosystem Science program of the Office of Biological and Environmental Research within the U.S. Department of Energy (DOE) Office of Science.

Publications
Kattge, J., G. Bönisch, S. Díaz, S. Lavorel, I. C. Prentice, P. Leadley, S. Tautenhahn, G. D. A. Werner, et al. (700+ co-authors). “TRY plant trait database – Enhanced coverage and open access.” Global Change Biology 26(1), 119–88 (2020). [DOI:10.1111/gcb.14904].

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Division: SC-23.1 Climate and Environmental Sciences Division, BER