BER Research Highlights

Search Date: May 27, 2020

20 Records match the search term(s):


August 08, 2019

Nutrient-Hungry Peatland Microbes Reduce Carbon Loss Under Warmer Conditions

Enzyme production in peatlands reduces carbon lost to respiration under future high temperatures.

The Science
As atmospheric temperatures and carbon dioxide concentrations rise, photosynthesis by plants is expected to increase, leading to more photosynthate released by roots to the soil microbial community. Researchers from Pacific Northwest National Laboratory and Iowa State University examined the response of boreal peatland soils under future high temperatures. The team found that the peatland’s soil microbial communities allocated more carbon to enzyme production in search of phosphorus as temperatures climbed. This diversion of carbon resources could reduce future carbon losses by microbial respiration from the peatland.

The Impact
As boreal peatlands face warmer and drier conditions, it is expected that more carbon will be lost from these carbon-rich soils through increased microbial activity. This study showed that enhanced respiration and concomitant loss of carbon is potentially constrained by nutrient demands of the microorganisms. This tradeoff may help the peatland ecosystem retain soil carbon as temperatures warm.

Summary
Root exudates are carbon compounds, such as sugars and organic acids, which are easily consumed by soil microorganisms. With a warming climate, science suggests that increased photosynthesis by plants could lead to more photosynthate released as root exudates to the soil microbial community. To examine this question, researchers used laboratory incubations to control both temperature and moisture and simulate belowground substrate additions under an accelerated growing season. Results showed that with a moderate increase in temperature, the addition of common root exude compounds in peatlands initially increased carbon lost through microbial respiration above those treatments receiving water only. However, when pushed to future expected high temperatures, additional exudate compounds dampened the amount of additional carbon respired as compared to treatments receiving water only. This reduction in respiration suggests the microorganisms allocated carbon compounds to enzyme production to mine for limited resources instead of respiring carbon. The data also support the idea that boreal peatland microbial communities maintain a more narrow range in function, measured as respiration, across a range in climate conditions. A wide climatic niche in addition to reallocation of carbon resources dampens the magnitude of change in carbon respiration with increasing temperatures.

Contacts
BER

Daniel B. Stover, PhD
Program Manager, Terrestrial Ecosystem Science
Climate and Environmental Sciences Division
daniel.stover@science.doe.gov

PNNL
Kirsten Hofmockel
Biological and Environmental Sciences Directorate
kirsten.hofmockel@pnnl.gov

Funding
This material is based on work supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science (TES) Program, under grant ER65430 to Iowa State University. The SPRUCE experiment is managed by Oak Ridge National Laboratory, which is managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725. 

Publications
Keiser, A. D., M. Smith, S. Bell, and K. S. Hofmockel. “Peatland microbial community response to altered climate tempered by nutrient availability.” Soil Biology and Biochemistry 137(107561), (2019). [10.1016/j.soilbio.2019.107561]

Topic Areas:

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


August 05, 2019

Amazon Forest Response to CO2 Fertilization Dependent on Plant Phosphorus Acquisition

AmazonFACE Model Intercomparison.

The Science
Plant growth is dependent on the availability of nutrients such as nitrogen, phosphorous, and potassium in the soil. Despite the importance of phosphorous in plant processes (e.g., growth and photosynthesis), global Earth system models used in the Coupled Model Intercomparison Project (CMIP5) have not previously included the effects of its availability in studying the global carbon cycle. This study shows that phosphorus availability could greatly reduce the projected CO2-induced carbon sink in Amazon rainforests. This study suggests that the Amazon rainforest response to increasing atmospheric CO2 depends on the ability of trees to upregulate phosphorus acquisition in response to increased carbon availability.

The Impact
Currently, CMIP5 models predict that Amazon rainforests will continue to act as carbon sinks in the future due to the CO2 fertilization effect. However, the role of phosphorus availability (which is impoverished across the Amazon Basin yet controls forest functioning) has not been considered within CMIP5 simulations. This study suggests that the CMIP5 predicted carbon sink would likely be much less due to phosphorus limitation, suggesting that Amazon rainforests may be less resilient to climate change than previously assumed.

Summary
An ensemble of 14 terrestrial ecosystem models was used to simulate the planned free-air CO2 enrichment experiment, AmazonFACE. Model simulations showed that phosphorus availability reduced the projected CO2- induced carbon sink by about 50% compared to estimates from models assuming no phosphorus limitation.

Large variations in ecosystem responses to elevated CO2 among phosphorous-enabled models (ranging from 5 to 140 g C m-2 yr-2 in biomass carbon response) are mainly due to contrasting representations of plant phosphorus use and acquisition strategies among models. This study highlights the importance of phosphorus acquisition and use, including alternative strategies, in Amazon rainforest responses to increasing atmospheric CO2 concentration.

Contacts (BER PM)
Dan Stover and Sally McFarlane (SC-23.1)
daniel.stover@science.doe.gov and sally.mcfarlane@science.doe.gov

(PI Contact)
Jeffrey Q. Chambers
Lawrence Berkeley National Lab
jchambers@lbl.gov

Funding
DE-AC02-05CH11231 as part of the Next-Generation Ecosystem Experiments–Tropics (NGEE-Tropics) and Energy Exascale Earth System Model (E3SM) programs.

Publication
Fleischer, K., A. Rammig, M. G. De Kauwe, A. P. Walker, T. F. Domingues, L. Fuchslueger, S. Garcia, D. Goll, A. Grandis, M. Jiang, V. E. Haverd, F. Hofhansl, J. Holm, B. Kruijt, F. Leung, B. Medlyn, L. M. Mercado, R. J. Norby, B. C. Pak, B. Quesada, C. von Randow, K. Schaap, O. Valverde-Barrantes, Y. Wang, X. Yang, S. Zaehle, Q. Zhu, and D. Lapola. “Amazon forest responses to CO2 fertilization dependent on plant phosphorus acquisition.” Nature Geoscience 12, 736–41 (2019). [DOI: 10.1038/s41561-019-0404-9]

Topic Areas:

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


July 29, 2019

A Slippery Slope: Soil Carbon Destabilization

Carbon gain or loss depends on the balance between competing biological, chemical, and physical reactions.

The Science
Despite a breadth of research on carbon accrual and persistence in soils, scientists lack a strong, general understanding of the mechanisms through which soil organic carbon (SOC) is destabilized in soils. In a new review article, researchers synthesized principles of soil chemistry, physics, and biology to explain carbon loss in soils. They found that destabilization does not equal stabilization in reverse. Rather, carbon gain or loss depends on the balance among competing biological, chemical, and physical reactions that can be altered by changes in weather and temperature.

The Impact
Rates of soil carbon respiration are increasing with current changes in climate and land use. Therefore, understanding destabilization processes in the soil carbon cycle is imperative. This review informs a more robust understanding of the processes that result in carbon loss and feedbacks to the Earth system. With this context, empirical and computational scientists can target better questions about the potential for soils to affect climate through the carbon cycle, which is important for improving predictive biogeochemical and climate models.

Summary
Most empirical and modeling research on soil carbon dynamics focuses on processes that control and promote carbon stabilization. However, the mechanisms through which SOC is destabilized in soils may be even more important to understand. Destabilization processes occur as SOC shifts from a “protected” or passive state, to an “available” or active state. In the available state, microbes can transform soil carbon to gaseous or soluble forms that are then lost from the soil.

The reviewers, from Pacific Northwest National Laboratory, Dartmouth College, and Oregon State University, considered two well-known phenomena—soil carbon priming and the Birch effect—to show how different mechanisms interact to increase carbon losses. They categorized carbon destabilization processes into three general categories: (1) release from physical occlusion through processes such as tillage, bioturbation, or freeze-thaw and wetting-drying cycles; (2) carbon desorption from soil solids and colloids; and (3) increased carbon metabolism by microbes.

By considering the different physical, chemical, and biological controls as processes that contribute to SOC destabilization, researchers can develop new hypotheses about the persistence and vulnerability of carbon in soils and make more accurate and robust predictions of soil carbon cycling in a changing environment.

Contacts (BER PM)
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Terrestrial Ecosystem Science
daniel.stover@science.doe.gov

PNNL Contact
Vanessa Bailey, Pacific Northwest National Laboratory, vanessa.bailey@pnnl.gov

Funding
V. L. Bailey was supported by the U.S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research as part of the Terrestrial Ecosystem Science program. Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC05-557 76RL01830. K. Lajtha was supported by National Science Foundation DEB-1257032.

Publication
Bailey, V., C. Hicks Pries, and K. Lajtha. “What do we know about soil carbon?” Environmental Research Letters 14(8), 083004 (2019). [DOI: 10.1088/1748-9326/ab2c11]

Topic Areas:

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


July 15, 2019

Field Evaluation of Gas Analyzers for Measuring Ecosystem Fluxes

How gas analyzer type and correction method impact measured fluxes.

The Science
A side-by-side comparison was conducted of five gas analyzers commonly used to measure ecosystem fluxes of water and carbon dioxide in observation networks such as AmeriFlux. Findings demonstrate that the correction methods applied play a significant role in the measured fluxes.

The Impact
The work describes a new spectral correction method for use in eddy covariance flux calculations that improves upon existing methods across a range of gas analyzers. Due to the variability of fluxes arising solely from the correction method used, researchers emphasize the importance of reporting the correction method as metadata when publishing and sharing flux data.

Summary
The eddy covariance technique (EC) is used at hundreds of field sites worldwide to measure trace gas exchange between the surface and the atmosphere. Data quality and correction methods for EC have been studied empirically and theoretically for many years. The recent development of new gas analyzers has led to an increase in technological options for users. Open-path (no inlet tube) and closed-path (long inlet tube) sensors have long been used, whereas enclosed-path (short inlet tube) sensors are relatively new. Researchers from Lawrence Berkeley National Laboratory and the AmeriFlux Network used five gas analyzers and three sonic anemometers deployed in an agricultural research field in Davis, California. Two different experimental setups were evaluated for 3-month periods. Two established spectral correction methods, as well as a new approach (described in the manuscript), were applied and evaluated for all analyzers. All gas analyzers were found to measure fluxes comparably, if appropriate corrections are applied and quality control measures are taken. Compared to carbon dioxide fluxes, water vapor fluxes were the most variable and sensitive to the gas analyzer type and correction method. Gas analyzers with inlet tubes exhibited larger signal attenuation for water vapor and should be corrected with empirical correction methods. This study provides valuable information for the eddy covariance community to help determine the best sensor, approach, and correction method at sites that meet their specific research questions, as well as potential issues with comparing multiple field sites.

Contacts (BER PM)
Daniel B. Stover
SC-23.1
Daniel.Stover@science.doe.gov

(PI Contact)
Sébastien Biraud
Lawrence Berkeley National Laboratory
scbiraud@lbl.gov

Funding
The work was supported by the Office of Biological and Environmental Research within the U.S. Department of Energy’s Office of Science as part of the Terrestrial Ecosystem Science program under contract DEAC0205CH11231 to Lawrence Berkeley National Laboratory.

Publications
Polonik, P., et al.. “Comparison of gas analyzers for eddy covariance: Effects of analyzer type and spectral corrections on fluxes.” Agriculture and Forest Meteorology 272–273, 128–42 (2019). [DOI: 10.1016/j.agrformet.2019.02.010]

Topic Areas:

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


June 17, 2019

Microbial Evolution: Nature Leads, Nurture Supports

(Microbial Evolution: Nature Leads, Nurture Supports

Across ecosystems, microbial traits are preserved along lineages, much like in multicellular organisms, and can improve the development of soil models.

The Science
To better predict how microbes influence how much carbon moves through the water, air, and land, scientists want to compare the influence of evolution (“nature”) and the surrounding climate (“nurture”). Based on an extensive study across environments, from mixed conifer forest to high-desert grassland, the team suggests that microbes are not so different from larger, more complex forms of life. That is, in determining species traits, nature takes the lead, while nurture plays a supporting role.

The Impact
With microbial species, less is known about the relative role of nature versus nurture than desired. Why? Microbes’ small size and great diversity make measuring their traits in nature challenging. This study offers an improved understanding of microbial trait distribution, which influences nutrient cycling, such as growth rate and carbon usage. How bacterial species influence soil carbon cycling may help enhance models to reduce uncertainty when forecasting soil carbon feedbacks to global change.

Summary
How much of a microbe’s makeup and destiny is determined by where it finds itself in the world, and how much is explained by its evolutionary past? While evolutionarily encoded traits (nature) have been more predictive in plants and animals than environmental variation (nurture), the small size and great diversity of microbial species have made it challenging to answer this question in life’s microscopic realm. Now, a team of researchers at West Virginia University, Northern Arizona University, University of Massachusetts Amherst, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory used a new approach to determine the traits of microbial species by tracking isotopes into their DNA, indicating rates of carbon assimilation and growth. The team measured these traits in four ecosystems along a gradient in elevation, temperature, and moisture.

They found that, as with plant and animal species, the evolutionary history of soil bacteria (that is, nature) explained more variation in the measured traits than did their local environment (that is, nurture). Evolutionary history explained up to 65 percent of the variation in trait values, while the variation explained by the ecosystem never exceeded 20 percent. Even across vast changes in temperature and precipitation, the traits of microbial species remained relatively consistent. For example, microbial species and families that rapidly used carbon in soil from warm desert grassland showed very similar activity rates when assessed in soil from a comparatively cool and wet forest.

Determining whether nature or nurture has more influence has practical value: if traits are hard-wired by evolution, they are consistent and can be used to make predictions about the natural world.

(Contacts)
BER Program Manager
Dawn Adin
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Biological Systems Science Division (SC-23.2)
Foundational Genomics Research
dawn.adin@science.doe.gov

(Principal Investigator)
Bruce Hungate
Northern Arizona University
Bruce.Hungate@nau.edu

Funding
This work was supported by the Biological Systems Science Division’s Genomic Science program (No. DE-SC0016207) of the Office of Biological and Environmental Research (BER), within the U.S. Department of Energy (DOE) Office of Science. It also was supported by the National Science Foundation’s Dimensions of Biodiversity (Nos. DEB-1645596 and DEB-1241094).

Publications
Morrissey, E. M., R. L. Mau, M. Hayer, et al., “Evolutionary history constrains microbial traits across environmental variation.Nature Ecology and Evolution 3, 1064–1069 (2019). [DOI:10.1038/s41559-019-0918-y].

Related Links
Northern Arizona University: Center for Ecosystem Science and Society

Contact: Cathy Ronning, SC-23.2, (301) 903-9549

Topic Areas:

Division: SC-23.2 Biological Systems Science Division, BER


May 21, 2019

Using Remotely Sensed Data to Advance Streamflow Forecasts in Subarctic Watersheds

MODIS fractional snow cover area improves streamflow modeling in undersampled regions of Alaska.

The Science
In the remote and understudied boreal forest of interior Alaska, scientists funded by the Next-Generation Ecosystem Experiments (NGEE)–Arctic project applied remotely sensed snow cover observations to improve snowmelt and streamflow forecasting in river basins with spatially and temporally sparse gaging networks.

The Impact
This paper highlights the challenges of modeling in subarctic environments through assimilating snow remote-sensing data with the discovery that assimilation improves streamflow forecasts in undermonitored systems. The implications of this work have great value for streamflow forecasting and indicate the utility of the remotely sensed fractional snow cover data in the subarctic. Additionally, their improvements to a widely used snow model increase robustness of the hydrological simulations, in support of the U.S. National Weather Service's move toward a physically based National Water Model.

Summary
This study seeks to integrate two different strains of the moderate resolution imaging spectroradiometer (MODIS) remotely sensed fractional snow cover area observations into the Alaska Pacific River Forecast Center’s modeling framework and analyze the results in four watersheds located near Fairbanks, Alaska. This analysis revealed that in well-instrumented systems, such as the Chena River basin, streamflow forecasts were unchanged by the data assimilation. However, for basins with poorly observed precipitation and streamflow, such as the Chatanika River, improving observations of fractional snow cover extent in the models led to a significantly better forecast of streamflow. Because Arctic systems are largely undermonitored, the Chatanika is representative of the challenge in understanding the hydrology of northern rivers, for which improvements in streamflow forecasting are badly needed to mitigate and plan for a changing north.

Contacts (BER PM)
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Terrestrial Ecosystem Science
daniel.stover@science.doe.gov

(PI Contact)
Katrina E. Bennett
Los Alamos National Laboratory, Earth and Environmental Sciences, Hydrologist and Team Leader
kbennett@lanl.gov

Jessica E. Cherry
Alaska Pacific River Forecast Center
jessica.cherry@noaa.gov

Funding
Alaska Climate Science Center, Natural Science and Engineering Research Council of Canada, GOES-R High Latitude Proving Ground award NA08OAR432075, and U.S. Department of Energy, Office of Science, Biological and Environmental Research program, Next-Generation Ecosystem Experiments (NGEE)–Arctic project.

Publications
Bennett, K. E., J. E. Cherry, B. Balk, and S. Lindsey. “Using MODIS estimates of fractional snow cover area to improve streamflow forecasts in interior Alaska.” Hydrology and Earth System Sciences 23(5), 2439–59 (2019). [DOI: 10.5194/hess-23-2439-2019]

Topic Areas:

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


May 20, 2019

Revealed: The Influence of Microbes on Soil Respiration

Research shows that microbial biomass has a greater influence than expected on how soils react to changes in temperature.

The Science
Millions of microbes living in the soil could influence how soils respond to temperature changes. They also influence the amount of carbon dioxide soils give off or respire. Yet scientists rarely consider these microbes when modeling temperature effects around the world. An international team of scientists analyzed the results of more than two dozen warming experiments to quantify how much these microbes influence soil respiration under various temperatures and in what ways.

The Impact
Increased temperatures often lead to soils giving off more organic carbon. More carbon in the air can in turn increase air temperature. By understanding the influence of microbes living in the soil, scientists can better calculate this carbon-temperature feedback cycle and predict temperature changes more accurately.

Summary
Scientists from Iowa State University, University of Maryland, Pacific Northwest National Laboratory, the Czech Academy of Sciences, and the Environmental Molecular Sciences Laboratory teamed up to review data from 27 warming experiments. These experiments ranged from laboratory studies to observations made at various locations and in various types of soil around the world under temperatures between just above freezing to scorching hot. Based on these studies, the team discovered that, when the mass of microbes decreased, soils were less likely to give off carbon dioxide as temperatures increased. When the mass of microbes increased, soils were more likely to respire carbon dioxide. Changes in respiration rates also varied by type of soil. The results suggest that microbial biomass needs to be explicitly measured and considered in models to calculate changes in temperature and their effect on soil.

BER PM Contact
Paul Bayer
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
DOE Environmental Molecular Sciences Laboratory
paul.bayer@science.doe.gov

PI Contact
Petr Capek
Environmental Molecular Sciences Laboratory
Peter.Capek@pnnl.gov

Funding
This work was supported by the U.S. Department of Energy (DOE),Office of Science, Office of Biological and Environmental Research, Climate and Environmental Sciences Division, including support of the Environmental Molecular Sciences Laboratory, a DOE Office of Science user facility, and the Terrestrial Ecosystem Science program.

Publication
Capek, P., R. Starke, K. S. Hofmockel, B. Bond-Lamberty, and N. Hess. “Apparent temperature sensitivity of soil respiration can result from temperature driven changes in microbial biomass.” Soil Biology and Biochemistry 135, 286–93 (2019). [DOI:10.1016/j.soilbio.2019.05.016]

 

Topic Areas:

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


May 13, 2019

Millennial and Fast-Cycling Arctic Soil Carbon are Equally Sensitive to Warming

Radiocarbon-based evidence from a soil warming experiment was used to understand carbon decomposition.

The Science
This study investigated the effects of warming on Arctic soil carbon and showed that decomposition rates of fast-cycling and slow-cycling soil carbon are equally temperature sensitive. The study used an incubation experiment and a novel method for analyzing radiocarbon content to evaluate soil carbon age and decomposability and to disentangle the effects of warming and substrate depletion on carbon mineralization.

The Impact
In soils from Utqiagvik (formerly Barrow), Alaska, ancient soil carbon was highly vulnerable to warming, with no relationship between temperature sensitivity and historical cycling rate. When soils were thawed and oxygen was not limiting, carbon that had been stored for centuries or millennia was poorly protected against microbial decomposition.

Summary
Intact (nonhomogenized) soil samples from Utqiagvik, Alaska, were sequentially incubated at 5°C and 10°C at Lawrence Berkeley National Laboratory. To account for substrate depletion as the experiment progressed, a third incubation was performed at 5°C. Carbon dioxide (CO2) production rates and natural abundance Δ14C of CO2 were measured after each incubation to evaluate vulnerability to warming of slow-cycling and fast-cycling soil carbon pools. Based on Δ14C values from the first incubation, very old soil carbon was readily decomposable when soils were thawed and aerobic. A novel regression technique was used to estimate temperature sensitivities using bulk (measured) CO2 production rates, and rates partitioned with radiocarbon into fast-cycling (carbon age = 50 years) and slow-cycling (carbon age = 5,000 years) pools. No difference in temperature sensitivity was found between fast-cycling and slow-cycling carbon. These findings suggest that mechanisms other than chemical recalcitrance mediate the effect of warming on soil carbon mineralization.

Contacts (BER PM)
Daniel Stover
SC-23.1
Daniel.Stover@science.doe.gov

(PI Contact)
Margaret Torn
Lawrence Berkeley National Laboratory
mstorn@lbl.gov

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

Publications
Vaughn, L. J. S., and M. S. Torn “14C evidence that millennial and fast-cycling soil carbon are equally sensitive to warming.” Nature Climate Change 9, 437–38 (2019). [DOI: 10.1038/s41558-019-0468-y]

Related Links
https://www.nature.com/articles/s41558-019-0483-z

Topic Areas:

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


April 13, 2019

Soil Property Variation Drives Large Differences in Tropical Forest Secondary Succession

Nutrient limitations and soil texture differences explained plant biomass variation during secondary succession in tropical forest inventories.

The Science
Scientists at the University of Notre Dame used a new mechanistic vegetation dynamics model based on the Ecosystem Demography (ED2) model, which has been augmented to account for nitrogen and phosphorus limitations of vegetation productivity, explicit soil microbial and enzyme processes, and plant-microbe competition for nutrients (Medvigy et al. 2019). The model realistically represented vegetation differences across tropical forests sites that have very large gradients in vegetation biomass and nutrient availability. The researchers used the model to explain observed variations in vegetation at spatial scales finer than those represented in current Earth system models, implying needed improvements to those models.

The Impact
Current land models applied for large-scale assessments of nutrient controls on vegetation processes have large uncertainties. This study used a mechanistic dynamic vegetation model to demonstrate that soil property variations can be mechanistically linked to plant biomass and composition. Representing geodiversity at sub-gridcell scales is therefore critical for large-scale dynamic vegetation models, such as the Department of Energy’s (DOE) Energy Exascale Earth System Model (E3SM) Land Model (ELM)-Functionally Assembled Terrestrial Ecosystem Simulator (FATES) model being developed for the E3SM.

Summary
Observations in tropical forests reveal large variation in biomass and plant composition. In this study, scientists from the University of Notre Dame evaluated whether such variation can emerge solely from realistic variation in a set of commonly measured soil chemical and physical properties. Controlled simulations were performed using a mechanistic model that includes forest dynamics, microbe-mediated biogeochemistry, and competition for nitrogen and phosphorus. Observations from 18 forest inventory plots in Guanacaste, Costa Rica, were used to determine realistic variation in soil properties. In simulations of secondary succession, the across-plot range in plant biomass reached 30% of the mean and was attributable primarily to nutrient limitation and secondarily to soil texture differences that affected water availability. The contributions of different plant functional types to total biomass varied widely across plots and depended on soil nutrient status. In simulations, large variation in plant biomass and ecosystem composition arose mechanistically from realistic variation in soil properties and climate. In general, model predictions can be improved through better representation of soil nutrient processes, including their spatial variation. These results inform ongoing development in DOE’s dynamic vegetation model integrated in E3SM (ELM-FATES).

Contacts (BER PM)

Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Terrestrial Ecosystem Science
daniel.stover@science.doe.gov

Renu Joseph
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Earth and Environmental Systems Modeling
renu.joseph@science.doe.gov

(PI Contact)
David Medvigy, University of Notre Dame, dmedvigy@nd.edu

Funding
David Medvigy, Bonnie Waring, and Jennifer S. Powers were supported by the U.S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research (BER),Terrestrial Ecosystem Science program, award DE-SC0014363. The field plots were maintained by National Science Foundation CAREER grant DEB-1053237 to JSP.

Funding for William J. Riley and Qing Zhu was provided by DOE BER under contract number DE-AC02-05CH11231 as part of the Regional and Global Model Analysis (RGMA) program in the Earth and Environmental Systems Modeling program’s RUBISCO Science Focus Area.

Gangsheng Wang was supported by the Energy Exascale Earth System Model (E3SM) project and the Climate Model Development and Validation (CMDV) project under contract DE-AC05-00OR22725 to Oak Ridge National Laboratory.

Publications
Medvigy, D., G. Wang, Q. Zhu, W. J. Riley, A. Trielweiler, B. Waring, X. Xu, and J. Powers. "Observed variation in soil properties can drive large variation in forest functioning and composition during tropical forest secondary succession." New Phytologist 223(4), 1820–33 (2019). [DOI: 10.1111/nph.15848]

Topic Areas:

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


March 29, 2019

Climate Change Will Result in Large Increase in Methane Emissions in Polygonal Tundra

Methane emissions responded strongly to changes in temperature, atmospheric carbon dioxide, precipitation, and landscape-scale hydrology.

The Science
Scientists from the Next-Generation Ecosystem Experiments (NGEE)–Arctic project used ecosys, a mechanistic three-dimensional ecosystem model, to project how carbon dioxide (CO2) and methane (CH4) emissions at the NGEE–Arctic Utqiagvik polygonal tundra site will change over the 21st century. The model very accurately matched a wide range of NGEE–Arctic observations. CH4 emissions responded strongly to changes in temperature, atmospheric CO2, and precipitation, and they represent large potential radiative feedbacks with climate.

The Impact
Land models predict a wide range of potential permafrost tundra CO2 and CH4 emissions over the 21st century. In this study, a team of scientists from Lawrence Berkeley National Laboratory identified dominant processes responsible for variations of these emissions over time and space. They found that predicted increases in CO2 uptake were offset by large CH4 emissions, and that potential increases in drainage would decrease net CH4 emissions, highlighting the importance of landscape-scale hydrology for 21st century predictions.

Summary
Model projections of CO2 and CH4 emissions in permafrost systems vary widely between land models. In this study, the researchers used ecosys to examine how climate change will affect these emissions in a polygonal tundra site at Utqiagvik (formerly Barrow) Alaska. The model has been thoroughly tested against NGEE–Arctic thermal, hydrological, and biogeochemical observations. During the Representative Concentration Pathway (RCP) 8.5 climate change scenario from 2015 to 2085, rising air temperatures, atmospheric CO2, and precipitation (P) increased net primary productivity consistently with biometric estimates. Concurrent increases in heterotrophic respiration (Rh) were offset by increases in CH4 emissions. Both these increases were smaller if boundary conditions were altered to increase landscape drainage, highlighting the importance of these large-scale hydrological dynamics for carbon cycle predictions.

Contacts (BER PM)
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Terrestrial Ecosystem Science
daniel.stover@science.doe.gov

(PI Contact)
William J. Riley, Lawrence Berkeley National Laboratory, wjriley@lbl.gov

Funding
This research was supported by the U.S. Department of Energy Office of Science, Office of Biological and Environmental Research under contract number DE-AC02-05CH11231 as part of the Next-Generation Ecosystem Experiments (NGEE)–Arctic project.

Publications
Grant, R. F., Z. A. Mekonnen, and W. J. Riley. "Modelling climate change impacts on an Arctic polygonal tundra. Part 2: Changes in CO2 and CH4 exchange depend on rates of permafrost thaw as affected by changes in vegetation and drainage." Journal of Geophysical Research-Biogeosciences 125(5), 1323–41 (2019). [DOI: 10.1029/2018JG004645]

Topic Areas:

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


March 29, 2019

Modeling Climate Change Impacts on an Arctic Polygonal Tundra: Rates of Permafrost Thaw Depend on Changes in Vegetation and Drainage

Accounting for 21st century polygonal tundra vegetation changes, and consequent effects on surface energy budgets, slows increases in active-layer deepening.

The Science
University of Alberta and Berkeley Lab researchers used a mechanistic three-dimensional ecosystem model (ecosys) to project how vegetation cover changes in polygonal tundra will interact with soil temperatures and active-layer dynamics (Grant et al. 2019). The model was shown to very accurately match a wide range of Next-Generation Ecosystem Experiments (NGEE)–Arctic observations at the Utqiagvik, Alaska, site. Vegetation and landscape-scale hydrology strongly affect surface energy budgets and thereby active-layer deepening, implying that land models must accurately represent these processes in 21st century simulations.

The Impact
Current land models applied for large-scale assessments of permafrost dynamics have poorly represented many of the processes known to affect these dynamics. In this study, the research team used a mechanistic three-dimensional model to explore the roles that vegetation changes and landscape-scale hydrology over the coming decades will have on soil thermal dynamics. Their results point toward the importance of representing vegetation dynamics (e.g., density and composition) and hydrology at relevant spatial scales, and that doing so will result in smaller changes to soil temperatures and active-layer deepening.

Summary
Model projections of permafrost thaw during the next century diverge widely. This study used ecosys to examine how climate change will affect permafrost thaw in a polygonal tundra at Utqiagvik (formerly Barrow), Alaska. The model was tested against observed diurnal and seasonal variation in energy exchange, soil heat flux, soil temperature (Ts) and active-layer depth (ALD), and interannual variation in observed ALD from 1991 to 2015. During Representative Concentration Pathway (RCP) 8.5 scenario climate change from 2015 to 2085, increases in air temperature and precipitation altered energy exchange by increasing the leaf area index (LAI) of dominant sedge relative to that of moss. Increased carbon dioxide concentrations and sedge LAI imposed greater stomatal control of transpiration and reduced soil heat fluxes, slowing soil warming, limiting increases in evapotranspiration, and thereby causing gradual soil wetting. Larger landscape drainage slowed ALD increases. The predicted rates are closer to those derived from current studies of warming impacts in the region, but were smaller than those of earlier modeling studies, primarily because they did not account for vegetation changes. Therefore, accounting for climate change effects on vegetation density and composition, and consequent effects on surface energy budgets, will cause slower increases in active-layer deepening over the 21st century.

Contacts (BER PM)
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Terrestrial Ecosystem Science
daniel.stover@science.doe.gov

(PI Contact)
William J. Riley, Lawrence Berkeley National Laboratory, wjriley@lbl.gov

Funding
This research was supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under contract number DE-AC02-05CH11231 as part of the Next-Generation Ecosystem Experiments (NGEE)–Arctic project.

Publications
Grant, R. F., Z. A. Mekonnen, and W. J. Riley. "Modelling climate change impacts on an Arctic polygonal tundra. Part 1: Rates of permafrost thaw depend on changes in vegetation and drainage." Journal of Geophysical Research-Biogeosciences 124(5), 1308–22 (2019). [DOI: 10.1029/2018JG004644, 2019]

Topic Areas:

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


March 18, 2019

Theoretical Foundation for Applying Sun-Induced Chlorophyll Fluorescence in Global Photosynthesis Research

An analytical framework is established to guide the observation and modeling of sun-induced chlorophyll fluorescence and its applications in ecosystem science.

The Science
Recent progress in observing sun-induced chlorophyll fluorescence (SIF) provides an unprecedented opportunity to advance photosynthesis research in natural environments. However, an analytical framework to guide SIF studies and integration with the well-developed active fluorescence approaches is lacking. A set of coupled fundamental equations was therefore derived to describe the dynamics of SIF and its relationship with C3 and C4 photosynthesis. These equations show that although SIF is dynamically as complex as photosynthesis, the measured SIF simplifies photosynthetic modeling from the perspective of light reactions by integrating over the dynamic complexities of photosynthesis. Specifically, the measured SIF contains direct information about the actual electron transport from photosystem II to photosystem I, giving a quantifiable link between light and dark reactions. With much-reduced requirements on inputs and parameters, the light reactions-centric, SIF-based biophysical model complements the traditional, dark reactions-centric biochemical model of photosynthesis. The SIF-photosynthesis relationship, however, is nonlinear because photosynthesis saturates at high light while SIF has a stronger tendency to keep increasing as fluorescence quantum yield has a relatively muted sensitivity to light levels.

The Impact
The theory developed in this study clarifies several conflicting issues in the SIF-photosynthesis relationship, provides a solid foundation for SIF research, and points to future research directions.

Summary
Chlorophyll a fluorescence (ChlF) is the emission of red and far-red photons from the excited states of chlorophyll molecules in competition with photochemical and non-photochemical energy uses. It is tightly coupled to photosynthesis at the level of fundamental biochemical and biophysical processes. The feasibility of remotely sensing SIF, which is also referred to as passive ChlF, has stimulated a flurry of research to correlate SIF with gross primary production (GPP) and related variables. This enthusiasm has raised the hope of making concrete progress toward understanding and predicting the dynamics of GPP from canopy to global scales, a recalcitrant challenge that has plagued generations of researchers in ecosystem, plant, and agricultural sciences. However, the precise relationship between SIF and GPP is currently unknown. The theory developed in this study fills this gap. Its application will advance a predictive understanding of several previously underexplored physiological and biophysical processes under natural conditions. Advances can be facilitated by coordinated efforts in plant physiology, remote sensing, and eddy covariance flux observations.

Contact (BER PM)
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Terrestrial Ecosystem Science
daniel.stover@science.doe.gov

PI Contact
Lianhong Gu  
Oak Ridge National Laboratory, lianhong-gu@ornl.gov

Funding
The U. S. Department of Energy, Office of Science, Office of Biological and Environmental Research

Publication
Gu, L., J. Han, J. D. Wood, C. Y. Y. Chang, and Y. Sun. “Sun-induced Chl fluorescence and its importance for biophysical modeling of photosynthesis based on light reactions.” New Phytologist 223(3), 1179–91 (2019). [DOI: 10.1111/nph.15796]

Topic Areas:

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


February 14, 2019

A Decade of CO2 Enrichment Stimulates Wood Growth by 30%

Synthesis of four long-term, DOE supported, CO2 enrichment experiments show that young temperate forests increase carbon uptake at climate-change relevant timescales.

The Science
A synthesis of long-term, DOE-supported experiments shows that in young temperate forests, tree biomass growth increased by 30 % in response to a decade of CO2-enrichment. This response was predictable with knowledge of the plant production response to CO2, and the relationship of wood production to whole plant production under ambient CO2 conditions.

The Impact
CO2-fertilization is the stimulation of gains in plant biomass by increased atmospheric CO2, which creates a feedback on the rate of increase in atmospheric CO2. The complexity combined with the global and decadal scales of this process means that estimates of the size of the feedback remain uncertain. By synthesizing the longest running experiments in forest or woody ecosystems this study develops understanding of the processes that determine CO2-fertilisation at longer timescales and ecosystem spatial scales.

Summary
Stimulation of photosynthesis by increasing atmospheric CO2 can increase plant production, but at longer timescales, may not necessarily increase plant biomass because all the additional production could be in short-lived tissues such as leaves and fine-roots. An international team of scientists, led by Oak Ridge National Laboratory, analyzed the four decade-long CO2 enrichment experiments in forests that measured total plant production and biomass (including below-ground). Using statistical mixed-models they showed that CO2 enrichment increased biomass increment by 1.05 ± 0.26 kg C m-2 over a full decade. This response was predictable with knowledge of the production response to CO2 (0.16 ± 0.03 kg C m-2 y-1) and the biomass retention rate (slope of the relationship between biomass increment and cumulative production; 0.55 ± 0.17) which was independent of CO2. An ensemble of terrestrial ecosystem models failed to predict both terms correctly, but with different reasons among sites. These results demonstrate that a decade of CO2 enrichment stimulates live-biomass increment in temperate, early-succession, forest ecosystems. CO2-independence of the biomass retention rate highlights the value of understanding ambient conditions for interpreting CO2 responses.

Contacts (BER PM)
Daniel Stover
SC-23.1
Terrestrial Ecosystem Science
Daniel.Stover@science.doe.gov

(PI Contact)
Anthony P. Walker
Oak Ridge National Laboratory
walkerap@ornl.gov

Funding
DOE Office of Science Biological and Environmental Research, Terrestrial Ecosystem Science, and Free Air CO2 Enrichment Model Data Synthesis (FACE-MDS).

Publications
Walker, A. P., et al. “Decadal biomass increment in early secondary succession woody ecosystems is increased by CO2 enrichment.” Nature Communications 10, 454 (2019) [DOI: 10.1038/s41467-019-08348-1].

Related Links
Paper
https://facedata.ornl.gov/facemds/
https://data.ess-dive.lbl.gov/view/doi:10.15485/1480328
https://data.ess-dive.lbl.gov/view/doi:10.15485/1480325
https://data.ess-dive.lbl.gov/view/doi:10.15485/1480327

Topic Areas:

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


February 14, 2019

Terrestrial Biosphere Models May Overestimate Arctic CO2 Assimilation if They Do Not Account for the Effect of Low Temperature on Photosynthesis

Reduced ability to utilize light at low temperature limits CO2 uptake at low light.

The Science
Terrestrial biosphere models (TBMs) assume that the amount of carbon dioxide (CO2) taken up by plants per unit of light absorbed (quantum yield) is a global constant. This study found that in Arctic vegetation, growing at low temperature, the quantum yield is reduced, limiting the capacity for CO2 assimilation at low light levels.

The Impact
If TBMs do not account for the reduction in quantum yield at low temperature, they could overestimate the capacity of Arctic ecosystems to take up CO2 when light is limiting photosynthesis.

Summary
How TBMs represent leaf photosynthesis and its sensitivity to temperature are two critical components of understanding and predicting the response of the Arctic carbon cycle to global change. Scientists at Brookhaven National Laboratory measured the effect of temperature on the response of photosynthesis to light in six Arctic plant species and determined the quantum yield of CO2 fixation and the convexity factor, which further describes the response of photosynthesis to light. They also determined leaf absorptance to calculate quantum yield on an absorbed light basis and enable comparison with nine TBMs. The mean quantum yield at 25°C closely agreed with the mean TBM parameterization, but at lower air temperatures, measured quantum yield diverged from TBMs. At 5°C quantum yield was markedly reduced and 60% lower than TBM estimates. The convexity factor also showed a significant reduction between 25°C and 5°C. At 5°C convexity was 38% lower than the common model parameterization. These data show that TBMs are not accounting for observed reductions in quantum yield and convexity that can occur at low temperature. Ignoring these reductions could lead to a marked overestimation of CO2 assimilation at low light and low temperature.

Contacts (BER PM)
Daniel Stover
U.S. Department of Energy Office of Science, Office of Biological and Environmental Research
Climate and Environmental Sciences Division (SC-23.1)
Terrestrial Ecosystem Science
daniel.stover@science.doe.gov

(PI Contact)
Alistair Rogers
Brookhaven National Laboratory
arogers@bnl.gov

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

Publications
Rogers, A., S. P. Serbin, K. S. Ely, and S. D. Wullschleger. “Terrestrial biosphere models may overestimate Arctic CO2 assimilation if they do not account for decreased quantum yield and convexity at low temperature.” New Phytologist 223(1), 167–79. [DOI: 10.1111/nph.15750]

Related Links
https://ngee-arctic.ornl.gov/

Topic Areas:

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


February 01, 2019

A New Entropy-Based Scheme Reveals Dominant Controls on Greenhouse Gas (GHG) Flux Variability in an Arctic Landscape

Soil characteristics, vegetation type, changes in vegetation during the growing season and the onset of seasonal thaw were found to be significant controls on GHG flux variability in a polygonal tundra landscape.

The Science
This study was used to develop, apply and assess a novel entropy-based scheme to characterize temporal variability in greenhouse gases (GHG), i.e., CO2 and CH4 fluxes, and identify controls of such variations in a polygonal tundra landscape near Barrow, Alaska.

The Impact
Arctic tundra environments store a vast amount of soil carbon with an acute possibility that these regions will convert from a global carbon sink to a carbon source under warmer conditions. In estimating future changes to global carbon budgets, it is therefore important to identify key controls and understand the mechanistic nature of GHG flux variations especially in carbon-rich environments. Here, we focus on a polygonal tundra environment - a dominant landscape in the Alaskan Arctic Coastal Plain - that demonstrates significant variability in GHG fluxes across space and time. Results from this study indicate that flat-centered polygons may become important sources of CO2 during warm and dry years, while high-centered polygons may become important during cold and wet years. Moreover, the identification of specific geomorphic, soil, vegetation or climatic factors that explain the most variability in GHG fluxes across three successive years (2012-14) - a dataset with significant variability in soil moisture and temperature - provides important insights on which ecosystem properties may be shifted regionally in a future climate.

Summary
Investigating the degree to which environmental factors can impact GHG fluxes in Arctic tundra environments can be especially complex and difficult to interpret because of complex spatial interactions, temporal shifts and strong interdependencies and feedbacks amongst the many primary controls. A research team from LBNL and NGEE-Arctic developed a novel entropy classification scheme that can disentangle these complex relationships and identify dominant controls on GHG flux variability within an Arctic tundra environment. Entropy analysis indicates that temporal variability in CO2 flux was governed by soil temperature variability, vegetation changes during the early and late growing season, and changes in soil moisture at higher topographic locations. Variability in CH4 flux at the site was primarily associated with vegetation changes during the growing season and temporal shifts in relationships between vegetation and environmental factors such as thaw depth. Further, results indicate that recent temperature trends and increasing length of the growing season may act to increase GHG efflux from the site. In this manner, entropy results can be used to identify mechanistic controls on GHG fluxes that may become important under changing climate.

Contacts (BER PM)
Daniel Stover
SC-23.1
Daniel.Stover@science.doe.gov

(PI Contact)
Susan Hubbard
Lawrence Berkeley National Laboratory
SSHubbard@lbl.gov

Funding
This material is based upon work supported as part of the Next-Generation Ecosystem Experiments (NGEE-Arctic) at Lawrence Berkeley National Laboratory funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under Award Number DE-AC02-05CH11231.

Publications
Arora, B., Wainwright, H.M., Dwivedi, D., Vaughn, L.J., Curtis, J.B., Torn, M.S., Dafflon, B. and Hubbard, S.S. “Evaluating temporal controls on greenhouse gas (GHG) fluxes in an Arctic tundra environment: An entropy-based approach.” Science of the Total Environment, 649, 284-299 (2018). [DOI: 10.1016/j.scitotenv.2018.08.251 ]

Topic Areas:

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


February 01, 2019

Volatile Monoterpene ‘Fingerprints’ of Resinous Protium Tree Species in the Amazon Rainforest

Tree resin monoterpene ‘fingerprints’ in terrestrial ecosystems.

The Science
The Amazon forest, with vast biodiversity and territorial extension, cycles more carbon and water than any other terrestrial ecosystem on the planet. However, understanding the tree species and chemical composition of this rich biodiversity and how its products can sustainably benefit humans remains a major challenge. In this study, researchers from LBNL present a new rapid field collection technique to characterize the composition of monoterpenes present in stem resins of 77 Protium individuals across 15 species in a primary rainforest ecosystem in the central Amazon rainforest. By normalizing the monoterpenes present in each tree sample by the most abundant monoterpene, they generated a database of monoterpene ‘fingerprints’ which allowed us to compare across individuals and species. From this analysis, 9 types of monoterpene ‘fingerprint’ patterns emerged, characterized by a distinct dominant monoterpene.

The Impact
The results are consistent with a previous study that found at least five divergent copies of monoterpene synthase enzymes in Protium, and suggest that each of the 9 monoterpene ‘fingerprint’ types may be determined by the presence of a distinct monoterpene synthase enzyme. A comparison of monoterpene ‘fingerprints’ between years from the same individuals showed excellent agreement, suggesting that the ‘fingerprints’ are highly sensitive to the individual/species, but show relatively low annual variability. They therefore conclude that Protium monoterpene ‘fingerprints’ show a strong dependence on species identity, but not time of collection.

This study suggests that the presented method can be used to help constrain the identity of unknown Protium species and therefore be used as a new tool in resinous tree chemotaxonomy. By characterizing the composition of monoterpene resins among Protium species in the central Amazon, the results will contribute to future Protium studies on plant-microbe and plant-insect interactions, phylogenetic relationships and evolutionary histories, atmospheric chemistry and land-surface climate interactions, and commercial uses of resins. Finally, knowledge of the distribution of specific monoterpene ‘fingerprints’ among Protium tree species will contribute to the conservation, management, and sustainable use of tropical ecosystems .

Summary
Volatile terpenoid resins represent a diverse group of plant defense chemicals involved in defense against herbivory, abiotic stress, and communication. However, their composition in tropical forests remains poorly characterized. As a part of tree identification, the ‘smell’ of damaged trunks is widely used, but is highly subjective. Here, researchers from LBNL analyzed trunk volatile monoterpene emissions from 15 species of the genus Protium in the central Amazon. By normalizing the abundances of 28 monoterpenes, 9 monoterpene ‘fingerprint’ patterns emerged, characterized by a distinct dominant monoterpene. While 4 of the ‘fingerprint’ patterns were composed of multiple species, 5 were composed of a single species. Moreover, among individuals of the same species, 6 species had a single ‘fingerprint’ pattern, while 9 species had two or more ‘fingerprint’ patterns among individuals. A comparison of ‘fingerprints’ between 2015 and 2017 from 15 individuals generally showed excellent agreement, demonstrating a strong dependence on species identity, but not time of collection. The results are consistent with a previous study that found multiple divergent copies of monoterpene synthase enzymes in Protium. They conclude that the monoterpene ‘fingerprint’ database has important implications for constraining Protium species identification and phylogenetic relationships and enhancing understanding of physiological and ecological functions of resins and their potential commercial applications.

Contacts (BER PM)
Daniel Stover
SC-23.1
Terrestrial Ecosystem Science
Daniel.Stover@science.doe.gov

(PI Contact)
Kolby J. Jardine
Lawrence Berkeley National Laboratory (LBNL), Climate and Ecosystem Sciences Division
kjjardine@lbl.gov

Funding
This material is based upon work supported as part of the Next Generation Ecosystem Experiments-Tropics (NGEE-Tropics) funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research through contract No. DE-AC02-05CH11231 to LBNL, as part of DOE's Terrestrial Ecosystem Science Program. Additional funding for this research was provided by the Brazilian Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).

Publications
Piva L, K. Jardine, B. Gimenez, V. Menezes, F. Durgante, L. Cobello, N. Higuchi, and J. Chambers. Volatile monoterpene ‘fingerprints’ of resinous Protium tree species in the Amazon Rainforest.” Phytochemistry 160, 61-70 (2019). [10.1016/j.phytochem.2019.01.014]

Related Links
Paper: Figure 1

Topic Areas:

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


January 29, 2019

Arctic Waterbodies have Consistent Spatial and Temporal Size Distributions

A high-resolution circum-Arctic assessment of pond and lake sizes reveals very consistent statistical properties over space and time.

The Science
Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Further, waterbody distributions are changing rapidly in the warming Arctic, and Earth System Models (ESMs) do not currently represent these dynamics. In this study, a new high-resolution (< 5 m) circum-Arctic water body data base (Permafrost Region Pond and Lake; PeRL) was used to create the first high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km2 (100 m2) to 1 km2. Surprisingly consistent relationships were found between mean waterbody size across a region and both the variance and skewness of the distributions. Further, these relationships held in two regions where multi-decadal repeat photography was available.

The Impact
Characterizing the size distributions of Arctic waterbodies is a critical missing piece in assessing 21st century changes in hydrological and biogeochemical cycles and exchanges with the atmosphere. The results from this study provide important information for how these fine-resolution dynamics can be represented in ESMs, which is a goal for our NGEE-Arctic work in the Energy Exascale Earth System Model (E3SM) land model (ELMv1).

Summary
In 2017, NGEE-Arctic DOE scientists worked with a group of collaborators to create an open-source database (PeRL) of high-resolution (< 5 m) Arctic waterbody sizes (surface areas ranging from 0.0001 km2 to 1 km2; Muster et al. (2017)). The current study (Muster et al. 2019) analyzed that database over thirty study regions and found large variation in waterbody size distributions and that no single size distribution function was appropriate across all the study regions. However, close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions clearly emerged: the spatial variance increased linearly with mean waterbody size (R2 = 0.97, p < 2.2e-16) and the skewness decreased hyperbolically. These relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of the regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for how these fine-resolution dynamics can be represented in ESMs, such as the Energy Exascale Earth System Model (E3SM) land model (ELMv1).

Contacts (BER PM)
Daniel Stover
SC-23.1
Terrestrial Ecosystem Science
Daniel.Stover@science.doe.gov

(PI Contact)
William J. Riley
Lawrence Berkeley National Laboratory
wjriley@lbl.gov

Funding
This research was supported by the Office of Science, Office of Biological and Environmental Research of the US Department of Energy as part of the NGEE Arctic program and the Energy Exascale Earth System Model (E3SM) project.

Publications
Muster, S., W. J. Riley, K. Roth, M. Langer, F. Cresto-Aleina, C. D. Koven, S. Lange, A. Bartsch, G. Grosse, C. J. Wilson, B. M. Jones, and J. Boike. “Size Distributions of Arctic Waterbodies Reveal Consistent Relations in Their Statistical Moments in Space and Time.” Frontiers in Earth Science 7, 5 (2019). [DOI: 10.3389/feart.2019.00005]

Further reading:
Muster, S., K. Roth, M. Langer, S. Lange, F. C. Aleina, A. Bartsch, A. Morgenstern, G. Grosse, B. Jones, B. K. Sannel, Y. Sjöberg, F. Gunther, C. Andresen, A. Veremeeva, P. R. Lindgren, F. Bouchard, M. J. Lara, D. Fortier, S. Charbonneau, T. A. Virtanen, G. Hugelius, J. Palmtag, M. B. Siewer, W. J. Riley, C. D. Koven, and J. Boike. “PeRL: A Circum-Arctic Permafrost Region Pond and Lake Database, Earth System Science Data, 9, (2017). [DOI: 10.5194/essd-9-317-2017]

Topic Areas:

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


January 21, 2019

Machine-Learning-Based Measurement of Ice Wedge Polygon Properties

A rapid assessment of wet-tundra arctic landscape conditions.

The Science
Ice wedge polygons are ubiquitous features in wet-tundra Arctic landscapes. Their topographic properties control the distribution of water, vegetation and biogeochemical processes. Measuring and counting these small-scale landscape features across the Arctic is an extremely difficult proposition, but necessary to assess the state and dynamics of the landscape. A new machine learning approach can now quickly quantify these small-scale features at regional scales, and enables improved estimates of ecosystem processes across large swaths of the Arctic landscape.

The Impact
This new capability now enables scientists to quickly assess the number, configuration, and state of ice wedge polygons across large swaths of the Arctic. With this technology, scientists will be able to quickly measure how these land forms are responding to rapid arctic warming and concurrent permafrost degradation that is reshaping local to regional topography. Products from this technology are informing models to project how changes in the structure of Arctic landscapes will influence feedbacks to the climate system.

Summary
Ice wedge polygons are the surface expression of ice wedges, or vertical veins of ground ice that divide tundra landscapes into a network of polygonal units, 10-30 m across. These polygons pervade the Arctic tundra and are categorized as low centered polygons, which are surrounded by rims of soil several tens of centimeter high, or high centered polygons, surrounded by troughs on the order of a meter deep. The spatial distribution of these two types of polygon controls important landscape processes, including redistribution of windblown snow, thermal regulation of the underlying permafrost, runoff and evaporation, and surface emissions of two important but very different greenhouse gasses, carbon dioxide and methane. Therefore, mapping polygon types across the Arctic is vital for understanding the hydrologic function of landscapes, as well as potential fluxes of carbon into the atmosphere. However, directly delineating each polygon across the Arctic is impractical. Scientists at the University of Texas in collaboration with Los Alamos National Laboratory have developed a new approach that utilizes machine learning algorithms to analyze high resolution digital elevation maps from airborne remote sensing. This approach has been shown to be fast and accurate at two test sites with complex polygonal terrain, near Prudhoe Bay and Utqiagvik (formerly Barrow), Alaska. The algorithm allows scientists to quickly and accurately inventory polygonal forms across broad tundra landscapes, which will ultimately inform projections of the fate of the large stock of organic matter stored in Arctic soils.

Contacts (BER PM)
Daniel Stover
SC-23.1
Terrestrial Ecosystem Science
Daniel.Stover@science.doe.gov

(PI Contacts)
Chuck Abolt
The University of Texas at Austin
chuck.abolt@utexas.edu

Adam Atchley
Los Alamos National Laboratory
Aatchley@lanl.gov

Funding
Funding is provided by DOE Biological and Environmental Research, Terrestrial Ecosystem Science, Next Generation Ecosystem Experiments Arctic (NGEE-Arctic) and NASA Earth and Space Science Fellowship program.

Publications
Abolt, C.J., M.H. Young, A.L. Atchley, and C.J. Wilson. “Brief communication: Rapid machine-learning-based extraction and measurement of ice wedge polygons in high-resolution digital elevation models.” The Cryosphere, 13(1), 234-245 (2019). [DOI: 10.5194/tc-13-237-2019]

Related Links
Code repository:
Abolt, C.J., M.H. Young, A.L. Atchley, and C.J. Wilson. “CNN-watershed: A machine learning-based tool for delineation and measurement of ice wedge polygons in high-resolution digital elevation models.” Zenodo repository. [DOI: 10.5281/zenodo.2554542]

Topic Areas:

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


January 03, 2019

Warming Effects of Spring Rainfall Increase Methane Emissions from Thawing Permafrost

By advecting thermal energy into soil, precipitation regulates the near-term global warming potential of thawing permafrost.

The Science 
In Interior Alaska, at a thawing wetland complex located within a black-spruce permafrost forest, we measured carbon, water, and energy exchange between the land and the atmosphere over three years (2014, 2-15, 2016). The dataset is unique because we captured an average precipitation year and two years with abnormally high rainfall. Researchers from the University of Washington found that interactions between rain and deep soil temperatures controlled methane emissions. When wetland soils were warmed by spring rainfall, methane emissions increased by ~30%.

The Impact
Northern regions are expected to receive more rainfall in the future. By warming soils and increasing methane release, this rainfall could increase near-term global warming associated with permafrost thaw.

Summary
Because the world is getting warmer, permanently frozen ground around the arctic, known as permafrost, is thawing. When permafrost thaws, the ground collapses and sinks. Often a wetland forms within the collapsed area. Conversion of permanently frozen landscapes to wetlands changes the exchange of greenhouse gases between the land and atmosphere, which impacts global temperatures. Wetlands release methane into the atmosphere. Methane is a potent greenhouse gas. The ability of methane to warm the Earth is 32-times stronger than that of carbon dioxide over a period of 100 years. In this study, researchers found that methane release from the thaw wetland was greater in rainy years when rain fell in the spring. The data indicated that when it rained, water from the surrounding permafrost forest flowed downhill, entered the wetland, and rapidly altered wetland soil temperatures down to deep depths (~80 cm). Rain has roughly the same temperature as the air, and during springtime in northern regions, the air is warmer than the ground. The microbial and plant processes that generate methane increase with temperature. Therefore, wetland soils, warmed by spring rainfall, supported more methane production and release. This study identifies an important and unconsidered role of rain in governing the radiative forcing of thawing permafrost landscapes.

Contacts (BER PM)
Daniel Stover SC-23.1
Terrestrial Ecosystem Science
Daniel.Stover@science.doe.gov

(PI Contact)
Rebecca B. Neumann
Associate Professor, Civil & Environmental Engineering, University of Washington, Seattle, WA
rbneum@uw.edu

Funding
This material is based upon work supported, in part, by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under Award Number DE-SC0010338 to R.B. Neumann and the USGS Land Change Science Program. Considerable logistic support was provided by the Bonanza Creek LTER Program, which is jointly funded by NSF (DEB 1026415) and the USDA Forest Service, Pacific Northwest Research Station (PNW01-JV112619320-16).

Publications
Neumann, R.B. et al. “Warming effects of spring rainfall increase methane emissions from thawing permafrost.” Geophysical Research Letters 46(3), 1393-1401 (2019). [DOI: 10.1029/2018GL081274]

Related Links
University of Washington News Press Release
AGU Newsroom Press Release
AAAS EurekAlert!
Inside Climate news story

Topic Areas:

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


January 02, 2019

A 2017 Planetary-Scale Power Outage: Weather and Ecological Impacts of a Total Solar Eclipse

A network of eddy covariance flux towers enabled the detailed study of micrometeorological and ecosystem responses to a total solar eclipse.

The Science
Cyclic variations in solar energy at the Earth’s surface is the reason we experience changes in weather and the driver of the natural rhythms of ecosystems. Solar eclipses offer the rare chance to study how the weather and ecosystems respond to an abrupt environmental disruption of known intensity and duration—allowing for an outdoor controlled light experiment at the scale of whole ecosystems. This enables novel analyses of ecosystem processes and biosphere-atmosphere interactions. Additionally, rare natural events such as a total solar eclipse captures the attention of the public, which can be the starting point for discussions that advance the general science education.

The Impact
Knowledge of these ecosystems responses to such an abrupt perturbation of the forces driving energy, water, and carbon through those systems can inform models that scientists use to forecast weather or evaluate probable effects of future climate on ecosystems.

Summary
Mid-Missouri experienced up to 2 minutes 40 seconds of totality at around noontime during the total eclipse of 2017. We conducted the Mid-Missouri Eclipse Meteorology Experiment (MMEME) to examine land-atmosphere interactions during the eclipse. Here, research examining the eclipse responses in three contrasting ecosystems (forest, prairie, and soybeans) is described. There was variable cloudiness around at the beginning and end of the eclipse at the forest and prairie, however, skies cleared during the eclipse. Unfortunately, there were thunderstorms at the soybean site, which masked the eclipse effect and exposed the field to cold outflow. Turbulence and wind speeds decreased during the eclipse at all sites. However, there was amplified turbulent intensity at the soybean during the passage of a gust front. Evaporation and heating of the atmosphere by the land surface shut off during the eclipse as air became more stable, with the atmosphere actually supplying some heat to the surface at totality. Although the eclipse had a large effect on surface energy balances, the air temperature response was relatively muted due to the absence of topographic effects and the relatively moist land and atmosphere.

Contact (BER PM)
Daniel Stover, SC-23.1,
Terrestrial Ecosystem Science
Daniel.Stover@science.doe.gov

Jeffrey Wood, University of Missouri
woodjd@missouri.edu
and
Lianhong Gu, Oak Ridge National Laboratory
lianhong-gu@ornl.gov

Funding
National Aeronautics and Space Administration, Goddard Space Flight Center
U. S. Department of Energy Biological and Environmental Research, Terrestrial Ecosystem Science
United States Department of Agriculture-Agricultural Research Service
National Science Foundation, Missouri EPSCoR

Publication
Wood JD, EJ Sadler, NI Fox, ST Greer, L Gu, PE Guinan, AR Lupo, PS Market, SM Rochette, A Speck, and LD White. “Land-atmosphere responses to a total solar eclipse in three ecosystems with contrasting structure and physiology.” Journal of Geophysical Research: Atmospheres 124(2), 530-543 (2019). [DOI: 10.1029/2018JD029630]

Topic Areas:

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