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Norby, Richard J

Publications and source records attributed to Norby, Richard J.

18 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

SPRUCE Sphagnum Growth and Photosynthesis Responses to Shading Treatments, 2021

This dataset reports growth, water content, nitrogen concentration, and photosynthesis of Sphagnum grown under shade cloth of different density in replicated plots adjacent to the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental study plots located in the S1-Bog. Data are reported for May to October 2021. Investigations were instigated from questions arising in the SPRUCE experiment where the Sphagnum-shrub-spruce/larch ecosystem is exposed to air and peat warming in combination with elevated atmospheric CO2. SPRUCE is located at the 8.1-ha S1 Bog forest site in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). Thirty plots (35 × 35 cm) were established in May, 2021, in three blocks on unused large plots on the S-1 bog. Data are reported for growth of Sphagnum angustifolium/fallax and S. divinum growing in plastic columns within the shade plots. Growth is reported as dry mass of new tissue measured when the columns were harvested in October 2021. Additional measurements in the final harvest datasetinclude Sphagnum water content, new stem length, mass per unit length, and nitrogen content. Stem extension was measured periodically during the summer and reported in a separate datasetas stem length. Photosynthesis of Sphagnum angustifolium/fallax samples from hollows under low and high shade was measured in the laboratory. Responses of sphagnum to shading are important for understanding the future of peatland systems under the encroachment of shrubs and other woody plant species. This dataset contains three data files in comma-separated values (.csv) format. Additional metadata are provided: three data dictionaries and a file-level metadata file in comma-separated values (.csv) format and a user guide in PDF (*.pdf) format.

carbon dioxide flux↗
DOE OSTI2018

FACE-MDS Phase 2: Data from Six US-Located Elevated CO2 Experiments

This dataset contains measured ecosystem data from four Free Air CO2 Enrichment (FACE) experiments–Duke, Oak Ridge (ORNL), and Rhinelander -- and one Open Top Chamber (OTC) experiment -- Kennedy Space Center (KSCO). The sites were located in the United States and contain data from 1996-2009. These sites were the study sites of the FACE Model Data Synthesis (FACE-MDS) project phase 2. The file naming convention can be found in the file 'facemds-file-table-sitedata.xml' and information about variable naming convention can be found in the file 'facemds-standard-name-table-modvars.xml'. We followed the ALMA v3 convention for meteorological variables and developed a hierarchical naming scheme for ecosystem variables. Additional info can be found in the protocols in the accompanying meteorological dataset (Walker et al. 2018: doi:10.15485/1480328). We replaced the original naming convention mentioned in the protocol with the one described in 'facemds-standard-name-table-modvars.xml'. The outputs of the FACE-MDS phase 2 are in Walker et al (2018: doi:10.15485/1480327). The dataset contains 18 data files that are available in comma-separate (*.csv), and 18 R Data Serialization (*.rds) format. 2 XML (*.xml) companion files and additional metadata are provided: 2 data dictionaries and a file-level metadata file in comma-separate (.csv) format and a user guide in PDF (*.pdf) format. This dataset was updated on 2019-06-28 to fix daily files at Duke and ORNL were incorrectly labelled and were standard error files instead of plot level data. Now corrected and all three (plot, mean, standard error) daily data files for both sites have been added. This dataset was updated on 2026-06-08 to add a user guide, data dictionary file, and a file-level metadata file. DUKE_ax_v2.csv was added to match the no data value format of other files in this dataset. DUKE_ax.csv is maintained as a data file. No previously released data values were changed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

FACE-MDS Phase 2: Model Output

Model output from Phase 2 of the Free Air CO2 Enrichment Model Data Synthesis (FACE-MDS) project. Results from 12 models simulating six elevated CO2 experiments using the protocols, met data, and other data supplied in the accompanying dataset: Phase 2 Free Air CO2 Enrichment Model-Data Synthesis: Meteorological Data and Protocols. File naming convention can be found in the file 'facemds-file-table-modeldata.xml' and information about variable naming convention can be found in the file 'facemds-standard-name-table-modvars.xml'. We followed the ALMA v3 convention for meteorological variables and developed a hierarchical naming scheme for ecosystem variables. Additional info can be found in the protocols in the accompanying meteorological dataset (doi:10.15485/1480328). We replaced the original naming convention mentioned in the protocol with the one described in 'facemds-standard-name-table-modvars.xml'.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

FACE-MDS Phase 2: Meteorological Data and Protocols

This dataset contains meteorological data, site parameterization data, and protocols for simulation of the five Free Air CO2 Enrichment (FACE) experiments and one Open Top Chamber (OTC) experiment that were the study sites of the FACE Model Data Synthesis (FACE-MDS) project. This dataset should contain everything necessary to simulate these six CO2 enrichment experiments -- Duke, Kennedy Space Center, NDFF, ORNL, PHACE, and Rhinelander -- following the FACE-MDS simulation protocol. Data cover 1998-2008 (1998-01-01 to 2008-12-31). File naming convention can be found in the file 'facemds-file-table-metdata.xml' and information about variable naming convention can be found in the file 'facemds-standard-name-table-metvars.xml'. Where possible, Assistance for the Land-surface Modelling Activities (ALMA) v3 convention for meteorological variables naming ontology was followed. Additional info can be found in the user guide, protocol documents, and readmes in this dataset. The original naming convention mentioned in the protocol was replaced with the one described in 'facemds-standard-name-table-modvars.xml' in the accompanying dataset (doi:10.15485/1480327). The dataset contains 21 data files that are available in comma-separate (*.csv), plain text (*.txt), and NetCDF (*.nc) format. Nine companion files and additional metadata are provided: three data dictionaries and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. This dataset was updated on 2026-06-02 to add a version of the data files in comma separate (.csv) format, a user guide, data dictionary files, and a file-level metadata file. No previously released data values were changed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Potential carbon emissions dominated by carbon dioxide from thawed permafrost soils

Increasing temperatures in northern high latitudes are causing permafrost to thaw, making large amounts of previously frozen organic matter vulnerable to microbial decomposition. Permafrost thaw also creates a fragmented landscape of drier and wetter soil conditions that determine the amount and form (carbon dioxide (CO2), or methane (CH4)) of carbon (C) released to the atmosphere. The rate and form of C release control the magnitude of the permafrost C feedback, so their relative contribution with a warming climate remains unclear. We quantified the effect of increasing temperature and changes from aerobic to anaerobic soil conditions using 25 soil incubation studies from the permafrost zone. Here we show, using two separate meta-analyses, that a 10 C increase in incubation temperature increased C release by a factor of 2.0 (95% confidence interval (CI), 1.8 to 2.2). Under aerobic incubation conditions, soils released 3.4 (95% CI, 2.2 to 5.2) times more C than under anaerobic conditions. Even when accounting for the higher heat trapping capacity of CH4, soils released 2.3 (95% CI, 1.5 to 3.4) times more C under aerobic conditions. These results imply that permafrost ecosystems thawing under aerobic conditions and releasing CO2 will strengthen the permafrost C feedback more than waterlogged systemsreleasingCO2 andCH4 for a given amount of C.

Schadel, Christina↗
DOE OSTI2015

Using Ecosystem Experiments to Improve Vegetation Models

Ecosystem responses to rising CO2 concentrations are a major source of uncertainty in climate change projections. Data from ecosystem-scale Free-Air CO2 Enrichment (FACE) experiments provide a unique opportunity to reduce this uncertainty. The recent FACE Model–Data Synthesis project aimed to use the information gathered in two forest FACE experiments to assess and improve land ecosystem models. A new 'assumption-centred' model intercomparison approach was used, in which participating models were evaluated against experimental data based on the ways in which they represent key ecological processes. Identifying and evaluating the main assumptions caused differences among models, and the assumption-centered approach produced a clear roadmap for reducing model uncertainty. We explain this approach and summarize the resulting research agenda. We encourage the application of this approach in other model intercomparison projects to fundamentally improve predictive understanding of the Earth system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Comprehensive ecosystem model-experiment synthesis using multiple datasets at two temperate forest free-air CO2 enrichment experiments: model performance and compensating biases

Free Air CO2 Enrichment (FACE) experiments provide a remarkable wealth of data to test the sensitivities of terrestrial ecosystem models (TEMs). In this study, a broad set of 11 TEMs were compared to 22 years of data from two contrasting FACE experiments in temperate forests of the south eastern US the evergreen Duke Forest and the deciduous Oak Ridge forest. We evaluated the models' ability to reproduce observed net primary productivity (NPP), transpiration and Leaf Area index (LAI) in ambient CO2 treatments. Encouragingly, many models simulated annual NPP and transpiration within observed uncertainty. Daily transpiration model errors were often related to errors in leaf area phenology and peak LAI. Our analysis demonstrates that the simulation of LAI often drives the simulation of transpiration and hence there is a need to adopt the most appropriate of hypothesis driven methods to simulate and predict LAI. Of the three competing hypotheses determining peak LAI (1) optimisation to maximise carbon export, (2) increasing SLA with canopy depth and (3) the pipe model the pipe model produced LAI closest to the observations. Modelled phenology was either prescribed or based on broader empirical calibrations to climate. In some cases, simulation accuracy was achieved through compensating biases in component variables. For example, NPP accuracy was sometimes achieved with counter-balancing biases in nitrogen use efficiency and nitrogen uptake. Combined analysis of parallel measurements aides the identification of offsetting biases; without which over-confidence in model abilities to predict ecosystem function may emerge, potentially leading to erroneous predictions of change under future climates.

Walker, Anthony P↗
DOE OSTI2013

Tropical forest responses to increasing [CO2]: current knowledge and opportunities for future research

Elevated atmospheric [CO2] (ca) will undoubtedly affect the metabolism of tropical forests worldwide; however, critical aspects of how tropical forests will respond remain largely unknown. Here we review the current state of knowledge about physiological and ecological responses, with the aim of providing a framework that can help to guide future experimental research. Modelling studies have indicated that elevated ca can potentially stimulate photosynthesis more in the tropics than at higher latitudes, because suppression of photorespiration by elevated ca increases with temperature. However, canopy leaves in tropical forests could also potentially reach a high temperature threshold under elevated ca that will moderate the rise in photosynthesis. Belowground responses, including fine root production, nutrient foraging, and soil organic matter processing, will be especially important to the integrated ecosystem response to elevated CO2. Water-use efficiency will increase as ca rises, potentially impacting upon soil moisture status and nutrient availability. Recruitment may be differentially altered for some functional groups, potentially decreasing ecosystem carbon storage. Whole-forest CO2 enrichment experiments are urgently needed to test predictions of tropical forest functioning under elevated ca. Smaller scale experiments in the understory and in gaps would also be informative, and could provide stepping stones toward stand-scale manipulations.

Cernusak, Lucas↗
DOE OSTI2013

Elevated CO2 increases tree-level intrinsic water use efficiency: insights from carbon and oxygen isotope analyses in tree rings across three forest FACE sites

Elevated CO2 increases intrinsic water use efficiency (WUEi) of forests, but the magnitude of this effect and its interaction with climate is still poorly understood. We combined tree ring analysis with isotope measurements at three Free Air CO2 Enrichment (FACE, POP-EUROFACE, in Italy; Duke FACE in North Carolina and ORNL in Tennessee, USA) sites, to cover the entire life of the trees. We used 13C to assess carbon isotope discrimination ( 13C ci/ca) and changes in WUEi, while direct CO2 effects on stomatal conductance were explored using 18O as a proxy. Across all the sites, elevated CO2 increased 13C-derived WUEi on average by 73% for Liquidambar styraciflua, 77% for Pinus taeda and 75% for Populus sp., but through different ecophysiological mechanisms. Our findings provide a robust means of predicting WUEi responses from a variety of tree species exposed to variable environmental conditions over time, and species-specific relationships that can help modeling elevated CO2 and climate impacts on forest productivity, carbon and water balances.

Battipaglia, Giovanna↗
DOE OSTI2013

Sensitivity of plants to changing atmospheric CO2 concentration: From the geological past to the next century

The rate of CO2 assimilation by plants is directly influenced by the concentration of CO2 in the atmosphere, ca. In response to a short-term change in ca, plants adjust stomatal conductance to CO2 and water vapour to maximise carbon gain in terms of the amount of water lost. This is one of several fundamental feedback processes between plants and their environment that govern the exchange of water for carbon. As an environmental variable, ca further has a unique global and historic significance. Although relatively stable and uniform in the short term, global ca has varied substantially on the timescale of thousands to millions of years, and currently is increasing at seemingly an unprecedented rate. This may exert profound impacts on both climate and plant function. Here we utilise extensive data sets and numerous models to develop an integrated, multi-scale assessment of the impact of changing ca on plant carbon dioxide uptake and water use. We find that, overall, the sensitivity of plants to rising or falling atmospheric CO2 concentration is qualitatively similar across all scales considered. It is characterised by an adaptive feedback response that moves towards maximising the rate of return, in the form of carbon, for the water and nitrogen resources invested in the process of carbon assimilation. This is achieved through predictable adjustments to stomatal anatomy and chloroplast biochemistry. Importantly, the long-term response to changing ca can be described by simple equations rooted in the formulation of more commonly studied short-term responses.

Franks, Peter J↗
DOE OSTI2013

Stored carbon partly fuels fine-root respiration but is not used for production of new fine roots

The relative use of new photosynthate compared to stored C for the production and maintenance of fine roots, and the rate of C turnover in heterogeneous fine-root populations, are poorly understood. We followed the relaxation of a 13C tracer in fine roots in a Liquidambar styraciflua plantation at the conclusion of a free-air CO2 enrichment experiment. Goals included quantifying the relative fractions of new photosynthate versus stored C used in root growth and root respiration, as well as the turnover rate of fine-root C fixed during [CO2] fumigation. New fine-root growth was largely from recent photosynthate, while nearly one-quarter of respired C was from a storage pool. Changes in the isotopic composition of the fine-root population over two full growing seasons indicated heterogeneous C pools; less than 10% of root C had a residence time < 3 months, while a majority of root C had a residence time > 2 years. Compared to a 1-pool model, a 2-pool model for C turnover in fine roots (with 5 and 0.37 yr-1 turnover times) doubles the fine-root contribution to forest NPP (9-13%) and supports the 50% root-to-soil transfer rate often used in models.

13C↗
DOE OSTI2012

A framework for benchmarking land models

Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1) targeted aspects of model performance to be evaluated, (2) a set of benchmarks as defined references to test model performance, (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4) model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data–model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties of land models to improve their prediction performance skills.

Biophysical Processes↗
DOE OSTI2012

ECOSYSTEM IMPACTS OF GEOENGINEERING: A Review for Developing a Science Plan

Geoengineering methods are intended to reduce the magnitude of climate change. Climate change in some regions is already having demonstrable effects on ecosystem structure and functioning. Two different types of geoengineering activities have been proposed: carbon dioxide removal (CDR), which includes a range of engineered and biological processes to remove carbon dioxide (CO2) from the atmosphere, and solar radiation management (SRM, or sunlight reflection methods), whereby a small percentage of sunlight is reflected back into space to offset warming from greenhouse gases. In this review, we evaluate some of the possible impacts of CDR and SRM on the physical climate and their subsequent influence on ecosystems, including the risks and uncertainties associated with new kinds of purposeful perturbations to Earth. Specifically, we find evidence that, if implemented successfully, some CDR methods and continue use of some SRM methods) could alleviate some of the deleterious ecosystem impacts associated with climate changes that might occur in the foreseeable future.

Geoengineering, Ecosystems, Climate Change, Carbon↗