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- Creator:
- Keppel-Aleks, Gretchen and Liptak, Jessica
- Description:
- -CESM_bdrd _NEP_pulse_response_CO2.nc contains time series from the ‘FullyCoupled’ simulation -CESM_bdrcs_NEP_pulse_response_CO2.nc contains time series from the ‘NoRad’ simulation -CESM_bdrd_pftcon_NEP_pulse_response_CO2.nc contains data from the ‘NoLUC’ simulation -CESM_bdrd_Regional_Fluxes_NEP.nc contains NEP time series for each terrestrial source region from the FullyCoupled simulation - CESM_bdrcs_Regional_Fluxes_NEP.nc contains NEP time series for each terrestrial source region from the CESM ‘NoRad’ simulation - CESM_bdrd_pftcon_Regional_Fluxes_NEP.nc contains NEP time series for each terrestrial source region from the CESM ‘NoLUC’ simulation The 3-letter station IDs, latitudes, and longitudes of the sample locations are: ID Latitude (ºN) Longitude (ºE) 1. BRW 71.3 203.4 2. ZEP 78.9 11.9 3. SHM 52.7 174.1 4. THD 41.1 235.8 5. TAP 36.7 126.1 6. BMW 32.3 295.1 7. MLO 19.5 204.4 8. POCN15 15.0 215.0 9. ALT 82.5 297.5 10. BHD -41.4 174.9 11. EIC -27.2 250.6 12. GMI 13.4 144.7 13. HUN 47.0 16.7 14. IZO 28.3 343.5 15. LLN 23.5 120.9 16. NAT -5.8 324.7 17. WLG 36.3 100.9 18. HBA -75.6 333.8 19. BKT -0.20 100.3 20. UUM 44.5 111.1 21. CGO -40.7 144.5 22. SDZ 40.7 117.1 23. ASC -8.0 345.6 24. SEY -4.7 55.5 25. POCS20 -20.0 186.0 26. POCS35 -35.0 180.0 27. PSA -64.9 296.0 28. SYO -69.0 39.6 29. CHR 1.7 202.8 30. KEY 25.7 279.8 31. BAL 55.4 17.2 32. HPB 47.8 11.0 33. LMP 35.5 12.6 34. NMB -23.6 15.0 35. RPB 13.2 300.2 36. WIS 30.0 35.1 37. POCS10 -10.0 199.0 38. POCN10 10.0 211.0 39. MID 28.2 182.6 40. SMO -14.2 189.4 41. SPO -90.0 335.2 The terrestrial CO2 source region abbreviations are: 1. NBNA 2. SBNA 3. ETNA 4. WTNA 5. CNAM 6. AMZN 7. EASA 8. WESA 9. EURO 10. SAME 11. MDAF 12. AFRF 13. SOAF 14. EABA 15. WEBA 16. SOBA 17. CNAS 18. SEAS 19. EQAS 20. AUST 21. GNLD 22. ATCA
- Keyword:
- atmospheric CO2 annual cycle amplitude and CESM extended concentration pathway
- Citation to related publication:
- Hornick, T., Bach, L. T., Crawfurd, K. J., Spilling, K., Achterberg, E. P., Woodhouse, J. N., Schulz, K. G., Brussaard, C. P. D., Riebesell, U., & Grossart, H.-P. (2017). Ocean acidification impacts bacteria–phytoplankton coupling at low-nutrient conditions. Biogeosciences, 14(1), 1–15. https://doi.org/10.5194/bg-14-1-2017
- Discipline:
- Science
-
- Creator:
- Singh, Deepak
- Description:
- This includes data for all the plots and maps I created for my paper publication entitled "Improvement of Mars surface snow albedo modeling in LMD Mars GCM with SNICAR".
- Discipline:
- Science
-
- Creator:
- Blesh, Jennifer
- Description:
- This dataset contains three data files used in: Blesh, J. 2017. Functional traits in cover crop mixtures: biological nitrogen fixation and multifunctionality. Journal of Applied Ecology. There are also three corresponding metadata files. The file “Ecosystem_functions_soil_species.csv” contains data organized by farm, treatment, replicate block, and species combining the fall and spring sampling time points. These data include aboveground biomass, nitrogen and carbon content, and biological nitrogen fixation for the plant species. The dataset also includes measured soil characteristics for each farm site. The file “Ecosystem_functions_soil_treatment.csv” contains data organized by farm, treatment, and replicate block for the fall and spring sampling time points combined. These data include aboveground biomass, nitrogen and carbon content, and biological nitrogen fixation aggregated by treatment. The dataset also includes measured soil characteristics for each farm site. The file “Traits_unstandardized.csv” contains individual plant trait data, a subset of which were used to calculate an index of functional diversity after they were standardized to have zero mean and unit variance. These data are organized by farm, treatment, replicate block, and species. The corresponding metadata files: “Ecosystem_functions_soil_species_metadata.csv”, “Ecosystem_functions_soil_treatment_metadata.csv”, and “Traits_unstandardized_metadata.csv” provide a detailed description of all variables in each dataset and any abbreviations used. Note: On Dec 19th 2017, the format of the files was changed to csv to aid preservation. The following information was added to the three metadata files: the name of the data file the metadata refers to, an explanation as to the meaning of blank cells in the data file, a full citation to the paper where the author describes her findings and contact information for the author.
- Keyword:
- agroecology, biological nitrogen fixation, functional diversity, and cover crop
- Citation to related publication:
- Blesh J. Functional traits in cover crop mixtures: Biological nitrogen fixation and multifunctionality. J Appl Ecol. 2018;55:38–48. https://doi.org/10.1111/1365-2664.13011
- Discipline:
- Science
-
- Creator:
- Engel, Daniel D. , Evans, Mary Anne, Low, Bobbi S., and Schaeffer, Jeff
- Description:
- This dataset was compiled as an attempt to understand how natural resource managers and research ecologists in the Great Lakes region integrate the ecosystem services (ES) paradigm into their work. The following text is the adapted abstract from a thesis associated with this data. Ecosystem services, or the benefits people obtain from ecosystems, have gained much momentum in natural resource management in recent decades as a relatively comprehensive approach to provide quantitative tools for improving decision-making and policy design. However, to date we know little about whether and how natural resource practitioners, from natural resource managers to research ecologists (hereafter managers and ecologists respectively), have adopted the ES paradigm into their respective work. Here, we addressed this knowledge gap by asking managers and ecologists about whether and how they have adopted the ES paradigm into their respective work. First, we surveyed federal, state, provincial and tribal managers in the Great Lakes region about their perception and use of ES as well as the relevance of specific services to their work. Although results indicate that fewer than 31% of the managers said they currently consider economic values of ES, 79% of managers said they would use economic information on ES if they had access to it. Additionally, managers reported that ES-related information was generally inadequate for their resource management needs. We also assessed managers by dividing them into identifiable groups (e.g. managers working in different types of government agencies or administrative levels) to evaluate differential ES integration. Overall, results suggest a desire among managers to transition from considering ES concepts in their management practices to quantifying economic metrics, indicating a need for practical and accessible valuation techniques. Due to a sample of opportunity at the USGS Great Lakes Science Center (GLSC), we also evaluated GLSC research ecologists’ integration of the ES paradigm because they play an important role by contributing requisite ecological knowledge for ES models. Managers and ecologists almost unanimously agreed that it was appropriate to consider ES in resource management and also showed convergence on the high priority ES. However, ecologists appeared to overestimate the adequacy of ES-related information they provide as managers reported the information was inadequate for their needs. This divergence may reflect an underrepresentation of ecological economists in this system who can aid in translating ecological models into estimates of human well-being. As a note, the dataset for the research ecologists has had some data removed as it could be considered personally identifiable information due to the small sample size in that population. The surveys associated with both datasets have also been included in PDF format. Curation Notes: Three files were added to the data set on Dec 21, 2017. Two csv files: "Ecosystem services and Research Ecologists - Data Index.csv" and "Ecosystem services and Research Managers - Data Index.csv" and one text file: "Ecosystem Services Adoption Readme.txt". The file names of the original four files were altered to replace an ampersand with the word "and".
- Keyword:
- Research Ecologist, Decision-Making, Ecosystem Services, Natural Resource Management, Paradigm Adoption, and Ecological Economics
- Citation to related publication:
- Engel, D.D., Evans, M.A., Low, B.S., Schaeffer, J. (2017) “Understanding Ecosystem Services Adoption by Natural Resource Managers and Research Ecologists.” Journal of Great Lakes Research, 43(3), 169-179. https://doi.org/10.1016/j.jglr.2017.01.005
- Discipline:
- Science and Social Sciences
-
- Creator:
- Steiner, Allison and Kawecki, Stacey
- Description:
- WRF-Chem model
- Keyword:
- aerosols and weather
- Citation to related publication:
- Kawecki, S., Steiner, A.L., 2018. The Influence of Aerosol Hygroscopicity on Precipitation Intensity During a Mesoscale Convective Event. Journal of Geophysical Research: Atmospheres 123, 424–442. https://doi.org/10.1002/2017JD026535
- Discipline:
- Science
-
- Creator:
- Blesh, Jennifer and King, Alison E.
- Description:
- This dataset contains three data files used in: King, A.E. and J. Blesh, 2017. Crop rotations for increased soil carbon: perenniality as a guiding principle. Ecological Applications. There are also three corresponding metadata files. The file “CRMA 2017 Main.csv” contains data for the control and treatment rotations used to construct pairwise comparisons for meta-analysis, response ratios calculated for soil organic carbon concentration, and change in carbon input. The dataset also includes management, soil, and other environmental characteristics for each site. The file “CRMA 2017 Diversity x Nitrogen.csv” contains data used to test whether N fertilizer inputs mediated the effect of functional diversity on SOC concentrations. The file “CRMA Annual grain.csv” contains data used to test for effects of crop rotation species diversity (one vs. two species, or two vs. three species) on SOC concentrations and C input (i.e., for the “grain-only” rotations). The dataset also includes management, soil, and other environmental characteristics for each site. The corresponding metadata files: “CRMA 2017 Main_metadata.csv”, “CRMA 2017 Diversity x Nitrogen_metadata.csv”, and “CRMA Annual grain _metadata.csv” provide a detailed description of all variables in each dataset. Note: On Jan 12, 2018 the following information was added to the three metadata files: the name of the data file the metadata refers to, an explanation as to the meaning of blank cells in the data file, a full citation to the paper where the author describes her findings and contact information for the author.
- Keyword:
- soil carbon, functional diversity, meta-analysis, cropping system, and student-friendly
- Discipline:
- Science
-
- Creator:
- Forrest, Stephen R., Panda, Anurag, Qu, Yue, Che, Xiaozhou, Coburn, Caleb, and Burlingame, Quinn
- Description:
- Mathematica Diffusion Simulation: Programmed by Coburn, Caleb. Simulation of diffusion in organic heterostructures, including least square fits and statistical goodness of fit analysis. Used to calculate fits to transient data in Fig 1, 3 and Extended Data Fig.2. Example data file included for download Matlab Montecarlo simulation: Programmed by Coburn, Caleb. Montecarlo simulation of charge diffusion on a cubic lattice to determine lateral diffusion length as a function of barrier height, assuming thermionic emission over the barrier. Matlab 2D Diffusion Simulation:Programmed by Coburn, Caleb. Modified from BYU Physics 430 Course Manual. Simulates diffusion around a film discontinuity, such a cut. Used to generate fits to Extended Data Fig. 1
- Keyword:
- Organic semiconductors and Charge diffusion
- Citation to related publication:
- Burlingame, Q., Coburn, C., Che, X., Panda, A., Qu, Y., & Forrest, S. R. (2018). Centimetre-scale electron diffusion in photoactive organic heterostructures. Nature, 554(7690), 77-80. https://doi.org/10.1038/nature25148
- Discipline:
- Science
-
- Creator:
- Flanner, Mark
- Description:
- Greenhouse gas (GHG) additions to Earth’s atmosphere initially reduce global outgoing longwave radiation (OLR), thereby warming the planet. In select environments with temperature inversions, however, increased GHG concentrations can actually increase local OLR. Negative top-of-atmosphere and effective radiative forcing (ERF) from this situation give the impression that local surface temperatures could cool in response to GHG increases. Here we consider an extreme scenario in which GHG concentrations are increased only within the warmest layers of winter near-surface inversions of the Arctic and Antarctic. We find, using a fully coupled Earth system model, that the underlying surface warms despite the GHG addition exerting negative ERF and cooling the troposphere in the vicinity of the GHG increase. This unique radiative forcing and thermal response is facilitated by the high stability of the polar winter atmosphere, which inhibits thermal mixing and amplifies the impact of surface radiative forcing on surface temperature. These findings also suggest that strategies to exploit negative ERF via injections of short-lived GHGs into inversion layers would likely be unsuccessful in cooling the planetary surface. and Note: A revised data description file was added to this work on April 11, 2018 containing additional information about the data set than was provided in the original description. Additional keywords and a full citation to the related article were added as well.
- Keyword:
- climate, greenhouse gas, polar inversion layers, radiative forcing (and/or effective radiative forcing), and MODTRAN simulation
- Discipline:
- Science
-
- Creator:
- Johnson, Jena E.
- Description:
- Note: The "Readme_Metadata" file was updated on March 15, 2018 to include a citation to the related article making use of this data and was reformatted to be presented as a pdf file rather than as a docx file. and This data set is comprised of synchrotron-based X-ray transmission and absorption spectroscopy data as well as X-ray diffraction patterns that were performed to characterize the best-preserved examples of nanoscale iron silicate mineral inclusions from 2.5 billion-year-old Banded Iron Formations (BIFs) and ferruginous cherts.
- Keyword:
- Precambrian banded iron formations and nanoparticle inclusions of iron silicates in chert
- Citation to related publication:
- Johnson, J. E., Muhling, J. R., Cosmidis, J., Rasmussen, B. & Templeton, A. S. (2018). Low-Fe(III) Greenalite Was a Primary Mineral from Neoarchean Oceans. Geophysical Research Letters, 45. https://doi.org/10.1002/2017GL076311
- Discipline:
- Science
-
- Creator:
- Ozturk, Dogacan
- Description:
- The global magnetosphere-ionosphere-thermosphere (M-I-T) system is intrinsically coupled and susceptible to external drivers such as solar wind dynamic pressure enhancements. In order to understand the large-scale dynamic processes in the M-I-T system due to the compression from the solar wind, the 17 March 2015 sudden commencement was studied in detail using global numerical models. This data set is comprised of the simulation data generated from these models. and NOTE: The following changes were made to this dataset on March 28, 2018. First, two mp4 files were added. Second, the symbol representing "degree" was not rendering properly in the README file. The symbols were removed and replaced with the word "degree". Third, the metadata in the "methodology" and "description" fields were revised for content and clarity. On April 16, 2018 a citation to the corresponding article was added to the metadata record.
- Keyword:
- MHD model, BATS'R'US, and GITM
- Citation to related publication:
- Ozturk, D. S., Zou, S., Ridley, A. J., & Slavin, J. A. (2018). Modeling study of the geospace system response to the solar wind dynamic pressure enhancement on 17 March 2015. Journal of Geophysical Research: Space Physics, 123, 2974–2989. https://doi.org/10.1002/2017JA025099
- Discipline:
- Science