Articles | Volume 13, issue 3
https://doi.org/10.5194/essd-13-943-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-943-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
09 Mar 2021
Data description paper |
| 09 Mar 2021
| 09 Mar 2021
The fortedata R package: open-science datasets from a manipulative experiment testing forest resilience
Jeff W. Atkins
CORRESPONDING AUTHOR
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Elizabeth Agee
Environmental Sciences Division and Climate Change Science Institute,
Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Alexandra Barry
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Kyla M. Dahlin
Department of Geography, Environment, and Spatial Sciences, Michigan
State University, East Lansing, MI 48824, USA
Kalyn Dorheim
Joint Global Change Research Institute at the University of Maryland,
Pacific Northwest National Laboratory, College Park, MD 20740, USA
Maxim S. Grigri
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Lisa T. Haber
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Laura J. Hickey
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Aaron G. Kamoske
Department of Geography, Environment, and Spatial Sciences, Michigan
State University, East Lansing, MI 48824, USA
Kayla Mathes
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Catherine McGuigan
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Evan Paris
Vassar College, Poughkeepsie, NY 12604, USA
Stephanie C. Pennington
Joint Global Change Research Institute at the University of Maryland,
Pacific Northwest National Laboratory, College Park, MD 20740, USA
Carly Rodriguez
Western Colorado University, Gunnison, CO 81231, USA
Autym Shafer
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Alexey Shiklomanov
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Jason Tallant
University of Michigan Biological Station, Pellston, MI 49769, USA
Christopher M. Gough
Department of Biology, Virginia Commonwealth University, Richmond, VA
23059, USA
Ben Bond-Lamberty
Joint Global Change Research Institute at the University of Maryland,
Pacific Northwest National Laboratory, College Park, MD 20740, USA
Related authors
No articles found.
Junyan Ding, Nate McDowell, Vanessa Bailey, Nate Conroy, Donnie J. Day, Yilin Fang, Kenneth M. Kemner, Matthew L. Kirwan, Charlie D. Koven, Matthew Kovach, Patrick Megonigal, Kendalynn A. Morris, Teri O’Meara, Stephanie C. Pennington, Roberta B. Peixoto, Peter Thornton, Mike Weintraub, Peter Regier, Leticia Sandoval, Fausto Machado-Silva, Alice Stearns, Nick Ward, and Stephanie J. Wilson
EGUsphere, https://doi.org/10.5194/egusphere-2025-1544, https://doi.org/10.5194/egusphere-2025-1544, 2025
Short summary
Short summary
We used a vegetation model to study why coastal forests are dying due to rising water levels and what happens to the ecosystem when marshes take over. We found that tree death is mainly caused by water-damaged roots, leading to major changes in the environment, such as reduced water use and carbon storage. Our study helps explain how coastal ecosystems are shifting and offers new ideas to explore in future field research.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Jiří Dušek, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
Short summary
Short summary
The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Abigail Snyder, Noah Prime, Claudia Tebaldi, and Kalyn Dorheim
Earth Syst. Dynam., 15, 1301–1318, https://doi.org/10.5194/esd-15-1301-2024, https://doi.org/10.5194/esd-15-1301-2024, 2024
Short summary
Short summary
From running climate models to using their outputs to identify impacts, modeling the integrated human–Earth system is expensive. This work presents a method to identify a smaller subset of models from the full set that preserves the uncertainty characteristics of the full set. This results in a smaller number of runs that an impact modeler can use to assess how uncertainty propagates from the Earth to the human system, while still capturing the range of outcomes provided by climate models.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
Short summary
Short summary
Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Danica L. Lombardozzi, William R. Wieder, Negin Sobhani, Gordon B. Bonan, David Durden, Dawn Lenz, Michael SanClements, Samantha Weintraub-Leff, Edward Ayres, Christopher R. Florian, Kyla Dahlin, Sanjiv Kumar, Abigail L. S. Swann, Claire M. Zarakas, Charles Vardeman, and Valerio Pascucci
Geosci. Model Dev., 16, 5979–6000, https://doi.org/10.5194/gmd-16-5979-2023, https://doi.org/10.5194/gmd-16-5979-2023, 2023
Short summary
Short summary
We present a novel cyberinfrastructure system that uses National Ecological Observatory Network measurements to run Community Terrestrial System Model point simulations in a containerized system. The simple interface and tutorials expand access to data and models used in Earth system research by removing technical barriers and facilitating research, educational opportunities, and community engagement. The NCAR–NEON system enables convergence of climate and ecological sciences.
Claudia Tebaldi, Abigail Snyder, and Kalyn Dorheim
Earth Syst. Dynam., 13, 1557–1609, https://doi.org/10.5194/esd-13-1557-2022, https://doi.org/10.5194/esd-13-1557-2022, 2022
Short summary
Short summary
Impact modelers need many future scenarios to characterize the consequences of climate change. The climate modeling community cannot fully meet this need because of the computational cost of climate models. Emulators have fallen short of providing the entire range of inputs that modern impact models require. Our proposal, STITCHES, meets these demands in a comprehensive way and may thus support a fully integrated impact research effort and save resources for the climate modeling enterprise.
Yilin Fang, L. Ruby Leung, Ryan Knox, Charlie Koven, and Ben Bond-Lamberty
Geosci. Model Dev., 15, 6385–6398, https://doi.org/10.5194/gmd-15-6385-2022, https://doi.org/10.5194/gmd-15-6385-2022, 2022
Short summary
Short summary
Accounting for water movement in the soil and water transport within the plant is important for plant growth in Earth system modeling. We implemented different numerical approaches for a plant hydrodynamic model and compared their impacts on the simulated aboveground biomass (AGB) at single points and globally. We found care should be taken when discretizing the number of soil layers for numerical simulations as it can significantly affect AGB if accuracy and computational costs are of concern.
Dong-Gill Kim, Ben Bond-Lamberty, Youngryel Ryu, Bumsuk Seo, and Dario Papale
Biogeosciences, 19, 1435–1450, https://doi.org/10.5194/bg-19-1435-2022, https://doi.org/10.5194/bg-19-1435-2022, 2022
Short summary
Short summary
As carbon (C) and greenhouse gas (GHG) research has adopted appropriate technology and approach (AT&A), low-cost instruments, open-source software, and participatory research and their results were well accepted by scientific communities. In terms of cost, feasibility, and performance, the integration of low-cost and low-technology, participatory and networking-based research approaches can be AT&A for enhancing C and GHG research in developing countries.
Jinshi Jian, Xuan Du, Juying Jiao, Xiaohua Ren, Karl Auerswald, Ryan Stewart, Zeli Tan, Jianlin Zhao, Daniel L. Evans, Guangju Zhao, Nufang Fang, Wenyi Sun, Chao Yue, and Ben Bond-Lamberty
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-87, https://doi.org/10.5194/essd-2022-87, 2022
Manuscript not accepted for further review
Short summary
Short summary
Field soil loss and sediment yield due to surface runoff observations were compiled into a database named AWESOME: Archive for Water Erosion and Sediment Outflow MEasurements. Annual soil erosion data from 1985 geographic sites and 75 countries have been compiled into AWESOME. This database aims to be an open framework for the scientific community to share field-based annual soil erosion measurements, enabling better understanding of the spatial and temporal variability of annual soil erosion.
Claudia Tebaldi, Kalyn Dorheim, Michael Wehner, and Ruby Leung
Earth Syst. Dynam., 12, 1427–1501, https://doi.org/10.5194/esd-12-1427-2021, https://doi.org/10.5194/esd-12-1427-2021, 2021
Short summary
Short summary
We address the question of how large an initial condition ensemble of climate model simulations should be if we are concerned with accurately projecting future changes in temperature and precipitation extremes. We find that for most cases (and both models considered), an ensemble of 20–25 members is sufficient for many extreme metrics, spatial scales and time horizons. This may leave computational resources to tackle other uncertainties in climate model simulations with our ensembles.
Dawn L. Woodard, Alexey N. Shiklomanov, Ben Kravitz, Corinne Hartin, and Ben Bond-Lamberty
Geosci. Model Dev., 14, 4751–4767, https://doi.org/10.5194/gmd-14-4751-2021, https://doi.org/10.5194/gmd-14-4751-2021, 2021
Short summary
Short summary
We have added a representation of the permafrost carbon feedback to the simple, open-source global carbon–climate model Hector and calibrated the results to be consistent with historical data and Earth system model projections. Our results closely match previous work, estimating around 0.2 °C of warming from permafrost this century. This capability will be useful to explore uncertainties in this feedback and for coupling with integrated assessment models for policy and economic analysis.
Eva Sinha, Kate Calvin, Ben Bond-Lamberty, Beth Drewniak, Dan Ricciuto, Khachik Sargsyan, Yanyan Cheng, Carl Bernacchi, and Caitlin Moore
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-244, https://doi.org/10.5194/gmd-2021-244, 2021
Preprint withdrawn
Short summary
Short summary
Perennial bioenergy crops are not well represented in global land models, despite projected increase in their production. Our study expands Energy Exascale Earth System Model (E3SM) Land Model (ELM) to include perennial bioenergy crops and calibrates the model for miscanthus and switchgrass. The calibrated model captures the seasonality and magnitude of carbon and energy fluxes. This study provides the foundation for future research examining the impact of perennial bioenergy crop expansion.
Alexey N. Shiklomanov, Michael C. Dietze, Istem Fer, Toni Viskari, and Shawn P. Serbin
Geosci. Model Dev., 14, 2603–2633, https://doi.org/10.5194/gmd-14-2603-2021, https://doi.org/10.5194/gmd-14-2603-2021, 2021
Short summary
Short summary
Airborne and satellite images are a great resource for calibrating and evaluating computer models of ecosystems. Typically, researchers derive ecosystem properties from these images and then compare models against these derived properties. Here, we present an alternative approach where we modify a model to predict what the satellite would see more directly. We then show how this approach can be used to calibrate model parameters using airborne data from forest sites in the northeastern US.
Dong-Gill Kim, Ben Bond-Lamberty, Youngryel Ryu, Bumsuk Seo, and Dario Papale
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-85, https://doi.org/10.5194/bg-2021-85, 2021
Manuscript not accepted for further review
Short summary
Short summary
While greenhouse gas (GHG) research has adopted highly advanced technology some have adopted appropriate technology and approach (AT&A) such as low-cost instrument, open source software and participatory research and their results were well accepted by scientific communities. In terms of cost, feasibility and performance, integration of low-cost and low-technology, participatory and networking based research approaches can be AT&A for enhancing GHG research in developing countries.
Jinshi Jian, Rodrigo Vargas, Kristina Anderson-Teixeira, Emma Stell, Valentine Herrmann, Mercedes Horn, Nazar Kholod, Jason Manzon, Rebecca Marchesi, Darlin Paredes, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 255–267, https://doi.org/10.5194/essd-13-255-2021, https://doi.org/10.5194/essd-13-255-2021, 2021
Short summary
Short summary
Field soil-to-atmosphere CO2 flux (soil respiration, Rs) observations were compiled into a global database (SRDB) a decade ago. Here, we restructured and updated the database to the fifth version, SRDB-V5, with data published through 2017 included. SRDB-V5 aims to be a data framework for the scientific community to share seasonal to annual field Rs measurements, and it provides opportunities for the scientific community to better understand the spatial and temporal variability of Rs.
Kalyn Dorheim, Steven J. Smith, and Ben Bond-Lamberty
Geosci. Model Dev., 14, 365–375, https://doi.org/10.5194/gmd-14-365-2021, https://doi.org/10.5194/gmd-14-365-2021, 2021
Short summary
Short summary
Simple climate models are frequently used in research and decision-making communities because of their tractability and low computational cost. Simple climate models are diverse, including highly idealized and process-based models. Here we present a hybrid approach that combines the strength of two types of simple climate models in a flexible framework. This hybrid approach has provided insights into the climate system and opens an avenue for investigating radiative forcing uncertainties.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, https://doi.org/10.5194/gmd-13-5175-2020, 2020
Short summary
Short summary
Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
Jinshi Jian, Xuan Du, Ryan D. Stewart, Zeli Tan, and Ben Bond-Lamberty
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-283, https://doi.org/10.5194/essd-2020-283, 2020
Preprint withdrawn
Short summary
Short summary
Field soil loss due to surface runoff observations were compiled into a global database (SoilErosionDB). The database focuses on three erosion-related metrics – surface runoff, soil erosion, and nutrient leaching – and also records background information. Data from 99 geographic sites and 22 countries around the world have been compiled into SoilErosionDB. SoilErosionDB aims to be a data framework for the scientific community to share field-based soil erosion measurements.
Cited articles
American Geophysical Union: The Responsibilities and Rights of
Scientists, available at: https://www.agu.org/Share-and-Advocate/Share/Policymakers/Position-Statements/Rights-and-responsibilities-of-scientists (last access: 23 April 2020), 2017.
Amiro, B. D., Barr, A. G., Barr, J. G., Black, T. A., Bracho, R., Brown, M.,
Chen, J. M., Clark, K. L., Davis, K. J., Desai, A. R., Dore, S., Engel, V.,
Fuentes, J. D., Goldstein, A. H., Goulden, M. L., Kolb, T. E., Lavigne, M.
B., Law, B. E., Margolis, H. A., Martin, T. A., McCaughey, J. H., Misson,
L., Montes-Helu, M., Noormets, A., Randerson, J. T., Starr, and G. Xiao, J.:
Ecosystem carbon dioxide fluxes after disturbance in forests of North
America, J. Geophys. Res.-Biogeo., 115, G00K02, https://doi.org/10.1029/2010JG001390, 2010.
Atkins, J. W., Bohrer, G., Fahey, R. T., Hardiman, B. S., Morin, T. H.,
Stovall, A. E., and Gough, C. M.: Quantifying vegetation and canopy
structural complexity from terrestrial LiDAR data using the forestr r
package, Methods Ecol. Evol., 9, 2057–2066, 2018.
Atkins, J. W., Bond-Lamberty, B., Fahey, R. T., Hardiman, B. S., Haber, L.,
Stuart-Haëntjens, E., and Tallant, J.: Multidimensional Structural
Characterization is Required to Detect and Differentiate Among Moderate
Disturbance Agents, Ecosphere, 11, 1–19, https://doi.org/10.1002/ecs2.3156, 2020a.
Atkins, J. W., Bond-Lamberty, B., Dorheim, K., Pennington, S., and
Shiklomanov, A.: fortedata v1.0.2 (Version 1.0.2), Zenodo,
https://doi.org/10.5281/zenodo.4399601, 2020b.
Atkins, J. W., Bond-lamberty, B., Dorheim, K., Pennington, S. C.,
Shiklomanov, A., Agee, E., Gough, C. M., Shiklomanov, A., Dorheim, K., Pennington, S., Barry, A., Dahlin, K., Grigri, M., Haber, L., Hickey, L., Kamoske, A., Mathes, K., McGuigan, C., Paris, E., Rodriguez, C., Shafer, A., and Tallant, J.: fortedata-1.0.2, Dataset,
figshare, https://doi.org/10.6084/m9.figshare.13499148.v1, 2020c.
Bond-Lamberty, B., Smith, A. P., and Bailey, V.: Running an open experiment:
transparency and reproducibility in soil and ecosystem
science, Environ. Res. Lett., 11, 084004, https://doi.org/10.1088/1748-9326/11/8/084004. 2016.
Coomes, D. A., Holdaway, R. J., Kobe, R. K., Lines, E. R., and Allen, R.
B.: A general integrative framework for modelling woody biomass production
and carbon sequestration rates in forests, J. Ecol., 100,
42–64, 2012.
Culina, A., Baglioni, M., Crowther, T. W., Visser, M. E.,
Woutersen-Windhouwer, S., and Manghi, P.: Navigating the unfolding open data
landscape in ecology and evolution, Nature E and E, 2, 420–426, 2018.
Fahey, R. T., Atkins, J. W., Gough, C. M., Hardiman, B. S., Nave, L. E.,
Tallant, J. M., and Haber, L. T.: Defining a spectrum of integrative
trait-based vegetation canopy structural types, Ecol. Lett., 22,
2049–2059, 2019.
Fahey, R. T., Atkins, J. W., Campbell, J. L., Rustad, L. E., Duffy, M.,
Driscoll, C. T., Fahey, T. J., and Schaberg, P. G.: Effects of an
experimental ice storm on forest canopy structure, Can. J. Forest Res., 50,
136–145, 2020.
Falster, D. S., FitzJohn, R. G., Pennell, M. W., and Cornwell, W. K.: Datastorr: a workflow and package for delivering successive versions of “evolving data” directly into R, GigaScience, 8, giz035,
https://doi.org/10.1093/gigascience/giz035, 2019.
Flower, C. E. and Gonzalez-Meler, M. A.: Responses of temperate forest
productivity to insect and pathogen disturbances, Annu. Rev. Plant
Biol., 66, 547–569, 2015.
Frelich, L. E. and Reich, P. B.: Minireviews: Neighborhood Effects,
Disturbance Severity, and Community Stability in Forests, Ecosystems, 2,
151–166, 1999.
Gallagher, R. V., Falster, D. S., Maitner, B. S., Salguero-Gómez, R.,
Vandvik, V., Pearse, W. D., and Ankenbrand, M. J.: Open Science
principles for accelerating trait-based science across the Tree of Life,
Nature Ecology & Evolution, 4, 294–303, 2020.
Gough, C. M., Hardiman, B. S., Nave, L. E., Bohrer, G., Maurer, K. D.,
Vogel, C. S., Nadelhoffer, K. J., and Curtis, P. S.: Sustained carbon uptake
and storage following moderate disturbance in a Great Lakes forest, Ecol.
Appl., 23, 1202–1215, 2013.
Gough, C. M., Atkins, J. W., Bond-Lamberty, B., Agee, E. A., Dorheim, K. R., Fahey, R. T., Grigri, M. S., Haber, L. T., Mathes, K. C. Pennington, S. C.,
Shiklomanov, A. N., and Tallant, J. M.: Forest Structural Complexity and Biomass Predict First-Year Carbon Cycling Responses to Disturbancem Ecosystems, 1–14, https://doi.org/10.1007/s10021-020-00544-1, 2020.
Gu, H., Williams, C. A., Hasler, N., and Zhou, Y.: The carbon balance of
the southeastern US forest sector as driven by recent disturbance trends,
J. Geophys. Res.-Biogeo., 124, 2786–2803, 2019.
Hicke, J. A., Allen, C. D., Desai, A. R., Dietze, M. C., Hall, R. J., Hogg,
E. H., and Vogelmann, J.: Effects of biotic disturbances on forest
carbon cycling in the United States and Canada, Glob. Change Biol.,
18, 7–34, 2012.
Johnstone, J. F., McIntire, E. J., Pedersen, E. J., King, G., and Pisaric,
M. J.: A sensitive slope: estimating landscape patterns of forest resilience
in a changing climate, Ecosphere, 1, 1–21, 2010.
Johnstone, J. F., Allen, C. D., Franklin, J. F., Frelich, L. E., Harvey, B.
J., Higuera, P. E., and Schoennagel, T.: Changing disturbance regimes,
ecological memory, and forest resilience, Front. Ecol.
Environ., 14, 369–378, 2016.
Luo, Y. and Weng, E.: Dynamic disequilibrium of the terrestrial carbon
cycle under global change, Trends Ecol. Evol., 26, 96–104,
2010.
Pearsall, D. R.: Landscape ecosystems of the University of Michigan Biological Station: Ecosystem diversity and ground-cover diversity, Doctoral dissertation, The University of Michigan, 1996.
Peters, E. B., Wythers, K. R., Bradford, J. B., and Reich, P. B.: Influence
of disturbance on temperate forest productivity, Ecosystems, 16, 95–110,
2013.
Powers, S. M. and Hampton, S. E.: Open science, reproducibility, and
transparency in ecology, Ecol. Appl., 29, e01822, https://doi.org/10.1002/eap.1822, 2019.
Rebane, S., Jõgiste, K., Põldveer, E., Stanturf, J. A., and
Metslaid, M.: Direct measurements of carbon exchange at forest disturbance
sites: a review of results with the eddy covariance method, Scand.
J. Forest Res., 34, 585–597, 2019.
Rosenthal, R.: The file drawer problem and tolerance for null results, Psychological Bulletin, 86, 638–641, 1979.
Schapira, M., Harding, R. J., and The Open Lab Notebook Consortium: Open
laboratory notebooks: good for science, good for society, good for
scientists, F1000Research, 8, 87, https://doi.org/10.12688/f1000research.17710.1, 2019.
Scheuermann, C. M., Nave, L. E., Fahey, R. T., Nadelhoffer, K. J., and
Gough, C. M.: Effects of canopy structure and species diversity on primary
production in upper Great Lakes forests, Oecologia, 2, 405–415,
https://doi.org/10.1007/s00442-018-4236-x, 2018.
Shiels, A. B. and González, G.: Understanding the key mechanisms of
tropical forest responses to canopy loss and biomass deposition from
experimental hurricane effects, Forest Ecol. Manage., 332, 1–10, 2014.
Shiklomanov, A. N., Bond-Lamberty, B., Atkins, J., and Gough, C. M.: Structure
and parameter uncertinty in centennial projections of forest community
structure and carbon cycling, Glob. Change Biol., 26, 6080–6096,
https://doi.org/10.1111/gcb.15164,
2021.
Vanderwel, M. C., Coomes, D. A., and Purves, D. W.: Quantifying variation
in forest disturbance, and its effects on aboveground biomass dynamics,
across the eastern United States, Glob. Change Biol., 19, 1504–1517,
2013.
White, P. S. and Jentsch, A.: The Search for Generality in Studies of
Disturbance and Ecosystem Dynamics, in: Progress in Botany: Genetics
Physiology Systematics Ecology, edited by: Esser, K., Lüttge, U.,
Kadereit, J. W., and Beyschlag, W., Springer Berlin Heidelberg,
Berlin, Heidelberg, 399–450, 2001.
Wickham, H., Hester, J., and Change, W.: devtools: Tools to Make
Developing R Packages Easier, R package version 2.3.0, available at:
https://CRAN.R-project.org/package=devtools (last access: 15 January 2021), 2020.
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A.,
Blomberg, N., Boiten, J. W., da Silva Santos, L. B., Bourne, P. E., and Bouwman, J.: The FAIR
Guiding Principles for scientific data management and stewardship,
Sci. Data, 3, 1–9,
https://doi.org/10.1038/sdata.2016.18, 2016.
Williams, C. A., Collatz, G. J., Masek, J. G., and Goward, S. N.: Carbon
consequences of forest disturbance and recovery across the conterminous
United States, Global Biochem. Cy., 26, GB1005, https://doi.org/10.1029/2010GB003947, 2012.
Williams, C. A., Gu, H., MacLean, R., Masek, J. G., and Collatz, G. J.:
Disturbance and the carbon balance of US forests: A quantitative
review of impacts from harvests, fires, insects, and droughts, Global
Planet. Change, 143, 66–80, 2016.
Short summary
The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment (FoRTE) – a modeling and manipulative field experiment that tests the effects of disturbance severity and disturbance type on carbon cycling dynamics in a temperate forest. The data included help to interpret how carbon cycling processes respond over time to disturbance.
The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment...
Altmetrics
Final-revised paper
Preprint