Articles | Volume 19, issue 5
https://doi.org/10.5194/bg-19-1435-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-19-1435-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Ideas and perspectives
| 
10 Mar 2022
Ideas and perspectives |
| 10 Mar 2022
| 10 Mar 2022
Ideas and perspectives: Enhancing research and monitoring of carbon pools and land-to-atmosphere greenhouse gases exchange in developing countries
Wondo Genet College of Forestry and Natural Resources, Hawassa
University, P.O. Box 128, Shashemene, Ethiopia
Ben Bond-Lamberty
Pacific Northwest National Laboratory, Joint Global Change Research
Institute, College Park, MD, USA
Youngryel Ryu
Department of Landscape Architecture and Rural Systems Engineering,
Seoul National University, Seoul, Republic of Korea
Bumsuk Seo
Land Use Change and Climate Research Group, Institute of Meteorology and Climate Research – Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology (KIT),
Kreuzeckbahnstr. 19, 82467 Garmisch-Partenkirchen, Germany
Dario Papale
Department for Innovation in Biological, Agro-food and Forest
systems (DIBAF), University of Tuscia, Via San C. De Lellis s.n.c., 01100
Viterbo, Italy
Impacts on Agriculture, Forests and Ecosystem Services Division, Euro-Mediterranean Center on Climate Change (CMCC) Viterbo, Italy
Related authors
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.
Benjamin Loubet, Nicolas P. Saby, Maryam Gebleh, Pauline Buysse, Jean-Philippe Chenu, Céline Ratie, Claudy Jolivet, Carmen Kalalian, Florent Levavasseur, Jose-Luis Munera-Echeverri, Sebastien Lafont, Denis Loustau, Dario Papale, Giacomo Nicolini, Bruna Winck, and Dominique Arrouays
EGUsphere, https://doi.org/10.5194/egusphere-2025-592, https://doi.org/10.5194/egusphere-2025-592, 2025
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Soil is a large pool of carbon storing globally from two to three times more carbon than the atmosphere and vegetation. We compute the soil stock evolution from 2005 to 2019 for a wheat-maize-barley-oilseed-rape crop rotation at a French crop site. The soil carbon stock decreased by around 70 ± 16 g C m-2 yr-1 over the period, leading to a total loss of around 8 % of the initial soil stock. This strong destocking is primarily explained by a decrease in the residue return to the site.
Alexandre Lhosmot, Gabriel Hould Gosselin, Manuel Helbig, Julien Fouché, Youngryel Ryu, Matteo Detto, Ryan Connon, William Quinton, Tim Moore, and Oliver Sonnentag
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-367, https://doi.org/10.5194/hess-2024-367, 2025
Revised manuscript accepted for HESS
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Climate change induces permanently frozen ground thaw, altering landscapes and water movements. We assess water balances (water entering and leaving difference) in a thawing boreal peatland complex in western Canada at two drainage scales: three < 1 km² basins (2014–2016) and one 130–202 km² basin (1996–2022). Both scales show similar patterns. We highlight challenges in accurate water balance estimation in low-relief areas. This study underscores ground thaw’s role in water movement dynamics.
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
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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.
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
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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.
Martin Jung, Jacob Nelson, Mirco Migliavacca, Tarek El-Madany, Dario Papale, Markus Reichstein, Sophia Walther, and Thomas Wutzler
Biogeosciences, 21, 1827–1846, https://doi.org/10.5194/bg-21-1827-2024, https://doi.org/10.5194/bg-21-1827-2024, 2024
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We present a methodology to detect inconsistencies in perhaps the most important data source for measurements of ecosystem–atmosphere carbon, water, and energy fluxes. We expect that the derived consistency flags will be relevant for data users and will help in improving our understanding of and our ability to model ecosystem–climate interactions.
Bo Qu, Alexandre Roy, Joe R. Melton, Jennifer L. Baltzer, Youngryel Ryu, Matteo Detto, and Oliver Sonnentag
EGUsphere, https://doi.org/10.5194/egusphere-2023-1167, https://doi.org/10.5194/egusphere-2023-1167, 2023
Preprint archived
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Accurately simulating photosynthesis and evapotranspiration challenges terrestrial biosphere models across North America’s boreal biome, in part due to uncertain representation of the maximum rate of photosynthetic carboxylation (Vcmax). This study used forest stand scale observations in an optimization framework to improve Vcmax values for representative vegetation types. Several stand characteristics well explained spatial Vcmax variability and were useful to improve boreal forest modelling.
Kukka-Maaria Kohonen, Roderick Dewar, Gianluca Tramontana, Aleksanteri Mauranen, Pasi Kolari, Linda M. J. Kooijmans, Dario Papale, Timo Vesala, and Ivan Mammarella
Biogeosciences, 19, 4067–4088, https://doi.org/10.5194/bg-19-4067-2022, https://doi.org/10.5194/bg-19-4067-2022, 2022
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Four different methods for quantifying photosynthesis (GPP) at ecosystem scale were tested, of which two are based on carbon dioxide (CO2) and two on carbonyl sulfide (COS) flux measurements. CO2-based methods are traditional partitioning, and a new method uses machine learning. We introduce a novel method for calculating GPP from COS fluxes, with potentially better applicability than the former methods. Both COS-based methods gave on average higher GPP estimates than the CO2-based estimates.
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
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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.
Anne Schucknecht, Bumsuk Seo, Alexander Krämer, Sarah Asam, Clement Atzberger, and Ralf Kiese
Biogeosciences, 19, 2699–2727, https://doi.org/10.5194/bg-19-2699-2022, https://doi.org/10.5194/bg-19-2699-2022, 2022
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Actual maps of grassland traits could improve local farm management and support environmental assessments. We developed, assessed, and applied models to estimate dry biomass and plant nitrogen (N) concentration in pre-Alpine grasslands with drone-based multispectral data and canopy height information. Our results indicate that machine learning algorithms are able to estimate both parameters but reach a better level of performance for biomass.
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
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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.
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
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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.
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
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Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
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
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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.
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
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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.
Jeff W. Atkins, Elizabeth Agee, Alexandra Barry, Kyla M. Dahlin, Kalyn Dorheim, Maxim S. Grigri, Lisa T. Haber, Laura J. Hickey, Aaron G. Kamoske, Kayla Mathes, Catherine McGuigan, Evan Paris, Stephanie C. Pennington, Carly Rodriguez, Autym Shafer, Alexey Shiklomanov, Jason Tallant, Christopher M. Gough, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 943–952, https://doi.org/10.5194/essd-13-943-2021, https://doi.org/10.5194/essd-13-943-2021, 2021
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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.
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
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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
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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.
Dario Papale
Biogeosciences, 17, 5587–5598, https://doi.org/10.5194/bg-17-5587-2020, https://doi.org/10.5194/bg-17-5587-2020, 2020
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FLUXNET is a large, bottom-up, self-coordinated network of sites. It provided ecosystem–atmosphere greenhouse gas fluxes from stations around the world that were used as bases for a large number of publications and studies. Today many applications require recent updates on the data to track more closely the ecosystem responses to climate change and link ground data with satellite programs. For this reason, a new organization of FLUXNET is needed, keeping as its target the FAIR principles.
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
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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
Agarwal, D., Cheah, Y.-W., Fay, D., Fay, J., Guo, D., Hey, T., Humphrey, M.,
Jackson, K., Li, J., and Poulain, C.: Data-intensive science: The Terapixel
and MODISAzure projects, Int. J. High Perform. Comput. Appl., 25, 304–316, https://doi.org/10.1177/1094342011414746,
2011.
Al-Haj, A. N. and Fulweiler, R. W.: A synthesis of methane emissions from
shallow vegetated coastal ecosystems, Glob. Change Biol., 26, 2988–3005,
https://doi.org/10.1111/gcb.15046, 2020.
Apesteguia, M., Plante, A. F., and Virto, I.: Methods assessment for organic
and inorganic carbon quantification in calcareous soils of the Mediterranean
region, Geoderma Reg., 12, 39–48, 2018.
Arzoumanian, E., Vogel, F. R., Bastos, A., Gaynullin, B., Laurent, O., Ramonet, M., and Ciais, P.: Characterization of a commercial lower-cost medium-precision non-dispersive infrared sensor for atmospheric CO2 monitoring in urban areas, Atmos. Meas. Tech., 12, 2665–2677, https://doi.org/10.5194/amt-12-2665-2019, 2019.
Atickem, A., Stenseth, N. C., Fashing, P. J., Nguyen, N., Chapman, C. A.,
Bekele, A., Mekonnen, A., Omeja, P. A., and Kalbitzer, U.: Build science in
Africa, Nature, 570, 297–300, https://doi.org/10.1038/d41586-019-01885-1, 2019.
Baldocchi, D.: Measuring fluxes of trace gases and energy between ecosystems
and the atmosphere – the state and future of the eddy covariance method,
Glob. Change Biol., 20, 3600–3609, 2014.
Bastin, J.-F., Clark, E., Elliott, T., Hart, S., van den Hoogen, J.,
Hordijk, I., Ma, H., Majumder, S., Manoli, G., and Maschler, J.:
Understanding climate change from a global analysis of city analogues, PLOS
One, 14, https://doi.org/10.1371/journal.pone.0217592, 2019.
Bastviken, D., Sundgren, I., Natchimuthu, S., Reyier, H., and Gålfalk, M.: Technical Note: Cost-efficient approaches to measure carbon dioxide (CO2) fluxes and concentrations in terrestrial and aquatic environments using mini loggers, Biogeosciences, 12, 3849–3859, https://doi.org/10.5194/bg-12-3849-2015, 2015.
Bastviken, D., Nygren, J., Schenk, J., Parellada Massana, R., and Duc, N. T.: Technical note: Facilitating the use of low-cost methane (CH4) sensors in flux chambers – calibration, data processing, and an open-source make-it-yourself logger, Biogeosciences, 17, 3659–3667, https://doi.org/10.5194/bg-17-3659-2020, 2020.
Bates, I., Chabala, L. M., Murray Lark, R., MacDonald, A., Mapfumo, P.,
Mtambanengwe, F., Nalivata, P. C., Owen, R., Phiri, E., and Pulford, J.:
Letter to the Editor: Response to Global soil science research collaboration
in the 21st century: Time to end helicopter research by Minasny et al.,
Geoderma, 378, 114559, https://doi.org/10.1016/j.geoderma.2020.114559, 2020.
Beillouin, D., Cardinael, R., Berre, D., Boyer, A., Corbeels, M., Fallot,
A., Feder, F., and Demenois, J.: A global overview of studies about land
management, land-use change, and climate change effects on soil organic
carbon, Glob. Change Biol., 28, 1690–1702, https://doi.org/10.1111/gcb.15998, 2021.
Bird, T. J., Bates, A. E., Lefcheck, J. S., Hill, N. A., Thomson, R. J.,
Edgar, G. J., Stuart-Smith, R. D., Wotherspoon, S., Krkosek, M., and
Stuart-Smith, J. F.: Statistical solutions for error and bias in global
citizen science datasets, Biol. Conserv., 173, 144–154, 2014.
Bockarie, M. J.: How a partnership is closing the door on “parachute”
research in Africa, The Conversation, available at:
https://theconversation.com/ (last access: 5 February 2022),
2019.
Bond-Lamberty, B.: Data sharing and scientific impact in eddy covariance
research, J. Geophys. Res.-Biogeo., 123, 1440–1443, 2018.
Bond-Lamberty, B.: dgk_biogeosci_2022, GitHub, https://github.com/PNNL-TES/dgk_biogeosci_2022, last
access: 5 February 2022.
Brändle, J. and Kunert, N.: A new automated stem CO2 efflux
chamber based on industrial ultra-low-cost sensors, Tree Phys., 39, 1975–1983, https://doi.org/10.1093/treephys/tpz104,
2019.
Burba, G.: Illustrative maps of past and present Eddy Covariance measurement
locations: II. high-resolution images, https://doi.org/10.13140/RG.2.2.33191.70561,
2019
Carbone, M. S., Seyednasrollah, B., Rademacher, T. T., Basler, D., Le Moine,
J. M., Beals, S., Beasley, J., Greene, A., Kelroy, J., and Richardson, A.
D.: Flux Puppy–An open-source software application and portable system
design for low-cost manual measurements of CO2 and H2O fluxes,
Agr. Forest Meteorol., 274, 1–6, https://doi.org/10.1016/j.agrformet.2019.04.012, 2019.
Castell, N., Dauge, F. R., Schneider, P., Vogt, M., Lerner, U., Fishbain,
B., Broday, D., and Bartonova, A.: Can commercial low-cost sensor platforms
contribute to air quality monitoring and exposure estimates?, Environ. Int.,
99, 293–302, 2017.
Choi, C. Q.: Seven ways scientists handle technology challenges in
resource-poor settings, Nature, 569, 147–149, 2019.
Collier-Oxandale, A., Casey, J. G., Piedrahita, R., Ortega, J., Halliday, H., Johnston, J., and Hannigan, M. P.: Assessing a low-cost methane sensor quantification system for use in complex rural and urban environments, Atmos. Meas. Tech., 11, 3569–3594, https://doi.org/10.5194/amt-11-3569-2018, 2018.
Cooper, C. B., Dickinson, J., Phillips, T., and Bonney, R.: Citizen science
as a tool for conservation in residential ecosystems, Ecol. Soc., 12, 11, http://www.ecologyandsociety.org/vol12/iss2/art11/ (last access: 5 February 2022)
2007.
Costello, A. and Zumla, A.: Moving to research partnerships in developing
countries, BMJ, 321, 827–829, https://doi.org/10.1136/bmj.321.7264.827,
2000.
Dai, S. Q., Li, H., Xiong, J., Ma, J., Guo, H. Q., Xiao, X., and Zhao, B.:
Assessing the extent and impact of online data sharing in eddy covariance
flux research, J. Geophys. Res.-Biogeo., 123, 129–137, 2018.
De-Arteaga, M., Herlands, W., Neill, D. B., and Dubrawski, A.: Machine
learning for the developing world, ACM Trans Inf. Syst., 9, 1–14, 2018.
DeVries, B., Pratihast, A. K., Verbesselt, J., Kooistra, L., and Herold, M.:
Characterizing forest change using community-based monitoring data and
Landsat time series, PLOS One, 11, e0147121, https://doi.org/10.1371/journal.pone.0147121, 2016.
Dias, N. L., Duarte, H. F., Maggiotto, S. R., and Grodzki, L.: An attenuated
eddy covariance method for latent heat flux measurements, Wat. Resour. Res.,
43, W04415, https://doi.org/10.1029/2006WR005259, 2007.
Djukic, I., Kepfer-Rojas, S., Schmidt, I. K., Larsen, K. S., Beier, C.,
Berg, B., Verheyen, K., Caliman, A., Paquette, A., and
Gutiérrez-Girón, A.: Early stage litter decomposition across biomes,
Sci. Tot. Environ., 628, 1369–1394, 2018.
Eldering, A., Taylor, T. E., O'Dell, C. W., and Pavlick, R.: The OCO-3 mission: measurement objectives and expected performance based on 1 year of simulated data, Atmos. Meas. Tech., 12, 2341–2370, https://doi.org/10.5194/amt-12-2341-2019, 2019.
Epule, T. E.: A new compendium of soil respiration data for Africa, Challenges,
6, 88–97, 2015.
Evans, K., Guariguata, M. R., and Brancalion, P. H.: Participatory
monitoring to connect local and global priorities for forest restoration,
Biol. Conserv., 32, 525–534, 2018.
Ewing, P. M., TerAvest, D., Tu, X., and Snapp, S. S.: Accessible,
affordable, fine-scale estimates of soil carbon for sustainable management
in sub-Saharan Africa, Soil Sci. Soc. Am. J., 85, 1814–1826,
https://doi.org/10.1002/saj1002.20263, 2021.
Feng, H., Guo, J., Han, M., Wang, W., Peng, C., Jin, J., Song, X., and Yu,
S.: A review of the mechanisms and controlling factors of methane dynamics
in forest ecosystems, Forest Ecol. Managm., 455, 117702,
https://doi.org/10.1016/j.foreco.2019.117702, 2020.
Ganesan, A. L., Schwietzke, S., Poulter, B., Arnold, T., Lan, X., Rigby, M., Vogel, F. R., van der Werf, G. R., Janssens-Maenhout, G., Boesch, H., Pandey, S., Manning, A. J., Jackson, R. B., Nisbet, E. G., and Manning, M. R.: Advancing Scientific Understanding of the Global Methane Budget in Support of the Paris Agreement, Global Biogeochem. Cy., 33, 1475–1512, https://doi.org/10.1029/2018GB006065, 2019.
Gatica, G., Fernández, M. E., Juliarena, M. P., and Gyenge, J.:
Environmental and anthropogenic drivers of soil methane fluxes in forests:
Global patterns and among-biomes differences, Glob. Change Biol., 26,
6604–6615, https://doi.org/10.1111/gcb.15331, 2020.
Gentemann, C. L., Holdgraf, C., Abernathey, R., Crichton, D., Colliander,
J., Kearns, E. J., Panda, Y., and Signell, R. P.: Science Storms the Cloud,
AGU Adv., 2, e2020AV000354, https://doi.org/10.1029/2020AV000354, 2021.
Geoghegan, H., Dyke, A., Pateman, R., West, S., and Everett, G.:
Understanding motivations for citizen science. Final report on behalf of
UKEOF, University of Reading, Stockholm Environment Institute (University of
York) and University of the West of England, available at: http://www.ukeof.org.uk/resources/citizen-science-resources/MotivationsforCSREPORTFINALMay2016.pdf (last access: 5 February 2022),
2016
Gessesse, T. A. and Khamzina, A.: How reliable is the Walkley-Black method
for analyzing carbon-poor, semi-arid soils in Ethiopia?, J. Arid Environ.,
153, 98–101, 2018.
Giller, K. E.: Grounding the helicopters, Geoderma, 373, 114302,
https://doi.org/10.1016/j.geoderma.2020.114302, 2020.
Giltrap, D. L., Li, C., and Saggar, S.: DNDC: A process-based model of
greenhouse gas fluxes from agricultural soils, Agr. Ecosyst. Environ., 136,
292–300, 2010.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore,
R.: Google Earth Engine: Planetary-scale geospatial analysis for everyone,
Remote Sens. Environ., 202, 18–27, 2017.
Grossman, R. B. and Reinsch, T. G.: Bulk density and linear extensibility,
in: Methods of soil analysis, Part. 4 physical methods, edited by: Dane,
J. H. and Topp, G. C., Soil Science Society of America, Inc., 201–254, 2002
Habib, A.: How academic journals price out developing countries, available at: http://theconversation.com/how-academic-journals-price-out-developing-countries-2484 (last access: 5 February 2022),
2011
Hampton, S. E., Anderson, S. S., Bagby, S. C., Gries, C., Han, X., Hart, E.
M., Jones, M. B., Lenhardt, W. C., MacDonald, A., and Michener, W. K.: The
Tao of open science for ecology, Ecosphere, 6, 1–13, 2015.
Han, M. and Zhu, B.: Changes in soil greenhouse gas fluxes by land use change from primary forest, Glob. Change Biol., 26, 2656–2667, https://doi.org/10.1111/gcb.14993, 2020.
Harden, J. W., Hugelius, G., Ahlström, A., Blankinship, J. C.,
Bond-Lamberty, B., Lawrence, C. R., Loisel, J., Malhotra, A., Jackson, R.
B., Ogle, S., Phillips, C., Ryals, R., Todd-Brown, K., Vargas, R., Vergara,
S. E., Cotrufo, M. F., Keiluweit, M., Heckman, K. A., Crow, S. E., Silver,
W. L., DeLonge, M., and Nave, L. E.: Networking our science to characterize
the state, vulnerabilities, and management opportunities of soil organic
matter, Glob. Change Biol., 24, e705–e718, https://doi.org/10.1111/gcb.13896, 2018.
Heigl, F., Kieslinger, B., Paul, K. T., Uhlik, J., and Dörler, D.: Opinion: Toward an international definition of citizen science, P. Natl. Acad. Sci., 116, 8089–8092, https://doi.org/10.1073/pnas.1903393116, 2019.
Hill, T., Chocholek, M., and Clement, R.: The case for increasing the
statistical power of eddy covariance ecosystem studies: why, where and how?,
Glob. Change Biol., 23, 2154–2165, 2017.
Hook, D., Adams, J., and Szomszor, M.: The Landscape of climate research
funding, available at: https://research.uarctic.org/media/ (last access: 5 February 2022), 2017
Hourdin, F., Mauritsen, T., Gettelman, A., Golaz, J.-C., Balaji, V., Duan,
Q., Folini, D., Ji, D., Klocke, D., and Qian, Y.: The art and science of
climate model tuning, Bull. Am. Meteorol. Soc., 98, 589–602, 2017.
Hurrell, J. W., Holland, M. M., Gent, P. R., Ghan, S., Kay, J. E., Kushner,
P. J., Lamarque, J.-F., Large, W. G., Lawrence, D., and Lindsay, K.: The
community earth system model: a framework for collaborative research, Bull.
Am. Meteorol. Soc., 94, 1339–1360, 2013.
Hwang, Y., Ryu, Y., Kimm, H., Jiang, C., Lang, M., Macfarlane, C., and
Sonnentag, O.: Correction for light scattering combined with sub-pixel
classification improves estimation of gap fraction from digital cover
photography, Agr. Forest Meteorol., 222, 32–44, 2016.
IPCC: Climate Change 2014: Impacts, Adaptation, and Vulnerability, Part B:
Regional Aspects, Contribution of Working Group II to the Fifth Assessment
Report of the Intergovernmental Panel on Climate Change, edited by: Barros, V. R.,
Field, C. B., Dokken, D. J., Mastrandrea, M. D., Mach, K. J., Bilir, T. E., Chatterjee, M.,
Ebi, K. L., Estrada, Y. O., Genova, R. C., Girma, B., Kissel, E. S., Levy, A. N.,
MacCracken, S., Mastrandrea, P. R., and White, L. L., Cambridge University
Press, Cambridge, United Kingdom and New York, NY, USA, 688 pp., ISBN 978-1-107-05816-3 2014
Irwin, A.: No PhDs needed: how citizen science is transforming research,
Nature, 562, 480–482, 2018.
Iyandemye, J. and Thomas, M. P.: Low income countries have the highest
percentages of open access publication: A systematic computational analysis
of the biomedical literature, PLOS One, 14, e0220229, https://doi.org/10.1371/journal.pone.0220229, 2019.
Jha, P., Biswas, A., Lakaria, B. L., Saha, R., Singh, M., and Rao, A. S.:
Predicting total organic carbon content of soils from Walkley and Black
analysis, Comm. Soil Sci. Plant Anal., 45, 713–725, 2014.
Jian, J., Vargas, R., Anderson-Teixeira, K., Stell, E., Herrmann, V., Horn,
M., Kholod, N., Manzon, J., Marchesi, R., Paredes, D., and Bond-Lamberty,
B.: A restructured and updated global soil respiration database (SRDB-V5),
Earth Syst. Sci. Data, 13, 255–267,
https://doi.org/10.5194/essd-13-255-2021, 2021.
Jose, V. S., Sejian, V., Bagath, M., Ratnakaran, A. P., Lees, A. M.,
Al-Hosni, Y. A., Sullivan, M., Bhatta, R., and Gaughan, J. B.: Modeling of
greenhouse gas emission from livestock, Front. Environ. Sci., 4, 27, https://doi.org/10.3389/fenvs.2016.00027, 2016.
Jung, M., Schwalm, C., Migliavacca, M., Walther, S., Camps-Valls, G., Koirala, S., Anthoni, P., Besnard, S., Bodesheim, P., Carvalhais, N., Chevallier, F., Gans, F., Goll, D. S., Haverd, V., Köhler, P., Ichii, K., Jain, A. K., Liu, J., Lombardozzi, D., Nabel, J. E. M. S., Nelson, J. A., O'Sullivan, M., Pallandt, M., Papale, D., Peters, W., Pongratz, J., Rödenbeck, C., Sitch, S., Tramontana, G., Walker, A., Weber, U., and Reichstein, M.: Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach, Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, 2020.
Kallimanis, A., Panitsa, M., and Dimopoulos, P.: Quality of non-expert
citizen science data collected for habitat type conservation status
assessment in Natura 2000 protected areas, Sci. Rep., 7, 8873, https://doi.org/10.1038/s41598-017-09316-9, 2017.
Kay, J. E., Deser, C., Phillips, A., Mai, A., Hannay, C., Strand, G.,
Arblaster, J. M., Bates, S., Danabasoglu, G., and Edwards, J.: The Community
Earth System Model (CESM) large ensemble project: A community resource for
studying climate change in the presence of internal climate variability,
Bull. Am. Meteorol. Soc., 96, 1333–1349, 2015.
Keuskamp, J. A., Dingemans, B. J., Lehtinen, T., Sarneel, J. M., and
Hefting, M. M.: Tea Bag Index: a novel approach to collect uniform
decomposition data across ecosystems, Methods Ecol. Evol., 4, 1070–1075,
2013.
Kim, D.-G. and Kirschbaum, M. U. F.: The effect of land-use change on the
net exchange rates of greenhouse gases: A compilation of estimates, Agr.
Ecosyst. Environ., 208, 114–126, 2015.
Kim, D.-G., Giltrap, D. J., and Hernandez-Ramirez, G.: Background nitrous
oxide emissions in agricultural and natural lands: a meta-analysis, Plant
Soil, 373, 17–30, 2013.
Kim, D.-G., Thomas, A. D., Pelster, D., Rosenstock, T. S., and Sanz-Cobena, A.: Greenhouse gas emissions from natural ecosystems and agricultural lands in sub-Saharan Africa: synthesis of available data and suggestions for further research, Biogeosciences, 13, 4789–4809, https://doi.org/10.5194/bg-13-4789-2016, 2016.
Kim, J., Ryu, Y., Jiang, C., and Hwang, Y.: Continuous observation of
vegetation canopy dynamics using an integrated low-cost, near-surface remote
sensing system, Agr. Forest Meteorol., 264, 164–177, 2019.
King, M., Pegrum, M., and Forsey, M.: MOOCs and OER in the Global South:
problems and potential, Int. Rev. Res. Open Distance Learn., 19, 5,
https://doi.org/10.19173/irrodl.v19i5.3742, 2018.
Lausch, A., Schmidt, A., and Tischendorf, L.: Data mining and linked open
data–New perspectives for data analysis in environmental research, Ecol.
Mod., 295, 5–17, 2015.
Lawrence, N. C. and Hall, S. J.: Capturing temporal heterogeneity in soil nitrous oxide fluxes with a robust and low-cost automated chamber apparatus, Atmos. Meas. Tech., 13, 4065–4078, https://doi.org/10.5194/amt-13-4065-2020, 2020.
Li, S., Xu, J., Tang, S., Zhan, Q., Gao, Q., Ren, L., Shao, Q., Chen, L.,
Du, J., and Hao, B.: A meta-analysis of carbon, nitrogen and phosphorus
change in response to conversion of grassland to agricultural land,
Geoderma, 363, 114149, https://doi.org/10.1016/j.geoderma.2019.114149, 2020.
Liang, A., Gong, W., Han, G., and Xiang, C.: Comparison of
satellite-observed XCO2 from GOSAT, OCO-2, and ground-based TCCON, Remote
Sens., 9, 1033, https://doi.org/10.3390/rs9101033, 2017.
López-Ballesteros, A., Beck, J., Bombelli, A., Grieco, E.,
Lorencová, E. K., Merbold, L., Brümmer, C., Hugo, W., Scholes, R.,
Vačkář, D., Vermeulen, A., Acosta, M., Butterbach-Bahl, K.,
Helmschrot, J., Kim, D.-G., Jones, M., Jorch, V., Pavelka, M., Skjelvan, I.,
and Saunders, M.: Towards a feasible and representative pan-African research
infrastructure network for GHG observations, Environ. Res. Lett., 13,
085003, https://doi.org/10.1088/1748-9326/aad66c, 2018.
Lowndes, J. S. S., Best, B. D., Scarborough, C., Afflerbach, J. C., Frazier,
M. R., O'Hara, C. C., Jiang, N., and Halpern, B. S.: Our path to better
science in less time using open data science tools, Nat. Ecol. Evol., 1,
1–7, 2017.
Luo, T., Hostetler, K., Freeman, C., and Stefaniak, J.: The power of open:
benefits, barriers, and strategies for integration of open educational
resources, Open Learn., 35, 140–158,
https://doi.org/10.1080/02680513.2019.1677222, 2020.
Macfarlane, C., Ryu, Y., Ogden, G. N., and Sonnentag, O.: Digital canopy
photography: exposed and in the raw, Agr. Forest Meteorol., 197, 244–253, 2014.
Mapfumo, P., Adjei-Nsiah, S., Mtambanengwe, F., Chikowo, R., and Giller, K.
E.: Participatory action research (PAR) as an entry point for supporting
climate change adaptation by smallholder farmers in Africa, Environ. Dev.,
5, 6–22, 2013.
Markwitz, C. and Siebicke, L.: Low-cost eddy covariance: a case study of evapotranspiration over agroforestry in Germany, Atmos. Meas. Tech., 12, 4677–4696, https://doi.org/10.5194/amt-12-4677-2019, 2019.
Marley, A. R., Smeaton, C., and Austin, W. E.: An assessment of the tea bag
index method as a proxy for organic matter decomposition in intertidal
environments, J. Geophys. Res.-Biogeo., 124, 2991–3004, 2019.
Martinsen, K. T., Kragh, T., and Sand-Jensen, K.: Technical note: A simple and cost-efficient automated floating chamber for continuous measurements of carbon dioxide gas flux on lakes, Biogeosciences, 15, 5565–5573, https://doi.org/10.5194/bg-15-5565-2018, 2018.
McDaniel, M. D., Saha, D., Dumont, M. G., Hernández, M., and Adams, M. A.: The effect of land-use change on soil CH4 and N2O fluxes: a global meta-analysis, Ecosys., 22, 1424–1443, https://doi.org/10.1007/s10021-019-00347-z, 2019.
Mims, F. M.: Sun photometer with light-emitting diodes as spectrally
selective detectors, Appl. Opt., 31, 6965–6967, 1992.
Minasny, B., Fiantis, D., Mulyanto, B., Sulaeman, Y., and Widyatmanti, W.:
Global soil science research collaboration in the 21st century: Time to end
helicopter research, Geoderma, 373, 114299,
https://doi.org/10.1016/j.geoderma.2020.114299, 2020.
Morawska, L., Thai, P. K., Liu, X., Asumadu-Sakyi, A., Ayoko, G., Bartonova, A., Bedini, A., Chai, F., Christensen, B., Dunbabin, M., Gao, J., Hagler, G. S. W., Jayaratne, R., Kumar, P., Lau, A. K. H., Louie, P. K. K., Mazaheri, M., Ning, Z., Motta, N., Mullins, B., Rahman, M. M., Ristovski, Z., Shafiei, M., Tjondronegoro, D., Westerdahl, D., and Williams, R.: Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?, Environ. Int., 116, 286–299, https://doi.org/10.1016/j.envint.2018.04.018, 2018.
Mtebe, J. S. and Raisamo, R.: Investigating perceived barriers to the use
of open educational resources in higher education in Tanzania, Int. Rev.
Res. Open Distance Learn., 15, 43–66,
https://doi.org/10.19173/irrodl.v15i2.1803, 2014.
Muenchow, J., Schäfer, S., and Krüger, E.: Reviewing qualitative GIS
research – Toward a wider usage of open-source GIS and reproducible research
practices, Geogr. Compass, 13, e12441, https://doi.org/10.1111/gec3.12441, 2019.
Murphy, H. M., McBean, E. A., and Farahbakhsh, K.: Appropriate technology –
A comprehensive approach for water and sanitation in the developing world,
Technol. Soc., 31, 158–167, 2009.
National Academies of Sciences, Engineering, and Medicine: Improving
characterization of anthropogenic methane emissions in the United States,
Washington, DC, The National Academies Press, https://doi.org/10.17226/24987, 2018.
Ng, W., Husnain, Anggria, L., Siregar, A. F., Hartatik, W., Sulaeman, Y.,
Jones, E., and Minasny, B.: Developing a soil spectral library using a
low-cost NIR spectrometer for precision fertilization in Indonesia, Geoderma
Reg., 22, e00319, https://doi.org/10.1016/j.geodrs.2020.e00319, 2020.
Nickless, A., Scholes, R. J., Vermeulen, A., Beck, J.,
López-Ballesteros, A., Ardö, J., Karstens, U., Rigby, M., Kasurinen,
V., Pantazatou, K., Jorch, V., and Kutsch, W.: Greenhouse gas observation
network design for Africa, Tellus B, 72,
1–30, https://doi.org/10.1080/16000889.2020.1824486, 2020.
Ochieng, R. M., Visseren-Hamakers, I. J., Arts, B., Brockhaus, M., and
Herold, M.: Institutional effectiveness of REDD+ MRV: Countries progress
in implementing technical guidelines and good governance requirements,
Environ. Sci. Policy, 61, 42–52, 2016.
Oertel, C., Matschullat, J., Zurba, K., Zimmermann, F., and Erasmi, S.:
Greenhouse gas emissions from soils – A review, Geochemistry, 76, 327–352,
2016.
Ogle, S. M., Olander, L., Wollenberg, L., Rosenstock, T., Tubiello, F.,
Paustian, K., Buendia, L., Nihart, A., and Smith, P.: Reducing greenhouse
gas emissions and adapting agricultural management for climate change in
developing countries: providing the basis for action, Glob. Change Biol.,
20, 1–6, https://doi.org/10.1111/gcb.12361, 2014.
Pal, J. S., Giorgi, F., Bi, X., Elguindi, N., Solmon, F., Gao, X., Rauscher,
S. A., Francisco, R., Zakey, A., and Winter, J.: Regional climate modeling
for the developing world: the ICTP RegCM3 and RegCNET, Bull. Am. Meteorol.
Soc., 88, 1395–1410, 2007.
Papale, D.: Ideas and perspectives: enhancing the impact of the FLUXNET
network of eddy covariance sites, Biogeosciences, 17, 5587–5598, https://doi.org/10.5194/bg-17-5587-2020, 2020.
Pearce, J.: Teaching science by encouraging innovation in appropriate
technologies for sustainable development, available at: https://hal.archives-ouvertes.fr/hal-02120521/document (last access: 5 February 2022), 2019
Peltier, R. E.: An Update on Low-cost Sensors for the Measurement of
Atmospheric Composition, available at:
https://library.wmo.int/index.php?lvl=notice_display&id=21508 (last access: 5 February 2022), 2021.
Pettorelli, N., Nagendra, H., Rocchini, D., Rowcliffe, M., Williams, R.,
Ahumada, J., De Angelo, C., Atzberger, C., Boyd, D., and Buchanan, G.:
Remote sensing in ecology and conservation: three years on, Remote. Sens.
Ecol., 3, 53–56, 2017.
Pinfield, S., Salter, J., Bath, P. A., Hubbard, B., Millington, P., Anders,
J. H. S., and Hussain, A.: Open-access repositories worldwide, 2005–2012:
Past growth, current characteristics, and future possibilities, J. Assoc.
Inf. Sci. Technol., 65, 2404–2421, https://doi.org/10.1002/asi.23131, 2014.
Pocock, M. J. O., Roy, H. E., August, T., Kuria, A., Barasa, F., Bett, J.,
Githiru, M., Kairo, J., Kimani, J., Kinuthia, W., Kissui, B., Madindou, I.,
Mbogo, K., Mirembe, J., Mugo, P., Muniale, F. M., Njoroge, P., Njuguna, E.
G., Olendo, M. I., Opige, M., Otieno, T. O., Ng'weno, C. C., Pallangyo, E.,
Thenya, T., Wanjiru, A., and Trevelyan, R.: Developing the global potential
of citizen science: Assessing opportunities that benefit people, society and
the environment in East Africa, J. Appl. Ecol., 56, 274–281, 2019.
Rai, A. C., Kumar, P., Pilla, F., Skouloudis, A. N., Di Sabatino, S., Ratti,
C., Yasar, A., and Rickerby, D.: End-user perspective of low-cost sensors
for outdoor air pollution monitoring, Sci. Total Environ., 607, 691–705,
2017.
Ramirez-Reyes, C., Brauman, K. A., Chaplin-Kramer, R., Galford, G. L.,
Adamo, S. B., Anderson, C. B., Anderson, C., Allington, G. R. H., Bagstad,
K. J., Coe, M. T., Cord, A. F., Dee, L. E., Gould, R. K., Jain, M., Kowal,
V. A., Muller-Karger, F. E., Norriss, J., Potapov, P., Qiu, J., Rieb, J. T.,
Robinson, B. E., Samberg, L. H., Singh, N., Szeto, S. H., Voigt, B., Watson,
K., and Wright, T. M.: Reimagining the potential of Earth observations for
ecosystem service assessments, Sci. Total Environ., 665, 1053–1063, 2019.
Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J.,
Carvalhais, N., and Prabhat: Deep learning and process understanding for
data-driven Earth system science, Nature, 566, 195–204, 2019.
Requena Suarez, D., Rozendaal, D. M. A., De Sy, V., Phillips, O. L.,
Alvarez-Dávila, E., Anderson-Teixeira, K., Araujo-Murakami, A., Arroyo,
L., Baker, T. R., Bongers, F., Brienen, R. J. W., Carter, S., Cook-Patton,
S. C., Feldpausch, T. R., Griscom, B. W., Harris, N., Hérault, B.,
Honorio Coronado, E. N., Leavitt, S. M., Lewis, S. L., Marimon, B. S.,
Monteagudo Mendoza, A., Kassi N'dja, J., N'Guessan, A. E., Poorter, L., Qie,
L., Rutishauser, E., Sist, P., Sonké, B., Sullivan, M. J. P., Vilanova,
E., Wang, M. M. H., Martius, C., and Herold, M.: Estimating aboveground net
biomass change for tropical and subtropical forests: Refinement of IPCC
default rates using forest plot data, Glob. Change Biol., 25, 3609–3624,
2019.
Richardson, A. D., Hufkens, K., Milliman, T., Aubrecht, D. M., Chen, M.,
Gray, J. M., Johnston, M. R., Keenan, T. F., Klosterman, S. T., and Kosmala,
M.: Tracking vegetation phenology across diverse North American biomes using
PhenoCam imagery, Sci. Data, 5, 180028, https://doi.org/10.1038/sdata.2018.28, 2018.
Riddick, S. N., Mauzerall, D. L., Celia, M., Allen, G., Pitt, J., Kang, M.,
and Riddick, J. C.: The calibration and deployment of a low-cost methane
sensor, Atmo. Environ., 230, 117440, https://doi.org/10.1016/j.atmosenv.2020.117440, 2020.
Ritchie, H.: How many internet users does each country have?,
avai;able at: https://ourworldindata.org/how-many-internet-users-does-each-country-have (last access: 5 February 2022),
2019.
Rocchini, D., Petras, V., Petrasova, A., Horning, N., Furtkevicova, L.,
Neteler, M., Leutner, B., and Wegmann, M.: Open data and open source for
remote sensing training in ecology, Ecol. Inform., 40, 57–61, 2017.
Romijn, E., Lantican, C. B., Herold, M., Lindquist, E., Ochieng, R., Wijaya,
A., Murdiyarso, D., and Verchot, L.: Assessing change in national forest
monitoring capacities of 99 tropical countries, Forest Ecol. Managm., 352,
109–123, https://doi.org/10.1016/j.foreco.2015.06.003, 2015.
Rose-Wiles, L. M.: The high cost of science journals: a case study and
discussion, J. Electron. Resour. Librariansh., 23, 219–241, 2011.
Roy, D. P., Jin, Y., Lewis, P. E., and Justice, C. O.: Prototyping a global
algorithm for systematic fire-affected area mapping using MODIS time series
data, Remote Sens. Environ., 97, 137–162, 2005.
Ryu, Y., Baldocchi, D. D., Verfaillie, J., Ma, S., Falk, M., Ruiz-Mercado,
I., Hehn, T., and Sonnentag, O.: Testing the performance of a novel spectral
reflectance sensor, built with light emitting diodes (LEDs), to monitor
ecosystem metabolism, structure and function, Agr. Forest Meteorol., 150,
1597–1606, 2010.
Ryu, Y., Berry, J. A., and Baldocchi, D. D.: What is global photosynthesis?
History, uncertainties and opportunities, Remote Sens. Environ., 223,
95–114, 2019.
Ryu, Y., Lee, G., Jeon, S., Song, Y., and Kimm, H.: Monitoring multi-layer
canopy spring phenology of temperate deciduous and evergreen forests using
low-cost spectral sensors, Remote Sens. Environ., 149, 227–238, 2014.
Ryu, Y., Verfaillie, J., Macfarlane, C., Kobayashi, H., Sonnentag, O.,
Vargas, R., Ma, S., and Baldocchi, D. D.: Continuous observation of tree
leaf area index at ecosystem scale using upward-pointing digital cameras,
Remote Sens. Environ., 126, 116–125, 2012.
Schimel, D., Stephens, B. B., and Fisher, J. B.: Effect of increasing
CO2 on the terrestrial carbon cycle, P. Natl. Acad. Sci. USA, 112, 436–441, 2015.
Shames, S., Heiner, K., Kapukha, M., Kiguli, L., Masiga, M., Kalunda, P. N.,
Ssempala, A., Recha, J., and Wekesa, A.: Building local institutional
capacity to implement agricultural carbon projects: participatory action
research with Vi Agroforestry in Kenya and ECOTRUST in Uganda, Agr. Food
Secur., 5, 13, https://doi.org/10.1186/s40066-016-0060-x, 2016.
Shi, S., Peng, C., Wang, M., Zhu, Q., Yang, G., Yang, Y., Xi, T., and Zhang,
T.: A global meta-analysis of changes in soil carbon, nitrogen, phosphorus
and sulfur, and stoichiometric shifts after forestation, Plant Soil, 407,
323–340, 2016.
Shusterman, A. A., Kim, J., Lieschke, K. J., Newman, C., Wooldridge, P. J., and Cohen, R. C.: Observing local CO2 sources using low-cost, near-surface urban monitors, Atmos. Chem. Phys., 18, 13773–13785, https://doi.org/10.5194/acp-18-13773-2018, 2018.
Smith, P., Soussana, J.-F., Angers, D., Schipper, L., Chenu, C., Rasse, D.
P., Batjes, N. H., van Egmond, F., McNeill, S., Kuhnert, M., Arias-Navarro,
C., Olesen, J. E., Chirinda, N., Fornara, D., Wollenberg, E.,
Álvaro-Fuentes, J., Sanz-Cobena, A., and Klumpp, K.: How to measure,
report and verify soil carbon change to realize the potential of soil carbon
sequestration for atmospheric greenhouse gas removal, Glob. Change Biol.,
26, 219–241, 2020.
Stell, E., Warner, D., Jian, J., Bond-Lamberty, B., and Vargas, R.: Spatial biases of information influence global estimates of soil respiration: How can we improve global predictions?, Glob. Change Biol., 27, 3923–3938, https://doi.org/10.1111/gcb.15666, 2021.
Tan, L., Ge, Z., Zhou, X., Li, S., Li, X., and Tang, J.: Conversion of
coastal wetlands, riparian wetlands, and peatlands increases greenhouse gas
emissions: A global meta-analysis, Glob. Change Biol., 26, 1638–1653,
https://doi.org/10.1111/gcb.14933, 2020.
Tang, Y., Jones, E., and Minasny, B.: Evaluating low-cost portable near
infrared sensors for rapid analysis of soils from South Eastern Australia,
Geoderma Reg., 20, e00240, https://doi.org/10.1016/j.geodrs.2019.e00240,
2020.
Theilade, I., Rutishauser, E., and Poulsen, M. K.: Community assessment of
tropical tree biomass: challenges and opportunities for REDD+, Carbon
Balance Manag., 10, 17, https://doi.org/10.1186/s13021-015-0028-3, 2015.
Tiago, P., Ceia-Hasse, A., Marques, T. A., Capinha, C., and Pereira, H. M.:
Spatial distribution of citizen science casuistic observations for different
taxonomic groups, Sci. Rep., 7, 12832, https://doi.org/10.1038/s41598-017-13130-8, 2017.
Vargas, R., Alcaraz-Segura, D., Birdsey, R., Brunsell, N. A.,
Cruz-Gaistardo, C. O., de Jong, B., Etchevers, J., Guevara, M., Hayes, D.
J., and Johnson, K.: Enhancing interoperability to facilitate implementation
of REDD+: Case study of Mexico, Carbon Manag., 8, 57–65, 2017.
Venter, M., Venter, O., Edwards, W., and Bird, M. I.: Validating community-led forest biomass assessments, PLOS One, 10, e0130529, https://doi.org/10.1371/journal.pone.0130529, 2015.
Villarreal, S. and Vargas, R.: Representativeness of FLUXNET Sites Across
Latin America, J. Geophys. Res.-Biogeo., 126, e2020JG006090,
https://doi.org/10.1029/2020JG006090, 2021.
Vogel, C., Steynor, A., and Manyuchi, A.: Climate services in Africa:
Re-imagining an inclusive, robust and sustainable service, Clim. Serv.,
15, 100107, https://doi.org/10.1016/j.cliser.2019.100107, 2019.
Walkley, A. and Black, I. A.: An examination of the Degtjareff method for
determining soil organic matter, and a proposed modification of the chromic
acid titration method, Soil Sci., 37, 29–38, 1934.
Wang, J.-P., Wang, X.-J., and Zhang, J.: Evaluating loss-on-ignition method
for determinations of soil organic and inorganic carbon in arid soils of
northwestern China, Pedosphere, 23, 593–599, 2013.
Willcock, S., Phillips, O. L., Platts, P. J., Swetnam, R. D., Balmford, A.,
Burgess, N. D., Ahrends, A., Bayliss, J., Doggart, N., Doody, K., Fanning,
E., Green, J. M. H., Hall, J., Howell, K. L., Lovett, J. C., Marchant, R.,
Marshall, A. R., Mbilinyi, B., Munishi, P. K. T., Owen, A. R.,
Topp-Jorgensen, E. J., and Lewis, S. L.: Land cover change and carbon
emissions over 100 years in an African biodiversity hotspot, Glob. Change
Biol., 22, 2787–2800, 2016.
Xu, M. and Shang, H.: Contribution of soil respiration to the global carbon
equation, J. Pl. Physiol., 203, 16–28, 2016.
Yan, L., and Roy, D. P.: Large-area gap filling of landsat reflectance time
series by spectral-angle-mapper based spatio-temporal similarity (SAMSTS),
Remote Sens., 10, 609, 2018.
Yang, S., Lei, L., Zeng, Z., He, Z., and Zhong, H.: An assessment of
anthropogenic CO2 emissions by satellite-based observations in China,
Sens., 19, 1118, https://doi.org/10.3390/s19051118, 2019.
Yoo, E.-H., Zammit-Mangion, A., and Chipeta, M. G.: Adaptive spatial
sampling design for environmental field prediction using low-cost sensing
technologies, Atmos. Environ., 221, 117091, https://doi.org/10.1016/j.atmosenv.2019.117091, 2020.
Zhao, M., Brofeldt, S., Li, Q., Xu, J., Danielsen, F., Læssøe, S. B.
L., Poulsen, M. K., Gottlieb, A., Maxwell, J. F., and Theilade, I.: Can
community members identify tropical tree species for REDD+ carbon and
biodiversity measurements?, PLOS One, 11, e0152061, https://doi.org/10.1371/journal.pone.0152061, 2016.
Zhu, Z., Wulder, M. A., Roy, D. P., Woodcock, C. E., Hansen, M. C.,
Radeloff, V. C., Healey, S. P., Schaaf, C., Hostert, P., and Strobl, P.:
Benefits of the free and open Landsat data policy, Remote Sens. Environ.,
224, 382–385, 2019.
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.
As carbon (C) and greenhouse gas (GHG) research has adopted appropriate technology and approach...
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