Articles | Volume 16, issue 4
https://doi.org/10.5194/esd-16-1365-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-16-1365-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Aug 2025
Research article |
| 26 Aug 2025
| 26 Aug 2025
Social norms and groups structure safe operating spaces in renewable resource use in a social–ecological multi-layer network model
Earth System Analysis & Earth Resilience Science Unit, Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Telegrafenberg A31, 14473 Potsdam, Germany
Institute of Physics and Astronomy, Potsdam University, Potsdam, Germany
Department Integrative Earth System Science, Max Planck Institute of Geoanthropology, Kahlaische Strasse 10, 07745 Jena, Germany
Wolfram Barfuss
Center for Development Research (ZEF), University of Bonn, Genscherallee 3, 53113 Bonn, Germany
Earth System Analysis & Earth Resilience Science Unit, Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Telegrafenberg A31, 14473 Potsdam, Germany
André Butz
Institute of Environmental Physics, University of Heidelberg, Im Neuenheimer Feld 229, 69120 Heidelberg, Germany
Jannes Breier
Earth System Analysis & Earth Resilience Science Unit, Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Telegrafenberg A31, 14473 Potsdam, Germany
Department Integrative Earth System Science, Max Planck Institute of Geoanthropology, Kahlaische Strasse 10, 07745 Jena, Germany
Sara M. Constantino
Department of Environmental Social Sciences, Stanford Doerr School of Sustainability, Stanford University, Stanford, CA 94305, USA
Jobst Heitzig
Complexity Science Department, Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Telegrafenberg A31, 14473 Potsdam, Germany
Luana Schwarz
Earth System Analysis & Earth Resilience Science Unit, Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Telegrafenberg A31, 14473 Potsdam, Germany
Department Integrative Earth System Science, Max Planck Institute of Geoanthropology, Kahlaische Strasse 10, 07745 Jena, Germany
Institute of Environmental Science and Geography, Potsdam University, Potsdam, Germany
Sanam N. Vardag
Institute of Environmental Physics, University of Heidelberg, Im Neuenheimer Feld 229, 69120 Heidelberg, Germany
Jonathan F. Donges
Earth System Analysis & Earth Resilience Science Unit, Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Telegrafenberg A31, 14473 Potsdam, Germany
Stockholm Resilience Centre, Stockholm University, Frescativägen 8, 106 91 Stockholm, Sweden
Department Integrative Earth System Science, Max Planck Institute of Geoanthropology, Kahlaische Strasse 10, 07745 Jena, Germany
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Christopher D. Wells, Lennart Ramme, Chris Smith, Jannes Breier, Adakudlu Muralidhar, Chao Li, Ada Gjermundsen, William Alexander Schoenberg, Benjamin Blanz, and Cecilie Mauritzen
EGUsphere, https://doi.org/10.5194/egusphere-2025-4766, https://doi.org/10.5194/egusphere-2025-4766, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Understanding the change in climate that would occur under different future pathways of greenhouse gas emissions and changes in land use is crucial. Here, we develop a new simple climate model to help study this. We reduce the number of inputs so that our model can be connected to a model of the human causes of climate change. This way, we can study the interaction between climate change and society, including climate impacts. Our model broadly agrees with historical observations.
William Schoenberg, Benjamin Blanz, Jefferson K. Rajah, Beniamino Callegari, Christopher Wells, Jannes Breier, Martin B. Grimeland, Andreas Nicolaidis Lindqvist, Lennart Ramme, Chris Smith, Chao Li, Sarah Mashhadi, Adakudlu Muralidhar, and Cecilie Mauritzen
Geosci. Model Dev., 18, 8047–8069, https://doi.org/10.5194/gmd-18-8047-2025, https://doi.org/10.5194/gmd-18-8047-2025, 2025
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The current crop of models assessed by the Intergovernmental Panel on Climate Change to produce their assessment reports lack endogenous process-based representations of climate-driven changes to human activities, limiting understanding of the feedback between climate and humans. FRIDA (Feedback-based knowledge Repository for IntegrateD Assessments) v2.1 integrates these systems and generate results that suggest standard scenarios the shared socioeconomic pathways baseline scenarios may overestimate economic growth, highlighting the importance of feedbacks for realistic projections and informed policymaking.
Jannes Breier, Luana Schwarz, Hannah Prawitz, Werner von Bloh, Christoph Müller, Stephen Björn Wirth, Max Bechthold, Dieter Gerten, and Jonathan F. Donges
EGUsphere, https://doi.org/10.5194/egusphere-2025-4475, https://doi.org/10.5194/egusphere-2025-4475, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We present a new modelling framework that links global vegetation and agricultural modelling with human decision-making processes in an integrated simulation approach. This makes it possible to explore how farming practices and environmental changes influence each other over time. By combining climate, land use, and social dynamics in one system, the framework opens new ways to study food security, climate adaptation strategies, and long-term impacts.
Benjamin Weyland, Simon Rosanka, Domenico Taraborrelli, Birger Bohn, Andreas Zahn, Florian Obersteiner, Eric Förster, Mariano Mertens, Patrick Jöckel, Helmut Ziereis, Katharina Kaiser, Horst Fischer, John N. Crowley, Nijing Wang, Achim Edtbauer, Jonathan Williams, Maria Dolores Andrés Hernández, John P. Burrows, Flora Kluge, Meike Rotermund, Andre Butz, and Klaus Pfeilsticker
EGUsphere, https://doi.org/10.5194/egusphere-2025-5085, https://doi.org/10.5194/egusphere-2025-5085, 2025
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The destruction by sunlight of nitrous acid (HONO) produces the so-called detergent of the atmosphere. HONO has been measured in concentrations which exceed predictions based on known chemistry for decades. Several reactions have been proposed which may explain this excess HONO. This study reports on airborne measurements of HONO; the observations exceed predictions and form a C-shaped profile in the troposphere. Together with a host of other measurements, various reactions are investigated.
Harikrishnan Charuvil Asokan, Jochen Landgraf, Pepijn Veefkind, Stijn Dellaert, and André Butz
Atmos. Meas. Tech., 18, 5247–5264, https://doi.org/10.5194/amt-18-5247-2025, https://doi.org/10.5194/amt-18-5247-2025, 2025
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Greenhouse gases like CO2 and CH4 drive climate change. Satellites enable monitoring of these emissions from space. Our simulations show that the upcoming Twin ANthropogenic Greenhouse gas Observers (TANGO) mission can detect about 500 targets per 4 d cycle under clear skies, but cloud cover reduces detection. Integrating cloud forecasts into TANGO’s manoeuvering boosts detection, highlighting its potential for improving global emission monitoring.
Sina Loriani, Yevgeny Aksenov, David I. Armstrong McKay, Govindasamy Bala, Andreas Born, Cristiano Mazur Chiessi, Henk A. Dijkstra, Jonathan F. Donges, Sybren Drijfhout, Matthew H. England, Alexey V. Fedorov, Laura C. Jackson, Kai Kornhuber, Gabriele Messori, Francesco S. R. Pausata, Stefanie Rynders, Jean-Baptiste Sallée, Bablu Sinha, Steven C. Sherwood, Didier Swingedouw, and Thejna Tharammal
Earth Syst. Dynam., 16, 1611–1653, https://doi.org/10.5194/esd-16-1611-2025, https://doi.org/10.5194/esd-16-1611-2025, 2025
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In this work, we draw on palaeo-records, observations, and modelling studies to review tipping points in the ocean overturning circulations, monsoon systems, and global atmospheric circulations. We find indications for tipping in the ocean overturning circulations and the West African monsoon, with potentially severe impacts on the Earth system and humans. Tipping in the other considered systems is regarded as conceivable but is currently not sufficiently supported by evidence.
Luana Schwarz, Jannes Breier, Hannah Prawitz, Max Bechthold, Werner von Bloh, Sara M. Constantino, Dieter Gerten, Jobst Heitzig, Ronja Hotz, Leander John, Christoph Müller, Johan Rockström, and Jonathan F. Donges
EGUsphere, https://doi.org/10.5194/egusphere-2025-4079, https://doi.org/10.5194/egusphere-2025-4079, 2025
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
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We present a novel global model that links farmer decisions with ecological processes to explore how agricultural systems co-evolve. Unlike previous tools, it captures feedbacks between society and nature at up-to planetary scale. We find that conservation practices can restore soil health and support stable harvests. Adoption spreads through learning and norms, showing how regeneration at the farm scale can ripple outward, contributing to global sustainability and Earth system resilience.
Vincent Enders, Astrid Müller, Matthias Max Frey, Frank Hase, Ralph Kleinschek, Marvin Knapp, Benedikt Löw, Isamu Morino, Shin-Ichiro Nakaoka, Hideki Nara, Hiroshi Tanimoto, Sanam N. Vardag, Karolin Voss, and André Butz
EGUsphere, https://doi.org/10.5194/egusphere-2025-4552, https://doi.org/10.5194/egusphere-2025-4552, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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We have deployed two spectrometers on a ship traveling along the coast of Japan. By that, we were able to repeatedly measure the greenhouse gas and air pollutant emissions of power plants, large industrial facilities, and cities. Using the ratios between the different gases, we are able to identify sources based on their unique signature. In addition, we are able to show that spectrometers can be operated on a ship, while still fulfilling the high standards of land-based observation networks.
Colin Jones, Isaline Bossert, Donovan P. Dennis, Hazel Jeffery, Chris D. Jones, Torben Koenigk, Sina Loriani, Benjamin Sanderson, Roland Séférian, Klaus Wyser, Shuting Yang, Manabu Abe, Sebastian Bathiany, Pascale Braconnot, Victor Brovkin, Friedrich A. Burger, Patrica Cadule, Frederic S. Castruccio, Gokhan Danabasoglu, Andrea Dittus, Jonathan F. Donges, Friederike Fröb, Thomas Frölicher, Goran Georgievski, Chuncheng Guo, Aixue Hu, Peter Lawrence, Paul Lerner, José Licón-Saláiz, Bette Otto-Bliesner, Anastasia Romanou, Elena Shevliakova, Yona Silvy, Didier Swingedouw, Jerry Tjiputra, Jeremy Walton, Andy Wiltshire, Ricarda Winkelmann, Richard Wood, Tokuta Yokohata, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2025-3604, https://doi.org/10.5194/egusphere-2025-3604, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We introduce a new Earth system model experiment protocol to help researchers understand how Earth might respond to positive, zero, and negative carbon emissions. This protocol enables different models to be compared following similar warming and cooling rates. Researchers use the models to explore how the Earth reacts to different climate futures, including the risk of tipping points being exceeded and whether changes can be reversed. The results will support improved long-term climate policy.
Jacques Bara, Nico Wunderling, and Wolfram Barfuss
EGUsphere, https://doi.org/10.5194/egusphere-2025-4077, https://doi.org/10.5194/egusphere-2025-4077, 2025
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When one tipping element collapses the likelihood of another collapsing may be significantly affected. Using our simplified network model, we find that on the whole these interactions destabilise the Earth system, both in the short term and at equilibrium, though the effects are most noticeable after the year 2100. We find that to minimise tipping risks, it is essential to keep temperatures as close as possible to 1.5 °C in the short term and below 1 °C in the longer run.
Theo Glauch, Julia Marshall, Christoph Gerbig, Santiago Botía, Michał Gałkowski, Sanam N. Vardag, and André Butz
Geosci. Model Dev., 18, 4713–4742, https://doi.org/10.5194/gmd-18-4713-2025, https://doi.org/10.5194/gmd-18-4713-2025, 2025
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The Vegetation Photosynthesis and Respiration Model (VPRM) estimates carbon exchange between the atmosphere and biosphere by modeling gross primary production and respiration using satellite data and weather variables. Our new version, pyVPRM, supports diverse satellite products like Sentinel-2, MODIS, VIIRS, and new land cover maps, enabling high spatial and temporal resolution. This improves flux estimates, especially in complex landscapes, and ensures continuity as MODIS nears decommissioning.
Christopher Wells, Benjamin Blanz, Lennart Ramme, Jannes Breier, Beniamino Callegari, Adakudlu Muralidhar, Jefferson K. Rajah, Andreas Nicolaidis Lindqvist, Axel E. Eriksson, William Alexander Schoenberg, Alexandre C. Köberle, Lan Wang-Erlandsson, Cecilie Mauritzen, and Chris Smith
EGUsphere, https://doi.org/10.5194/egusphere-2025-2756, https://doi.org/10.5194/egusphere-2025-2756, 2025
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Computer models built to study future developments of human activity and climate change often exclude the impacts of climate change. Here, we include these effects in a new model. We create functions connecting changes in global temperature, carbon dioxide, and sea level to energy supply and demand, food systems, mortality, economic damages, and other important quantities. Including these effects will allow us to explore their impact on future changes in the human and climate realms.
Ricarda Winkelmann, Donovan P. Dennis, Jonathan F. Donges, Sina Loriani, Ann Kristin Klose, Jesse F. Abrams, Jorge Alvarez-Solas, Torsten Albrecht, David Armstrong McKay, Sebastian Bathiany, Javier Blasco Navarro, Victor Brovkin, Eleanor Burke, Gokhan Danabasoglu, Reik V. Donner, Markus Drüke, Goran Georgievski, Heiko Goelzer, Anna B. Harper, Gabriele Hegerl, Marina Hirota, Aixue Hu, Laura C. Jackson, Colin Jones, Hyungjun Kim, Torben Koenigk, Peter Lawrence, Timothy M. Lenton, Hannah Liddy, José Licón-Saláiz, Maxence Menthon, Marisa Montoya, Jan Nitzbon, Sophie Nowicki, Bette Otto-Bliesner, Francesco Pausata, Stefan Rahmstorf, Karoline Ramin, Alexander Robinson, Johan Rockström, Anastasia Romanou, Boris Sakschewski, Christina Schädel, Steven Sherwood, Robin S. Smith, Norman J. Steinert, Didier Swingedouw, Matteo Willeit, Wilbert Weijer, Richard Wood, Klaus Wyser, and Shuting Yang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1899, https://doi.org/10.5194/egusphere-2025-1899, 2025
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The Tipping Points Modelling Intercomparison Project (TIPMIP) is an international collaborative effort to systematically assess tipping point risks in the Earth system using state-of-the-art coupled and stand-alone domain models. TIPMIP will provide a first global atlas of potential tipping dynamics, respective critical thresholds and key uncertainties, generating an important building block towards a comprehensive scientific basis for policy- and decision-making.
E. Keith Smith, Marc Wiedermann, Jonathan F. Donges, Jobst Heitzig, and Ricarda Winkelmann
Earth Syst. Dynam., 16, 545–564, https://doi.org/10.5194/esd-16-545-2025, https://doi.org/10.5194/esd-16-545-2025, 2025
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Social tipping dynamics have received recent attention as a potential mechanism for effective climate actions – yet how such tipping dynamics could unfold remains largely unquantified. We explore how social tipping processes can develop by enabling necessary conditions (exemplified by climate change concern) and increased perceptions of localized impacts (sea level rise). The likelihood of social tipping varies regionally, mostly along areas with the highest exposure to persistent risks.
Eva-Marie Metz, Sanam Noreen Vardag, Sourish Basu, Martin Jung, and André Butz
Biogeosciences, 22, 555–584, https://doi.org/10.5194/bg-22-555-2025, https://doi.org/10.5194/bg-22-555-2025, 2025
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We estimate CO2 fluxes in semiarid southern Africa from 2009 to 2018 based on satellite CO2 measurements and atmospheric inverse modeling. By selecting process-based vegetation models, which agree with the satellite CO2 fluxes, we find that soil respiration mainly drives the seasonality, whereas photosynthesis substantially influences the interannual variability. Our study emphasizes the need for better representation of the response of semiarid ecosystems to soil rewetting in vegetation models.
Jordan P. Everall, Fabian Tschofenig, Jonathan F. Donges, and Ilona M. Otto
Earth Syst. Dynam., 16, 189–214, https://doi.org/10.5194/esd-16-189-2025, https://doi.org/10.5194/esd-16-189-2025, 2025
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A social tipping process is a large change in a social group that can be started by few people. Does the 80/20 rule apply here? We see if this is the case for human social groups. We find that, if the social conditions allow, change occurs when around 25 % of people engage. While tipping can happen between 10 % and 43 %, most cases tip by 40 %. However, tipping is not guaranteed: when people are resistant, trusted friend groups and context-appropriate messaging help the process along.
Viktoria Spaiser, Sirkku Juhola, Sara M. Constantino, Weisi Guo, Tabitha Watson, Jana Sillmann, Alessandro Craparo, Ashleigh Basel, John T. Bruun, Krishna Krishnamurthy, Jürgen Scheffran, Patricia Pinho, Uche T. Okpara, Jonathan F. Donges, Avit Bhowmik, Taha Yasseri, Ricardo Safra de Campos, Graeme S. Cumming, Hugues Chenet, Florian Krampe, Jesse F. Abrams, James G. Dyke, Stefanie Rynders, Yevgeny Aksenov, and Bryan M. Spears
Earth Syst. Dynam., 15, 1179–1206, https://doi.org/10.5194/esd-15-1179-2024, https://doi.org/10.5194/esd-15-1179-2024, 2024
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In this paper, we identify potential negative social tipping points linked to Earth system destabilization and draw on related research to understand the drivers and likelihood of these negative social tipping dynamics, their potential effects on human societies and the Earth system, and the potential for cascading interactions and contribution to systemic risks.
Karolin Voss, Philip Holzbeck, Klaus Pfeilsticker, Ralph Kleinschek, Gerald Wetzel, Blanca Fuentes Andrade, Michael Höpfner, Jörn Ungermann, Björn-Martin Sinnhuber, and André Butz
Atmos. Meas. Tech., 17, 4507–4528, https://doi.org/10.5194/amt-17-4507-2024, https://doi.org/10.5194/amt-17-4507-2024, 2024
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A novel balloon-borne instrument for direct sun and solar occultation measurements of several UV–Vis absorbing gases (e.g. O3, NO2, BrO, IO, and HONO) is described. Its major design features and performance during two stratospheric deployments are discussed. From the measured overhead BrO concentration and a suitable photochemical correction, total stratospheric bromine is inferred to (17.5 ± 2.2) ppt in air masses which entered the stratosphere around early 2017 ± 1 year.
Marvin Knapp, Ralph Kleinschek, Sanam N. Vardag, Felix Külheim, Helge Haveresch, Moritz Sindram, Tim Siegel, Bruno Burger, and André Butz
Atmos. Meas. Tech., 17, 2257–2275, https://doi.org/10.5194/amt-17-2257-2024, https://doi.org/10.5194/amt-17-2257-2024, 2024
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Imaging carbon dioxide (CO2) plumes of anthropogenic sources from planes and satellites has proven valuable for detecting emitters and monitoring climate mitigation efforts. We present the first images of CO2 plumes taken with a ground-based spectral camera, observing a coal-fired power plant as a validation target. We develop a technique to find the source emission strength with an hourly resolution, which reasonably agrees with the expected emissions under favorable conditions.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Astrid Müller, Hiroshi Tanimoto, Takafumi Sugita, Prabir K. Patra, Shin-ichiro Nakaoka, Toshinobu Machida, Isamu Morino, André Butz, and Kei Shiomi
Atmos. Meas. Tech., 17, 1297–1316, https://doi.org/10.5194/amt-17-1297-2024, https://doi.org/10.5194/amt-17-1297-2024, 2024
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Satellite CH4 observations with high accuracy are needed to understand changes in atmospheric CH4 concentrations. But over oceans, reference data are limited. We combine various ship and aircraft observations with the help of atmospheric chemistry models to derive observation-based column-averaged mixing ratios of CH4 (obs. XCH4). We discuss three different approaches and demonstrate the applicability of the new reference dataset for carbon cycle studies and satellite evaluation.
Nico Wunderling, Anna S. von der Heydt, Yevgeny Aksenov, Stephen Barker, Robbin Bastiaansen, Victor Brovkin, Maura Brunetti, Victor Couplet, Thomas Kleinen, Caroline H. Lear, Johannes Lohmann, Rosa Maria Roman-Cuesta, Sacha Sinet, Didier Swingedouw, Ricarda Winkelmann, Pallavi Anand, Jonathan Barichivich, Sebastian Bathiany, Mara Baudena, John T. Bruun, Cristiano M. Chiessi, Helen K. Coxall, David Docquier, Jonathan F. Donges, Swinda K. J. Falkena, Ann Kristin Klose, David Obura, Juan Rocha, Stefanie Rynders, Norman Julius Steinert, and Matteo Willeit
Earth Syst. Dynam., 15, 41–74, https://doi.org/10.5194/esd-15-41-2024, https://doi.org/10.5194/esd-15-41-2024, 2024
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This paper maps out the state-of-the-art literature on interactions between tipping elements relevant for current global warming pathways. We find indications that many of the interactions between tipping elements are destabilizing. This means that tipping cascades cannot be ruled out on centennial to millennial timescales at global warming levels between 1.5 and 2.0 °C or on shorter timescales if global warming surpasses 2.0 °C.
Tobias D. Schmitt, Jonas Kuhn, Ralph Kleinschek, Benedikt A. Löw, Stefan Schmitt, William Cranton, Martina Schmidt, Sanam N. Vardag, Frank Hase, David W. T. Griffith, and André Butz
Atmos. Meas. Tech., 16, 6097–6110, https://doi.org/10.5194/amt-16-6097-2023, https://doi.org/10.5194/amt-16-6097-2023, 2023
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Our new observatory measures greenhouse gas concentrations of carbon dioxide (CO2) and methane (CH4) along a 1.55 km long light path over the city of Heidelberg, Germany. We compared our measurements with measurements that were taken at a single point at one end of our path. The two mostly agreed but show a significant difference for CO2 with certain wind directions. This is important when using greenhouse gas concentration measurements to observe greenhouse gas emissions of cities.
Benedikt A. Löw, Ralph Kleinschek, Vincent Enders, Stanley P. Sander, Thomas J. Pongetti, Tobias D. Schmitt, Frank Hase, Julian Kostinek, and André Butz
Atmos. Meas. Tech., 16, 5125–5144, https://doi.org/10.5194/amt-16-5125-2023, https://doi.org/10.5194/amt-16-5125-2023, 2023
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We developed a portable spectrometer (EM27/SCA) that remotely measures greenhouse gases in the lower atmosphere above a target region. The measurements can deliver insights into local emission patterns. To evaluate its performance, we set up the EM27/SCA above the Los Angeles Basin side by side with a similar non-portable instrument (CLARS-FTS). The precision is promising and the measurements are consistent with CLARS-FTS. In the future, we need to account for light scattering.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, Andre Butz, Otto P. Hasekamp, Lianghai Wu, and Jochen Landgraf
Atmos. Meas. Tech., 15, 6585–6603, https://doi.org/10.5194/amt-15-6585-2022, https://doi.org/10.5194/amt-15-6585-2022, 2022
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The TROPOspheric Monitoring Instrument (TROPOMI) performs observations over ocean in every orbit, enhancing the monitoring capabilities of methane from space. In the sun glint geometry the mirror-like reflection at the water surface provides a signal that is high enough to retrieve methane with high accuracy and precision. We present 4 years of methane concentrations over the ocean, and we assess its quality. We also show the importance of ocean observations to quantify total CH4 emissions.
Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, André Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crevoisier, Jérome Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen Roehl, Paul O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David W. T. Griffith, Voltaire A. Velazco, and David F. Pollard
Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
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We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
Maria Zeitz, Jan M. Haacker, Jonathan F. Donges, Torsten Albrecht, and Ricarda Winkelmann
Earth Syst. Dynam., 13, 1077–1096, https://doi.org/10.5194/esd-13-1077-2022, https://doi.org/10.5194/esd-13-1077-2022, 2022
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The stability of the Greenland Ice Sheet under global warming is crucial. Here, using PISM, we study how the interplay of feedbacks between the ice sheet, the atmosphere and solid Earth affects the long-term response of the Greenland Ice Sheet under constant warming. Our findings suggest four distinct dynamic regimes of the Greenland Ice Sheet on the route to destabilization under global warming – from recovery via quasi-periodic oscillations in ice volume to ice sheet collapse.
Andreas Luther, Julian Kostinek, Ralph Kleinschek, Sara Defratyka, Mila Stanisavljević, Andreas Forstmaier, Alexandru Dandocsi, Leon Scheidweiler, Darko Dubravica, Norman Wildmann, Frank Hase, Matthias M. Frey, Jia Chen, Florian Dietrich, Jarosław Nȩcki, Justyna Swolkień, Christoph Knote, Sanam N. Vardag, Anke Roiger, and André Butz
Atmos. Chem. Phys., 22, 5859–5876, https://doi.org/10.5194/acp-22-5859-2022, https://doi.org/10.5194/acp-22-5859-2022, 2022
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Coal mining is an extensive source of anthropogenic methane emissions. In order to reduce and mitigate methane emissions, it is important to know how much and where the methane is emitted. We estimated coal mining methane emissions in Poland based on atmospheric methane measurements and particle dispersion modeling. In general, our emission estimates suggest higher emissions than expected by previous annual emission reports.
Carlos Alberti, Frank Hase, Matthias Frey, Darko Dubravica, Thomas Blumenstock, Angelika Dehn, Paolo Castracane, Gregor Surawicz, Roland Harig, Bianca C. Baier, Caroline Bès, Jianrong Bi, Hartmut Boesch, André Butz, Zhaonan Cai, Jia Chen, Sean M. Crowell, Nicholas M. Deutscher, Dragos Ene, Jonathan E. Franklin, Omaira García, David Griffith, Bruno Grouiez, Michel Grutter, Abdelhamid Hamdouni, Sander Houweling, Neil Humpage, Nicole Jacobs, Sujong Jeong, Lilian Joly, Nicholas B. Jones, Denis Jouglet, Rigel Kivi, Ralph Kleinschek, Morgan Lopez, Diogo J. Medeiros, Isamu Morino, Nasrin Mostafavipak, Astrid Müller, Hirofumi Ohyama, Paul I. Palmer, Mahesh Pathakoti, David F. Pollard, Uwe Raffalski, Michel Ramonet, Robbie Ramsay, Mahesh Kumar Sha, Kei Shiomi, William Simpson, Wolfgang Stremme, Youwen Sun, Hiroshi Tanimoto, Yao Té, Gizaw Mengistu Tsidu, Voltaire A. Velazco, Felix Vogel, Masataka Watanabe, Chong Wei, Debra Wunch, Marcia Yamasoe, Lu Zhang, and Johannes Orphal
Atmos. Meas. Tech., 15, 2433–2463, https://doi.org/10.5194/amt-15-2433-2022, https://doi.org/10.5194/amt-15-2433-2022, 2022
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Space-borne greenhouse gas missions require ground-based validation networks capable of providing fiducial reference measurements. Here, considerable refinements of the calibration procedures for the COllaborative Carbon Column Observing Network (COCCON) are presented. Laboratory and solar side-by-side procedures for the characterization of the spectrometers have been refined and extended. Revised calibration factors for XCO2, XCO and XCH4 are provided, incorporating 47 new spectrometers.
Qiansi Tu, Frank Hase, Matthias Schneider, Omaira García, Thomas Blumenstock, Tobias Borsdorff, Matthias Frey, Farahnaz Khosrawi, Alba Lorente, Carlos Alberti, Juan J. Bustos, André Butz, Virgilio Carreño, Emilio Cuevas, Roger Curcoll, Christopher J. Diekmann, Darko Dubravica, Benjamin Ertl, Carme Estruch, Sergio Fabián León-Luis, Carlos Marrero, Josep-Anton Morgui, Ramón Ramos, Christian Scharun, Carsten Schneider, Eliezer Sepúlveda, Carlos Toledano, and Carlos Torres
Atmos. Chem. Phys., 22, 295–317, https://doi.org/10.5194/acp-22-295-2022, https://doi.org/10.5194/acp-22-295-2022, 2022
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We use different methane ground- and space-based remote sensing data sets for investigating the emission strength of three waste disposal sites close to Madrid. We present a method that uses wind-assigned anomalies for deriving emission strengths from satellite data and estimate their uncertainty to 9–14 %. The emission strengths estimated from the remote sensing data sets are significantly larger than the values published in the official register.
Jonathan F. Donges, Wolfgang Lucht, Sarah E. Cornell, Jobst Heitzig, Wolfram Barfuss, Steven J. Lade, and Maja Schlüter
Earth Syst. Dynam., 12, 1115–1137, https://doi.org/10.5194/esd-12-1115-2021, https://doi.org/10.5194/esd-12-1115-2021, 2021
Julian Kostinek, Anke Roiger, Maximilian Eckl, Alina Fiehn, Andreas Luther, Norman Wildmann, Theresa Klausner, Andreas Fix, Christoph Knote, Andreas Stohl, and André Butz
Atmos. Chem. Phys., 21, 8791–8807, https://doi.org/10.5194/acp-21-8791-2021, https://doi.org/10.5194/acp-21-8791-2021, 2021
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Abundant mining and industrial activities in the Upper Silesian Coal Basin lead to large emissions of the potent greenhouse gas methane. This study quantifies these emissions with continuous, high-precision airborne measurements and dispersion modeling. Our emission estimates are in line with values reported in the European Pollutant Release and Transfer Register (E-PRTR 2017) but significantly lower than values reported in the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2).
Nico Wunderling, Jonathan F. Donges, Jürgen Kurths, and Ricarda Winkelmann
Earth Syst. Dynam., 12, 601–619, https://doi.org/10.5194/esd-12-601-2021, https://doi.org/10.5194/esd-12-601-2021, 2021
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In the Earth system, climate tipping elements exist that can undergo qualitative changes in response to environmental perturbations. If triggered, this would result in severe consequences for the biosphere and human societies. We quantify the risk of tipping cascades using a conceptual but fully dynamic network approach. We uncover that the risk of tipping cascades under global warming scenarios is enormous and find that the continental ice sheets are most likely to initiate these failures.
Sebastian H. R. Rosier, Ronja Reese, Jonathan F. Donges, Jan De Rydt, G. Hilmar Gudmundsson, and Ricarda Winkelmann
The Cryosphere, 15, 1501–1516, https://doi.org/10.5194/tc-15-1501-2021, https://doi.org/10.5194/tc-15-1501-2021, 2021
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Pine Island Glacier has contributed more to sea-level rise over the past decades than any other glacier in Antarctica. Ice-flow modelling studies have shown that it can undergo periods of rapid mass loss, but no study has shown that these future changes could cross a tipping point and therefore be effectively irreversible. Here, we assess the stability of Pine Island Glacier, quantifying the changes in ocean temperatures required to cross future tipping points using statistical methods.
Hiroshi Suto, Fumie Kataoka, Nobuhiro Kikuchi, Robert O. Knuteson, Andre Butz, Markus Haun, Henry Buijs, Kei Shiomi, Hiroko Imai, and Akihiko Kuze
Atmos. Meas. Tech., 14, 2013–2039, https://doi.org/10.5194/amt-14-2013-2021, https://doi.org/10.5194/amt-14-2013-2021, 2021
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The Japanese Greenhouse gases Observing SATellite-2 (GOSAT-2), in orbit since October 2018, is the follow-up mission of GOSAT, which has been operating since January 2009. Both satellites are dedicated to the monitoring of global carbon dioxide and methane to further knowledge of the global carbon cycle. This paper has reported on the function and performance of the TANSO-FTS-2 instrument, level-1 data processing, and calibrations for the first year of GOSAT-2 observation.
Marvin Knapp, Ralph Kleinschek, Frank Hase, Anna Agustí-Panareda, Antje Inness, Jérôme Barré, Jochen Landgraf, Tobias Borsdorff, Stefan Kinne, and André Butz
Earth Syst. Sci. Data, 13, 199–211, https://doi.org/10.5194/essd-13-199-2021, https://doi.org/10.5194/essd-13-199-2021, 2021
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We developed a shipborne variant of a remote sensing spectrometer for direct sunlight measurements of column-averaged atmospheric mixing ratios of carbon dioxide, methane, and carbon monoxide. The instrument was deployed on the research vessel Sonne during a longitudinal transect over the Pacific during June 2019. The campaign yielded more than 32 000 observations which compare excellently to atmospheric composition data from a state-of-the-art model (CAMS) and satellite observations (TROPOMI).
Alba Lorente, Tobias Borsdorff, Andre Butz, Otto Hasekamp, Joost aan de Brugh, Andreas Schneider, Lianghai Wu, Frank Hase, Rigel Kivi, Debra Wunch, David F. Pollard, Kei Shiomi, Nicholas M. Deutscher, Voltaire A. Velazco, Coleen M. Roehl, Paul O. Wennberg, Thorsten Warneke, and Jochen Landgraf
Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, https://doi.org/10.5194/amt-14-665-2021, 2021
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TROPOMI aboard Sentinel-5P satellite provides methane (CH4) measurements with exceptional temporal and spatial resolution. The study describes a series of improvements developed to retrieve CH4 from TROPOMI. The updated CH4 product features (among others) a more accurate a posteriori correction derived independently of any reference data. The validation of the improved data product shows good agreement with ground-based and satellite measurements, which highlights the quality of the TROPOMI CH4.
Cited articles
Ajzen, I.: The theory of planned behavior, Organ. Behav. Hum. Dec., 50, 179–211, https://doi.org/10.1016/0749-5978(91)90020-T, 1991. a
Ali, Q., Bauch, C. T., and Anand, M.: Coupled Human-Environment Dynamics of Forest Pest Spread and Control in a Multi-Patch, Stochastic Setting, PLOS ONE, 10, e0139353, https://doi.org/10.1371/journal.pone.0139353, 2015. a
Anderies, J. M., Barfuss, W., Donges, J. F., Fetzer, I., Heitzig, J., and Rockström, J.: A modeling framework for World-Earth system resilience: Exploring social inequality and Earth system tipping points, Environ. Res. Lett., 18, 095001, https://doi.org/10.1088/1748-9326/ace91d, 2023. a
Andreoni, J., Nikiforakis, N., and Siegenthaler, S.: Predicting social tipping and norm change in controlled experiments, P. Natl. Acad. Sci. USA, 118, e2014893118, https://doi.org/10.1073/pnas.2014893118, 2021. a
Andrighetto, G. and Vriens, E.: A research agenda for the study of social norm change, Philos. T. R. Soc. A, 380, 20200411, https://doi.org/10.1098/rsta.2020.0411, 2022. a, b
APA: APA Dictionary of Psychology, https://dictionary.apa.org/group (last access: 24 April 2023), 2023. a
Axelrod, R.: An Evolutionary Approach to Norms, Am. Polit. Sci. Rev., 80, 1095–1111, https://doi.org/10.2307/1960858, 1986. a
Bak-Coleman, J. B., Alfano, M., Barfuss, W., Bergstrom, C. T., Centeno, M. A., Couzin, I. D., Donges, J. F., Galesic, M., Gersick, A. S., Jacquet, J., Kao, A. B., Moran, R. E., Romanczuk, P., Rubenstein, D. I., Tombak, K. J., Bavel, J. J. V., and Weber, E. U.: Stewardship of global collective behavior, P. Natl. Acad. Sci. USA, 118, e2025764118, https://doi.org/10.1073/pnas.2025764118, 2021. a
Barabási, A.-L. and Albert, R.: Emergence of Scaling in Random Networks, Science, 286, 509–512, https://doi.org/10.1126/science.286.5439.509, 1999. a
Barfuss, W.: Dynamical systems as a level of cognitive analysis of multi-agent learning: Algorithmic foundations of temporal-difference learning dynamics, Neural Comput. Appl., 34, 1653–1671, 2022. a
Barfuss, W., Donges, J. F., Vasconcelos, V. V., Kurths, J., and Levin, S. A.: Caring for the future can turn tragedy into comedy for long-term collective action under risk of collapse, P. Natl. Acad. Sci. USA, 117, 12915–12922, https://doi.org/10.1073/pnas.1916545117, 2020. a
Barlow, L.-A., Cecile, J., Bauch, C. T., and Anand, M.: Modelling Interactions between Forest Pest Invasions and Human Decisions Regarding Firewood Transport Restrictions, PLOS ONE, 9, e90511, https://doi.org/10.1371/journal.pone.0090511, 2014. a
Bauch, C. T., Sigdel, R., Pharaon, J., and Anand, M.: Early warning signals of regime shifts in coupled human–environment systems, P. Natl. Acad. Sci. USA, 113, 14560–14567, https://doi.org/10.1073/pnas.1604978113, 2016. a, b, c
Bechthold, M., Heitzig, J., Donges, J., Barfuss, W., Marc, W., Zimmerer, K. B., Kolb, J., Kolster, T., Müller-Hansen, F., and Breitbach, P.: pycopancore: Reference implementation of the Nexploit model in the copan:CORE World-Earth modelling framework, Zenodo [code], https://doi.org/10.5281/zenodo.13220767, 2024. a, b
Beckage, B., Gross, L., Lacasse, K., Carr, E., Metcalf, S., Winter, J., Howe, P., Fefferman, N., Franck, T., Zia, A., Kinzig, A., and Hoffman, F.: Linking models of human behaviour and climate alters projected climate change, Nat. Clim. Change, 8, 79–84, https://doi.org/10.1038/s41558-017-0031-7, 2018. a, b, c
Bernhard, H., Fehr, E., and Fischbacher, U.: Group Affiliation and Altruistic Norm Enforcement, Am. Econ. Rev., 96, 217–221, https://doi.org/10.1257/000282806777212594, 2006. a
Bianchi, F. and Squazzoni, F.: Agent-based models in sociology, WIREs Computational Statistics, 7, 284–306, https://doi.org/10.1002/wics.1356, 2015. a
Bicchieri, C.: Norms in the Wild: How to Diagnose, Measure, and Change Social Norms, Oxford University Press, ISBN 9780190622046, https://doi.org/10.1093/acprof:oso/9780190622046.001.0001, 2017. a, b, c
Biermann, F., Betsill, M. M., Gupta, J., Kanie, N., Lebel, L., Liverman, D., Schroeder, H., Siebenhüner, B., and Zondervan, R.: Earth system governance: a research framework, Int. Environ. Agreem.-P., 10, 277–298, 2010. a
Boccaletti, S., Bianconi, G., Criado, R., del Genio, C., Gómez-Gardeñes, J., Romance, M., Sendiña-Nadal, I., Wang, Z., and Zanin, M.: The structure and dynamics of multilayer networks, Phys. Rep., 544, 1–122, https://doi.org/10.1016/j.physrep.2014.07.001, 2014. a, b
Bonan, J., Cattaneo, C., d'Adda, G., and Tavoni, M.: The interaction of descriptive and injunctive social norms in promoting energy conservation, Nature Energy, 5, 900–909, https://doi.org/10.1038/s41560-020-00719-z, 2020a. a
Bonan, J., Cattaneo, C., d’Adda, G., and Tavoni, M.: The interaction of descriptive and injunctive social norms in promoting energy conservation, Nature Energy, 5, 900–909, https://doi.org/10.1038/s41560-020-00719-z, 2020b. a
Breier, J., Schwarz, L., Donges, J. F., Gerten, D., and Rockström, J.: Regenerative agriculture for food security and ecological resilience: illustrating global biophysical and social spreading potentials, Potsdam Institute for Climate Impact Research, 16 pp., https://doi.org/10.48485/pik.2023.001, 2023. a
Brulle, R. J. and Norgaard, K. M.: Avoiding cultural trauma: climate change and social inertia, Environ. Polit., 28, 886–908, https://doi.org/10.1080/09644016.2018.1562138, 2019. a
Bury, T. M., Bauch, C. T., and Anand, M.: Charting pathways to climate change mitigation in a coupled socio-climate model, PLOS Comput. Biol., 15, e1007000, https://doi.org/10.1371/journal.pcbi.1007000, 2019. a, b
Calvin, K. and Bond-Lamberty, B.: Integrated human-earth system modeling – State of the science and future directions, Environ. Res. Lett., 13, 063006, https://doi.org/10.1088/1748-9326/aac642, 2018. a
Carpenter, S. R., Folke, C., Scheffer, M., and Westley, F. R.: Dancing on the volcano: social exploration in times of discontent, Ecol. Soc., 24, 23, https://doi.org/10.5751/ES-10839-240123, 2019. a
Carrington, M. J., Neville, B. A., and Whitwell, G. J.: Why Ethical Consumers Don't Walk Their Talk: Towards a Framework for Understanding the Gap Between the Ethical Purchase Intentions and Actual Buying Behaviour of Ethically Minded Consumers, J. Bus. Ethics, 97, 139–158, https://doi.org/10.1007/s10551-010-0501-6, 2010. a
Castilla-Rho, J. C., Rojas, R., Andersen, M., Holley, C., and Mariethoz, G.: Social tipping points in global groundwater management, Nature Human Behaviour, 1, 640–649, https://doi.org/10.1038/s41562-017-0181-7, 2017. a, b, c
Centola, D.: The Spread of Behavior in an Online Social Network Experiment, Science, 329, 1194–1197, https://doi.org/10.1126/science.1185231, 2010. a
Centola, D.: The Social Origins of Networks and Diffusion, Am. J. Sociol., 120, 1295–1338, https://doi.org/10.1086/681275, 2015. a, b
Centola, D., Willer, R., and Macy, M.: The Emperor’s Dilemma: A Computational Model of Self‐Enforcing Norms, Am. J. Sociol., 110, 1009–1040, https://doi.org/10.1086/427321, 2005. a
Ceschi, A., Sartori, R., Dickert, S., Scalco, A., Tur, E., Tommasi, F., and Delfini, K.: Testing a norm-based policy for waste management: An agent-based modeling simulation on nudging recycling behavior, J. Environ. Manage., 294, 112938, https://doi.org/10.1016/j.jenvman.2021.112938, 2021. a
Cialdini, R., Reno, R., and Kallgren, C.: A Focus Theory of Normative Conduct: Recycling the Concept of Norms to Reduce Littering in Public Places, J. Pers. Soc. Psychol., 58, 1015–1026, https://doi.org/10.1037/0022-3514.58.6.1015, 1990. a, b
Constantino, S. M., Schlüter, M., Weber, E., and Wijermans, N.: Cognition and behavior in context: a framework and theories to explain natural resource use decisions in social-ecological systems, Sustain. Sci., 16, 1651–1671, https://doi.org/10.1007/s11625-021-00989-w, 2021a. a
Constantino, S. M., Pianta, S., Rinscheid, A., Frey, R., and Weber, E. U.: The source is the message: the impact of institutional signals on climate change–related norm perceptions and behaviors, Climatic Change, 166, 35, https://doi.org/10.1007/s10584-021-03095-z, 2021b. a
Constantino, S. M., Sparkman, G., Kraft-Todd, G., Bicchieri, C., Centola, D., Shell-Duncan, B., Vogt, S., and Weber, E.: Scaling Up Change: A Critical Review and Practical Guide to Harnessing Social Norms for Climate Action, Psychol. Sci. Publ. Int., 23, 50–97, https://doi.org/10.1177/15291006221105279, 2022. a, b, c, d, e, f, g, h, i, j
Crameri, F., Shephard, G. E., and Heron, P. J.: The misuse of colour in science communication, Nat. Commun., 11, 5444, https://doi.org/10.1038/s41467-020-19160-7, 2020. a
Crutzen, P.: Geology of Mankind, Nature, 415, 23, https://doi.org/10.1038/415023a, 2002. a
Davis, C. A., Heiman, J. R., and Menczer, F.: A Role for Network Science in Social Norms Intervention, Procedia Comput. Sci., 51, 2217–2226, https://doi.org/10.1016/j.procs.2015.05.499, 2015. a, b
Donges, J. F., Lucht, W., Müller-Hansen, F., and Steffen, W.: The technosphere in Earth System analysis: A coevolutionary perspective, The Anthropocene Review, 4, 23–33, https://doi.org/10.1177/2053019616676608, 2017a. a
Donges, J. F., Winkelmann, R., Lucht, W., Cornell, S. E., Dyke, J. G., Rockström, J., Heitzig, J., and Schellnhuber, H.: Closing the loop: Reconnecting human dynamics to Earth System science, The Anthropocene Review, 4, 151–157, https://doi.org/10.1177/2053019617725537, 2017b. a, b
Donges, J. F., Heitzig, J., Barfuss, W., Wiedermann, M., Kassel, J. A., Kittel, T., Kolb, J. J., Kolster, T., Müller-Hansen, F., Otto, I. M., Zimmerer, K. B., and Lucht, W.: Earth system modeling with endogenous and dynamic human societies: the copan:CORE open World–Earth modeling framework, Earth Syst. Dynam., 11, 395–413, https://doi.org/10.5194/esd-11-395-2020, 2020. a, b, c, d, e, f, g, h, i, j
Donges, J. F., Lucht, W., Cornell, S. E., Heitzig, J., Barfuss, W., Lade, S. J., and Schlüter, M.: Taxonomies for structuring models for World–Earth systems analysis of the Anthropocene: subsystems, their interactions and social–ecological feedback loops, Earth Syst. Dynam., 12, 1115–1137, https://doi.org/10.5194/esd-12-1115-2021, 2021. a, b, c
Elsenbroich, C. and Gilbert, N.: Modelling Norms, Springer Dordrecht, ISBN 978-94-017-8514-3, https://doi.org/10.1007/978-94-007-7052-2, 2015. a, b, c, d
Epstein, J.: Learning to Be Thoughtless: Social Norms and Individual Computation, Comput. Econ., 18, 9–24, https://doi.org/10.1023/A:1013810410243, 2001. a
Erdős, P. and Rényi, A.: On the evolution of random graphs, Publ. Math. Inst. Hung. Acad. Sci, 5, 17–60, 1960. a
Falk, A., Andre, P., Boneva, T., and Chopra, F.: Fighting Climate Change: The Role of Norms, Preferences, and Moral Values, SSRN Journal, 59 pp., https://doi.org/10.2139/ssrn.3885418, 2021. a
Farahbakhsh, I., Bauch, C. T., and Anand, M.: Best response dynamics improve sustainability and equity outcomes in common-pool resources problems, compared to imitation dynamics, J. Theor. Biol., 509, 110476, https://doi.org/10.1016/j.jtbi.2020.110476, 2021. a
Finnemore, M. and Sikkink, K.: International Norm Dynamics and Political Change, Int. Organ., 52, 887–917, https://doi.org/10.1162/002081898550789, 1998. a
Gavrilets, S.: The dynamics of injunctive social norms, Evolutionary Human Sciences, 2, e60, https://doi.org/10.1017/ehs.2020.58, 2020. a
Gavrilets, S. and Richerson, P. J.: Collective action and the evolution of social norm internalization, P. Natl. Acad. Sci. USA, 114, 6068–6073, https://doi.org/10.1073/pnas.1703857114, 2017. a
Geier, F., Barfuss, W., Wiedermann, M., Kurths, J., and Donges, J. F.: The physics of governance networks: critical transitions in contagion dynamics on multilayer adaptive networks with application to the sustainable use of renewable resources, Eur. Phys. J.-Spec. Top., 228, 2357–2369, https://doi.org/10.1140/epjst/e2019-900120-4, 2019. a, b, c, d, e, f, g
Gelfand, M. J., Gavrilets, S., and Nunn, N.: Norm Dynamics: Interdisciplinary Perspectives on Social Norm Emergence, Persistence, and Change, Annu. Rev. Psychol., 75, 341–378, https://doi.org/10.1146/annurev-psych-033020-013319, 2024. a, b
Geschke, D. and Frindte, W.: Henri Tajfel (Hg.): Social Identity and Intergroup Relations, Cambridge University Press: Cambridge 1982, 546 S., in: Klassiker der Sozialwissenschaften, chap. 75, Springer VS Wiesbaden, 325–329, https://doi.org/10.1007/978-3-658-13213-2, 2016. a
Gössling, S., Humpe, A., and Bausch, T.: Does “flight shame” affect social norms? Changing perspectives on the desirability of air travel in Germany, J. Clean. Prod., 266, 122015, https://doi.org/10.1016/j.jclepro.2020.122015, 2020. a
Gross, T. and Blasius, B.: Adaptive coevolutionary networks: a review, J. R. Soc. Interface, 5, 259–271, https://doi.org/10.1098/rsif.2007.1229, 2008. a
Guilbeault, D., Becker, J., and Centola, D.: Complex Contagions: A Decade in Review, in: Complex Spreading Phenomena in Social Systems, edited by: Lehmann, S. and Ahn, Y.-Y., 3–25, ISBN 978-3-319-77331-5, https://doi.org/10.1007/978-3-319-77332-2_1, 2018. a, b, c, d
Heitzig, J., Kittel, T., Donges, J. F., and Molkenthin, N.: Topology of sustainable management of dynamical systems with desirable states: from defining planetary boundaries to safe operating spaces in the Earth system, Earth Syst. Dynam., 7, 21–50, https://doi.org/10.5194/esd-7-21-2016, 2016. a
Henrich, J. and Ensminger, J.: Theoretical foundations: The coevolution of social norms, intrinsic motivation, markets, and the institutions of complex societies, in: Experimenting with social norms: Fairness and punishment in cross-cultural perspective, Russell Sage Foundation, 19–44, ISBN 978-1-61044-840-6, 2014. a
Homans, G. C.: The Human Group, Routledge, https://doi.org/10.4324/9781315132518, 2017. a
Hunter, S.: If Ever the Twain Shall Meet: Graph Theoretical Dimensions of Formal and Informal Organization Structure, Int. J. Soc. Sci. Stud., 4, 79, https://doi.org/10.11114/ijsss.v4i10.1872, 2016. a
Janssen, M.: Modelling social norms of water conservation, Nature Human Behaviour, 1, 624–625, https://doi.org/10.1038/s41562-017-0196-0, 2017. a, b, c
Kinzig, A., Ehrlich, P., Alston, L., Arrow, K., Barrett, S., Buchman, T., Daily, G., Levin, B., Levin, S. A., and Oppenheimer, M.: Social Norms and Global Environmental Challenges: The Complex Interaction of Behaviors, Values, and Policy, BioScience, 63, 164–175, https://doi.org/10.1525/bio.2013.63.3.5, 2013. a
Lade, S., Tavoni, A., Levin, S. A., and Schlüter, M.: Regime shifts in a social-ecological system, Theor. Ecol., https://doi.org/10.1007/s12080-013-0187-3, 2013. a, b, c
Legros, S. and Cislaghi, B.: Mapping the Social-Norms Literature: An Overview of Reviews, Perspect. Psychol. Sci., 15, 62–80, https://doi.org/10.1177/1745691619866455, 2019. a, b
Lenton, T. M. and Latour, B.: Gaia 2.0, Science, 361, 1066–1068, https://doi.org/10.1126/science.aau0427, 2018. a
Li, N., Hilgard, J., Scheufele, D. A., Winneg, K. M., and Jamieson, K. H.: Cross-pressuring conservative Catholics? Effects of Pope Francis' encyclical on the U.S. public opinion on climate change, Climatic Change, 139, 367–380, https://doi.org/10.1007/s10584-016-1821-z, 2016. a
Lin, C.-Y., Yang, Y. C. E., Malek, K., and Adam, J. C.: An investigation of coupled natural human systems using a two-way coupled agent-based modeling framework, Environ. Modell. Softw., 155, 105451, https://doi.org/10.1016/j.envsoft.2022.105451, 2022. a
Liu, H., Alharthi, M., Atil, A., Zafar, M., and Khan, I.: A non-linear analysis of the impacts of natural resources and education on environmental quality: Green energy and its role in the future, Resour. Policy, 79, 102940, https://doi.org/10.1016/j.resourpol.2022.102940, 2022. a
Malhi, Y., Roberts, J. T., Betts, R. A., Killeen, T. J., Li, W., and Nobre, C. A.: Climate Change, Deforestation, and the Fate of the Amazon, Science, 319, 169–172, https://doi.org/10.1126/science.1146961, 2008. a
Maurstad, A.: To Fish or Not to Fish: Small-Scale Fishing and Changing Regulations of the Cod Fishery in Northern Norway, Hum. Organ., 59, 37–47, https://doi.org/10.17730/humo.59.1.q0242m112x223862, 2000. a
McDonald, R. I. and Crandall, C. S.: Social norms and social influence, Current Opinion in Behavioral Sciences, 3, 147–151, https://doi.org/10.1016/j.cobeha.2015.04.006, 2015. a, b
McPherson, M., Smith-Lovin, L., and Cook, J. M.: Birds of a Feather: Homophily in Social Networks, Annu. Rev. Sociol., 27, 415–444, https://doi.org/10.1146/annurev.soc.27.1.415, 2001. a
Müller-Hansen, F., Schlüter, M., Mäs, M., Donges, J. F., Kolb, J. J., Thonicke, K., and Heitzig, J.: Towards representing human behavior and decision making in Earth system models – an overview of techniques and approaches, Earth Syst. Dynam., 8, 977–1007, https://doi.org/10.5194/esd-8-977-2017, 2017. a, b
Neidhardt, F.: Das innere System sozialer Gruppen, Kölner Z. Soziol. Soz., 69, 433–454, https://doi.org/10.1007/s11577-017-0415-8, 2017. a
Newman, M.: Social networks, in: Networks, Oxford University Press, ISBN 9780198805090, https://doi.org/10.1093/oso/9780198805090.003.0004, 2018. a, b
Nhim, T., Richter, A., and Zhu, X.: The resilience of social norms of cooperation under resource scarcity and inequality – An agent-based model on sharing water over two harvesting seasons, Ecol. Complex., 40, 100709, https://doi.org/10.1016/j.ecocom.2018.06.001, publisher: Elsevier, 2019. a, b, c
Nitzbon, J., Heitzig, J., and Parlitz, U.: Sustainability, collapse and oscillations in a simple World-Earth model, Environ. Res. Lett., 12, 074020, https://doi.org/10.1088/1748-9326/aa7581, 2017. a
Nowak, M. and Sigmund, K.: A strategy of win-stay, lose-shift that outperforms tit-for-tat in the Prisoner's Dilemma game, Nature, 364, 56–58, https://doi.org/10.1038/364056a0, 1993. a, b
Nyborg, K., Anderies, J. M., Dannenberg, A., Lindahl, T., Schill, C., Schlüter, M., Adger, W. N., Arrow, K. J., Barrett, S., Carpenter, S., Chapin, F. S., Crépin, A., Daily, G., Ehrlich, P., Folke, C., Jager, W., Kautsky, N., Levin, S. A., Madsen, O. J., Polasky, S., Scheffer, M., Walker, B., Weber, E. U., Wilen, J., Xepapadeas, A., and de Zeeuw, A.: Social norms as solutions, Science, 354, 42–43, https://doi.org/10.1126/science.aaf8317, 2016. a, b, c, d, e, f
Nøstbakken, L.: Formal and informal quota enforcement, Resour. Energy Econ., 35, 191–215, https://doi.org/10.1016/j.reseneeco.2012.10.001, 2013. a
Olson, M.: The Logic of Collective Action: Public Goods and the Theory of Groups, Second Printing with a New Preface and Appendix, Harvard University Press, ISBN 9780674537507, https://doi.org/10.2307/j.ctvjsf3ts, 1971. a
Opp, K.: How do norms emerge? An outline of a theory, Mind & Society, 2, 101–128, https://doi.org/10.1007/BF02512077, 2001. a, b, c, d
Ostrom, E.: Collective Action and the Evolution of Social Norms, J. Econ. Perspect., 14, 137–158, https://doi.org/10.1257/jep.14.3.137, 2000. a, b, c, d
Otto, I. M., Donges, J. F., Cremades, R., Bhowmik, A., Hewitt, R. J., Lucht, W., Rockström, J., Allerberger, F., McCaffrey, M., Doe, S. S. P., Lenferna, A., Morán, N., van Vuuren, D. P., and Schellnhuber, H.: Social tipping dynamics for stabilizing Earth’s climate by 2050, Proceedings of the National Acad. Sci. USA, 117, 2354–2365, https://doi.org/10.1073/pnas.1900577117, 2020. a, b
Perman, R.: Natural Resource and Environmental Economics, Pearson Education, ISBN 978-0-273-65559-6, 2003. a
Restrepo-Plaza, L. and Fatas, E.: When ingroup favoritism is not the social norm a lab-in-the-field experiment with victims and non-victims of conflict in Colombia, J. Econ. Behav. Organ., 194, 363–383, https://doi.org/10.1016/j.jebo.2021.12.025, 2022. a
Rockström, J., Steffen, W., Noone, K., Persson, A., Chapin III, F. S., Lambin, E., Lenton, T., Scheffer, M., Folke, C., and Schellnhuber, H.: A Safe Operating Space for Humanity, Nature, 461, 472–475, 2009. a
Roth-Fauchere, K.: Chaos – Complexity – Evolution, https://arolla.net/werkstatt/science/chaos-complexity-evolution (last access: 24 May 2023), 2023. a
Saaty, T. L.: Résumé of Useful Formulas in Queuing Theory, Oper. Res., 5, 161–200, 1957. a
Satake, A., Leslie, H., Iwasa, Y., and Levin, S. A.: Coupled ecological–social dynamics in a forested landscape: Spatial interactions and information flow, J. Theor. Biol., 246, 695–707, https://doi.org/10.1016/j.jtbi.2007.01.014, 2007. a, b
Schelling, T.: Micromotives and Macrobehavior, Norton, ISBN 0393090094, 1978. a
Schelling, T. C.: Dynamic models of segregation, J. Math. Sociol., 1, 143–186, https://doi.org/10.1080/0022250X.1971.9989794, 1971. a
Schellnhuber, H.: “Earth system” analysis and the second Copernican revolution, Nature, 402, C19–C23, 1999. a
Schellnhuber, H.: Tipping elements in the Earth System, P. Natl. Acad. Sci. USA, 106, 20561–20563, https://doi.org/10.1073/pnas.0911106106, 2009. a
Schlüter, M., Mcallister, R. R. J., Arlinghaus, R., Bunnefeld, N., Eisenack, K., Hölker, F., Milner-Gulland, E., Müller, B., Nicholson, E., Quaas, M., and Stoeven, M.: New Horizons for Managing the Environment: A Review of Coupled Social-Ecological Systems Modeling. Natural Resource Modeling, Nat. Resour. Model., 25, 219–272, https://doi.org/10.1111/j.1939-7445.2011.00108.x, 2012. a, b
Schlüter, M., Tavoni, A., and Levin, S. A.: Robustness of norm-driven cooperation in the commons, P. Roy. Soc. B-Biol. Sci., 283, 20152431, https://doi.org/10.1098/rspb.2015.2431, 2016. a
Schultz, P., Nolan, J., Cialdini, R., Goldstein, N., and Griskevicius, V.: The Constructive, Destructive, and Reconstructive Power of Social Norms, Psychol. Sci., 18, 429–34, https://doi.org/10.1111/j.1467-9280.2007.01917.x, 2007. a
Sherif, M. and Sherif, C. W.: Research on intergroup relations, in: Perspectives in Social Psychology, edited by: Klineberg, O. and Christie, R., Holt, Rinehart and Winston, 153–177, ISBN 9780030481253, 1965. a
Sigdel, R., Anand, M., and Bauch, C. T.: Competition between injunctive social norms and conservation priorities gives rise to complex dynamics in a model of forest growth and opinion dynamics, J. Theor. Biol., 432, 132–140, https://doi.org/10.1016/j.jtbi.2017.07.029, 2017. a, b, c
Smith, J. R., Louis, W. R., Terry, D. J., Greenaway, K. H., Clarke, M. R., and Cheng, X.: Congruent or conflicted? The impact of injunctive and descriptive norms on environmental intentions, J. Environ. Psychol., 32, 353–361, https://doi.org/10.1016/j.jenvp.2012.06.001, 2012. a
Spears, R.: Social Influence and Group Identity, Annu. Rev. Psychol., 72, 367–390, https://doi.org/10.1146/annurev-psych-070620-111818, 2021. a, b
Staunton, M., Louis, W. R., Smith, J. R., Terry, D. J., and McDonald, R. I.: How negative descriptive norms for healthy eating undermine the effects of positive injunctive norms, J. Appl. Soc. Psychol., 44, 319–330, https://doi.org/10.1111/jasp.12223, 2014. a
Steffen, W., Broadgate, W., Deutsch, L., Gaffney, O., and Ludwig, C.: The Trajectory of the Anthropocene: The Great Acceleration, The Anthropocene Review, https://doi.org/10.1177/2053019614564785, 2015. a
Steffen, W., Richardson, K., Rockström, J., Schellnhuber, H., Dube, O. P., Dutreuil, S., Lenton, T., and Lubchenco, J.: The emergence and evolution of Earth System Science, Nature Reviews Earth & Environment, 1, 54–63, https://doi.org/10.1038/s43017-019-0005-6, 2020. a, b
Suzuki, Y. and Iwasa, Y.: Conflict between groups of players in coupled socio-economic and ecological dynamics, Ecol. Econ., 68, 1106–1115, https://doi.org/10.1016/j.ecolecon.2008.07.024, 2009. a
Thampi, V. A., Anand, M., and Bauch, C. T.: Socio-ecological dynamics of Caribbean coral reef ecosystems and conservation opinion propagation, Sci. Rep., 8, 2597, https://doi.org/10.1038/s41598-018-20341-0, 2018. a
Tichy, N. and Fombrun, C.: Network Analysis in Organizational Settings, Hum. Relat., 32, 923–965, https://doi.org/10.1177/001872677903201103, 1979. a
Tilman, A., Watson, J., and Levin, S. A.: Maintaining cooperation in social-ecological systems: Effective bottom-up management often requires sub-optimal resource use, Theor. Ecol., 10, 155–165, https://doi.org/10.1007/s12080-016-0318-8, 2016. a
Tomasello, M.: Becoming Human: A Theory of Ontogeny, Harvard University Press, ISBN 9780674980853, https://doi.org/10.2307/j.ctv24tr9w1, 2019. a, b
Traulsen, A., Semmann, D., Sommerfeld, R., Krambeck, H.-J., and Milinski, M.: Human strategy updating in evolutionary games, P. Natl. Acad. Sci. USA, 107, 2962–2966, https://doi.org/10.1073/pnas.0912515107, 2010. a
Tu, C., Wu, Y., Chen, R., Fan, Y., and Yang, Y.: Balancing Resource and Strategy: Coevolution for Sustainable Common-Pool Resource Management, Earth Systems and Environment, 9, 1529–1542, https://doi.org/10.1007/s41748-024-00489-8, 2024. a, b
Turner, J. C.: Towards a cognitive redefinition of the social group, in: Social Identity and Intergroup Relation, edited by: Tajfel, H., chap. 1, Cambridge University Press, 15–36, ISBN 978-0-521-15365-2, 2010. a
Verburg, P., Dearing, J., Dyke, J., Van der Leeuw, S., Seitzinger, S., Steffen, W., and Syvitski, J.: Methods and approaches to modelling the Anthropocene, Global Environmental Change, 39, 328–340, https://doi.org/10.1016/j.gloenvcha.2015.08.007, 2015. a
Voss, T.: Game-theoretical perspectives on the emergence of social norms, in: Social Norms, 105–136, ISBN 978-1-61044-280-0, 2005. a
Winkelmann, R., Donges, J. F., Smith, E. K., Milkoreit, M., Eder, C., Heitzig, J., Katsanidou, A., Wiedermann, M., Wunderling, N., and Lenton, T. M.: Social tipping processes towards climate action: A conceptual framework, Ecol. Econ., 192, 107242, https://doi.org/10.1016/j.ecolecon.2021.107242, 2022. a, b
Short summary
Social norms are a major influence on human behaviour. In natural resource use models, norms are often included in a simplistic way leading to “black or white” sustainability outcomes. We find that a dynamic representation of norms, including social groups, determines more nuanced states of the environment in a stylised model of resource use while also defining the success of attempts to manage the system, suggesting the importance of representing both aspects well in coupled models.
Social norms are a major influence on human behaviour. In natural resource use models, norms are...
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