Cross-system interactions for positive tipping cascades

Eker, Sibel; Lenton, Timothy M.; Powell, Tom; Scheffran, Jürgen; Smith, Steven R.; Swamy, Deepthi; Zimm, Caroline

doi:https://doi.org/10.5194/egusphere-2023-2544

Preprints

https://doi.org/10.5194/egusphere-2023-2544

Preprints

11 Dec 2023

| 11 Dec 2023

Cross-system interactions for positive tipping cascades

Sibel Eker, Timothy M. Lenton, Tom Powell, Jürgen Scheffran, Steven R. Smith, Deepthi Swamy, and Caroline Zimm

Abstract. Positive tipping points are promising leverage points in social systems for accelerated progress towards climate and sustainability targets. Besides their impact in specific social systems such as energy, food, or social norms and values, positive tipping dynamics may in some cases spread across different systems, amplifying the impact of tipping interventions. However, the cross-system interactions that can create such tipping cascades are sparsely examined. Here, we review interactions across sociotechnical, -ecological, -economic and -political systems that can lead to tipping cascades based on the emerging and relevant past evidence. We show that there are several feedback mechanisms where a strategic input can trigger secondary impacts for a disproportionately large positive response, and various agents that can trigger such cascades. This review of cross-system interactions facilitates the quantification and analysis of positive tipping cascades in future studies.

Received: 30 Oct 2023 – Discussion started: 11 Dec 2023

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Sibel Eker, Timothy M. Lenton, Tom Powell, Jürgen Scheffran, Steven R. Smith, Deepthi Swamy, and Caroline Zimm

Status: final response (author comments only)

RC1:
'Comment on egusphere-2023-2544', J David Tabara, 03 Jan 2024
I read this paper with great interest as it addresses the very core of the research needs to trigger and accelerate positive large-scale systems change to cope with global and existential risks. The paper is in an advanced stage for publication but also in my view it also has room for improvement. The following comments may apply:
The paper argues (l.31-32) that “If there are strong interconnections between these systems, a positive tipping intervention can lead to a sequence of secondary impacts across different systems” which I totally agree. However, and related to this, some of these questions may need also to be addressed: what kinds of interconnections need to be considered? how do we qualify, assess or even anticipate the strength of such interconnections? To which extent some interconnections can be detrimental to particular systems resilience or adaptation? (e.g., in biosystems invasive species is a main source of biodiversity loss; and in socio-economic systems, some systems would be better if they remain unconnected, thus policies supporting local economies, now being hit by large multi-national distribution companies); and, to which particular connections (e.g., policy arrangements) between governance systems may be positive or negative to harness negative TP and create the conditions for the emergence of positive ones?

The paper partly addresses such different interconnections, as expressed in the arrows of figure 1, but not in systematic way. In my view, it may be worth mentioning that different systems (that have different natures) may be/are/can be connected by different mechanisms and that such connections may have ambivalent effects. For instance, some systems are connected by financial/monetary flows (e.g., costs) and information while others by biophysical ones (e.g., GHGs). Also, some apparently disconnected systems -as it was originally thought of COVID when it first appeared in China- prove to be much more connected and exhibit a total-system’s-like dynamics than we tend to imagine. So I just wonder whether some additional lines on this may be useful, as it is not necessarily apparent and it is at the core of discussion on tipping cascades. The point is that different systems may be connected by different mechanisms and perhaps what we would need is to provide a typology/mapping of different connecting mechanisms. It may also be useful to think that it may also be also a hierarchy of connecting mechanisms across tipping processes- e.g., in terms of scaling, diffusion speed and connectivity impact- that we don’t yet fully understand. On this, we could probably argue that, at present, monetary flows are probably some the most important ones although there are others related to cultural changes, being the later crucial for positive tipping points and to accelerate sustainability learning (as well as the opposite, growing meat demand globally in lower and mid income countries also affects negative global GHG emissions).

Therefore, it seems to me that the paper has a main focus on the ‘what’ is connected, but needs to place further emphasis on the ‘how’ -different types of connecting mechanisms and different potentialities and dynamics of them- as well as, and most importantly, on the ‘whom’; that is, on who are the agents enabling or impeding such connections -as well as the principles that need to be applied for enhancing a ‘good interconnection’.

In this respect, we should not lead the readers to assume that increasing the connectivity of systems is necessarily good -or even static, as their connectivity is also influenced by human action (either deliberate or not). We need social-ecological systems to be diverse and resilient, hence in some systems connectivity may erode intrinsic complexity necessary to cope with systemic global risks (something that was also learned also during the pandemic and that showed the importance of disconnected /local food systems and the vulnerability of large-scale just-in-time distribution systems). Connecting systems may be good if such strategies to linking systems -and to provoke positive cascades among them- follow a transformative (e.g., regenerative) vision and a set of governing principles – e.g., based on sustainability and equity- and that are also aware of the risks of ‘connecting too much’ or ‘connecting for the bad purposes’; mostly, because in complex systems we can never anticipate fully what will be the final outcome of such complex tipping processes - we can only create the conditions for the emergence of some positive outcomes so their development need to be continuously monitored and assessed -to prevent and harness their potential negative effects (Tàbara et al. 2021 (2024)).

Therefore, some reference to the kinds of governing principles that need to be followed to assess the what is positive or negative in connecting and extending different kinds of systems may apply -but also using a wide complex systems approach. The move to electric vehicles can be assessed as positive but some may consider that this is only the case if that does not create new social inequalities or resource scarcities in other socio-ecological / political systems.

Moreover, and perhaps because of the above, it is not clear to me the criteria that have been used to separate and classify the different domains of action that appear in Figure 1, e.g. the different agents involved in the different systems, some who operate at different scales. It seems however that the main criteria used is the level of influence upon other systems; so, if that is the case, again a more systematic treatment of different forms of influence of each domain/system upon others may be needed. It seems that the authors have only selected some of these forms of influence, but there may be others that need to be considered or that there may be some overlaps (in fact, it looks like many interactions and chains of influence that could be depicted in a systems’ map similar to Figure 2 may be missing, e.g., information systems (like distorted social media in negative TP, but political education in positive TPs)-> affects voting -> affects governance -> affects resource consumption, etc).

Another way to think about this could be to focus on where is the room for deliberate action in each selected subsystem, so we would need to assess where there is higher potential for tipping interventions, which in turns depends on various systems sensitivities to other systems’ dynamics and changes.

Consider whether in line 126 you need this first part of the sentence (I would just delete it): ‘The role of society is considered a key driver of transformation in the food system’, because later you focus on behavioural changes, which I think is what you mean (‘society’ is rather large concept and it is a driver of and it is driven by many things).

On cascading effects and tipping points in sociopolitical systems it may be worth having a look at the report produced by Mey and Lilliestam (2021) out of the TIPPING+ project, particularly section 2.3 and 3 including the various tables on indicators. It also seems to me that the treatment provided in this paper misses quite a lot of these indicators and factors that need to be considered to assess tipping processes and cascades in sociopolitical systems. But most importantly, it treats them as a single system, instead of acknowledging the existence of many different kinds of sociopolitical systems governed by different ideological principles and structures in different places, countries and scales. In fact, the actual structure of a given sociopolitical system, as emphasized strongly by E. Ostrom, is crucial in influencing or preventing the potential of positive tipping points, e.g, those more polycentric being more conducive to institutional learning, integrate multiple perspectives, support innovations, etc.

On governance systems, it may be then also worth mentioning the paper by Eder and Stadelmann-Steffen (2023), who treat the political either as context that provides the rules of the game or as part of the system that may tip itself and trigger tipping cascades. They contend that political complexity requires distinguishing between policy (as the set of political institutions), politics (in terms of decision-making processes) and policy regarding particular goals, interests and solutions.

Line 270: It seems to me that the first sentence of this paragraph does not fully apply here: “To overcome collective action problem and the tragedy of the commons”. The tragedy of the commons is about free-riding of open access resources with differential individual gains on limited resource use. In my view the discussion on positive tipping cascades much goes beyond that and I’m not sure it should be narrowly framed within that discourse. But if the authors think it worth, then one needs to elaborate on to which extent and how (e.g., explaining which mechanisms and using the whole Ostrom principles and theoretical CPR framework) a positive tipping point would be reached. (I believe Carl Folke has a recent paper on this). So, I would either just delete that sentence or further elaborate on this a lot more, or simply I would focus on the second part of the paragraph, that of the various mechanisms that are being mentioned. Unfortunately, such crucial part of the paper, those of the various mechanisms for tipping cascades in my view is too short and in any case requires further elaboration.

Finally, the conclusion, and probably because the comments above, seems also a bit loose and not directly or systematically addressing the various insights derived from the review - including the kinds of research need or gaps that to be addressed – which actually began to be mentioned at the end of the previous section on cascading mechanisms.

References:

Tàbara J.D., Mangalagiu D, Frantal B, Mey F, Maier R, Lilliestam J, Sarrica M, Mandel A, Lieu J, Cottone P., Veland S, Martínez-Reyes A. 2021. Towards transformative emergence. Research challenges for enabling social-ecological tipping points toward regional sustainability transformations. TIPPING+ Working Paper. https://tipping-plus.eu/sites/default/files/Working%20Documents/T%2BWorking%20Document%20Series%202021.01-Transformative%20emergence.pdf ; to be published (Feb 2024) in: Tàbara J.D., Flamos, A., Mangalagiu, D., Michas, S. (eds). Forthcoming. Positive tipping points towards sustainability. Understanding the Conditions and Strategies for Fast Decarbonization in Regions. Springer. https://link.springer.com/book/9783031507618

Mey, F., Lilliestam, J. 2021. Report with literature review advancing the state of the art on tipping points in Public Policy and governance research. Deliverable D3.1. https://tipping-plus.eu/sites/default/files/deliverables/D3.1%20Literature%20Review%20WP3.pdf
Citation: https://doi.org/10.5194/egusphere-2023-2544-RC1
- AC2:
  'Reply on RC1', Sibel Eker, 08 Apr 2024
  Thanks for your interest in this manuscript and your thorough review, which helped to improve it significantly. Below, we respond to your comments and suggestions bullet by bullet, where bulleted paragraphs are your original comments. and summarize how we will address them in the revised manuscript:
  The paper argues (l.31-32) that “If there are strong interconnections between these systems, a positive tipping intervention can lead to a sequence of secondary impacts across different systems” which I totally agree. However, and related to this, some of these questions may need also to be addressed: what kinds of interconnections need to be considered? how do we qualify, assess or even anticipate the strength of such interconnections? To which extent some interconnections can be detrimental to particular systems resilience or adaptation? (e.g., in biosystems invasive species is a main source of biodiversity loss; and in socio-economic systems, some systems would be better if they remain unconnected, thus policies supporting local economies, now being hit by large multi-national distribution companies); and, to which particular connections (e.g., policy arrangements) between governance systems may be positive or negative to harness negative TP and create the conditions for the emergence of positive ones?
  
  Thanks for raising this point to clarify the meaning of a positive tipping cascade. In response, we revised the first paragraph of the Introduction section about positive tipping points for textual clarity, and in the second paragraph about cascades, we specifically added the following sentence on what delineates positive tipping cascades from other cross-system interactions:
  “…These secondary impacts, called cascades, result in a much larger eventual impact. As positive tipping in a specific system, positive tipping cascades are characterized by desirability and intentionality towards decarbonization and sustainability, hence the existing cross-system interconnections that enable, facilitate or strengthen climate change mitigation, adaptation and sustainability efforts are considered a positive tipping cascade.”
  In the last paragraph of the Introduction, the aim of this paper was stated as “describing key examples of cascading effects and feedback loops”. We expanded this paragraph with the following sentence, by acknowledging that the list presented in this paper is not exhaustive, and we focus on existing cross-system interconnections rather than arguing for establishing new interconnections for positive tipping:
  “We note that the examples we present here do not constitute the whole range of possible positive tipping cascades, especially from the hard-to-abate sectors such as heavy industry, and the cross-system connections that do not exist yet but can be built purposefully.”
  Furthermore, Section 3.1 includes a discussion on justice and equity aspects of positive tipping, acknowledging that it must be positive for everyone. While the relevance of interconnections to be taken into account is set by their impact on further decarbonization or sustainability in each system, their relevance in terms of the magnitude and intensity of impacts can be judged by empirical studies based on observed-data or model-based analyses (Section 3.2).
  The paper partly addresses such different interconnections, as expressed in the arrows of figure 1, but not in systematic way. In my view, it may be worth mentioning that different systems (that have different natures) may be/are/can be connected by different mechanisms and that such connections may have ambivalent effects. For instance, some systems are connected by financial/monetary flows (e.g., costs) and information while others by biophysical ones (e.g., GHGs). Also, some apparently disconnected systems -as it was originally thought of COVID when it first appeared in China- prove to be much more connected and exhibit a total-system’s-like dynamics than we tend to imagine. So I just wonder whether some additional lines on this may be useful, as it is not necessarily apparent and it is at the core of discussion on tipping cascades. The point is that different systems may be connected by different mechanisms and perhaps what we would need is to provide a typology/mapping of different connecting mechanisms. It may also be useful to think that it may also be also a hierarchy of connecting mechanisms across tipping processes- e.g., in terms of scaling, diffusion speed and connectivity impact- that we don’t yet fully understand. On this, we could probably argue that, at present, monetary flows are probably some the most important ones although there are others related to cultural changes, being the later crucial for positive tipping points and to accelerate sustainability learning (as well as the opposite, growing meat demand globally in lower and mid income countries also affects negative global GHG emissions).
  
  Thanks for raising this point about a systematic identification of cross-system interconnections. We agree that this is a useful future research avenue. In the revised manuscript, we added a new paragraph to the beginning of Section 3.2 on future research that can potentially include the development of a typology in terms of scale, speed, and potential as below:
  “… Furthermore, a typology of cross-system interactions underlying positive tipping cascades would enhance the communication and prioritization of research efforts. Such a typology can categorize the identified interactions in terms of their scale (local, national, global), speed of change (days, years, decades) and the agents who can manage or participate in directing those interacting systems towards the tipping point.”
  Therefore, it seems to me that the paper has a main focus on the ‘what’ is connected, but needs to place further emphasis on the ‘how’ -different types of connecting mechanisms and different potentialities and dynamics of them- as well as, and most importantly, on the ‘whom’; that is, on who are the agents enabling or impeding such connections -as well as the principles that need to be applied for enhancing a ‘good interconnection’.
  
  Thanks for this diagnosis that our manuscript focuses on “what”, rather than how and whom, which was indeed the purpose. Still, we explicitly state that triggering positive tipping cascades requires joint work by multiple actors that we exemplify in Section 3.1. In Section 3.2 of the revised manuscript, we briefly outline future work to identify the cross-system interactions systematically and developing a typology you recommended not only to categorize them but also to match them with the agents involved. It reads as:
  “…Such a typology can categorize the identified interactions in terms of their scale (local, national, global), speed of change (days, years, decades) and the agents who can manage or participate in directing those interacting systems towards the tipping point. ”
  In this respect, we should not lead the readers to assume that increasing the connectivity of systems is necessarily good -or even static, as their connectivity is also influenced by human action (either deliberate or not). We need social-ecological systems to be diverse and resilient, hence in some systems connectivity may erode intrinsic complexity necessary to cope with systemic global risks (something that was also learned also during the pandemic and that showed the importance of disconnected /local food systems and the vulnerability of large-scale just-in-time distribution systems). Connecting systems may be good if such strategies to linking systems -and to provoke positive cascades among them- follow a transformative (e.g., regenerative) vision and a set of governing principles – e.g., based on sustainability and equity- and that are also aware of the risks of ‘connecting too much’ or ‘connecting for the bad purposes’; mostly, because in complex systems we can never anticipate fully what will be the final outcome of such complex tipping processes - we can only create the conditions for the emergence of some positive outcomes so their development need to be continuously monitored and assessed -to prevent and harness their potential negative effects (Tàbara et al. 2021 (2024)).
  
  We are sorry to give the impression that connectivity or cross-system interactions are always good and more of them should be built purposefully so that positive tipping can be achieved. This is not our intention, and we fully agree that many cross-system interactions prevent or dampen positive tipping dynamics instead of reinforcing them. To clarify our stance, we added the following text to the introduction, stating that within the scope of this paper we focus on existing connections that can potentially create positive tipping cascades.
  “We acknowledge that not every cross-system interaction leads to a cascading effect for positive tipping, and many of those might be preventing or dampening the change towards rapid climate action and sustainability. While considering such dampening effects is of utmost importance to assess the plausible potential of positive tipping, in this paper, we focus only on the cross-system feedbacks that can amplify the positive tipping dynamics. We note that the examples we present here do not constitute the whole range of possible positive tipping cascades, especially from the hard-to-abate sectors such as heavy industry, and do not necessarily include cross-system connections that do not exist yet. Therefore, in Section 3.2 we briefly outline a future research agenda that can systematically identify further positive tipping cascades.”
  Therefore, some reference to the kinds of governing principles that need to be followed to assess the what is positive or negative in connecting and extending different kinds of systems may apply -but also using a wide complex systems approach. The move to electric vehicles can be assessed as positive but some may consider that this is only the case if that does not create new social inequalities or resource scarcities in other socio-ecological / political systems.
  
  Section 3.1 of the original manuscript already acknowledges that “positive tipping” should not create negative outcomes for any vulnerable group or system (Lines 228-231), hence include multiple knowledge sources and participatory approaches in identifying positive tipping elements and designing interventions. As a governing principle for cascades, in the revised manuscript we highlight “polycentric governance” that was discussed already by Pereira et al (2023) for positive tipping dynamics in Chapter 4.6 of the Global Tipping Points Report.
  Moreover, and perhaps because of the above, it is not clear to me the criteria that have been used to separate and classify the different domains of action that appear in Figure 1, e.g. the different agents involved in the different systems, some who operate at different scales. It seems however that the main criteria used is the level of influence upon other systems; so, if that is the case, again a more systematic treatment of different forms of influence of each domain/system upon others may be needed. It seems that the authors have only selected some of these forms of influence, but there may be others that need to be considered or that there may be some overlaps (in fact, it looks like many interactions and chains of influence that could be depicted in a systems’ map similar to Figure 2 may be missing, e.g., information systems (like distorted social media in negative TP, but political education in positive TPs)-> affects voting -> affects governance -> affects resource consumption, etc).
  
  Another way to think about this could be to focus on where is the room for deliberate action in each selected subsystem, so we would need to assess where there is higher potential for tipping interventions, which in turns depends on various systems sensitivities to other systems’ dynamics and changes.
  
  We state the purpose of this manuscript as “describing examples of cascading effects and feedback loops” that can amplify positive tipping across multiple systems. Therefore, we don’t aim to present a systematically identified list of cross-system connections yet in this manuscript. However, we fully acknowledge the necessity of it. Therefore, in Section 3.2 on future research, we discuss how such connections and positive tipping cascades can be identified and categorized more systematically for instance based on expert elicitation as presented in Eker, Wilson et al. 2022. This new paragraph on future research reads as:
  “This manuscript presents examples of potential positive tipping cascades, which are distilled from the emerging literature on positive tipping dynamics. Future research can identify a more complete range of positive tipping cascades more systematically. Expert elicitation, systems mapping, and systematic literature reviews can facilitate delineation of cross-system interactions that can possibly enable and impede positive tipping cascades, as exemplified in (Eker and Wilson, 2022). Case studies of historical tipping dynamics (Stadelmann-Steffen et al., 2021), local decarbonization (Tàbara et al., 2022), or statistical analyses on time-series data cross-system connections, such as finance and economic development (Chakraborty and Mandel, 2022) can support the identification and understanding of these connections, whereas future-oriented modelling studies help analyse their potential to trigger positive tipping cascades. Furthermore, a typology of cross-system interactions underlying positive tipping cascades would enhance the communication and prioritization of research efforts. Such a typology can categorize the identified interactions in terms of their scale (local, national, global), speed of change (days, years, decades) and the agents who can manage or participate in directing those interacting systems towards the tipping point.       ”
  Consider whether in line 126 you need this first part of the sentence (I would just delete it): ‘The role of society is considered a key driver of transformation in the food system’, because later you focus on behavioural changes, which I think is what you mean (‘society’ is rather large concept and it is a driver of and it is driven by many things).
  
  Thanks for this suggestion. We agree and deleted this sentence in the revised manuscript.
  On cascading effects and tipping points in sociopolitical systems it may be worth having a look at the report produced by Mey and Lilliestam (2021) out of the TIPPING+ project, particularly section 2.3 and 3 including the various tables on indicators. It also seems to me that the treatment provided in this paper misses quite a lot of these indicators and factors that need to be considered to assess tipping processes and cascades in sociopolitical systems. But most importantly, it treats them as a single system, instead of acknowledging the existence of many different kinds of sociopolitical systems governed by different ideological principles and structures in different places, countries and scales. In fact, the actual structure of a given sociopolitical system, as emphasized strongly by E. Ostrom, is crucial in influencing or preventing the potential of positive tipping points, e.g, those more polycentric being more conducive to institutional learning, integrate multiple perspectives, support innovations, etc.
  
  Thanks for suggestion the deliverable of the Tipping+ project. We acknowledge the complexity of sociopolitical systems beyond what is discussed in our manuscript. We use the tipping indicators listed in Mey and Lulliestam as examples of society-policy interactions, and use it to expand on our examples, by adding the following sentence in the first paragraph of Section 2.3:
  “…Similarly, based on a literature review of tipping and transition studies, Mey and Lilliestam (2020) identify the key variables that indicate, hence help monitoring tipping dynamics in the interaction of society and politics. Those are social acceptance of climate science, public support for and trust in government, as well as civil engagement and participation in public consultations, number of NGOs focusing on climate and environmental problems, and the share of citizens active in those. Below, we discuss additional variables and mechanisms of society’s influence on policy and politics. ”
  On governance systems, it may be then also worth mentioning the paper by Eder and Stadelmann-Steffen (2023), who treat the political either as context that provides the rules of the game or as part of the system that may tip itself and trigger tipping cascades. They contend that political complexity requires distinguishing between policy (as the set of political institutions), politics(in terms of decision-making processes) and policyregarding particular goals, interests and solutions.
  
  We agree that this new study by Eder and Stadelmann-Steffen clearly highlights the policy and political system not as a context but as part of tipping mechanisms, in line with our view in this paper. Therefore, in the revised manuscript we start Section 2.3 on sociopolitical systems by quoting them as below:
  “Political systems are often considered the context of positive tipping dynamics in the existing literature as highlighted by Eder and Stadelmann-Steffen (2023), even though they can change and tip in a positive direction for decarbonization and sustainability, too. Here, we consider the policies and political system not as a static context but as part of dynamic co-evolutionary tipping mechanisms. For instance, the interaction between society and policy can be key to tipping global carbon emissions by…”
  Line 270: It seems to me that the first sentence of this paragraph does not fully apply here: “To overcome collective action problem and the tragedy of the commons”. The tragedy of the commons is about free-riding of open access resources with differential individual gains on limited resource use. In my view the discussion on positive tipping cascades much goes beyond that and I’m not sure it should be narrowly framed within that discourse. But if the authors think it worth, then one needs to elaborate on to which extent and how (e.g., explaining which mechanisms and using the whole Ostrom principles and theoretical CPR framework) a positive tipping point would be reached. (I believe Carl Folke has a recent paper on this). So, I would either just delete that sentence or further elaborate on this a lot more, or simply I would focus on the second part of the paragraph, that of the various mechanisms that are being mentioned. Unfortunately, such crucial part of the paper, those of the various mechanisms for tipping cascades in my view is too short and in any case requires further elaboration.
  
  We agree that the concept of the “tragedy of commons” is not fully appropriate in this paragraph where we intend to provide practical examples of how and at which scales polycentric, cooperative governance can support positive tipping cascades. Therefore, we deleted the term and revised the paragraph accordingly:
  “To overcome collective action problem and ensure such a cooperative, polycentric governance to support positive tipping cascades,, various mechanisms offer promising signs: implementing co-benefits and co-evolution, neighbourhood collaboration,…”
  Finally, the conclusion, and probably because the comments above, seems also a bit loose and not directly or systematically addressing the various insights derived from the review - including the kinds of research need or gaps that to be addressed – which actually began to be mentioned at the end of the previous section on cascading mechanisms.
  
  Thank you for this suggestion to revise the conclusion section. We have expanded it to include the findings in the paper about a polycentric governance to involve multiple agents beyond conventional policymakers, and future research directions about systematic evaluation of cross-system interactions.
  
  Citation: https://doi.org/10.5194/egusphere-2023-2544-AC2
RC2:
'Comment on egusphere-2023-2544', Alaa Al Khourdajie, 07 Feb 2024
General comments:
Thank you very much for the valuable contribution. This is indeed an area that requires further attentions in the scientific literature. I found the way that the paper formalises and structures the discussion around positive tipping point very insightful. I do think however that more work can be done on the “next steps” for the community, a point I elaborate upon further below. Many thanks again and I look forward to seeing this paper published in due course.
Specific comments
The arguments are implicitly discussing mitigation and adaption implications of positive tipping point. It would be great if author make this aspect more explicit, and hence an explicit link between the physical science of tipping point, and the sociotechnical, -ecological, -economic and -political considerations under both mitigation and adaption. (e.g. l26, 27)

Section 2 and Figure 1: What about heavy industry and building? Perhaps framing them as energy end-use sectors would expand the focus, and it would be nice to reflect on how the tipping cascades and dynamic may differ for these sectors given the different challenges they face. This discussion is already presented in section 2.1 (lines 102 onwards).

Looking at figure 1, adding other end-use sector would formalise their role, and that subsequently means that the arrow between them (instead of transport only) and energy would require listing additional mechanisms (beyond low-cost storage). This very much emphasise the point around dynamic systems perspective.

Figure 1: shouldn’t there be a grey arrow between society and end-use sectors / transport? Demand and behaviour very much shape how these sectors evolve?

There is strong emphasise that society drives changes in food systems. The same emphasise is not as strong when it come to other end-use sector, a point to, I suggest, strengthen in the paper. The socio in socio-technical is not as prominent as in socio-ecological.

The discussion in section 2.1 on sociotechnical systems is more grounded with empirical evidence than that in section 2.2 on socio-ecological systems. It would be good to strengthen section 2.2 with more empirical evidence.

The point on stakeholders’ engagement (l260): a useful reference: https://www.sciencedirect.com/science/article/pii/S2211467X24000269?via%3Dihub

Section 3.2 does not offer a “concrete blue print” on how to capture these cascades in scientific modelling (and indeed other approaches of research). I appreciate this is perhaps not the intension of the paper, but it would be more useful for a researcher to be guided more concretely as to how they can approach this problem. In similar vein, expand the future research agenda more concretely in the Conclusions section in order to guide the community on what needs to be done to address these issues.
Citation: https://doi.org/10.5194/egusphere-2023-2544-RC2
- AC1:
  'Reply on RC2', Sibel Eker, 08 Apr 2024
  Thanks for your careful review and evaluation of our manuscript. Your comments were very helpful in clarifying and improving the manuscript. Below, we summarize how we will accommodate them in the revised manuscript :
  (Bulleted paragraphs refer to your original comments)
  The arguments are implicitly discussing mitigation and adaption implications of positive tipping point. It would be great if author make this aspect more explicit, and hence an explicit link between the physical science of tipping point, and the sociotechnical, -ecological, -economic and -political considerations under both mitigation and adaption. (e.g. l26, 27)
  
  Thanks for this comment. We revised the paragraph to clarify the relation of positive tipping to climate change mitigation and adaptation. In the revised manuscript, it will read as:
  “A tipping point refers to a critical threshold in complex systems beyond which self-propelling feedback leads to a fundamentally different system state (Lenton, 2020). The concept of positive (or social) tipping has gained wide attention recently to accelerate climate change mitigation and adaptation. Conceptually, tipping dynamics are characterized by alternative stable states, nonlinearity, underlying positive feedback loops, and limited reversibility, and “positive” tipping is specifically marked by desirability and intentionality in advancing decarbonization and sustainability (Milkoreit, 2022). Due to the promise of rapid change once the positive feedback mechanisms are triggered, such tipping points are considered high-leverage opportunities to use limited policy resources most efficiently for rapid decarbonization (Otto et al., 2020; Tàbara et al., 2018). and to counteract the risk of nonlinear climate change due to climate tipping points (Armstrong McKay et al., 2022) that may be observed by the end-of-century climate targets are reached.”
  Section 2 and Figure 1: What about heavy industry and building? Perhaps framing them as energy end-use sectors would expand the focus, and it would be nice to reflect on how the tipping cascades and dynamic may differ for these sectors given the different challenges they face. This discussion is already presented in section 2.1 (lines 102 onwards).
  
  Looking at figure 1, adding other end-use sector would formalise their role, and that subsequently means that the arrow between them (instead of transport only) and energy would require listing additional mechanisms (beyond low-cost storage). This very much emphasise the point around dynamic systems perspective.
  
  Thank you for these suggestions about other energy end-use sectors. We acknowledge the necessity of positive tipping in those, too, and the possibility of other cross-system interactions that can facilitate such a tipping dynamic. However, as we note in the objective of the manuscript (Line 49 of the original manuscript), we describe key examples of cascading effects and feedback loops emerging in the tipping literature. We do not aim to list all possible examples, Therefore, in the revised manuscript, we will expand the last paragraph of the Introduction section to include “We note that the examples we present here do not constitute the whole range of possible positive tipping cascades, especially from the hard-to-abate sectors such as heavy industry. Therefore, in Section 3.2 we outline a future research agenda that can systematically identify further positive tipping cascades.”
  Figure 1: shouldn’t there be a grey arrow between society and end-use sectors / transport? Demand and behaviour very much shape how these sectors evolve?
  
  Yes, there the society surely affects the transport system through norm and behaviour changes, too. We did not include that arrow in the first manuscript for visual simplicity, but added t other revised manuscript for accurateness.
  There is strong emphasise that society drives changes in food systems. The same emphasise is not as strong when it come to other end-use sector, a point to, I suggest, strengthen in the paper. The socioin socio-technical is not as prominent as in socio-ecological.
  
  Thanks for noting this. We did not want to focus on behavior changes in the transport and energy systems since this is done more fairly in other studies. Still, we added the following paragraph to the end of Section 2.1 to make sure that the society’s effect on sociotechnical systems is not overlooked.
  “The effect of society on the energy and transport systems through norm and behaviour changes is also expected to be significant, even though it is not visualized in Figure 2 for simplicity. Demand-side mitigation solutions, that is, changes in consumers’ technology choices, consumption, behaviour and lifestyles, could provide reductions of up to 78%, 62%, and 41% of the expected GHG emissions by 2050 in the residential energy, transport, and industry sectors, respectively (Creutzig et al. 2022). In other words, social and behavioural changes are cross-cutting enablers of positive tipping dynamics in various sociotechnical and -economic systems (Spaiser et al. 2023).”
  The discussion in section 2.1 on sociotechnical systems is more grounded with empirical evidence than that in section 2.2 on socio-ecological systems. It would be good to strengthen section 2.2 with more empirical evidence.
  
  We agree, hence improved this section with more empirical evidence on the relationships between fertilizer consumption and agricultural land pressure, social norms and behavior change, and public procurement and behaviour change. The paragraph that started in Line 133 of the original manuscript now reads as follows:
  “As illustrated in Figure 3, dietary behaviour changes towards sustainable food consumption reduce agricultural land needs, hence the land pressure (Springmann et al., 2018). As the land pressure declines, fertiliser consumption is expected to decline, because the increasing need for crop- and grassland to supply the required food to a growing population has been the main driver of increasing fertilizer use in agriculture in the last five decades (Lu and Tian, 2017). Similarly, a declining land pressure is expected to increase the adoption of diversified and regenerative farming practices are expected to increase (Gosnell and Gill and Voyer, 2019), as well as ecological restoration and associated carbon sequestration, leading to more rapid decarbonisation in agriculture. In climate vulnerable, low-income economies, these feedbacks can also drive diversification of livelihoods, new economic opportunities, and other social benefits. Social norms have been repeatedly shown to be a key driver of widespread dietary changes in model-based studies (Elliot, 2022; Eker and Reese and Obersteiner, 2019) and experimental studies (Mollen et al., 2013; Sparkman and Walton, 2017). As more people adopt sustainable diets, the visibility of it will lead to a stronger perception of the sustainability norms, leading to more people adopting the norm, as illustrated by the positive feedback loop in Figure 3. Since increased availability of plant-based meals at cafes was shown to affect the sales of them strongly (Garnett et al., 2019), public procurement of sustainable food is considered a strategic intervention to accelerate the adoption of new norms (IGS, 2023), and food labelling and certification in alternative food networks (Lenton et al., 2022) is key for facilitating market penetration of alternative proteins. Therefore, such triggers in society and policy can have cascading impacts on intensified and accelerated transformation of food and land use systems.”
  The point on stakeholders’ engagement (l260): a useful reference: https://www.sciencedirect.com/science/article/pii/S2211467X24000269?via%3Dihub
  
  Thanks, we have added this reference to strengthen our argument.
  Section 3.2 does not offer a “concrete blue print” on how to capture these cascades in scientific modelling (and indeed other approaches of research). I appreciate this is perhaps not the intension of the paper, but it would be more useful for a researcher to be guided more concretely as to how they can approachthis problem. In similar vein, expand the future research agenda more concretely in the Conclusions section in order to guide the community on what needs to be done to address these issues.
  
  To clarify how integrated system modeling can support future research on positive tipping dynamics, we expanded the paragraph starting in Line 252 of the original manuscript as follows. However, we refrained from a detailed discussion, since the preprint we are referring to (Eker et al. 2023, A dynamic systems approach to harness the potential of social tipping) provides a more detailed discussion on the pillars of integrated modelling to study positive tipping.
  “Such an integrated systems modelling approach, as elaborated in (Eker et al., 2023), can especially include not only the positive feedback loops that underlie positive tipping dynamics, but also their coupling with counteracting negative and positive feedback mechanisms. In that way, the plausible potential of tipping dynamics emerging from interconnections not only within specific systems but also across them can be evaluated, and the effectiveness of interventions to trigger positive tipping can be tested.”
  
  Citation: https://doi.org/10.5194/egusphere-2023-2544-AC1

Sibel Eker, Timothy M. Lenton, Tom Powell, Jürgen Scheffran, Steven R. Smith, Deepthi Swamy, and Caroline Zimm

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