This section presents the results and discussion regarding the approach proposed to foster long-term and regenerative perspectives on global sustainability, encompassing (i) a critical analysis and synthesis of insights from the fields of systems and resilience thinking, (ii) a conceptual framework for modeling and envisioning socio-ecological systems, and (iii) the proposition of the “flourishing within boundaries” archetype.
3.1. Modeling and Envisioning Socio-Ecological Systems—A Conceptual Framework
From an epistemological viewpoint, every knowledge construct is a model. What is referred to as the “real world” is contingent upon how deeply human understanding is able to probe reality. Models are belief systems built as a set of assumptions and explanations aimed at representing and sense making the experienced world [
28]. Every model is inevitably influenced by prevailing social perspectives, actions, and goals. Although models are designed to improve understanding of complex relationships and manifest a strong congruence with the experienced world, they fall far short of representing it fully [
2,
3]. The realism of a model is inherently dependent not on its realistic representativeness, but on its faculty to respond with a coherent pattern of behavior over time [
24]. Additionally, isolated systems with well-defined boundaries are conceptual constructs (based on perceptions, logical constructs, and social agreements) and do not exist in the intertwined tissues of the observed world, in which everything comes from somewhere and goes somewhere, and continuously evolves [
2].
Model creation and analysis is a highly investigative hands-on activity that fulfills learning by doing. The starting point of socio-ecological system’s modeling is divided into the selection and representation of the constituents of the studied systems. The selection of what to include in a model depends concomitantly on how broadly the systems net is cast and how deeply it probes. Models should encompass constituents whose interaction is capable of self-generating the event of interest, filtering out non-essential ones, and distancing from details that jeopardize the examination of patterns and trends. However, it is also important to bear in mind that missing information is one of the most common sources of modeling inaccuracies. The representation of the selected system’s constituents in the model must be clearly defined in some form of correlational and cause-and-effect logic, acknowledging that coupled social-ecological systems operate through interdependent causality structures [
21].
In the prevalent vernacular systems, words in sentences, as well as sentences in texts, come one at a time and are linearly ordered. However, socio-ecological systems are commonly interconnected in many directions at once [
18,
21,
23,
29,
30]. To perform an effective systems analysis, it is crucial to use a language whose lexicon and syntax share some characteristics with the phenomena under consideration. The most widely utilized language in systems studies is the language of stocks-and-flows, in which the systems’ structures are described in terms of diagrams of interlocking stock, flows, and feedback loops [
2,
3,
19,
22,
24,
31]. The language of stocks and flows is particularly visual and operational, facilitating both mental and computer simulation within multi-, inter-, and transdisciplinary domains. The diagrams contain systems structures depicted in an icon-based lexicon, signifying stock-and-flows models of the observed world [
2,
32,
33].
An essential precept of systems thinking is that there is an inherent interdependence between the system’s structure and its functionality [
2,
3,
19,
22,
31,
34]. In this regard, systems problems are understood as undesirable patterns of dynamic behavior that emerge from characteristic system structures [
2,
3,
22]. In sustainability science, systems thinking is operationalized by examining social-ecological systems, which are modeled as a collection of subsystems along with their self-reinforcing and balancing mechanisms that regulate stock levels by governing physical and informational flows [
2,
9,
10,
11,
12,
21,
22,
23,
35]. In this case, the model is a selective abstraction of the social-ecological system in itself, typically described in terms of storytelling and computer stock-and-flow diagrams [
2,
3,
22]. In this context,
Figure 1 depicts a conceptual diagram (storytelling stock-and-flow diagram) for modeling and envisioning socio-ecological systems. It was conceived to provide a set of conceptual tools meant to illuminate long-term and regenerative perspectives on how the socio-ecological systems we are all part of actually operate.
Both mental and computer simulation play an essential role in modeling and envisioning social-ecological systems. In
Figure 1, the connector (illustrated as an arrow)—that runs from the stock [Represented constituents in the model] (represented by a rectangle) to the flow {Simulating “what if” scenarios} (represented by valves and pipes) indicates that the simulation process can only proceed if a model is designed. Aiming to understand what occurs over time and why, it is necessary to model the interplay of the adopted causal relations under various “what if” scenarios, reviewing the performed assumptions accordingly. Furthermore, the two connectors run from the stock [Modeling outcomes] to the {Selecting} and {Representing} flows, indicating a feedback loop mechanism of self-reinforcing learning in the model creation. This also indicates that the performed assumptions are inspected for adequacy and improvement in a self-scrutiny circular process.
In light of the obtained modeling outcomes, it is crucial to examine evolutionary patterns of behavior over broad time horizons spatial realms, examining desirable and undesirable scenarios for the future, drawing hypotheses, and defining the best courses for action. Another essential precept of systems thinking is that although the future cannot be predicted, it can be envisioned and brought into being [
2,
36]. The evolutionary behavior of socio-ecological systems can be envisioned and imaginatively designed and redesigned. However, the more complex the socio-ecological system becomes, the more surprising its dynamic behavior. Socio-ecological systems may exhibit adaptive, transformative, goal-seeking, self-preserving, self-repairing, hierarchical, and balancing and reinforcing evolutionary features [
21,
24,
27]. They may also exhibit the property of self-organizing, i.e., the ability to structure themselves, to create new structures, to learn, diversify, and complexify, producing resilience, heterogeneity, and unpredictability [
21]. Out of one system, other completely novel systems can emerge. Self-organizing systems develop their own structure and behavior spontaneously without being guided from the top-down [
26]. In the process of creating new structures and increasing complexity, self-organizing systems generate dynamic patterns of hierarchy and integration [
2,
21,
29].
Given that acting only when a problem becomes evident may be too late to solve it, the connector that runs from the stock [Modeling outcomes] to the flow {Envisioning futures} emphasizes that a historical and foresight analysis is a determining element in the decision-making and acting process. Decisions are influenced by a wide variety of factors, including the quality of the information, social values, education, structural means, methods, and personal perspective. As Meadows [
2] (p. 167) observed, “Social systems are the external manifestations of cultural thinking patterns and of profound human needs, emotions, strengths, and weaknesses. Changing them is not as simple as saying now all change, or of trusting that he who knows the good shall do the good.” Particularly, human’s perspective on time and space depends on their culture, their past experiences, their sense of the future, and on the urgency to meet essential needs and resolve problems in their lives. In general, the longer the time horizon and the larger the spatial realm associated with a problem, the shorter the human capacity to perceive it and know the existence of it and, consequently, to think and cope with the demands that arise from it. Broadly, most human perspective is concentrated on short-term issues (e.g., weeks and/or months) related to the closest community (e.g., household, neighborhood), part of it extends slightly farther ahead (e.g., years, life time) into a larger community (e.g., city, states, nations), a smaller part of it extends farther ahead (e.g., ancestors’ and next generations’ life time) into an even larger community (e.g., planet), and a very small part of it extends far into the long-term past and future of the phenomenon of life, human society, and universe. In this regard,
Figure 2 depicts in broad contours the distribution of human perspective over distinctive spatial realms (structured in a qualitative scale varying from household to universe) and time horizons (from now to the past and future of life and human society). In
Figure 2, the human perspective is assumed to decay exponentially over longer past and future time horizons and larger spatial realms. To acknowledge the greater unknowability of the future in comparison to the past, increased exponential decay is also assumed, therefore signifying a narrower and shorter human perspective in future time horizons and spatial realms.
Transgressing short-term vision and directing changes to desirable futures requires sensitivity and a robust background in redefining long-term vision and strategies for societal development. In this case, the actions taken must extend not only for days or months, but for years, decades, and centuries into the future. Long-term thinking counteracts the fallacies of narrow-short-term thinking, looking beyond immediate constraints, widening understanding, and offering imaginative ways of addressing unknowability. It also enlightens the ways that actions can be taken, and societal changes spread, nurturing desirable futures and preventing undesirable ones. The process of envisioning long-term dynamic behavior provides key understandings to the underlying socio-ecological systems’ structure, which is crucial to the comprehension not just of what is happening but what has been happening, why, how, and for whom. This also gives rise to meaningful engagement, boosting discussions on the nature of undesirable outcomes, and fostering shared insights for desirable ones.
The connector that runs from the stock [Conclusions and decisions] to the flow {Taking actions} signifies that accumulated knowledge and meaningful sense of the future are driving forces in the implementation process of actions. It also suggests that actions are mainly taken when there is a rational understanding of and human care for the problem. Societal actions are likely to grow and be disseminated when their cause, cost, and benefits are collectively clear. People typically act when the benefits are timely enough to offset the cost of their actions. In this regard, the connectors that run from the stocks [Actions taken and Changes spread] to the flows {Spreading changes} and {Taking actions} imply an interdependent relationship between the ways and means that actions are taken and societal changes are spread. The connector that runs from the stock [Changes spread] to the flow {Shifting feedback loops dominance} indicates that societal changes are the main raw material in shifting dominant structures of socio-ecological systems. The connector that circles back from the stock [Changed socio-ecological systems] to the flow {Selecting} specifies a self-enhancement circling procedure in the modeling design.
Aiming to foster societal awareness and also enhance the modeling construct as a whole, it is crucial to make information available for scrutiny and communicate it accordingly. The connectors that join the variable “Made Available for scrutiny by others” emphasize that the process of communicating boosts societal awareness and control. It generates a common understanding of why a problem persists despite people’s best efforts to solve it. By making the information available and communicating it to society, people can reflect on it, question it, learn from it, and act on and spread changes inspired by it. Societal awareness depends on the information provided as well as on people’s willingness and ability to perceive it and judge it. Those involved in modeling and envisioning socio-ecological systems make assumptions about what is important to include in the analysis and what is imperative to value from it. Finally, what belongs to the system’s model is utterly dependent on (and relative to) the systems thinker’s perspective and/or conceptual boundaries.
3.2. Flourishing within Boundaries—A Proposed Archetype
Out of the myriad of systems categories in the world, archetypes are unique systems structures because they produce distinctive patterns of behavior over time [
2]. Archetypes constructs provide building blocks for understanding and sense-making of dynamic behavioral patterns, fostering insights on how systems operate, what makes them produce undesirable results, and how to identify leverage points. Archetypes reveal underlying structures, interactions and interrelationships, enabling the addressal of core issues rather than treating the symptoms. As a result of their capability to represent a wide range of complex problems, for over 40 years archetypes have been well suited towards examining systems in interdisciplinary domains. In particular, playing an important role in sociological debates, the “success to the successful” archetype reveals the underlying drivers of exclusion, unfairness, poverty, monopoly of wealth, and social inequality [
2]. Inaugurating a new era in the debate of global environmental issues, the “tragedy of the commons” archetype depicts a circumstance in which individuals pursue actions for their self-interests and benefits, although sharing finite and erodable stocks of natural resources [
37]. Notably contributing to the debate on the future of human society at a planetary scale, the “limits to growth” archetype describes the process of quantitative growth in a constrained environment, in which stocks of nonrenewable resources are finite and available at once [
4,
38,
39,
40].
In sustainability science, archetypes structures can be pervasive and destructive, producing persistent and labyrinthine patterns of behaviors over time, commonly called socio-ecological traps, i.e., systems structures in which social and ecological feedback loops mutually reinforce each other and maintain or push social-ecological systems towards undesirable states [
41]. A socio-ecological trap can be avoided by recognizing it in advance or by altering the system’s structure, goals, and shifting their feedback loops’ dominance. Aiming to portray in broad evolutionary contours the pathways in and out of socio-ecological traps as well as understand how socio-ecological systems can be guided towards one pathway or another,
Figure 3 depicts (in a stock-and-flow computer diagram) the proposed “flourishing within boundaries” archetype. Taking into consideration the Sustainable Development Goals [
6] and Planetary Boundaries Framework [
9,
10,
11,
12], this proposed archetype, as well as the following scenarios, are modeled to provide meaningful insights regarding the essential conditions that would enable global society to flourish not just safely but also fairly. Acknowledged worldwide as a blueprint to achieve a flourishing future for all, the Sustainable Development Goals are conceived to address essential issues of human society, galvanizing actions at multiple scales for shared and lasting prosperity [
6,
27,
42]. The Planetary Boundaries lays out precautionary thresholds for critical biogeophysical processes that regulate the stability of Earth’s life-giving systems. Transgressing one or more planetary boundaries means transgressing the limits of a safe operating space for the development of a flourishing global society, which could prove deleterious, or even catastrophic [
9,
10,
11,
12].
In
Figure 3, the stock [Socio-ecological systems’ outcomes] is the accumulation of results over a period of time, signifying the current state of the flows within the socio-ecological system. The flows go into and out from stock, signifying activities that cause conditions to change. In this regard, the inflow {Societal growing action} and the outflow {Societal limiting action} regulate the stock [Socio-ecological systems’ outcomes]. The stock is decreased by decreasing the growth rate of the inflow as well as by increasing the growth rate of the outflow. Therefore, changes in the stock [Socio-ecological systems’ outcomes] set the pace of the overall system’s dynamics. Given that both flows are not immediate processes, it takes time for the stock to change, thereby acting as a source of momentum and shock absorber.
The two connectors that run from the stock to the flows indicate feedback loop mechanisms. In this regard, every societal action triggers a reaction with a feedback loop causality structure that brings results from the past action back to control future actions. The inflow {Societal growing action} adds to the stock [Socio-ecological systems’ outcomes] that adds to the inflow {Societal growing action} in a reinforcing feedback loop mechanism. After some accomplishment in the growing process, this reinforcing mechanism is then offset by an action of a balancing feedback loop. Every feedback loop has its critical threshold, which defines the region in which there is a change from one dynamic regime to another.
Given that physical systems cannot everlastingly grow in a finite environment, self-reinforcing mechanisms must have at least one reinforcing feedback loop—driving the socio-ecological systems’ behavior – and one balancing feedback loop—constraining the growth behavior. In this case, the goal-seeking mechanism shifts (either temporarily or permanently) the reinforcing feedback loop dominance either by strengthening the outflow or by weakening the inflow. Furthermore, feedback loops give rise to nonlinear behavior, even if all constituent causal relationships are linear. Nonlinearities in feedback loops change their relative strengths, shifting dominance of self-reinforcing or goal-seeking mechanisms. While the reinforcing mechanism is operating, the stock interacts with “Limiting social factors” and “Limiting ecological factors”, that add to the outflow {Societal limiting action}. These limiting factors are defined in alignment with the existing 17 Sustainable Development Goals and 9 Planetary Boundaries. Finally, systems boundaries are represented by clouds on the flows and are purpose-problem-dependent, delimited by spatial and temporal thresholds.
The proposed “flourishing within boundaries” archetype is modeled to allow the scrutiny of essential direction-setters of the system’s evolutionary behavior, indicating circumstances that require societal actions, and signaling failure or success toward a desirable state and feedback loop dominance. Aiming to envision the long-term implications of distinctive values of growth rate for the inflow {Societal growing actions} and for the outflow {Societal limiting actions} in the evolutionary behavior of the stock [Social-ecological systems’ outcomes],
Figure 4 depicts the simulation results for a set of scenarios within the time frame of 500 years (labeled from S0 to S7).
In
Figure 4, fixed in an arbitrary value, the parameter
C denotes the current state of the flows within the system. In
S0, the growth rate for the inflow and outflow are equal. As expected for this baseline scenario, no transition is identified in the evolutionary behavior of the stock, indicating that the reinforcing feedback loop associated with the flow of societal actions is consistently offset by the balancing feedback loop that arises from the net results of the social and ecological limiting factors. In
S1,
S2, and
S3, the growth rates for the inflow are, respectively, 1.0%, 3.0%, and 4.0% higher than the growth rates for the outflow. In these scenarios, the higher the growth rate for the inflow the greater the pace of the system towards higher values of the stock. In
S4,
S5,
S6, and
S7, the growth rates for the outflow are, respectively, 1.0%, 3.0%, 4.0%, and 50.0% higher than the growth rates for the inflow. Conversely, in these scenarios the higher the growth rate for the outflow the greater the pace of the system towards lower values of the stock.
The flourishing patterns of behavior over time portrayed in the scenarios S1, S2, and S3 are characterized by persistent actions towards increasing values of the stock [socio-ecological systems’ outcomes]. In this regard, the direction-setters of the system’s evolutionary behavior are the promising pace of the inflow, the degree of achievement of positive outcomes within boundaries, and the societal ability to identify leverage points in order to intervene in socio-ecological structures. In these scenarios, the socio-ecological systems are understood as highly regenerative and resilient. Societies are proactively committed to sustainability and enlightened by meaningful aspirations, such as solidarity, dignity, fairness, quality of life, collective consciousness, synergistic connection with nature, ecological sensibility and responsibility, and integral ecological worldview.
By contrast, the scenarios S4, S5, S6, and S7 are characterized by traps and collapsing mechanisms, in which the net results of the limiting factors go beyond critical thresholds, continuously decreasing the values of the stock. In this regard, the main direction-setters of the system’s evolutionary behavior are the alarming pace of the outflow, the narrow range of the critical thresholds associated with Earth’s planetary boundaries, and the societal difficulty to achieve the Sustainable Development Goals. Given the self-reinforcing mechanisms associated with both limiting factors, the more thresholds are transgressed, the less the socio-ecological systems are able to adapt and regenerate themselves, or the more likely they are to collapse. In these scenarios, the socio-ecological systems are neither resilient nor sufficiently regenerative. Societies are highly dysfunctional and evolve with a growing risk of calamitous disruptions, including major threatening events, an abrupt decline of Earth’s life-giving systems, and civilizational failure.
As observed in
Figure 4, all portrayed scenarios exhibit an exponential behavior over time. However, the pace of the transitions associated with the reinforcing feedback loop dominance (i.e., scenarios
S1, S2, and
S3) is notably higher over time than the ones associated with the balancing feedback loop dominance (i.e.,
S4, S5, S6, and
S7). Aiming to illustrate this important feature,
Figure 5 depicts the comparative results for
S1 (black color)
, S2 (very dark grey)
, S3 (dark grey),
S4 (grey),
S5 (light grey), and
S6 (very light grey).
In
Figure 5, the variable
is the variation in the value of the stock [Socio-ecological systems’ outcomes] in relation to the stock value of
S0. Structured on a comparative scale, the value of
is assessed at selected times and expressed in terms of the proportionality factor α. The ratios between
and their counterparts
, are, respectively, 1.03, 0.71, and 0.82 for
25.0 years, and 1.65, 2.21, and 4.01 for
500.0 years. Particularly,
is invariably higher than its counterpart
, signifying that the reinforcing feedback loop is consistently dominant. Nevertheless,
and
are only higher than their counterparts
and
from the time horizons of 165.0 years and 84.0 years, respectively, specifying that up to these times the balancing feedback loop is dominant. Therefore, the reinforcing feedback loop associated with the inflow {Societal growing actions} adds to the stock in a gradual upward process, increasingly offsetting the balancing feedback loop that arises from net results of both limiting factors. In this regard, the speed of the threats dictates the required growth rate of societal actions. Given that both flows and feedback loop mechanisms are not immediate processes, it takes time for the stock to change. Actions taken by individuals in the local realm and short-term time horizon may not only have immediate local effects but also a variety of innumerous ones that radiate out for years, decades, and even centuries to come. However, varying the length of delays significantly alter the socio-ecological systems’ responses to change, including how timely changes are transmitted within the socio-ecological systems. Particularly, a delayed response regarding the disruption of the Earth’s life-giving systems is highly risky of being too late to prevent serious damage at a planetary scale.