While the adaptive cycle and panarchical connections reflect the possiblity of movement from one stable state to another, it’s possible to get “stuck” in a disfavoured trap. Social ecological systems involve both natural systems and human systems.
After widespread recognition of the 2002 Panarchy book, reflections in 2010 revealed further development of the theory and practice.
Applying Resilience Theory
[….] The theory has shifted focus away from managing for particular equilibria to the management of regimes, as described below.
Adaptive capacity has been defined in the ecological literature as the ability to manage resilience (Gunderson 2000, Walker et al. 2004). Humans manipulate ecological systems to secure goods and services and in doing so leave the system more vulnerable to change, by eroding ecological resilience (Holling and Meffe 1996). Ecological resilience is difficult to assess and measure a priori and is often known only after the fact — that is, the complexities, nonlinearities, and self-organized processes that generate regime shifts or ecological phase transitions are generally understood only after a shift has occurred, and then only partly. Even so, humans do manage for adaptive capacity. Those management actions can be categorized as those that are aimed at buffering the impact of disturbances (Berkes and Folke 1998, 2002), those that accelerate recovery and renewal, and those that attempt to choose and manage transitions among alternative regimes.
Regime management has two key components that must be actively managed. Quite simply, they revolve around two basic questions: (1) “What kind of system do we want?” and (2) “What kind of system can we get?” (Clark and Munn 1986). The first question is beguilingly simple but actually very complex. The issue of desirability is at the core of many social-ecological problems. [p. 434]
There are circumstances when systems get “stuck” in bad way.
When Resilience May Not Be a Good Thing
While many social-ecological systems exhibit rhythms of change (Walters 1986, Gunderson et al. 1995, Berkes and Folke 1998, 2002), many others do not. Systems can become trapped when they cannot or do not change or adapt to new conditions nor escape from a trajectory toward an undesired regime. Trapped systems exist in narrow management regimes, with few or no options for the future. The following paragraphs describe some examples of trapped systems; some are perversely resilient, whereas others are pathologic or maladaptive (Holling and Gunderson 2002). [pp. 435-436]
At least four different types of resource management traps can be identified (Table 1). These different types are each defined by a combination of three properties: (1) capital or potential, (2) degree of connectivity, and (3) level of resilience (Holling and Gunderson 2002). Although it is possible to have eight combinations of these three properties, four combinations have been identified and are listed in Table 1.
- A system in a rigidity trap has high capital, connectivity, and resilience (Holling and Gunderson 2002).
- A system in a poverty trap has low amounts of these three properties.
- A system caught in a lock-in trap has low capital but high levels of connectivity and resilience.
- The fourth trap — an isolation trap — is the least well understood of the four. It has high capital or potential but is not tightly coupled nor is it resilient. [p. 436, editorial paragraphing added]
Source: Modified from Holling and Gunderson 2002, Allison and Hobbs 2004.
This four systems traps are an extension of the usual two identified maladaptations, of a ridigity trap and poverty trap, originally published in 2002, Chapter 3.
Could we imagine systems in other combinations of those three attributes where variability is sharply constrained and opportunity is limited? We suggest two possibilities in Figure 3-12. [p. 95]
If an adaptive cycle collapses because the potential and diversity have been eradicated by misuse or an external force, an impoverished state can result with low connectedness, low potential, and low resilience, creating a poverty trap. That condition can then propagate downward through levels of the panarchy, collapsing levels as it goes. An ecological example is the productive savanna that, through human overuse and misuse, flips into an irreversible, eroding state with sparse vegetation, where subsequent drought precipitates further erosion, and economic disincentives maintain sheep production (Box 2-4, Chapter 2). An example of such a collapse occurs when a society is traumatized by social disruption or conflict, where cultural cohesion and adaptive abilities have been lost. Individuals can depend only on themselves and perhaps family members. In a sweeping analysis of poverty, Dasgupta (1993), for example, resolves the paradox of population growth at times of increasing impoverishment by explaining that children become needed for their work and minimum demands. [pp. 95-96]
We could imagine that some such societies might exist in this degraded state of bare subsistence, barely able to persist but unable to accumulate enough potential to form the larger structures and sustaining properties of a panarchy. Still others might collapse in anarchy. That, in many ways, has been the history of both ecological and economic imperialism (Crosby 1986), following waves of human migration and expansion, initially from the Middle East and subsequently from Europe over the last seven centuries. If we have difficulties defining the conditions for sustainable, adaptive systems, we certainly have no difficulties in identifying the conditions for unsustainable, maladaptive ones. [….]
Figure 3-10 [“Panarchical connections”] also suggests that it might be possible to have a sustainable but maladaptive system. Imagine a situation where potential is high, connectedness great, and, unlike the phase where those conditions exist in an adaptive cycle, resilience is high. The high resilience would mean a great ability for a system to resist external disturbances and persist, even beyond the point where it is adaptive and creative. The high potential would be measured in accumulated wealth. The high connectedness would come from efficient methods of social control whereby any novelty is either smothered or sees its inventor ejected. It would represent a rigidity trap. [p. 96]
We see signs of such sustained but maladaptive conditions in great “hierocracies,” such as those that include rigid and apparently immutable caste systems. An example is described in Box 3-4 for the Hindu caste system. We are tempted to suggest, from our own frustrating experiences, that other examples might be found in present universities controlled by unchangeable, disciplinary departmental structures, or in agro-industry, where command and control have squeezed out diversity and power, politics, and profit have reinforced one another. But all such systems might well have the seeds of their own destruction built in, much as in the case of the dictatorship of the bureaucracy in the now defunct Soviet Union. The speculation is interesting, maybe even useful, but we are now way beyond our own knowledge and conviction. [pp. 96-98]
As ecologists, Holling, Gunderson and Peterson admit to stretching panarchy from ecological systems into political systems. This is an aim towards theory-building, with support and criticism to follow in the normal course of science as a process.
As a reminder …
- the r phase is “the instantaneous rate of growth of a population”;
- the K phase is “the sustained plateau or maximum population that is attained”;
- the Ω phase is release, in which “the tightly bound accumulation of biomass and nutrients becomes increasingly fragile (overconnected, in systems terms) until suddenly released by agents such as forest fires, drought, insect pests, or intense pulses of grazing”; and
- the α phase is reorganization, “in which soil processes minimize nutrient loss and reorganize nutrients so that they become available for the next phase of exploitation”. [2002 Chapter 2, pp. 34-35]
To get a better sense of the three-dimensionality in the diagram, let’s borrow a depiction of the two traps from Ludwig, Wilmes, Schrader (2018), in their description of soils.
Opposing legacies are drivers for and links between cycles across scales. However, extreme pulse disturbance as a single event and/or press disturbance as a gradually cumulated multiple event may lead the system into a so-called poverty trap or a rigidity trap (Fig. 4).
For soils, this can be due to misuse leading in a highly degraded or depleted soil (poverty trap) of low resilience, connectedness and potential, or leading to a state where the soil is not a self-organized system anymore (rigidity trap) due to high-performance cultivars forced to stay in a state of high potential and connectedness and artificial resilience by external input (fertilizer, pesticides, genetically modified material, etc.)
An example for a poverty trap is a highly degraded soil due to repeated and severe compaction by means of heavy machinery. Within the adaptive cycle it occurs in the backloop Ω → α and prevents recovery of soil and soil biota diversity as well as restructuring after collapsing from harvest and tillage (K → Ω). Now at this tipping point a critical threshold of resilience is crossed and the system leaves the current cycle for another one characterized by a different set of boundaries and feedbacks. In this example, a regime shift happens from cultivated field to a set-aside field no longer under production.
An example for a rigidity trap is a monocultural soil management that causes diversity loss and poor genetic variability of a high-performance cultivar. Within the adaptive cycle it concerns the frontloop (r → K) and results in loss of adaptive potential against for instance environmental stressors like extreme climate events or loss of power to resist diseases and pests. Here a regime shift will be discarding the old cultivar and breeding a new and more adaptive one. [p. 1489, editorial paragraphing added]
Adding the two additional traps to the Ludwig, Wilms, Schrader Fig. 4 image would put …
- a lock-in trap in front of the rigidity trap (i.e. lower potential), in the 2-dimensional phase of high resilience and high connectedness; and
- an isolation trip behind the poverty trap (i.e. higher potential) in the 2-dimensional phase of low resilience and low connectedness.
Let’s return to the 2010 chapter to get fuller description of the four traps.
A rigidity trap fails to reorganize internally, generally receiving resources from an external contributor. With the example in the chapter described primarily with social systems, we might keep an eye open for a rigidity trap with a non-human natural system.
The Everglades management system has been and continues to be in a management trap (Gunderson and Holling 2002, Gunderson and Light 2006). This is a type of social trap (Rothstein 2005), defined as a system configuration or regime that persists over time despite being subjected to a wide range of shocks or perturbations (Allison and Hobbs 2004). It is a very resilient system (sensu Holling 1973) that is maintained by considerable infusions of money, which are tied to the conventional bureaucratic system. This system is governed by rules and procedures that are no longer appropriate to accomplish a highly complex and mul- tiobjective mission. The result is that, for the sake of consistency, Everglades restoration remains in a policy straitjacket. [pp. 416-417]
In addition to the command-and-control culture (Holling and Meffe 1996) mentioned above, rigidity traps have other characteristics, including (1) avoidance of learning (from past mistakes), (2) lack of trust among management institutions and stakeholders, and (3) strong feedbacks that maintain core elements of the status quo. [….] There are fiscal and political costs to experimentation. Moreover, the reasons that more experiments have not been conducted are related to the fear of risking conflict and the fear of failure to produce desired or even meaningful results. This is compounded by the inability of current bureaucracies to comprehend the value received from learning now when compared to the costs of inaction.
Unfortunately, current practices have government agencies supporting large scientific endeavors that focus on modeling and data collection rather than on using experiments to reduce uncertainties and explore new options. A recent National Academy of Sciences panel (2003) indicated that ongoing and future research should move away from self-serving, piecemeal studies to ones that are more synthetic and integrative. To do so will require scientists to become motivated to pursue collective learning. Perhaps the main reason for the rigidity trap is a lack of social capital and trust fostered by institutional power imbalances in the region (Rothstein 2005). Special interests and resource managers who feel that experimentation would supplant an opportunity to secure water options for the park and conservation interests have stymied attempts at adaptive experiments. Rather than acknowledge that it is currently unknown what it would take to restore the lost environmental values, some chose to replace scientific uncertainty with political certitude, as false as it may be. [p. 417]
The example for a poverty trap is a natural system, although finding under-resourced social ecological systems wouldn’t be difficult.
Systems in a poverty trap are not very resilient and are characterized by little capital or connectivity. Open-water pelagic systems are an ecological example. In these systems, productivity (ability to convert sunlight to plant material) is very low. These blue-water systems are limited by nutrients and hence build little, if any, structure. Because of a fluid and changing environment, few connections develop among parts of the system. Other systems, where capital (in any form) has been mined or used can also fall into a poverty trap. Areas where soils are degraded through poor management (organic soil oxidation in the Everglades, soil salinization in many arid regions, or loss of topsoil in tropical regions) are in poverty traps, as they lack the resources for renewal and connections and are vulnerable to change into many different states. [p. 438]
The idea of a lock-in trap seems somewhat obvious in business and technology contexts, but the ecologists focus more on natural systems.
The agricultural region of Western Australia (wheat belt) has gone through boom-and-bust cycles over multiple decades (Allison and Hobbs 2004). Currently, it is in a type of trap where capital is low but connectivity and resilience remain relatively high. The system has lost many natural resources (such as native biodiversity), primarily through land conversion. Over the past few decades, pollution has increased and social structures (such as towns) have declined. Yet, wheat production has been maintained by improved agricultural practices and crop varieties in spite of increases in soil salinity. The system of farming and agro-business maintains a tight connection. This has led to characterizing the system as being in a lock-in trap. It is locked in, because the supports (external and policy) and connections maintain the current agricultural system. It is trapped, as social capital (in the form of communities, churches, schools, and so forth) and natural capital have degraded. [p. 438]
An isolation trap would seem to almost a system unto itself, with ties to larger-slower cycles via “remember” loop cut off.
Remnant plant or animal populations (including human cultures) can be in an isolation trap. This trap is characterized by relatively high capital or potential capital, low connectivity, and low resilience. Many isolated populations are classified (and receive special management consideration) as threatened or endangered because they are very vulnerable to perturbations (i.e., they are not very resilient). One such example is found in the Colorado River in the United States, where the endangered humpback chub (Gila cypha) persists in areas that are remnants of former range. Because of dams that prohibit movement, former meta-populations are now isolated populations. The isolated populations have the potential to increase in number, and the numbers are low enough to warrant special designation and management. But with increased preda- tion and temperature changes, among other factors, the populations are not very resilient and the species is in danger of extinction (an alternate and undesirable state). [pp. 438-439]
Panarchy theory comes from ecologists firstly focused on natural environments, who have extended their purview to social ecological systems that include human beings. The poverty trap and and rigidity trap have seen the most interest. More thought might be given to looking into cases of a lock-in trap, or an isolation trap.
Gunderson, Lance H., C. S. Holling, and Craig R. Allen. 2010. “The Evolution of an Idea — the Past, Present, and Future of Ecological Resilience.” In Foundations of Ecological Resilience, edited by Lance H. Gunderson, Craig R. Allen, and C. S. Holling, 423–44. Washington, DC: Island Press. https://islandpress.org/books/foundations-ecological-resilience.
Holling, C. S., and Lance H Gunderson. 2002. “Resilience and Adaptive Cycles.” In Panarchy: Understanding Transformations in Human and Natural Systems, edited by Lance H Gunderson and C.S. Holling, 25–62. Island Press.
Holling, C. S., Lance H Gunderson, and Garry D Peterson. 2002. “Sustainability and Panarchies.” In Panarchy: Understanding Transformations in Human and Natural Systems, edited by Lance H Gunderson and C. S. Holling, 63–102. Island Press.
Ludwig, Marie, Paul Wilmes, and Stefan Schrader. 2018. “Measuring Soil Sustainability via Soil Resilience.” Science of The Total Environment 626 (June): 1484–93. https://doi.org/10.1016/j.scitotenv.2017.10.043.