6.4 Resilience analysis .1 Model diagnosis
6.4.3 Pathological states
Table 6.5.Relationship between the phases of the Kondratiev Cycle and the adaptive cycle
Kondratiev Cycle Adaptive cycle
Recovery –r
Prosperity r–K
Recession K–
Depression −
The Kondratiev upwave consists of the Recovery and Prosperity phases
The Kondratiev downwave consists of the Recession and Depression phases
Cycles may be used to explain the behaviour of the WA agricultural system.
The economic/technical factors at the global scale, which are responsible for the dynamics of the Kondratiev Cycle have entrained a similar cycle in the WA agricultural region. That is to say, the dynamics of the WA agricultural system were strongly influenced by exogenous factors at the global scale with little controlling influence from natural resource policy or by other endogenous balancing feedback to change the behaviour of the system.
Fig. 6.5. Heuristic model of the adaptive cycle with pathological states of the Poverty Trap and the Rigidity Trap shown. The Poverty Trap has low levels of all three properties and lies below the adaptive cycle in the figure whereas the Rigidity Trap has high levels of all properties and lies above the adaptive cycle in the figure. The Poverty Trap may be most easily entered from the release or exploitation (r) phase of the adaptive cycle shown by the arrows in the figure.
Source:Gunderson and Holling (2002)
and reorganisation) because it would require a change from high levels to low levels in two properties. Conversely, it is easier to enter the Rigidity Trap from either the reorganisation or conservation phase (K). An example of a Rigidity Trap may occur in social systems in which the members of organisations and their institutions become so tightly connected that they are highly resilient to change and become rigid and inflexible, such as some bureaucracies. Hollinget al. (2002c) contended that one example of a Rigidity Trap may be found in the agriculture industry, where command and control have squeezed out diversity, and power, politics and profit have reinforced one another. The two other possible alternative pathological states were not described. It is proposed here that one of the undescribed pathological states could be labelled the Lock-in Trap, which is characterised by low potential for change, high connectedness and high resilience (Table 6.6). The Lock- in Trap is most likely to occur by changes in the conservation (K) phase shown by the curving arrow in Figure 6.6. This proposition is developed below.
Pathological traps and biophysical resilience thresholds may be avoided through human innovations that effectively redefine the system by extending
Table 6.6.The level of each of the three variables that characterise the two identified pathological states called the Poverty Trap and the Rigidity Trap
and the proposed Lock-in Trap
Pathological state Potential Connectedness Resilience
Poverty Trap low low low
Rigidity Trap high high high
Lock–in Trap low high high
? high low low
Source:derived from Gunderson and Holling (2002)
Fig. 6.6. A heuristic model showing eight possible phases of the adaptive cycle.
Four phases that make up the adaptive cycle are shown by the white boxes and labelled r, K, . The four grey boxes are alternative phases, two of which were identified by Hollinget al. (2002c) as pathological traps, the Poverty Trap and the Rigidity Trap. A third alternative phase we have identified as the Lock-in Trap.
the boundaries of the thresholds outward (Walker et al., 2002). Human innovation can take a number of forms, for example, technical or institutional change. In the WA agricultural region technical advances in fertilisers and improvement in wheat varieties increased wheat production over time, essentially masking the reductions in land degradation including the reduced productive area caused by increased soil salinity, now approximately 16% of the WA agricultural region.
The ecosystem has been changed from a species rich system to a specialised commodity system with low species richness and loss of system function, for example, flood mitigation and water purification. The costs of loss of system function are the costs to maintain and increase productivity (for example, the costs of fertilisers, herbicides, pesticides, new wheat varieties and miti- gation of soil degradation, including acidification and erosion, drainage, and revegetation). It is proposed that the WA agricultural region has lost impor- tant system components involved with the hydrological cycle and that the system has been irreversibly modified, which potentially will require a contin- uous stream of increasing and additional inputs to control the symptoms. For example, pumping to keep freshwater wetlands from becoming saline and the digging of drainage channels to prevent land becoming saline.
The reference modes described the WA agricultural region as a SES with the unintended effects of resource depletion, environmental pollution and social decline. Why has there not been a profound collapse of the system?
Hollinget al. (2002c) proposed that an adaptive cycle will collapse because the potential and diversity have been eradicated by misuse or an external force, illustrated by an example of an irreversible eroding state of a savanna (Holling and Gunderson, 2002). Human activity may ‘mine’ the resource (for example, depleting the soil through erosion) in a situation in which the land manager is under greater and greater pressure to produce more while the economic return from the land diminishes, either because of lowered productivity or reducing terms of trade or both. Ultimately the ecological system will become severely impoverished, causing the resilience to increase because the system has reached such a depauperate state that it is extremely stable or perhaps irreversibly stable. We suggest that this situation is represented by one of the remaining two unaccounted for pathological states. This state we have labelled the Lock-in Trap in which an industry or enterprise has high amounts of ‘sunk-costs’ causing it to continue to degrade the resource it relies upon until the natural resource capital is totally removed. The concept of ‘sunk- cost’ is well defined in the economic literature as that part of any cost that has been incurred in the past (or that part of a cost resulting from a commitment entered into in the past) that cannot be eliminated or recovered
by present and future actions (Baumolet al., 1992). This type of relationship is characterised by reinvestment at the macroeconomic scale in agriculture in terms of technology and at the microeconomic scale by investment by the individual in, for example, plant, equipment and intellectual property.
The Lock-in Trap has low potential for change, high connectedness and high resilience. High resilience would mean a great ability for the system to resist external disturbances and persist due to the depauperate ecological system. It can be deduced from resilience theory that some subregions or catchments of the WA agricultural region with the most productive soils and not prone to soil salinity will be adaptive and others may well get caught in one or other of the pathological traps through a combination of factors but ultimately through natural resource degradation.
Long-wave economic cycles cause build up and collapse in societies.
Records for ancient societies show that in some cases renewal from collapse was possible while in other cases recovery was not possible (Janssenet al., 2002). It is proposed that some societies may become fragile and vulnerable to collapse from a phenomenon known as the ‘sunk-cost effect’ (Janssen et al., 2002; Tainter, 1988). This phenomenon is attributed to a society that becomes highly interconnected and may not be flexible enough to react to unfavourable climatic events such as drought (Janssen et al., 2002). Such a society has lost its resilience to be able to respond to sudden changes and a threshold may be crossed. This event has also been described as a tipping point (Gladwell, 2002). Tainter (1988) developed an argument of diminishing returns to increasing complexity and ascribed to this cause the collapse of 24 societies. Tainter (1988) proposed that increasing complexity was beneficial up to a certain degree, beyond which the effects were detrimental. Tainter (1988) argued that the development of complexity was an economic process and that society evolved along the marginal return curve in a phenomenon known as ‘the law of diminishing returns’. That is to say, at a certain level of complexity the ratio of returns to costs diminishes resulting in negative returns to investment. At this tipping point a society may become extremely vulnerable to collapse.