10
proactive, mitigating, and/or adaptive responses requires a multi-criteria assessment
in different contexts (Ocampo-Melgar et al. 2017).
When SES are managed, restored, or protected, necessarily through the lens of
CAS theory, they will not remain or can be maintained at a mature or desirable state,
respectively, but rather undergo adaptive cycles (Gunderson and Holling 2002).
Complex systems may organize around one of several stable states within a desirable (from a stakeholder perspective) regime of the system. Thus, rather than focusing on detailed characteristics of one stable state, one may want to understand the
internal and external drivers that cause the transition to alternative states and how
systems elements reorganize without losing the underlying interconnectedness,
structure, function, and feedback responses of the system, thus maintaining its resilience (Westoby et al. 1989; Scheffer and Carpenter 2003).
In Holling’s adaptive cycle, the systems once fully developed are commonly held
in the so-called conservation phase (Walker and Salt 2006). Humans tend to interfere in the adaptive cycle and frequently prolong this phase. For instance, by maximizing the production of a single ecosystem service, for example, forage production,
water extraction, and so on, thereby eliminating unnecessary system variability and
redundancy. However, this comes at the cost of eradicating high levels of diversity
including biotic (species and functional groups, ecosystem service bundles), cultural (flexibility to adapt and adopt new livelihoods, high adaptive capacity related
to local knowledge), and social diversity (institutional organizations, social networks, social memory, adaptive local governance systems). This diversity is needed
as it confers insurance and buffer against unpredictable future changes (e.g., prolonged drought, fire, diseases, pests, drop in prices of commodities, new legislation). Similarly, we may want to ask do high levels of response diversity also provide
systems with a potentially broad adaptive capacity to reorganize once a system has
collapsed and shifted from the conservation to the release phase. How do SES reorganize, after they have lost the internal connectedness and release all resources,
energy, and/or information itself?
Acknowledging and eventually managing the cyclic behavior of SES requires the
incorporation of different sources of knowledge. The trajectory of system development follows both the system’s memory and the current social–ecological context
and conditions, thus conferring new ecological and/or social opportunities characterizing a certain system state within the desired regime (Huber-Sannwald et al. 2012).
Lack of ability to respond to or recover after a system has collapsed may trigger the
crossing of a threshold (biophysical or socio-economic) or tipping point (social, ecological, or socio-ecological (Milkoreit et al. 2017), and the shift into a new (albeit
less desirable) regime. A system’s capacity to build and maintain resilience and to
re(self)-organize after a shock or severe disturbance event is critical, whether external, internal, or interacting drivers induce system change. Since the 1950s, in the
time of Great Acceleration (Steffen et al. 2007), this may occur more rapidly, unpredictably, or irreversibly (global population growth, local and regional migration, land
use change, soil erosion), directionally (loss of vegetation cover, change in species
composition, climate warming, exploitation of aquifers, fisheries) (Steffen et al. 2015),
or as an emerging phenomenon (loss of system resilience, landscape dysfunction,
E. Huber-Sannwald et al.
proactive, mitigating, and/or adaptive responses requires a multi-criteria assessment
in different contexts (Ocampo-Melgar et al. 2017).
When SES are managed, restored, or protected, necessarily through the lens of
CAS theory, they will not remain or can be maintained at a mature or desirable state,
respectively, but rather undergo adaptive cycles (Gunderson and Holling 2002).
Complex systems may organize around one of several stable states within a desirable (from a stakeholder perspective) regime of the system. Thus, rather than focusing on detailed characteristics of one stable state, one may want to understand the
internal and external drivers that cause the transition to alternative states and how
systems elements reorganize without losing the underlying interconnectedness,
structure, function, and feedback responses of the system, thus maintaining its resilience (Westoby et al. 1989; Scheffer and Carpenter 2003).
In Holling’s adaptive cycle, the systems once fully developed are commonly held
in the so-called conservation phase (Walker and Salt 2006). Humans tend to interfere in the adaptive cycle and frequently prolong this phase. For instance, by maximizing the production of a single ecosystem service, for example, forage production,
water extraction, and so on, thereby eliminating unnecessary system variability and
redundancy. However, this comes at the cost of eradicating high levels of diversity
including biotic (species and functional groups, ecosystem service bundles), cultural (flexibility to adapt and adopt new livelihoods, high adaptive capacity related
to local knowledge), and social diversity (institutional organizations, social networks, social memory, adaptive local governance systems). This diversity is needed
as it confers insurance and buffer against unpredictable future changes (e.g., prolonged drought, fire, diseases, pests, drop in prices of commodities, new legislation). Similarly, we may want to ask do high levels of response diversity also provide
systems with a potentially broad adaptive capacity to reorganize once a system has
collapsed and shifted from the conservation to the release phase. How do SES reorganize, after they have lost the internal connectedness and release all resources,
energy, and/or information itself?
Acknowledging and eventually managing the cyclic behavior of SES requires the
incorporation of different sources of knowledge. The trajectory of system development follows both the system’s memory and the current social–ecological context
and conditions, thus conferring new ecological and/or social opportunities characterizing a certain system state within the desired regime (Huber-Sannwald et al. 2012).
Lack of ability to respond to or recover after a system has collapsed may trigger the
crossing of a threshold (biophysical or socio-economic) or tipping point (social, ecological, or socio-ecological (Milkoreit et al. 2017), and the shift into a new (albeit
less desirable) regime. A system’s capacity to build and maintain resilience and to
re(self)-organize after a shock or severe disturbance event is critical, whether external, internal, or interacting drivers induce system change. Since the 1950s, in the
time of Great Acceleration (Steffen et al. 2007), this may occur more rapidly, unpredictably, or irreversibly (global population growth, local and regional migration, land
use change, soil erosion), directionally (loss of vegetation cover, change in species
composition, climate warming, exploitation of aquifers, fisheries) (Steffen et al. 2015),
or as an emerging phenomenon (loss of system resilience, landscape dysfunction,
E. Huber-Sannwald et al.