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endorsed by the fifth Conference of the Parties to the Convention on Biological Diversity
(CBD) (Smith and Maltby 2003). The goals of ecosystem management include:
Maintaining viable populations of all native species in situ.
Maintaining representative protected area networks that cover native ecosystem types
across their natural range of variation.
Maintaining evolutionary and ecological processes (i.e. disturbance regimes, hydro-
logical processes, nutrient cycles, etc.).
Managing over periods of time that are long enough to maintain the evolutionary poten-
tial of species and ecosystems.
• Accommodating human use and occupancy within these constraints, and managing natural
resources in a fair and equitable manner.
Ecosystem management requires a flexible, adaptive approach to management in the face of
uncertainty and flux. Adaptive management has emerged as the best option for developing
conservation interventions that can respond rapidly to changing environmental conditions,
societal demands, and emerging knowledge (Grumbine 1994, Biggs and Rogers 2003). Adap-
tive management treats conservation interventions as experiments, in which observations
are fed back into the decision-making process in cycles of goal-setting, implementation,
monitoring, and re-adjustment.
In the face of complexity and flux, resilience theory has emerged as a major unifying thread
in ecological thinking and ecosystem management. Drawing on complexity theory, ecolo-
gists now describe ecosystems in terms that are scale specific and concerned with the pro-
cesses that maintain stability and drive innovation and reorganization when ecological or
environmental thresholds were crossed (Holling 1973, 1996a, Gunderson and Holling 2001).
In ecology, resilience is defined as the capacity of a system to absorb disturbance, while a
threshold is the point at which resilience is exceeded and the system reorganizes to a new
state, maintained by a different set of ecological processes (Figure 1.3a). In a varying environ-
ment, reorganization of complex socioecological systems will take place once an ecological
threshold is crossed, unless resilience can be increased through adaptation (Figure 1.3b).
Most conservation decisions are embedded within socioecological systems. We are faced
with the messy reality of understanding networks of interacting causes, effects, and inter-
pretations, while still needing to retain the requisite simplicity that allows decisions to be
made and action to be taken (Stirzaker et al. 2010, Adams and Sandbrook 2013, Rogers et al.
2013). In conventional ('normal') science, scientific research provides the basis for decisions
by predicting what will happen by inference, but there are relatively few conservation deci-
sions that can be made on purely scientific grounds. Such instances usually involve small,
closed systems where the drivers and responders of change are well understood—for exam-
ple, the restoration of a pond after a point pollution event (du Toit 2012, Sutherland et  al.
2012, Sutherland 2013). 'Scaling up' from such simple building blocks cannot usually resolve
complex conservation decisions, because of the non-linearity, stochasticity and emergent
properties of complex systems and the myriad values and perspectives of different stake-
holder groups (Stirzaker et al. 2010, Sutherland et al. 2012, Rogers et al. 2013). Therefore an
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