17 – Saving our Species^235evaluated as being ‘not on track’ (i.e. a threat or population not meeting annual
target) triggers an assessment of the project. Monitoring outcomes at multiple
levels (i.e. outputs, threat response or population response) is particularly useful for
diagnosing the source of management ineffectiveness (Fig. 17.1). For example, if all
managed threats are responding well and below target thresholds but monitoring
of the threatened species reveals that the local population is in decline, this is clear
evidence that our knowledge of the system is f lawed (e.g. a critical threat has been
overlooked). Under such circumstances, SoS prescribes a more experimental
approach (i.e. adaptive management) whereby the relative effects of different
drivers (e.g. threats, environmental conditions) can be partitioned to identify the
best course of management.
Adaptive management under SoS
Adaptive management (AM) may require a sacrifice of some immediate
conservation outcomes and/or additional investment via designing management
and monitoring for the purpose of learning something about the system
(McCarthy and Possingham 2007). For SoS, the value of AM lies in its ability to
generate information beyond that provided by the standard monitoring framework
outlined above, and where it is feasible to change management in response to this
information. Under these circumstances, AM can inform management in a way
that maximises the likelihood of a population response and minimises the
likelihood of wasting resources on interventions with uncertain outcomes. To
ensure investment in monitoring is cost-effective, the value of AM relative to its
associated cost must be considered: AM is only justified if the potential savings (i.e.
investment in management) are greater than the cost premium associated with
implementing the AM (e.g. Runge et al. 2 011).
Given the uncertainties involved with managing threatened species, AM is
desirable but often not feasible (e.g. populations with extremely limited numbers of
individuals or locations) or cost-effective (e.g. Moore and Runge 2012). Under SoS,
AM is recommended where the approach is feasible and cost-effective, such that
the value of information gained is greater than the cost of obtaining it. This is
mostly likely to apply under circumstances where there is high uncertainty in the
system’s response to management, the ongoing investment required is high, or
both. Examples where AM is desirable in NSW include widespread, mobile fauna,
such as the brush-tailed rock-wallaby Petrogale penicillata and malleefowl Leipoa
by the conceptual model. Given the availability of suitable habitat in the area,
experts predict that the population could double or triple over the next 10–20
years, before reaching carrying capacity.