and outcomes (Carrick and Krüger 2007; Standish et al. 2007; Holl et al. 2011; Le
Maitre et al. 2011; Davies et al. 2018). Threshold models have played a significant
conceptual role. Initially they were applied in semi-arid rangelands to describe
sudden shifts in ecosystem structure or functioning, where the degraded alternative
ecosystem state was resistant to natural recovery (Milton and Siegfried 1994;
Whisenant 1999). Subsequent work showed that sudden regime shifts (sometimes
termed tipping points) also operate in many other types of ecosystems previously
assumed to follow linear degradation or successional trajectories (Gaertner et al.
2012b; Richardson et al. 2007). Traditional restoration approaches in degraded lands
may fail due to constraints such as local loss of native species, seed dispersal
limitations, shifts in dominance, altered biogeochemical processes and altered feedbacks that entrench an undesirable stable state (Beisner et al. 2003; Norton 2009;
Suding et al. 2004). Threshold models that incorporate alternative ecosystem states
and feedbacks can be applied to assist in habitat management decision-making
(Standish et al. 2007; Gaertner et al. 2012b; Suding and Hobbs 2009).
It is reasoned that restoring ecosystem structure (including functional group
diversity) will simultaneously restore ecosystem functioning (Holmes and Richardson 1999). Mori et al. (2013) explored the links between biodiversity, ecosystem
stability and functionality, and how degradation may affect these. They suggested
that traditional measures such as species diversity do not adequately capture aspects
that are pivotal for ecosystem resilience, which requires the recovery of guilds
representing the range of functional responses required to drive key processes.
Sudden shifts to alternative ecosystem states coincide with a rapid loss of functional
diversity that results from an aggregated loss of response diversity. Mori et al. (2013)
emphasise that perspectives incorporating functional effects and responses of biodiversity are essential for developing restoration management strategies. However, the
recovery of functions may lag behind structure in some ecosystems such as riparian
forests (Matzek et al. 2016). Furthermore, where abiotic thresholds have been
crossed, such as under climate change, the situation is likely to be more challenging.
Climate change might reduce the effect of some stressors whilst enhancing others,
further complicating restoration efforts (Rohr et al. 2018, 2013).
Implementing ecological restoration is complex: managers need to assess the
impacts of degradation on ecosystem functions and recovery potential as well as the
likely impacts of different management interventions. Lack of consideration for all
aspects involved in restoration has likely resulted in limited success of implementation (Kettenring and Adams 2011). In addition, global change impacts such as
habitat loss, fragmentation, biological invasions, and climate change may influence
restoration outcomes. In South Korea, an approach using flexible restoration targets
was applied: this considered ecosystem functions and functional trait diversity,
rather than historic precedents, to create model restoration projects and implement
adaptive management (Temperton et al. 2014). Because there is a need to improve
restoration outcomes, share information from different restoration projects, and
acknowledge stakeholder contexts, James and Carrick (2016) advocated the use of
quantitative systems models. These models link ecological processes, and potentially social processes, that influence the desired outcome. Data gathered from
668
P. M. Holmes et al.
Maitre et al. 2011; Davies et al. 2018). Threshold models have played a significant
conceptual role. Initially they were applied in semi-arid rangelands to describe
sudden shifts in ecosystem structure or functioning, where the degraded alternative
ecosystem state was resistant to natural recovery (Milton and Siegfried 1994;
Whisenant 1999). Subsequent work showed that sudden regime shifts (sometimes
termed tipping points) also operate in many other types of ecosystems previously
assumed to follow linear degradation or successional trajectories (Gaertner et al.
2012b; Richardson et al. 2007). Traditional restoration approaches in degraded lands
may fail due to constraints such as local loss of native species, seed dispersal
limitations, shifts in dominance, altered biogeochemical processes and altered feedbacks that entrench an undesirable stable state (Beisner et al. 2003; Norton 2009;
Suding et al. 2004). Threshold models that incorporate alternative ecosystem states
and feedbacks can be applied to assist in habitat management decision-making
(Standish et al. 2007; Gaertner et al. 2012b; Suding and Hobbs 2009).
It is reasoned that restoring ecosystem structure (including functional group
diversity) will simultaneously restore ecosystem functioning (Holmes and Richardson 1999). Mori et al. (2013) explored the links between biodiversity, ecosystem
stability and functionality, and how degradation may affect these. They suggested
that traditional measures such as species diversity do not adequately capture aspects
that are pivotal for ecosystem resilience, which requires the recovery of guilds
representing the range of functional responses required to drive key processes.
Sudden shifts to alternative ecosystem states coincide with a rapid loss of functional
diversity that results from an aggregated loss of response diversity. Mori et al. (2013)
emphasise that perspectives incorporating functional effects and responses of biodiversity are essential for developing restoration management strategies. However, the
recovery of functions may lag behind structure in some ecosystems such as riparian
forests (Matzek et al. 2016). Furthermore, where abiotic thresholds have been
crossed, such as under climate change, the situation is likely to be more challenging.
Climate change might reduce the effect of some stressors whilst enhancing others,
further complicating restoration efforts (Rohr et al. 2018, 2013).
Implementing ecological restoration is complex: managers need to assess the
impacts of degradation on ecosystem functions and recovery potential as well as the
likely impacts of different management interventions. Lack of consideration for all
aspects involved in restoration has likely resulted in limited success of implementation (Kettenring and Adams 2011). In addition, global change impacts such as
habitat loss, fragmentation, biological invasions, and climate change may influence
restoration outcomes. In South Korea, an approach using flexible restoration targets
was applied: this considered ecosystem functions and functional trait diversity,
rather than historic precedents, to create model restoration projects and implement
adaptive management (Temperton et al. 2014). Because there is a need to improve
restoration outcomes, share information from different restoration projects, and
acknowledge stakeholder contexts, James and Carrick (2016) advocated the use of
quantitative systems models. These models link ecological processes, and potentially social processes, that influence the desired outcome. Data gathered from
668
P. M. Holmes et al.