Editing IPCC:AR6/SRCCL/Chapter-7 (section)

=== 7.6.3 Adaptive climate governance responding to uncertainty ===

<div id="section-7-6-3-adaptive-climate-governance-responding-to-uncertainty-block-1"></div>

In the 1990s, adaptive governance emerged from adaptive management (Holling 1978, 1986), combining resilience and complexity theory, and reflecting the trend of moving from government to governance (Hurlbert 2018b <sup>[[#fn:r1336|1336]]</sup> ). Adaptive governance builds on multi-level and polycentric governance. Adaptive governance is ‘a process of resolving trade-offs and charting a course for sustainability’ (Boyle et al. 2001, p. 28) through a range of ‘political, social, economic and administrative systems that develop, manage and distribute a resource in a manner promoting resilience through collaborative, flexible and learning-based issue management across different scales’ (Hurlbert 2018,p.25). There is ''medium evidence'' and ''medium agreement'' that few alternative governance theories handle processes of change characterised by nonlinear dynamics, threshold effects, cascades and limited predictability; however, the majority of literature relates to the USA or Canada (Karpouzoglou et al. 2016 <sup>[[#fn:r1337|1337]]</sup> ). Combining adaptive governance with other theories has allowed good evaluation of important governance features such as power and politics, inclusion and equity, short-term and long-term change, and the relationship between public policy and adaptive governance (Karpouzoglou et al. 2016).

There is ''robust evidence'' and ''high agreement'' that resource and disaster crises are crises of governance (Pahl-Wostl 2017b <sup>[[#fn:r1338|1338]]</sup> ; Villagra and Quintana 2017 <sup>[[#fn:r1339|1339]]</sup> ; Gupta et al. 2013b <sup>[[#fn:r1340|1340]]</sup> ). Adaptive governance of risk has emerged in response to these crises and involves four critical pillars (Fra.Paleo 2015 <sup>[[#fn:r1341|1341]]</sup> ):

# Sustainability as a response to environmental degradation, resource depletion and ES deterioration
# Recognition that governance is required as government is unable to resolve key societal and environmental problems, including climate change and complex problems
# Mitigation as a means to reduce vulnerability and avoid exposure
# Adaptation responds to changes in environmental conditions.

Closely related to (and arguably components of) adaptive governance are adaptive management (Section 7.5.4) (a regulatory environment that manages ecological system boundaries through hypothesis testing, monitoring, and re-evaluation (Mostert et al. 2007 <sup>[[#fn:r1342|1342]]</sup> )), adaptive co-management (flexible community-based resource management (Plummer and Baird 2013 <sup>[[#fn:r1343|1343]]</sup> )), and anticipatory governance (flexible decision-making through the use of scenario planning and reiterative policy review (Boyd et al. 2015 <sup>[[#fn:r1344|1344]]</sup> )). Adaptive governance can be conceptualised as including multilevel governance with a balance

between top-down and bottom-up decision-making that is performed by many actors (including citizens) in both formal and informal networks, allowing policy measures and governance arrangements to be tailored to local context and matched at the appropriate scale of the problem, allowing for opportunities for experimentation and learning by individuals and social groups (Rouillard et al. 2013 <sup>[[#fn:r1345|1345]]</sup> ; Hurlbert 2018b <sup>[[#fn:r1346|1346]]</sup> ).

There is ''high confidence'' that anticipation is a key component of adaptive climate governance wherein steering mechanisms in the present are developed to adapt to and/or shape uncertain futures (Vervoort and Gupta 2018 <sup>[[#fn:r1347|1347]]</sup> ; Wiebe et al. 2018 <sup>[[#fn:r1348|1348]]</sup> ; Fuerth 2009 <sup>[[#fn:r1349|1349]]</sup> ). Effecting this anticipatory governance involves simultaneously making short-term decisions in the context of longer-term policy visioning, anticipating future climate change models and scenarios in order to realise a more sustainable future (Bates and Saint-Pierre 2018 <sup>[[#fn:r1350|1350]]</sup> ; Serrao-Neumann et al. 2013 <sup>[[#fn:r1351|1351]]</sup> ; Boyd et al. 2015 <sup>[[#fn:r1352|1352]]</sup> ). Utilising the decision- making tools and practices in Section 7.5, policymakers operationalise anticipatory governance through a foresight system considering future scenarios and models, a networked system for integrating this knowledge into the policy process, a feedback system using indicators (Section 7.5.5) to gauge performance, an open-minded institutional culture allowing for hybrid and polycentric governance (Fuerth and Faber 2013 <sup>[[#fn:r1353|1353]]</sup> ; Fuerth 2009 <sup>[[#fn:r1354|1354]]</sup> ).

There is ''high confidence'' that, in order to manage uncertainty, natural resource governance systems need to allow agencies and stakeholders to learn and change over time, responding to ecosystem changes and new information with different management strategies and practices that involve experimentation (Camacho 2009 <sup>[[#fn:r1355|1355]]</sup> ; Young 2017b <sup>[[#fn:r1356|1356]]</sup> ).Thereis emerging literature on experimentation in governance surrounding climate change and land use (Kivimaa et al. 2017a <sup>[[#fn:r1357|1357]]</sup> ) including policies such as REDD+ (Kaisa et al. 2017 <sup>[[#fn:r1358|1358]]</sup> ). Governance experiment literature could be in relation to scaling up policies from the local level for greater application, or downscaling policies addressing broad complex issues such as climate change, or addressing necessary change in social processes across sectors (such as water energy and food) (Laakso et al. 2017 <sup>[[#fn:r1359|1359]]</sup> ). Successful development of new policy instruments occurred in a governance experiment relating to coastal policy adapting to rising sea levels and extreme weather events through planned retreat (Rocle and Salles 2018 <sup>[[#fn:r1360|1360]]</sup> ). Experiments in emissions trading between 1968 and 2000 in the USA helped to realise specific models of governance and material practices through mutually supportive lab experiments and field applications that advanced collective knowledge (Voß and Simons 2018 <sup>[[#fn:r1361|1361]]</sup> ).

There is ''high confidence'' that an SLM plan is dynamic and adaptive over time to (unforeseen) future conditions by monitoring indicators as early warnings or signals of tipping points, initiating a process of change in policy pathway before a harmful threshold is reached (Stephens et al. 2018, 2017; Haasnoot et al. 2013 <sup>[[#fn:r1362|1362]]</sup> ; Bloemen et al. 2018 <sup>[[#fn:r1363|1363]]</sup> ) (Section 7.5.2.2). This process has been applied in relation to coastal sea level rise, starting with low-risk, low-cost measures and working up to measures requiring greater investment after review and reevaluation (Barnett et al. 2014 <sup>[[#fn:r1364|1364]]</sup> ). A first measure was stringent controls of new development, graduating to managed relocation of low-lying critical infrastructure, and eventually movement of habitable dwellings to more elevated parts of town, as flooding and inundation triggers are experienced (Haasnoot et al. 2018 <sup>[[#fn:r1365|1365]]</sup> ; Lawrence et al. 2018 <sup>[[#fn:r1366|1366]]</sup> ; Barnett et al. 2014 <sup>[[#fn:r1367|1367]]</sup> ; Stephens et al. 2018 <sup>[[#fn:r1368|1368]]</sup> ). Nanda et al. (2018) <sup>[[#fn:r1369|1369]]</sup> apply the concept to a wetland in Australia to identify a mix of short- and long-term decisions, and Prober et al. (2017) <sup>[[#fn:r1371|1371]]</sup> develop adaptation pathways for agricultural landscapes, also in Australia. Both studies identify that longer-term decisions may involve a considerable change to institutional arrangements at different scales. Viewing climate mitigation as a series of connected decisions over a long time period and not an isolated decision, reduces the fragmentation and uncertainty endemic of models and effectiveness of policy measures (Roelich and Giesekam 2019 <sup>[[#fn:r1372|1372]]</sup> ).

There is ''medium evidence'' and ''high agreement'' that participatory processes in adaptive governance within and across policy regimes overcome limitations of polycentric governance, allowing priorities to be set in sustainable development through rural land management and integrated water resource management (Rouillard et al. 2013 <sup>[[#fn:r1373|1373]]</sup> ).Adaptive governance addresses large uncertainties and their social amplification through differing perceptions of risk (Kasperson 2012 <sup>[[#fn:r1374|1374]]</sup> ; Fra.Paleo 2015 <sup>[[#fn:r1375|1375]]</sup> ) offering an approach to co-evolve with risk by implementing policy mixes and assessing effectiveness in an ongoing process, making mid-point corrections when necessary (Fra.Paleo 2015). In respect of climate adaptation to coastal and riverine land erosion due to extreme weather events impacting on communities, adaptive governance offers the capacity to monitor local socio-economic processes and implement dynamic locally informed institutional responses. In Alaska, adaptive governance responded to the dynamic risk of extreme weather events and issue of climate migration by providing a continuum of policy from protection in place to community relocation, integrating across levels and actors in a more effective and less costly response option than other governance systems (Bronen and Chapin 2013 <sup>[[#fn:r1376|1376]]</sup> ). In comparison to other governance initiatives of ecosystem management aimed at conservation and sustainable use of natural capital, adaptive governance has visible effects on natural capital by monitoring, communicating and responding to ecosystem-wide changes at the landscape level (Schultz et al. 2015 <sup>[[#fn:r1377|1377]]</sup> ). Adaptive governance can be applied to manage drought assistance as a common property resource. Adaptive governance can manage complex, interacting goals to create innovative policy options, facilitated through nested and polycentric systems of governance, effected by watershed or catchment management groups in areas of natural resource management (Nelson et al. 2008 <sup>[[#fn:r1378|1378]]</sup> ).

There is ''medium evidence'' and ''high agreement'' that transformational change is a necessary societal response option to manage climate risks which is uniquely characterised by the depth of change needed to reframe problems and change dominant mindsets, the scope of change needed (that is larger than just a few people) and the speed of change required to reduce emissions (O’Brien et al. 2012 <sup>[[#fn:r1379|1379]]</sup> ; Termeer et al. 2017 <sup>[[#fn:r1380|1380]]</sup> ). Transformation of governance occurs with changes in values to reflect an understanding that the environmental crisis occurs in the context of our relation with the earth (Hordijk et al. 2014 <sup>[[#fn:r1381|1381]]</sup> ; Pelling 2010 <sup>[[#fn:r1382|1382]]</sup> ). Transformation can happen by intervention strategies that enable small in-depth wins, amplify these small wins through integration into existing practices, and unblock stagnations (locked in structures) preventing transformation by confronting social and cognitive fixations with counterintuitive interventions (Termeer et al. 2017 <sup>[[#fn:r1383|1383]]</sup> ). Iterative consideration of issues and reformulation of policy instruments and response options facilitates transformation by allowing experimentation (Monkelbaan 2019 <sup>[[#fn:r1384|1384]]</sup> ).

<div id="section-7-6-3-adaptive-climate-governance-responding-to-uncertainty-block-2" class="box"></div>

<span id="b7.2-adaptive-governance-and-interlinkages-of-food-fibre-water-energy-and-land"></span>