Towards Enhancing Adaptive Capacity for Climate Change Response in South East Queensland

The Australasian Journal of Disaster
and Trauma Studies
ISSN:  1174-4707
Volume : 2010-1

Towards Enhancing Adaptive Capacity for
Climate Change Response in South East Queensland

Timothy F. Smith, Sustainability Research Centre, University of the Sunshine Coast, Maroochydore DC, 4551, Australia. Email: Tim.Smith@usc.edu.au
Timothy Lynam, CSIRO Sustainable Ecosystems, Davies Laboratory, University Road, Douglas, 4814, Australia
Benjamin L. Preston, CSIRO Marine and Atmospheric Research, Private Bag 1, 107-121 Station Street, Aspendale, Victoria 3195, Australia
Julie Matthews, R. W. (Bill) Carter, Dana C. Thomsen, Jennifer Carter, Anne Roiko, Rodney Simpson, Peter Waterman, Marcus Bussey, Noni Keys & Craig Stephenson, Sustainability Research Centre, University of the Sunshine Coast, Maroochydore DC, 4551, Australia

Timothy F. Smith Sustainability Research Centre, University of the Sunshine Coast, Maroochydore DC, 4551, Australia.	Timothy Lynam CSIRO Sustainable Ecosystems, Davies Laboratory, University Road, Douglas, 4814, Australia	Benjamin L. Preston CSIRO Marine and Atmospheric Research, 107-121 Station Street, Aspendale, Victoria 3195, Australia
Julie Matthews, R. W. (Bill) Carter, Dana C. Thomsen, Jennifer Carter, Anne Roiko, Rodney Simpson, Peter Waterman, Marcus Bussey, Noni Keys & Craig Stephenson Sustainability Research Centre, University of the Sunshine Coast, Maroochydore DC, 4551, Australia.

Abstract

Discussion of climate change adaptation is gaining increased prominence in sustainability policy and the academic literature. A key factor in the selection of climate adaptation initiatives is the understanding of vulnerability. However, past approaches to understanding climate change vulnerability have largely focused on assessments of exposure (e.g., change in temperature), to the exclusion of assessments of sensitivity (e.g., regions with an aging population) or adaptive capacity (e.g., the ability to implement adaptation initiatives). The authors argue that an understanding of adaptive capacity is critical to inform climate change vulnerability and to help prioritise climate change adaptation initiatives. The authors propose an approach to understand adaptive capacity, which is currently being applied in South East Queensland.

Towards Enhancing Adaptive Capacity for
Climate Change Response in South East Queensland

Introduction

South East Queensland (SEQ), Australia, is experiencing rapid population growth, which could exacerbate the effects of climate change. While governments, industries and communities recognise the need for adaptation, there has been no comprehensive regional assessment of climate vulnerability. To understand vulnerability and the feasibility of adaptation strategies, the authors argue that assessments of the capacity of the region to adapt to the effects of climate change are critical. The authors begin by describing the climate change adaptation context for Australia, and more specifically, SEQ. The concept of vulnerability in relation to climate change is then discussed, as well as the need to better understand adaptive capacity. Finally, the authors propose a method for enhancing adaptive capacity for climate change response.

Australian Responses to Climate Change Adaptation

While several mitigation-related activities remain, Australian governments have now embraced the need to act on unavoidable impacts of climate change through adaptation measures. Although there remains a void of specific adaptation policy at the State and, more particularly, the national scales, there has been funding allocated to support local adaptation planning through the Federal Government Local Adaptation Pathways Program (LAPP) grants to local governments. The need to adapt has also been reinforced at the State level (e.g., through adoption of increased sea-level projections over the next 100 years). Several industry spokespeople have also espoused the need to adapt to climate change, perhaps the most vocal of which has emanated from the insurance sector.

The acceptance of the need to act on climate change impacts has also shifted the balance of research imperatives (reflected in national funding streams) towards adaptation research. Within the last 5 years there have been significant investments across several adaptation research program areas. For example, the activities of the CSIRO Climate Adaptation National Research Flagship (CAF) and the National Climate Change Adaptation Research Facility (NCCARF) receive well in excess of AUD$100m towards research and associated research networks. However, the funding for climate change related activities (both adaptation and mitigation) remains miniscule compared to other initiatives such as economic stimulus investments on the part of the Australian government.

The emphasis of climate change research in Australia has mirrored that of the rest of the world, with a past focus on assessments of exposure but with an emerging recognition of the need for assessments of sensitivity and adaptive capacity. For example, one of the eight research themes that comprise NCCARF is dedicated to socio-economic and institutional dimensions of climate change, and many of the other research themes have social, economic and institutional sub-themes such as the Communities Theme that forms part of the Adaptation Research Network for Marine Biodiversity and Resources. However, there are only a few region-scale assessments of climate change adaptation that integrate across various sectors and across the components of vulnerability (i.e., exposure, sensitivity and adaptive capacity). One such assessment is currently underway in SEQ.

The South East Queensland Context

The Department of Infrastructure and Planning (2008a) states that SEQ is Australia’s fastest growing region and covers “22,420 square kilometres, stretching 240 kilometres from Noosa in the north to Coolangatta in the south, and 140 kilometres west to Toowoomba” (Figure 1).

Figure 1: Map of South East Queensland
(adapted from the Department of Infrastructure and Planning 2008b)

The population of SEQ has almost doubled in the period from 1976 to 2001 (from about 1.3 million people to almost 2.5 million people) (Office of Urban Management 2005), with similar trends predicted for the period from 2001 to 2026 (Table 1). Some regions within SEQ are also likely to experience greater than average growth. For example, the population of the Sunshine Coast is projected to increase by 80% to 450,000 residents over the period from 2002 to 2022 (Queensland Department of Infrastructure and Planning 2008). The increase in population combined with the continuing trend for fewer people per household is estimated to create demand for about another 575 000 new dwellings in SEQ by 2026 (Office of Urban Management 2005). Similarly, demand on both hard and soft infrastructure will also increase.

Table 1: Medium growth population projections for South East Queensland from 2001 to 2026
(adapted from the Office of Urban Management 2005)

The population growth and associated pressures for development and maintenance of infrastructure and services may exacerbate the impacts of climate change in SEQ (Table 2; CSIRO and BOM, 2007). Projected changes in the climate of SEQ from the latest suite of global climate models (utilised in the Intergovernmental Panel on Climate Change’s Fourth Assessment Report; IPCC, 2007), suggest that the region is likely to become warmer as well as drier. However, one must note that increases in rainfall cannot be excluded. In addition, the coastal zone will be affected by the projected increase in global sea level of between 18 and 79 cm by 2100 (IPCC, 2007). As with average annual rainfall, however, there is significant uncertainty associated with this range. As such, sea-level rise greater than 79 cm cannot be excluded, and how such global changes translate into changes at the scale of SEQ is less clear.

Table 2: Projected changes in average annual climatic conditions in 2030 and 2070 (relative to 1990) for Southeast Queensland

While such projected changes in the mean state of the climate system are indicative of a significant shift in climatic conditions, from a natural hazards perspective, such changes are of lesser relevance than the potential for changes in the frequency, intensity and duration of climatic extremes (Abbs et al., 2006; CSIRO and BOM, 2007). For example, the number of days SEQ experiences extreme temperatures is projected to rise. Similarly, simulations of thunderstorms, extreme rainfall and large hail events indicate the intensities of these types of events may rise, particularly in the latter-half of the century (CSIRO and BOM, 2007). Tropical cyclones are also projected to increase in intensity in response to climate change (CSIRO and BOM, 2007). Estimates of changes in the total number of such storms are more ambiguous. There is some evidence that the region of tropical cyclone occurrence will shift south, potentially increasing the risk of tropical cyclone events to SEQ.

The projected changes in extreme events in SEQ combined with the growth trajectories suggests that societal vulnerability to climate will rise in the future through an increased number of people at risk, as well as increased threats to the infrastructure, and goods and services that support the region’s population (e.g., agricultural produce and commuter transport facilities). For example, Preston and Jones (2006) describe a number of climate change impacts for Australia. In terms of SEQ, these impacts include southward penetration of the dengue transmission and increases in peak energy demand (see also Woodruff et al. 2005). Yet, it is increasingly evident that SEQ has a much broader set of climate challenges with which to contend including coastal erosion and inundation, damages to buildings and infrastructure, increased costs for goods and services, increased risk of heat-related illness and death, and constraints on water supply amidst growing demand. Therefore, the authors recognise the importance of better understanding vulnerability to climate change in SEQ and of providing strategies for building the adaptive capacity necessary for the effective, cost-efficient and equitable implementation of adaptation options.

Understanding Vulnerability

The Intergovernmental Panel on Climate Change Third Assessment Report glossary (2001, p. 995) defines vulnerability as “a function of the character, magnitude, and rate of climate variation to which a system is exposed, its sensitivity, and its adaptive capacity”. Using this definition, Allen Consulting (2005) illustrate ‘vulnerability’ diagrammatically and demonstrate that exposure to a climate event combined with sensitivity to that event may be interpreted as potential harm. Furthermore, that potential harm may be exaggerated or offset by adaptive capacity, resulting in a particular vulnerability level for a system. Smith (in press) contests that the past focus of published climate-science has been on assessments of exposure to climate hazards, whereas assessments of sensitivity and adaptive capacity are emerging concerns (Figure 2).

Figure 2: A framework for understanding vulnerability
(Smith in press, adapted from Allen Consulting 2005 after IPCC 2001)

Brooks et al. (2005) adopt another definition of vulnerability – one that is based on the internal variables within a system. For example, they explain that some determinants of vulnerability to a drought in Africa are likely to include context-specific determinants that are quite different to those that would be relevant to vulnerability to floods in Scandinavia. Brooks et al. also explain that context-specific determinants may be either placed-based or based on hazard type (e.g., floods, storm surge, and temperature extremes). However, they also acknowledge that there are generic determinants of vulnerability that would affect vulnerability across regions and hazards (see also Adger et al. 2004). For example, Preston et al. (2008) illustrate variance in adaptive capacity, and thus vulnerability, within the Sydney region being partly attributed to unequal distribution of wealth – which may affect adaptive capacity at local, regional, national and global scales. This article builds on the IPCC’s initial definitions and Brooks et al.’s (2005) conceptualisation of the determinants of vulnerability to highlight the need to distinguish between contextually-specific and generic vulnerability determinants. Thus, the contribution of this article is to address the emerging area of adaptive capacity by providing a brief commentary on its determinants and proposing an approach to enhance the capacity for climate change adaptation.

Understanding Adaptive Capacity

The Intergovernmental Panel on Climate Change Third Assessment Report (2001, p. 982) defines adaptive capacity as “The ability of a system to adjust to climate change … to moderate potential damages, to take advantage of opportunities, or to cope with the consequences”. Similarly, Adger & Vincent (2005, p. 402) describe adaptive capacity as the domain “within which adaptation decisions are feasible”. In this article, we adopt the IPCC definition but acknowledge that adaptive capacity may not only offset potential harm through improving the feasibility of adaptation options, but also might exacerbate vulnerability to climate change under certain conditions. For example, a flood event may affect communities to a greater extent if government or market forces encourage flood-prone development on floodplains. Timescales are also an important factor when considering adaptive capacity; whereby response to climate change impacts may require combinations of short, medium and long-term adaptive capacity variables to facilitate effective adaptation (Brooks et al. 2005). Similarly, spatial scales are also important; whereby adaptive capacity may require combinations of responses at local, regional, national, and global scales to facilitate effective adaptation (Folke et al. 2002).

A number of both context-specific and generic variables of adaptive capacity have been cited by various authors (e.g., Adger 1996, 1999; Adger et al. 2004; Brooks et al. 2005; Füssel 2007; Naess et al. 2005; Preston et al. 2008; Sen 1981; Smith et al. 2008; Tompkins & Adger 2004; Yohe & Tol 2002). A list of generic determinants of adaptive capacity has been developed by Yohe & Tol (2002) and includes:

• The range of available technological options for adaptation;
• The availability of resources and their distribution;
• The structure of critical institutions;
• The stocks of human and social capital;
• Access to risk spreading mechanisms;
• The ability of decision-makers to manage risks and information; and
• The public’s perceived attribution of the source of stress and the significance of climate change exposure to its local manifestations.

Consistent with the generic determinants reported by Yohe and Tol, a recent report by Smith et al. (2008), which focused on building adaptive capacity to climate change with local governments in the Sydney coastal region, synthesized the context-specific determinants of adaptive capacity as: access to resources; extent of social capital; structure and functionality of institutional arrangements; ability to generate knowledge; and capacity for social learning. Smith et al. also propose that adaptive capacity assessments may benefit from an assessment broken into contextual, structural, procedural, and outcome influences, which builds on regional natural resource planning assessments by Bellamy et al. (2005). These capacity determinants recognise the importance of understanding the context in which adaptation takes place (e.g., acceptance by communities); the structures that affect adaptation (e.g., legislation and policies); the processes that affect adaptation (e.g., financial and human resources); and outcome measures to inform the success or failure (learning) from adaptation initiatives (e.g., monitoring and evaluation). By understanding adaptive capacity through these determinants, interventions to build adaptive capacity can be targeted, and the feasibility of interventions better understood.

A Method for Enhancing Adaptive Capacity

While adaptive capacity has been identified as an emerging area of climate change adaptation research, it is perhaps through integrated assessments (i.e., combining assessments of exposure, sensitivity and adaptive capacity across sectors) where the greatest practical impact and contributions to knowledge can be made. In contrast to Brooks et al. (2005), the authors describe an emergent approach to determining key variables of adaptive capacity. As adaptive capacity is enhanced through learning (Lebel et al. 2006, Smith & Smith 2006) the authors contend that a proactive and participatory, co-learning approach is needed to ensure that learning occurs in the critical areas of all social systems that are affected by climate change. Engaging key stakeholders at the outset of the research programme aims to maximise the adoption of research findings into decision making systems of key stakeholders. As a result, the authors suggest the following five research stages to contribute to the understanding of adaptive capacity within a broader integrated assessment:

• Identifying relevant socio-economic patterns and trends;
• System conceptualisation – identifying the perceived and likely vulnerabilities of each sector to climate change as well as the major and most likely adaptations to climate change;
• Identifying the key attributes and determinants of, as well as threats to, adaptive capacity;
• Refining sectoral level understanding of and ability to manage adaptive capacity through institutional and empirical data analyses; and
• Designing cost effective strategies to enhance adaptive capacity that include institutionalised monitoring, evaluation and learning.

Stage 1: Identification of socio-economic trends and historical analysis
‘Non-climate’ system drivers may exacerbate climate change impacts. For example, socio-economic trends such as the nature and density of population change and consumption patterns may affect the magnitude of climate change impacts. An assessment of non-climate system drivers may be informed through secondary data analysis of socio-economic trends and projections (e.g., Australian Bureau of Statistics data), as well as through expert focus groups for input on specific socio-economic indicators for which there is limited data.

Concurrent to the identification of drivers, an analysis of historical adaptations to climate variability may be used to identify reasons for past adaptation successes, and reasons why past adaptation opportunities were not realised for a range of climate-related issues (e.g., water shortage). The analysis of historical adaptations to climate variability may be undertaken through desk-top assessment and key informant interviews. The historical assessment can be used to inform potential adaptation strategies both now and into the future.

Stage 2: System conceptualisation
The impacts of climate change may differ between sectors and may be variously exacerbated by different external drivers (e.g., population growth, economic conditions) and internal drivers (e.g., organisational culture). Sector-based workshops, using climate change and other drivers as stimuli, may allow the identification of the various key system interactions to be identified – enabling the identification of direct and indirect drivers of regional outcomes, and direct and indirect consequences of adaptation interventions. A system conceptualisation (mind mapping) can also be used to identify those impacts for which management responses are currently robust, even in the event of significant climate change, and those which are absent or under-developed, thereby contributing to vulnerability. In addition, this stage allows the examination of perceived benefits and limitations of autonomous or self-correcting mechanisms such as market response. A system conceptualisation would ideally be informed by regional climate change and socio-economic projections (even if they are preliminary) and result in the identification of perceived sector and cross-sector vulnerabilities.

Stage 3: Identification of the key attributes of adaptive capacity
Bayesian Belief Network (BBN) modelling is a means to explore key issues, barriers and opportunities identified in system conceptualisation workshops, as well as formalise and make broadly available the knowledge and uncertainties generated through workshops. BBN models (Cain, 2001; Jensen, 1996; Kjaerulff and Madsen, 2008) provide a powerful mechanism for supporting learning in the face of uncertainty. The philosophy of Bayesian probability is one of iterative learning; establishing prior probabilities for states of the world and then updating these probabilities based on additional data or observations. One of the strengths of a Bayesian network modelling approach is the potential of the models to use a variety of data sources; from empirical observations, through model outputs to expert or lay opinion. Once an initial model of the relationships between determining factors and attributes of adaptive capacity has been developed (using the best available data sets) then the knowledge in this model is used to identify where major additions to the knowledge of key sectors could be enhanced through further enquiry. The BBN thus forms a transparent and updatable repository of knowledge on barriers to, and opportunities for, enhancing adaptive capacity. The BBN can also be populated by a combination of on-line surveys, workshops and other available data sources to determine perceived key attributes of adaptive capacity as well as the perceived determinants, threats, opportunities and barriers to adaptation within major social and economic sectors. This allows the identification of potential sector-specific interventions and potential high leverage interventions that may cut across sectors. The BBN models may be expanded to capture the expectations of key capacity leaders as to key areas of adaptive capacity for each sector (expanded in stage 4). This activity assists with identifying perceptions of adaptive capacity and the key variables, sensitivities and uncertainties affecting adaptive capacity.

Stage 4: Analysis of adaptive capacity
Institutional analysis (through key informant interviews and analysis of secondary data sources) can be used to inform adaptive capacity leaders as champions of change in each sector. The analysis provides the empirical evidence for or against the attributes and determinants of (as well as the threats to) adaptive capacity. The analysis may be supplemented with input from earlier stages such as historical approaches to adaptation and internal sector drivers. The information collected through the interviews and secondary data can be used to update the BBN models of adaptive capacity. The analysis may then be informed by the regional climate change and socio-economic projections and enables targeted interventions to build adaptive capacity both within and between sectors. Thus, this activity analyses adaptive capacity and devises pathways to implement adaptive capacity interventions. This represents a first step in a continuous process of learning how best to enhance adaptive capacity with the BBN providing an ongoing learning device to guide sectoral representatives on where best to invest capacity building efforts in relation to increasing knowledge (reducing uncertainty) and achieving the goal of enhanced adaptive capacity.

Stage 5: Designing strategies to enhance effective adaptive capacity
Using the findings of stages 1–4, combined with findings from other studies, a series of sectoral and cross sectoral workshops are a means to firstly summarise the major findings of an integrated climate change assessment to key capacity leaders in each sector and then to design, with them, strategies for enhancing the most important areas of adaptive capacity. An integral part of these designs are institutionalised mechanisms to learn from those strategies. Both implementation plans and a monitoring and evaluation framework may enable benchmarking and improve targeted climate change adaptation interventions. A monitoring and evaluation framework can include both process and outcomes criteria to assess the feasibility of the interventions and potential transfer to other sectors and regions. The activities described in stage 5 allows the testing of the enhancement of adaptive capacity.

Through the implementation of stages 1 through 5 it is likely that the following outcomes would result:

• Increased sector and cross-sector understanding of climate change impacts and vulnerabilities;
• Increased understanding of the capacity of discrete sectors to adapt to climate change and the determinants of that capacity;
• Potential enhancement of the capacity to manage the impacts of climate change within and between sectors; and
• Stakeholder implementation and improvement of climate adaptation interventions.

Application of the Approach in South East Queensland

To enhance responses to climate change in SEQ a major research project (the SEQ Climate Adaptation Research Initiative) involving the CSIRO, Griffith University, the University of the Sunshine Coast, and the University of Queensland has recently commenced. The project has been funded by the CSIRO Collaboration Fund; Queensland Innovation Projects Fund (National and International Research Alliances Program); the Australian Department of Climate Change; and participating universities, and will conclude at the end of 2011. The project has targeted four specific sector clusters for vulnerability and adaptation assessments (Figure 3), including:

• Infrastructure, human settlements, and health;
• Ecosystems and biodiversity, pests, weeds and diseases;
• Energy; and
• Agriculture, forestry, and fisheries.

The project also has three cross-cutting research themes, including:

• Climate change projections – to inform vulnerability assessments;
• Adaptive capacity – to explore factors likely to offset or exacerbate climate change impacts, and to help inform the feasibility of adaptation strategies within and between sectors; and
• Regional synthesis – to integrate and synthesize project lessons, allow an adaptive approach throughout the life of the project, and to help inform transferability of research approaches and findings to other regions.

Figure 3: Framework for connections between South East Queensland climate adaptation project components

It is anticipated that the project will result in a number of positive outcomes in relation to climate change response in SEQ, including:

• Improved public health initiatives through understanding and managing impacts such as increased heat stress and vector-borne diseases;
• Improved public safety through emergency services being better prepared for extreme weather events and bushfires;
• Improved infrastructure planning and design through understanding potential future climate change impacts;
• Improved viability of agricultural and tourism activities through technologies and management systems to underpin early action on climate adaptation; and
• Improved ability of governments to better manage ecosystems and biodiversity through provision of climate change information and improved management tools.

Despite these ambitions, the authors recognise that regional climate change assessment alone is not sufficient to secure such outcomes. Assessment can aid in addressing knowledge gaps and creating incentives for the uptake of that knowledge by regional stakeholders in adaptation planning. Nevertheless, there are no guarantees. This is why explicit consideration of adaptive capacity in such assessments is of such vital importance, as the early identification of potential adaptation barriers and the development of strategies to overcome those barriers within adaptation planning is essential for facilitating the successful implementation of adaptation.

Conclusions

Vulnerability to climate change is comprised of a combination of exposure to climate change, sensitivity to those changes, and capacity to adapt and thus build resilience to climate change. However, past studies have predominately focused on assessments of exposure, rather than sensitivity or adaptive capacity. While recognising that climate change adaptation is best informed by an integrated research approach, the authors propose a participatory and transformative method to understand and enhance adaptive capacity. The authors recommend that the approach ought to include: (i) assessment of past adaptation options; (ii) conceptualisation of the climate change systems as perceived by various sectors (based on regional climate change projections); (iii) identification of key adaptive capacity attributes; (iv) analysis of adaptive capacity; and (v) design of strategies to enhance adaptive capacity. The application of this approach is currently the focus of an integrated assessment in SEQ, where population growth pressures are likely to exacerbate climate change impacts. It is anticipated that the outcomes from the participatory and transformative method would help to assist disaster and trauma managers cope with future climate changes.

Acknowledgements

This project has been funded by the CSIRO Collaboration Fund; Queensland Innovation Projects Fund (National and International Research Alliances Program); the Australian Department of Climate Change; University of the Sunshine Coast; Griffith University; and the University of Queensland.

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