Many climate change adaptation scholars recognise the complexities in the governance of adaptation. Most have used the concept of ‘barriers to adaptation’ in an attempt to describe why governance of adaptation is challenging. However, these studies have recently been critiqued for over simplifying complex governance processes by referring to the static concept of barriers, thereby ignoring dynamic complexity as a root explanatory cause. This paper builds the argument that how barriers are currently used in the literature is insufficient to explain why the governance of adaptation often proves difficult. We adopt a so-called mechanism-based approach to investigate how and why the governance of ecosystem-based adaptation (EbA) reaches impasses in five cases in Thailand and the Netherlands. Our findings show six causal mechanisms that explain impasses in the five case studies: (1) frame polarisation, (2) timing synchronisation, (3) risk innovation, (4) rules of the game, (5) veto players and (6) lost in translation. Several of these causal mechanisms are recurring and emerge under specific contextual conditions or are activated by other mechanisms. Our findings provide valuable insights into the impasses in the governance of EbA and allow for critical reflections on the analytical value of the mechanism-based approach in explaining why the governance of adaptation proves difficult and how this can be overcome.
For the past two decades, the need to shield strategic maritime interests, to tackle criminality and terrorism at or from the sea and to conserve valuable marine resources has been recognized at the highest political level. Acknowledging and accounting for the interplay between climate change, the vulnerability of coastal populations and the occurrence of maritime criminality should be part of any ocean governance process. Still, given the complex interactions between climate change and socio-economic components of the marine realm, it has become urgent to establish a solid methodological framework, which could lead to sound and effective decisions. We propose that any such framework should not be built from scratch. The adaptation of well tested, existing uncertainty-management tools, such as Cumulative Effect Assessments, could serve as a solid basis to account for the magnitude and directionality of the dependencies between the impacts of climate change and the occurrence of maritime criminality, offering spatial explicit risk evaluations. Multi-Criteria Decision Making could then be employed to better and faster inform decision-makers. These mechanisms could provide a framework for comparison of alternative mitigation and adaptation actions and are essential in assessing responses to tackle maritime crime in the context of climate change.
The role of traditional fishing institutions appears, paradoxically, to be waning despite scientific support and rhetoric about the value of fishers’ involvement in local marine management. Relational data of fishers have been used in this paper as a lens through which to explore the status of their participation in Marine Protected Area (MPA) management and to identify structural and contextual barriers to participation. Fieldwork was carried out during 2013–2015 in Cabo de Palos-Islas Hormigas MPA (CPH-MPA) using a mixed method approach involving the collection and analysis of data from institutional surveys and community meetings. The analysis shows that the fishers’ self-perception of having low influence in decision-making is consistent with the perception towards fishers of the wider social system. Several barriers and constraints to participation in CPH-MPA management are identified. The inefficient structure of the information exchange network further explained fishers’ feelings of distrust and marginalisation regarding decision-making. Understanding how structural barriers make it difficult to set in motion a collective learning process – necessary for an efficient decision-making process – breaks new ground for the design of interventions. Recommendations include clarifying the scope for participation in an appropriate institutional setting and careful consideration of the space in which dialogue takes place in order to integrate diverse knowledge and to acknowledge differential power relations.
Analysis of coastal climate change adaptation requires combining environmental and resource economics with other disciplines. Sea level rise, ocean warming and acidification, and increased storminess threaten to alter or intensify biophysical coastal changes. Communities respond in ways that neither maximize total economic value nor apply the appropriate spatial scale of policy response. Focusing on coastline change, particularly in North Carolina, we synthesize modeling approaches and empirical studies to identify research that is needed to support coastal climate adaptation policy. Modeling coastlines as coupled human–natural systems explains historical patterns of coastline change, clarifies the need for empirical estimates, and provides a roadmap for interdisciplinary policy analysis. Despite the extensive literature on coastal amenities, hazards, and ex post policy evaluation, more empirical information is needed to parameterize coupled models of complex coastal environments facing climate change. Extending coupled models of coastal adaptation to incorporate spatial dynamics and market and nonmarket values highlights fundamental problems with current governance structures. We conclude that to maximize total economic value in the coastal zone, adaptation will require governance coordination across multiple levels, attention to intensive and extensive margins of adaptation, and trade-offs across market and nonmarket values. These findings echo recent advances in fisheries bioeconomics.
To minimize the impacts of climate change on human wellbeing, governments, development agencies, and civil society organizations have made substantial investments in improving people’s capacity to adapt to change. Yet to date, these investments have tended to focus on a very narrow understanding of adaptive capacity. Here, we propose an approach to build adaptive capacity across five domains: the assets that people can draw upon in times of need; the flexibility to change strategies; the ability to organize and act collectively; learning to recognize and respond to change; and the agency to determine whether to change or not.
This paper describes a probabilistic approach for mapping of coastal flood hazards associated with sea-level rise and storm intensification toward the end of the 21st century. Under the Representative Concentration Pathway (RCP) 8.5, the Coupled Model Intercomparison Project Phase 5 (CMIP5) predicts a 0.6-m ensemble mean of sea-level rise for the Central Pacific from the 1986–2005 to 2081–2100 epochs. Fifty downscaling simulations of the 2080–2099 period from the CMIP5 NCAR-CCSM4 model produce 2492 hurricanes around the Hawaiian Islands. In comparison with a control dataset for the 1980–1999 period, the simulated future hurricanes show a slight increase in number and a northward shift of the tracks toward the Hawaiian Islands. There are 627 hurricanes in the 2080–2099 dataset with potential impact on Oahu, and the top 24 storms selected by wind speed at the urban Honolulu coast define a scenario set for inundation mapping. A suite of spectral wave, circulation, and Boussinesq models in a nested grid system describes generation and propagation of surge and waves across the ocean as well as wave setup and runup at the coast. The interoperable package includes phase-averaged and phase-resolving processes to determine the coastal flood hazards over a range of spatial and temporal scales during a hurricane event. Since the simulated dataset corresponds to a quasi 1000-year period, barring the tail end of the distribution, the suite of inundation scenarios enables definition of flood hazard maps with return periods of up to 500 years or annual exceedance probabilities of 0.2% or greater for climate change adaptation.
Coastal erosion is a worldwide problem, so accurate knowledge of the factors involved in the shoreline evolution is of great importance. This study analysed three gravel beaches that were nourished with sand from the same source. However, the evolution of their shoreline was different in each case. For its analysis, different factors were studied such as the shoreline and cross-shore profile evolution, the maritime climate, sedimentology and mineralogy. From the results, it should be noted that Centro beach is the most stable with a loss of surface after the first regeneration of 12.8%, while Carrer de mar is the most instable with a loss of 20.9%. The Posidonia oceanica meadow is one of the factors that make Centro beach the most stable despite being the one that receives the most wave energy. Another factor is its mineralogy and more specifically the composition of the particles that form the sample. Thus, it is observed how the cracking or the formation of particles by different minerals with a fragile union, are factors that make the beaches behave differently against erosion. For this reason, it is concluded that in order for the shoreline to be as stable as possible over time, a previous study of the sediment to be used for nourishment is necessary, as well as its possible effect on the ecosystem, since the future shoreline evolution will depend on it.
Coastal communities around the world face challenges in planning for coastal flooding and sea-level rise related to climate change. This paper develops an approach for identifying typologies of communities on the basis of their hazard vulnerability characteristics. The approach first characterizes communities with a suite of vulnerability indicators, selected to meet criteria of breadth, relevance, and data requirements. Cluster analysis is then applied to the indicator profiles to identify groups of similar communities. The statistical centrotype of each group represents the corresponding community type. A new community from outside the original set can then be matched to the typology using a Hazard Vulnerability Similarity Index (HVSI). The approach is demonstrated with a case study of 50 communities on Canada's Pacific coast. Results yielded 10 community types, of which four were predominant. The types range from highly urbanized, wealthier, diverse central cities to remote, resource-dependent towns with semi-developed, flat coastlines. Three selected communities from a distant region, in Atlantic Canada, were then successfully matched to the most similar of these 10 types. Identifying groups of communities that share vulnerability profiles can facilitate sharing knowledge, lessons, and resources that are most relevant to local efforts to reduce natural hazard risk. This support may be especially valuable for connecting communities that are unfamiliar with one another, yet similarly vulnerable.
Evaluating progress towards environmental sustainability goals can be difficult due to a lack of measurable benchmarks and insufficient or uncertain data. Marine settings are particularly challenging, as stakeholders and objectives tend to be less well defined and ecosystem components have high natural variability and are difficult to observe directly. Fuzzy logic expert systems are useful analytical frameworks to evaluate such systems, and we develop such a model here to formally evaluate progress towards sustainability targets based on diverse sets of indicators. Evaluation criteria include recent (since policy enactment) and historical (from earliest known state) change, type of indicators (state, benefit, pressure, response), time span and spatial scope, and the suitability of an indicator in reflecting progress toward a specific objective. A key aspect of the framework is that all assumptions are transparent and modifiable to fit different social and ecological contexts. We test the method by evaluating progress towards four Aichi Biodiversity Targets in Canadian oceans, including quantitative progress scores, information gaps, and the sensitivity of results to model and data assumptions. For Canadian marine systems, national protection plans and biodiversity awareness show good progress, but species and ecosystem states overall do not show strong improvement. Well-defined goals are vital for successful policy implementation, as ambiguity allows for conflicting potential indicators, which in natural systems increases uncertainty in progress evaluations. Importantly, our framework can be easily adapted to assess progress towards policy goals with different themes, globally or in specific regions.
Although tourism destination governance has been a subject of academic enquiry for some time now, in practice, governance is still a challenge for many tourism destinations around the world. Adaptive co-management (ACM) is a dynamic approach to governance whereby institutional arrangements and ecological knowledge are continually revised through a process of ‘learning-by-doing’. Founded on the active participation and collaboration of diverse stakeholder groups, ACM has been used extensively in the governance of natural resource contexts and so may offer valuable synergies for tourism governance; particularly the governance of tourism in protected areas. This review paper presents a critical review and synthesis of the ACM literature, identifying synergies and opportunities for enhancing tourism governance practices in protected area contexts through an ACM approach. A conceptual framework is developed from the review that identifies principles, stages, variables and expected outcomes of the ACM approach. Future research directions for ACM in tourism are proposed that incorporate governance, social learning and multi-stakeholder engagement.