- 1Department of Geography and Environmental Management, Faculty of Environment, University of Waterloo, Waterloo, ON, Canada
- 2School of Planning, Faculty of Environment, University of Waterloo, Waterloo, ON, Canada
We live in a world of constant change, where multiple factors that generate vulnerability coincide, such as pandemics, climate change, and globalization, among other political and societal concerns. This demands the development of approaches capable of dealing with diverse sources of vulnerability and strategies that enable us to plan for and mitigate harm in the face of uncertainty. Our paper shows that the interpretation and conception that one gives to vulnerability in climate change can influence how decision-making solutions and adaptation measures are proposed and adopted. In this context, our approach integrates contextual vulnerability and decision-making planning tools to bolster the capacity to adapt at a local scale. We link our analysis to the evolution of vulnerability in climate change studies and some core articles and decisions on climate change adaptation and capacity building under the United Nations Framework Convention on Climate Change (UNFCCC) and the Conference of Parties throughout this study.
1 Introduction
The concept of vulnerability is relevant to research in several disciplinary fields, including areas such as political economy, natural hazards, food security, public health, and environmental change, for describing states of susceptibility to harm (Blaikie et al., 1994; Cutter, 1996; Adger, 2006; Smit and Wandel, 2006; Barnett, 2020). However, the treatment of the term “vulnerability” in climate change has been notoriously ambiguous. Understanding of the term has evolved as our understanding of the causes and complex feedback mechanisms associated with the impact of climate change has developed. Therefore, different epistemological orientations have influenced the term's use, giving rise to varying interpretations of vulnerability and ways in which it has been approached over time (Kelly and Adger, 2000; Füssel, 2007; Klein and Möhner, 2011).
This paper highlights that in a world full of constant and rapid changes, there is a pressing need to bolster the capacity of complex social-ecological systems to anticipate and respond to diverse adverse climate change-related exposure, political-economy relations and other societal concerns that generate vulnerability (Folke et al., 2002; Engle, 2011; Whitney et al., 2017; Cinner et al., 2018). In this study, we integrate contextual vulnerability with decision-making planning tools as a means intended to increase the capacity to adapt locally in light of diverse sources of exposure. This paper is divided into four sections. Section 2 outlines vulnerability due to climate change viewed from different perspectives, including the dimensions of outcome and contextual vulnerabilities. Based on these insights, we show how we integrate contextual vulnerability with some decision-making planning tools in Section 3. Section 4 shows the conclusions of this paper.
2 Notion of vulnerability in climate change interventions
Frequently, researchers define the term “vulnerability” as the “susceptibility of a system to adverse effects” or its “capacity to be wounded” (Turner et al., 2003; Ford and Smit, 2004; Füssel, 2007). However, the conceptualization of vulnerability in climate-change studies depends on the lens through which it is viewed and assessed (Ford and Smit, 2004; Eakin and Luers, 2006; Füssel, 2007). The word “vulnerability” means different things in different discourses (O'Brien et al., 2004a, 2007; Füssel, 2010). Therefore, the term's ambiguity has led to its indistinct use and triggered numerous diagnoses and cures regarding the climate-change problem (O'Brien et al., 2004a), influenced, among various circumstances, by theories on lack of entitlements and natural hazards (Sen, 1981; Turner et al., 2003; Adger, 2006; Füssel and Klein, 2006).
2.1 Vulnerability viewed through a risk-hazard perspective
Often, climate change has been understood and conceived as a scientific and technical problem in the scientific community. The risk-hazard research tradition has influenced assessments of climate change and continues to do so. This research tradition describes the hazard of a system of analysis as a dose-response relationship between an external hazard and its consequences for the system (Adger, 2006; Füssel, 2007; Tonmoy et al., 2014). This approach represents the classic conceptualization of vulnerability in engineering science, focusing on the physical elements of exposure and hazard impacts in terms of magnitude, rapidity of onset, duration, and frequency (Schröter et al., 2005; Füssel, 2007; McLaughlin and Dietz, 2008; Shitangsu, 2014). This view represents the most basic form in which climate-change discussions treat climate-change impacts at the onset of the problem through climate model projections. Influenced by Article 2 of UNFCCC, which calls on countries to reduce their greenhouse gas emissions to avoid dangerous anthropogenic interference in the climate system, adaptation was considered a defeatist option that climate-change negotiators did not accept at the time, as support for adaptation implied recognizing that mitigation would be insufficient to address climate change (Oppenheimer, 2005; Pielke et al., 2007; Schipper et al., 2020). Adaptation was absent in the global policy discourse. Therefore, climate-change assessments were focused primarily on the projected impacts of external factors of change on a system (Thomas et al., 2019).
As a result of a robust mitigation-oriented view, much of the discussion surrounding vulnerability has relied on “climate-change impact assessments,” through the use of greenhouse gas (GHG) scenarios and climate models derived from global circulation models (GCM) (Downing, 2003; O'Brien et al., 2004b; Ford et al., 2010). This linear interpretation of vulnerability has given rise to one group of vulnerability assessments of climate change, which the risk-hazard school of thought influences. It projects potential future conditions and assumes adaptations to estimate damages, ignoring internal characteristics that vary from place to place. The underlying point of this view is that it considers vulnerability as the residual impacts of climate change after speculating upon some adaptation measures (Dessai et al., 2004; Brooks et al., 2005; Eakin and Luers, 2006; Smit and Wandel, 2006; Prno et al., 2011). Commonly, this interpretation of vulnerability follows a sequence of steps beginning with GHG scenarios and climate projections, to estimate possible future impacts quantitatively, monetarily, or in terms of biophysical change. Then, it assumes some adaptation options aimed at reducing the adverse effects of climate change. Vulnerability is the last stage of this series of analyses (the end state of a system of interest) (Smit and Pilifosova, 2003; O'Brien et al., 2004a). In other words, vulnerability is the result of the projected net impacts of climate change on a system, offset by assuming adaptation options. Under this view of vulnerability autonomous adaptation options are undertaken in response to experiencing some climate-condition changes—i.e., one individual adopts some standalone adaptation options in response to experiencing some changing conditions in the environment. Essentially, the main focus and starting point of this view of vulnerability is the stimulus, i.e., the net impacts of climate change derived from climate-change scenarios (Brooks, 2003; Smit and Pilifosova, 2003). This linear way of thinking represents the classical approach to vulnerability, inherited from the initial Intergovernmental Panel on Climate Change (IPCC) guidelines and initial reports from the ceased United Nations Disaster Relief Office (UNDRO) to assess vulnerability (Burton et al., 2002; Cardona, 2004; Füssel and Klein, 2006; Thomas et al., 2019). Therefore, this approach has been particularly important in comprehending the potential impacts of climate change and raising public and political awareness of the adverse effects of climate change (Cardona, 2004; Ford and Smit, 2004).
Influenced by climate-change negotiations, the “first generation of vulnerability assessments” has been used for purposes such as meeting Article 2 of the UNFCCC, particularly when referring to the phrase “dangerous interference” (Smit et al., 2000; Burton et al., 2002), and to meet decision 11/CP.1, which divided adaptation work into three stages. Stage 1 was to carry out impact assessments to identify possible impacts of climate change and potentially vulnerable countries and regions (Adger et al., 2003; Burton, 2003; Füssel, 2004). In this context, the first-generation vulnerability assessments, which the literature also calls impact assessments (Smit and Pilifosova, 2003), outcome vulnerability assessments (O'Brien et al., 2007), top-down approaches (Dessai and Hulme, 2004), endpoint assessments (Kelly and Adger, 2000), or biophysical vulnerability assessments (Brooks, 2003), have played a significant role not only in meeting the objectives of the UNFCCC and resolutions under its auspices but also in generating the first IPCC reports, the first National Communications on Climate Change, the first Biennial Update Reports (BURs), and early research efforts in this field.
With this background, we note that climate-change vulnerability assessments have given considerable attention to the mismatch between the scale of GCMs and the local scale (Fowler et al., 2007). The use of climate models and scenarios derived from GCM, through statistical analysis and historical data, forecasts the potential effects of climate change on different scales. This linear form of approaching vulnerability locates the causality in climate hazards and not nearly enough on the social causation of vulnerability despite that they are both causal and have causes (Wisner, 1976; Wisner et al., 2003; Ribot, 2014). Systemic risks induced by climate change (e.g., the collapse of the local economy of a system of analysis due to diminishing agricultural production or diminishing tourism revenues) can trigger a cascade of detrimental effects on a system of analysis on social, ecological, political, and economic levels (Li et al., 2021). Therefore, vulnerability, defined as the projected impacts of external stressors on the exposed system of analysis, becomes one diagnosis rather than a way of identifying specific and actual vulnerability factors in systems of concern (Turner et al., 2003). In this context, it is significant that this technocratic view and rigid risk-hazard perspectives are shifting as our understanding of global dynamics and interactions evolves. Examples of this paradigm shift can be found, for instance, in the 5th assessment report (AR5) of the IPCC Working Group 2. AR5 is primarily focused on climate-related risks, taking into consideration human and natural systems and the Sendai Framework for Disaster Risk Reduction (SFDRR), a human-based approach rather than merely a technocratic view focused on risk reduction (Schipper et al., 2014; Räsänen et al., 2016; Busayo et al., 2020). Although still criticized from a political-economy perspective, these frameworks enable the integration of risk-hazard perspectives into climate change adaptation more coherently. In particular, the SFDRR's approach stresses the importance of vulnerability dimensions, disaster risk governance and stakeholders' participation in measures, strategies, and policy development during risk management processes (Lee and Chen, 2019; Matsuoka and Gonzales Rocha, 2021). As such, the SFDRR's approach has provided a platform to explore and integrate relationships and synergies between disaster risk reduction, climate change adaptation and other societal concerns at diverse levels and sectors in more depth, hand in hand with other significant frameworks, including the Sustainable Development Goals, the Paris Agreement (PA), and the New Urban Agenda (Wisner, 2020).
2.2 Vulnerability viewed through a social constructivism perspective
In contrast to impact assessments, climate change alone does not determine decision-making in current climate-change vulnerability studies. The social constructivism school of thought has influenced contemporary climate-change vulnerability assessments. The rationale of this research tradition is that social stressors (internal conditions) (e.g., vested interests, institutional factors, governance structures, unequal access to property and resources, corruption and nepotism, elite interests, marginalization, power relations, and other socio-economic and political factors) also determine the state of a system of analysis (Turner et al., 2003; Ford and Smit, 2004; Wisner et al., 2003; Füssel, 2005, 2007; Schröter et al., 2005; Füssel and Klein, 2006; Tonmoy et al., 2014; Pearse, 2016; Arifeen and Eriksen, 2019; Barnett, 2020; Mikulewicz, 2020; Scoville-Simonds et al., 2020; Eriksen et al., 2021).
This interpretation of vulnerability incorporates human dimensions and food-security studies have widely used it to explain the implications of both physical and socioeconomic circumstances in unfolding famines (Wisner, 1976; Sen, 1981; Watts and Bohle, 1993; Downing, 2003; Füssel, 2005). This rationale draws on the “wounded soldier perspective”, in which pre-existing pressures (existing wound), rather than the effects of future external factors alone (future attacks), determine vulnerability (Kelly and Adger, 2000). The etymological foundations of this analogy link “vulnerability” with the Latin vulnerabilis, describing the state of an injured soldier on a battlefield, implying an army already at risk and vulnerable, regardless of a future attack (Kelly and Adger, 2000). This view of vulnerability contends that both climate and non-climate factors, not just external factors, can harm a system of analysis (Tschakert et al., 2013; Thomas et al., 2019; Eriksen et al., 2021). From this perspective, vulnerability is the starting point of the analysis rather than a sequence of steps. It is the result of the interaction of multidimensional factors spanning multiple scales and levels, from global to local, including both internal conditions (e.g., social, political, economic, environmental, institutional, urban and demographic) and external conditions (e.g., climatic and market conditions) (Neil Adger, 1999; Kelly and Adger, 2000; Smit and Pilifosova, 2003; O'Brien et al., 2004a; Eakin and Luers, 2006; Ford et al., 2006a,b; Garschagen and Romero-Lankao, 2015; Räsänen et al., 2016; Constable, 2017; Thomas et al., 2019).
This generation of climate-change vulnerability assessments is one of the applications used for meeting Article 4.4 of the UNFCCC, which commits developed countries to assist developing countries (particularly those most vulnerable to the adverse effects of climate change) in meeting the costs of adaptation (Füssel, 2004). The lack of specificity of Article 4.8 of the UNFCCC (i.e., potentially sensitive places) has appeared, from the perspective of developing countries, as an opportunity to get international funds and, from the developed countries' perspective, as a way to identify vulnerable locations for assigning resources. Commonly referred to as “second-generation vulnerability assessments,” the literature variously identifies these as vulnerability assessments (Smit and Pilifosova, 2003), contextual vulnerability assessments (O'Brien et al., 2007), bottom-up approaches (Dessai and Hulme, 2004), starting-point assessments (Kelly and Adger, 2000), and social vulnerability assessments (Brooks, 2003). This generation of climate-change vulnerability assessments has played and does play a significant role in the development of recent IPCC Assessment Reports, contemporary National Communications on Climate Change Reports, Biennial Update Reports, National Adaptation Programmes of Action (NAPAs), National Adaptations Plans (NAPs), Nationally Determined Contributions (NDCs), and current research efforts in the field.
2.3 Embracing contextual vulnerability interventions
Although numerous vulnerability interventions have attempted to measure vulnerability across different sectors of interest, remembering that it is a theoretical concept that reflects a dynamic state, not an outcome, is crucial (Adger, 2006). The contextual approach to vulnerability assessment often identifies indicator-based approaches as the dominant method of measuring vulnerability to determine and prioritize vulnerable areas and groups (Eriksen and Kelly, 2007). In doing so, indicator-based approaches often seek to operationalize vulnerability by combining socioeconomic and biophysical data to then aggregate them into an overall measure to quantify vulnerability (Tonmoy et al., 2014; Gaworek-Michalczenia et al., 2022). The construction of these indicators has often followed the relationship: Vulnerability = Exposure + Sensitivity – Adaptive capacity. However, while the policy arena has valued the use of the vulnerability-indices arena because it enables a straightforward interpretation of the results of indices, allowing the synthesis of complex relationships into numeric results that facilitate rapid decision-making (Hinkel, 2011), intense criticism has confronted indicator-based approaches' methods and calculations. Much of this criticism arises because they do not capture the specific socio-political economy relations that generate vulnerability in complex social–ecological systems, and the selection and creation of indices depend heavily on the availability of physical and socioeconomic data variables, generally gathered from national censuses or national and international datasets (Brooks et al., 2005; Klein and Möhner, 2011; El-Zein and Tonmoy, 2015; Eriksen et al., 2021).
We refer to vulnerability more accurately in terms of assessment than measurements (Leichenko and O'Brien, 2002; Downing, 2003; Hinkel, 2011; Nguyen et al., 2016). The term “vulnerability” refers to particularly vulnerable situations (Brooks, 2003). This means that it does not presume variables. It seeks to identify empirically the different underlying conditions driving vulnerability in one system of analysis regardless their geneses (Belliveau et al., 2006; Fazey et al., 2010; Ford et al., 2010; Hopkins, 2015; McCubbin et al., 2015). Exploring the root causes of vulnerability and possible adaptation measures requires context-specific and cultural-specific investigations (Mills-Novoa, 2023). Decisive action in one place may lead to maladaptation or reinforce power relationships in another place or other groups (Eriksen et al., 2015, 2021; Antwi-Agyei et al., 2018; Work et al., 2019). This can be observed, for instance, in Victoria del Portete, a local community in Ecuador where adaptation interventions intended to provide irrigation systems ultimately only benefitted those with the financial resources to replace broken pipes, leaving the poorest within the association without access to the project (Mills-Novoa, 2023).
Any system of concern involves different social, institutional, environmental, cultural, and political-economy conditions, which can vary significantly from place to place, regardless of their closeness (Turner et al., 2003; Ford et al., 2008; Nightingale, 2017). As such, the ability of vulnerability assessments to capture the climate-society dynamics of a particular system of concern decreases as distance increases (Thomas et al., 2019). Assuming a relation of behaviors and features across locations will inevitably lead to wrong decisions. Therefore, if vulnerability interventions aim to extrapolate outcomes from nearby areas, they will not capture the specific variables and the dynamics that make people vulnerable (Atteridge and Remling, 2018). Mindful of such constraints, many scholars in this context employ ethnographic techniques such as semistructured interviews, focus groups, participant observation, walking transects, seasonal calendars, climate diaries, and hazard mapping, considering the local experience from the beginning of the research to prevent inconsistencies and biased outcomes (Schröter et al., 2005; Belliveau et al., 2006; Ford et al., 2008; van Aalst et al., 2008; Pearce et al., 2009; Fazey et al., 2010; Hopkins, 2015; McCubbin et al., 2015; Mills-Novoa, 2023).
3 Contextual vulnerability and decision-making planning tools
Bearing in mind that within a new architecture of climate governance under the PA, the global adaptation goal centers on enhancing adaptive capacity, strengthening resilience and reducing vulnerability to climate change, with a view to contributing to sustainable development (see Article 7 of PA). We argue that if we integrate the planning tools and strategies (described below) to address the specific underlying sources of vulnerability in a system of interest, these strategies serve as means to enhance adaptive capacity at a local scale.
3.1 No-regrets adaptation options
Political instability often influences systems of analysis, particularly in developing countries where political positions are variable in the short term, and political disputes might render previous decisions invalid (Helmke, 2020; Warsame et al., 2022; Asfaw et al., 2023). Although it is not considered to be transformational or the best option for strengthening the capacity of a system to adapt, the “no-regrets” adaptation option is a method worth mentioning for decision-making in such a scenario. This approach involves actions thought wise regardless of climate change, which, if implemented, improve the adaptive capacity of a system of analysis in light of climate-change effects (Dessai and Hulme, 2007; Hallegatte, 2009). Significantly, no-regret actions can reduce the “adaptation deficit”—also called “development deficit” and “wounded soldier” (i.e., minimize exploitation, raise prices on primary goods, allow access to markets and to representation and rights for all ethnic and religious groups, abolish racial hierarchies, patriarchy norms and skewed cultural norms, diminish job and education segregation, protect water resources, and enhance the public health system among other societal concerns) (Táíwò, 2022), underlying issues and sources of vulnerability in developing countries usually identified after carrying out contextual vulnerability assessments.
3.2 Climate-change mainstreaming
Climate change and development concerns have often been dealt with separately, creating a gap between development agendas and local realities (Adam, 2015; Smucker et al., 2015). Evidence shows that adaptive capacity and adaptation strategies are linked to different societal concerns and factors of vulnerability, usually stemming from underdevelopment, including such social demands as electricity and water supply, access to adequate public health services, better purchasing power, access to quality education, and infrastructure and technology improvement (Smit and Pilifosova, 2003; Agrawala, 2004; Ayers et al., 2014; Milman and Arsano, 2014; Abrahams and Carr, 2017; Robinson, 2019; Braunschweiger and Pütz, 2021; Kundo et al., 2021). Therefore, analyzing climate change and development separately not only increases vulnerability but also has the potential to generate ineffective responses to tackling the underlying factors that make people vulnerable (maladaptation) (Antwi-Agyei et al., 2018). There is broad agreement that current problems, such as climate change or novel pandemics such as the 2019 novel coronavirus or COVID-19, can potentially worsen present socioeconomic factors and needs that make people vulnerable, a priori. Therefore, development is and has been the primary concern [see decision 2/CP.17; (2011)], and the best form of adaptation is in places that still face issues related to underdevelopment (Milman and Arsano, 2014; Robinson, 2019; Schipper et al., 2020). Mainstreaming adaptation into development enables formulating long-lasting actions across various sectors, by including climate-change issues and development priorities (underlying drivers of vulnerability) together. Therefore, separating progress and responses to climate change makes no sense, bearing in mind that Article 4.1(f) of the UNFCCC call countries to include climate change adaptation into their development programs and that the majority of international financial cooperation destines to support development in developing countries (Smit and Pilifosova, 2003; Ayers et al., 2014; Milman and Arsano, 2014).
This method of creating policy coherence allows the inclusion of climate-vulnerability concerns in ongoing decision-making structures at various scales, and eliminates unnecessary double efforts and conflicts between priorities and strategies (Agrawala, 2004; Ayers et al., 2014; Rauken et al., 2015). For example, initiating such development programs as climate-smart agriculture indirectly encourages concrete adaptation actions and monitoring processes. Using the Pru District in Ghana as an empirical case, Ahenkan et al. (2021) show that through Mobile Weather Alert Messaging training, farmers can learn to use their mobiles phones to obtain daily weather forecasts. This gives them insight into when to plant their crops and when not to, thus increasing their productivity.
In the agriculture sector, a vital area for many developing countries, mainstreaming allows the inclusion of development and climate-change concerns in decision-making policies (e.g., through subsidies). Mainstreaming influences farmers to choose crop varieties better adapted to drier or more saline conditions, considering the prospect of damages and losses. The cost of a sudden reduction in agricultural production could be devastating for a local community in terms of economic or food security, for both the short and the long term. These unexpected events not only create environmental damage but also exacerbate poverty and other social problems, due to the high dependency of countries considered vulnerable to climate change on climate-dependent sectors (e.g., agriculture and livestock, fisheries, tourism). In that regard, the incorporation of adaptation into development policies in the agriculture sector, through the implementation of subsidies for seed that is more tolerant of drier conditions, could decrease damages and losses from drought. Sorghum bicolor, for example, is a climate-smart crop that is widely grown throughout the world, particularly in Africa (Pixley et al., 2023). We must bear in mind that Article 8 of the PA formalizes Loss and Damage within the climate regime. This Article calls on countries to avert, minimize and address loss and damage associated with the adverse effects of climate change in vulnerable developing countries [see, also, decision 2/CP.19 regarding the Warsaw International Mechanism for Loss and Damage; (2013)].
Although some adaptation interventions may seem highly successful initially, after project closures, local actions and strategies intended to foster the adaptive capacity of a system have uncertain futures (Mills-Novoa, 2023). Therefore, mainstreaming is a vital planning tool for creating a coherent umbrella of policies to bridge adaptation and ongoing development efforts across different sectors and levels (horizontally and vertically). Given that the causes of vulnerability of one system of analysis are location-specific, mainstreaming is an approach that contributes to ensuring that development efforts aim at reducing the root causes of vulnerability and, therefore, achieve actual tangible adaptation measures aimed at building adaptive capacity. This mainstreaming has been referred to as “mainstreaming plus,” a vulnerability-based focus rather than a technology-based view, known as a “mainstreaming minimum” (Ayers et al., 2014). Mainstreaming plus aims to incorporate specific drivers of the vulnerability of a system of analysis into ongoing decisions on development in short and medium timeframes, particularly significant in countries characterized by political instability, where the political will and direction can change on short (or no) notice. This can be observed, for instance, in Latin America, where around 15 Presidents from different countries in the region (including Honduras, Bolivia, Ecuador, Peru, Paraguay, Brazil, and Argentina, among others) have been overthrown or forced to end their presidential mandates due to impeachments through parliaments, economic crises, civil protests, and social riots in the last 20 years (Helmke, 2020).
3.3 Adaptation pathways
Similarly, we deem “adaptation pathways” (AP) to be another planning approach, the features of which might contribute to the adaptive capacity of socio-ecological systems at a local scale if they incorporate specific drivers of the vulnerability into the analysis. Following the analogy that Mitchell (2019) uses, any road will take one to a destination if one is unsure about where to go. AP provides different pathways, each of which uses different strategies, to achieve a common desired future (Haasnoot et al., 2019). Central to AP is the identification of tipping points (Haasnoot et al., 2013, 2019). To achieve this, possible trajectories are set, which can change direction depending on defined tipping points (Barnett et al., 2014; Wise et al., 2014). Using the language of Haasnoot et al. (2013), in a manner similar to a metro map, the AP presents different alternative routes to get to the same desired point in the future. If an action no longer meets one specific criterion (tipping point or terminal station), a new action becomes necessary (transfer to a new station or a new action); therefore, decision-makers can change to an AP (Haasnoot et al., 2013). The exact date of a tipping point is not rigid; it might be reached within 30, 40, or 50 years, or more, which enables decision-makers to adjust measures as events unfold (Haasnoot et al., 2013). Developed initially in infrastructure projects, to recognize the influence of sea-level rise (Thames 2100 Project/The Thames Barrier), the AP approach helped decision-makers to identify a set of possible adaptation pathways (or, in Haasnoot et al.'s language, different routes), each with specific measures and thresholds (or, using Haasnoot et al.'s language, terminal stations). Decision-makers can switch directions (or, using Haasnoot et al.'s words, transfer to a new station) if tipping points are reached, depending on the water-level rise to keep the risk low (Ranger et al., 2013). We argue that this approach is significant in systems at the local level, with the capacity to positively transform common-pool resources management. For example, if the desired future is to avoid saltwater intrusion in a common-pool livelihood (an underlying factor of vulnerability identified in a contextual vulnerability assessment), and one path encounters difficulties impossible to overcome (tipping points such as a sea level rise of 30 centimeters), decision-makers can switch from that route to another (e.g., a path on which the tipping point is a sea-level rise of 1 meter) to achieve the same desired future (Figure 1) (Barnett et al., 2014; Wise et al., 2014). An example of the adoption of adaptation pathways for sea-level rise is the Delta Programme in the Netherlands. This is a low-lying, country prone to flooding, and the implementation of an adaptation path approach has enabled decision-makers to incorporate uncertainty pertaining to the future by considering climatic and social developments in decision-making structures (Bloemen et al., 2019). The Delta Programme applies different measures across different time frames, with the aim of protecting the country in case of extreme weather events and providing sufficient freshwater until 2050 and 2100 (Restemeyer et al., 2017; Bloemen et al., 2019). Another example of the application of adaptation pathways for sea-level rise can be found in Lakes Entrance, Australia, a coastal town in eastern Victoria where the conception of adaptation pathways has enabled decision-makers to work at the community level (Barnett et al., 2014). The approach applies different paths and actions across diverse timeframes ranging from immediate low-cost actions (e.g., stringent controls over new developments) to actions that other generations should determine as future adaptation pathways as other socio-ecological circumstances unfold (Barnett et al., 2014).
Figure 1. Adaptation pathways. The blue arrow indicates different Pathways to achieve a desired future (e.g., avoid saltwater intrusion in a common-pool livelihood). The red arrow indicates the tipping points (thresholds) set for each path (e.g., Pathway 1: a sea-level rise of 30 centimeters, Pathway 2: a sea-level rise of 1 meter and Pathway 3: a sea-level rise of 1.5 meters). If sea level rise reaches the tipping points (thresholds) set for each path, moving to a new alternative (Pathway) is necessary. Often, Pathway 1 starts with planned actions focused on a short time frame vision, including policy-making measures and the construction of natural structures such as mangroves. In contrast, Pathway 2 and Pathway 3 focus on planned strategies in more extended time frames, including dune constructions and the relocation of critical infrastructure (Barnett et al., 2014). The materialization of planned actions designed for each Pathway can be considered good tipping points (e.g., Pathway 1: construction of natural structures such as mangroves).
3.4 Scenario planning
Similarly, we deem “Scenario Planning” (SP) to be another planning approach, the features of which might contribute to the adaptive capacity of socio-ecological systems at a local scale if they incorporate specific drivers of the vulnerability into the analysis. SP enables the incorporation of uncertainty about future conditions into decisions, in extended time frames (Rounsevell and Metzger, 2010; Star et al., 2016). Initially developed for military and business purposes and explored in depth by the Royal Dutch Shell oil company for strategic planning (a “what if” planning approach) (Schoemaker and van der Heijden, 1993; Rounsevell and Metzger, 2010; Star et al., 2016). SP is an approach that identifies specific drivers of vulnerability to explore how they likely might unfold in the future (Haasnoot et al., 2013; Wise et al., 2014). Significantly, SP provides a framework that entertains a vision of multiple long-term potential futures (Figure 2), allowing us to think more about anticipatory measures than reactive ones and providing a foundation for discussions of policy development and adaptive strategies (Rounsevell and Metzger, 2010; Cairns et al., 2013; Haasnoot et al., 2013; Wise et al., 2014; Star et al., 2016). SP has often been used primarily for large-scale strategic business planning, where the causes of change are relatively well-known and can be selected by following broad categories. Examples include the STEEP approach—Social, Technological, Economic, Environmental, and Policy Governance, developed by Metzger et al. (2010) and shown in Rounsevell and Metzger (2010)—or the drivers used to show Shared socioeconomic pathways (SSPs), discussed by O'Neill et al. (2014). Yet, we believe that SP has the potential to enable decision-makers and planners to assess and estimate more closely the implications of current context-specific factors of vulnerability so that a system seeks a desirable future and avoids adverse ones (Rounsevell and Metzger, 2010; Haasnoot et al., 2013; Wise et al., 2014). An example of the adoption of SP can be found in Baan Talae Nok, a coastal community in Thailand that has been shifting away from traditional livelihoods (e.g., fisheries) toward new livelihoods, including tourism and agriculture (Bennett et al., 2015). SP has enabled decision-makers to prioritize local actions and desirable future scenarios for livelihoods in Baan Talae Nok and the community's environment. These desirable future scenarios include adequate infrastructure for tourism, better community water and risk management, healthy habitats, forests and mangrove areas managed by the community, productive agriculture areas, and reduced coastal erosion, among others (Bennett et al., 2015).
Figure 2. Scenario planning (SP). SP is a planning tool that creates images of potential futures under uncertainty and complexity (Star et al., 2016; Serrao-Neumann et al., 2019). Blue circles indicate multiple potential long-term futures. Data and insights used to construct these possible scenarios should include, among other information, local priorities, information from contextual vulnerability assessments, and desirable future scenarios from community stakeholders through participatory approaches. Although the future is uncertain, SP provides decision-makers a way to plan actions and be better prepared. Integrating SP with recent computational intelligence techniques, like machine and deep learning, can help decision-makers handle uncertainties and achieve more accurate outcomes.
3.5 Collaborative governance
Bolstering the capacity of a system to adapt at the local scale requires addressing the multiple sources of vulnerability, affecting various sectors alike (e.g., agriculture, health, energy, tourism, and food security) (Bullock et al., 2022). Today, the extent of sources of vulnerability can affect various livelihoods and alter the socio-economic dynamics of different productive sectors together (i.e., systemic risks). For example, in the Galapagos Islands in Ecuador, climate variability, in combination with the adverse effects of COVID-19, has affected the archipelago's tourism sector. This has prompted a cascade of negative consequences on the other sectors of the islands, including fishing and conservation (Escobar-Camacho et al., 2021; Cáceres et al., 2022; Viteri Mejía et al., 2022). Systemic risks triggered in the tourism, fishing, and conservation sectors included a disruption of food supply, the closure of national borders, the prohibition of all national and international tourist arrivals, drastic changes in consumer demands, the closure of restaurants, and requests to use banned fishing techniques (e.g., longlining), among others (Cáceres et al., 2022; Viteri Mejía et al., 2022; Castrejón et al., 2024).
Contrary to the conceptualization of government that refers to elected people at different levels or to the various governmental institutions responsible for delivering goods and services to people in a society, collaborative governance facilitates multilevel participation beyond the state, involving in decision-making the public sector, the private sector, and civil society, from local to broader scales (Kooiman, 2003a; Mitchell, 2019). Following Kooiman's (2003b) work, collaborative governance involves the totality of interactions, in which the whole range of institutions, networks, and linkages that are part of decision-making processes, including formal and informal actors, public and private actors, non-governmental organizations (NGOs), Local and Indigenous peoples, interest groups, and corporations, participate in solving societal problems and in creating societal opportunities (Kooiman, 2003a; Lemos and Agrawal, 2006; Armitage et al., 2009; Keskitalo, 2009; Plummer and Armitage, 2010; Mitchell, 2019).
Even though not all civil society represents society and governance systems tend to be marked by participation disputes and power relations, we argue that how governments, local users and civil society in general address societal problems is crucial in responding to vulnerability factors (Thomas et al., 2019; Mudaliar, 2020). Actors formulate innovative solutions on many geographical and administrative scales, such as within local communities, at subnational levels, and among business sectors, advocacy groups, and private companies, which generates different niches of knowledge and expertise (Ostrom, 2010; Tran et al., 2020). Therefore, participants in collaborative governance have the advantage of learning from others (Ostrom, 2010; Bullock et al., 2022). For example, Local and Indigenous peoples have a close relationship with their environment that allows them to see and feel what the scientific community or decision-making structures usually cannot capture and from whom there is much to learn (Zurba et al., 2018; Bullock et al., 2022, 2023). They are on the front lines of change and know first-hand the dynamics that make a particular place vulnerable (Zurba et al., 2018; Mehta et al., 2019; Eriksen et al., 2021; Bullock et al., 2022). This relationship with the environment has enabled them to have linkages in multiple sectors, including farming, fisheries, tourism, and forestry (Nilsson et al., 2012; Leonard et al., 2013; Ford et al., 2020; Bullock et al., 2022). Consistent with Article 7.5 of PA (2015), the latter considerations are central features in building adaptive capacity at a local scale. In particular, if we keep in mind double-loop learning, change that points to correcting errors by adjusting behaviors and attitudes rather than correcting mistakes by adjusting resource management strategies and actions, e.g., modifying harvesting techniques (single-loop learning) (Armitage et al., 2007, 2008).
Among the different strands of collaborative decision-making (e.g., participatory appraisal and integrated conservation), we argue that co-management is one of the leading management strategies that formalize linkages among local resource stakeholders and governments to share management rights and responsibilities (Armitage et al., 2007). Usually defined as a power-sharing approach, co-management gives rise to cross-sectoral interactions. Therefore, collaborative and power-sharing links across sectors under a co-management context, including partnerships with multilevel stakeholders groups, allow the understanding of local vulnerability and traditional values, the development of shared actions, redistribution of rights and responsibilities, and a co-production of knowledge, adding fundamental considerations to reduce vulnerability and bolster the governance systems capacity to adapt at the local level (Armitage et al., 2007, 2011; Plummer and Armitage, 2007; Plummer, 2013; Andrachuk et al., 2019; Zurba et al., 2022).
4 Conclusion
While the possible adaptation strategies to climate change are numerous in the literature, they often fail to capture the underlying nature of sources of vulnerability, making them insufficient to bolster the adaptive capacity at a local scale. This paper shows that the interpretation and understanding that one gives to vulnerability can lead to diverse adaptation measures and likely ill decisions. Therefore, we remark on the importance of consolidating vulnerability as a dynamic and unmeasurable concept often embedded in political economy matters to capture underlying sources of exposure. Adaptation and vulnerability to climate change are subject to grants, political visibility aspirations, and power relations involving actors with specific interests and agendas. Therefore, we echo the claims by Eriksen et al. (2021), who showed that a limited understanding of contextual vulnerability dimensions, including socio-political relations, might lead to exacerbating, reallocating, or creating new sources of vulnerability.
Our study contributes to the growing vulnerability and climate change adaptation literature. This contribution integrates contextual vulnerability with decision-making planning tools to foster the capacity to adapt and improve decision-making processes on a local scale. We apply context-specific perspectives with different planning horizons at a local scale, a geographical and administrative scale that often lacks the necessary tools, as occurs in developing countries. Our approach shows a series of planning strategies, which, if they rely on political economy factors and other societal concerns that shape people's vulnerabilities, are powerful planning tools that might guide practitioners to work at a local scale. Notably, with the rapid changes and uncertainties within social-ecological systems driven by complex factors, all strategies and decisions must deal with uncertainty. Thus, our approach incorporates flexibility into decision-making and provides scholars and policymakers with avenues to plan in the face of uncertainty.
Notably, the insights presented throughout this paper may help practitioners and decision-makers decentralize adaptation programs often conceived from top-down approaches and institutions with power, authority, and control over decision-making regarding natural resources, including solutions for climate change vulnerability and adaptation agendas. Within the contemporary research on climate change, decentralizing and downsizing the scale of adaptation programs are critical to depoliticizing the programs and approximating decision-making processes and policy-making solutions—shifting closer to the actual sources of vulnerability at the local scale—including socio-political causes of vulnerability and other societal concerns.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Author contributions
RC: Conceptualization, Validation, Visualization, Writing—original draft, Writing—review & editing. JW: Supervision, Writing—review & editing. JP: Funding acquisition, Supervision, Writing—review & editing. PD: Supervision, Writing—review & editing.
Funding
The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This project was supported by funding provided by the University of Waterloo through a Graduate Research Studentship (GRS), the Inter-American Institute for Global Change Research (grant number SGP-HW 017), and the National Secretary of Higher Education, Science, Technology and Innovation (SENESCYT) through a scholarship under the Top World Universities 2016 program.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
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References
Abrahams, D., and Carr, E. R. (2017). Understanding the connections between climate change and conflict: contributions from geography and political ecology. Curr. Clim. Chang. Rep. 3, 233–242. doi: 10.1007/s40641-017-0080-z
Adam, H. N. (2015). Mainstreaming adaptation in India – the Mahatma Gandhi National Rural Employment Guarantee Act and climate change. Clim. Dev. 7, 142–152. doi: 10.1080/17565529.2014.934772
Adger, W. N. (2006). Vulnerability. Glob. Environ. Chang. 16, 268–281. doi: 10.1016/j.gloenvcha.2006.02.006
Adger, W. N., Huq, S., Brown, K., Conway, D., and Hulme, M. (2003). Adaptation to climate change in the developing world. Prog. Dev. Stud. 3, 179–195. doi: 10.1191/1464993403ps060oa
Agrawala, S. (2004). Adaptation, development assistance and planning: challenges and opportunities. IDS Bull. 35, 50–54. doi: 10.1111/j.1759-5436.2004.tb00134.x
Ahenkan, A., Chutab, D. N., and Boon, E. K. (2021). Mainstreaming climate change adaptation into pro-poor development initiatives: evidence from local economic development programmes in Ghana. Clim. Dev. 13, 603–615. doi: 10.1080/17565529.2020.1844611
Andrachuk, M., Armitage, D., Hoang, H. D., and Van Le, N. (2019). A network perspective on spatially clustered territorial use rights for fishers (TURFs) in Vietnam. Coast. Manag. 47, 292–311. doi: 10.1080/08920753.2019.1596677
Antwi-Agyei, P., Dougill, A. J., Stringer, L. C., and Codjoe, S. N. A. (2018). Adaptation opportunities and maladaptive outcomes in climate vulnerability hotspots of northern Ghana. Clim. Risk Manag. 19, 83–93. doi: 10.1016/j.crm.2017.11.003
Arifeen, A., and Eriksen, S. (2019). The politics of disaster vulnerability: flooding, post-disaster interventions and water governance in Baltistan, Pakistan. Environ. Plan. E Nat. Space 3, 1137–1157. doi: 10.1177/2514848619880899
Armitage, D., Berkes, F., Dale, A., Kocho-Schellenberg, E., and Patton, E. (2011). Co-management and the co-production of knowledge: learning to adapt in Canada's Arctic. Glob. Environ. Change 21, 995–1004. doi: 10.1016/j.gloenvcha.2011.04.006
Armitage, D., Berkes, F., and Doubleday, N. (2007). Adaptive Co-management: Collaboration, Learning and Multi-level Governance. Vancouver, BC: UBC Press.
Armitage, D., Marschke, M., and Plummer, R. (2008). Adaptive co-management and the paradox of learning. Glob. Environ. Chang. 18, 86–98. doi: 10.1016/j.gloenvcha.2007.07.002
Armitage, D. R., Plummer, R., Berkes, F., Arthur, R. I., Charles, A. T., Davidson-Hunt, I. J., et al. (2009). Adaptive co-management for social–ecological complexity. Front. Ecol. Environ. 7, 95–102. doi: 10.1890/070089
Asfaw, M., Abddisa, F., Gobena, A. G., Bekele, Y., and Bekele, T. (2023). Do climate change and political instability affect crop production in sub-Saharan Africa countries? J. Agric. Food Res. 12:100576. doi: 10.1016/j.jafr.2023.100576
Atteridge, A., and Remling, E. (2018). Is adaptation reducing vulnerability or redistributing it? WIREs Clim. Change 9:e500. doi: 10.1002/wcc.500
Ayers, J., Huq, S. M., Faisal, A., and Tanveer Hussain, S. (2014). Mainstreaming climate change adaptation into development: A case study of Bangladesh. Clim. Dev. 6, 293–305. doi: 10.1080/17565529.2014.977761
Barnett, J. (2020). Global environmental change II: political economies of vulnerability to climate change. Prog. Hum. Geogr. 44, 1172–1184. doi: 10.1177/0309132519898254
Barnett, J., Graham, S., Mortreux, C., Fincher, R., Waters, E., and Hurlimann, A. (2014). A local coastal adaptation pathway. Nat. Clim. Change 4:1103. doi: 10.1038/nclimate2383
Belliveau, S., Smit, B., and Bradshaw, B. (2006). Multiple exposures and dynamic vulnerability: evidence from the grape industry in the Okanagan Valley, Canada. Glob. Environ. Chang. 16, 364–378. doi: 10.1016/j.gloenvcha.2006.03.003
Bennett, N., Kadfak, A., and Dearden, P. (2015). Community-based scenario planning: a process for vulnerability analysis and adaptation planning to social–ecological change in coastal communities. Environ. Dev. Sustain. 18, 1771–1799. doi: 10.1007/s10668-015-9707-1
Blaikie, P., Cannon, T., Davis, I., and Wisner, B. (1994). At Risk: Natural Hazards, People Vulnerability and Disasters, 1st Edn.
Bloemen, P., Van Der Steen, M., and Van Der Wal, Z. (2019). Designing a century ahead: climate change adaptation in the Dutch Delta. Policy Soc. 38, 58–76. doi: 10.1080/14494035.2018.1513731
Braunschweiger, D., and Pütz, M. (2021). Climate adaptation in practice: how mainstreaming strategies matter for policy integration. Environ. Policy Gov. 31, 361–373. doi: 10.1002/eet.1936
Brooks, N. (2003). Vulnerability, Risk and Adaptation: A Conceptual Framework. Norwich: Tyndall Centre for Climate Change Research.
Brooks, N., Neil Adger, W., and Mick Kelly, P. (2005). The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation. Glob. Environ. Chang. 15, 151–163. doi: 10.1016/j.gloenvcha.2004.12.006
Bullock, R., Zurba, M., Reed, M. G., and McCarthy, D. (2023). Strategic options for more effective indigenous participation in collaborative environmental governance. J. Plan. Educ. Res. 43, 841–856. doi: 10.1177/0739456X20920913
Bullock, R. C. L., Diduck, A., Luedee, J., and Zurba, M. (2022). Integrating social learning, adaptive capacity and climate adaptation for regional scale analysis: a conceptual framework. Environ. Manage. 69, 1217–1230. doi: 10.1007/s00267-022-01630-x
Burton, I. (2003). “Do We Have the Adaptive Capacity to Develop and Use the Adaptive Capacity to Adapt?,” in Climate Change, Adaptive Capacity and Development, eds J. B. Smith, R. J. T. Klein, and S. Huq (London: Imperial College Press), 137–161. doi: 10.1142/9781860945816_0007
Burton, I., Huq, S., Lim, B., Pilifosova, O., and Schipper, E. L. (2002). From impacts assessment to adaptation priorities: the shaping of adaptation policy. Clim. Policy 2, 145–159. doi: 10.3763/cpol.2002.0217
Busayo, E. T., Kalumba, A. M., Afuye, G. A., Ekundayo, O. Y., and Orimoloye, I. R. (2020). Assessment of the Sendai framework for disaster risk reduction studies since 2015. Int. J. Disaster Risk Reduct. 50:101906. doi: 10.1016/j.ijdrr.2020.101906
Cáceres, R., Pittman, J., Castrejón, M., and Deadman, P. (2022). The evolution of polycentric governance in the galapagos small-scale fishing sector. Environ. Manage. 70, 254–272. doi: 10.1007/s00267-022-01666-z
Cairns, G., Ahmed, I., Mullett, J., and Wright, G. (2013). Scenario method and stakeholder engagement: critical reflections on a climate change scenarios case study. Technol. Forecast. Soc. Change 80, 1–10. doi: 10.1016/j.techfore.2012.08.005
Cardona, O. (2004). The Need for Rethinking the Concepts of Vulnerability and Risk From a Holistic Perspective: A Necessary Review and Criticism for Effective Risk Management. London: Earthscan Publishers.
Castrejón, M., Pittman, J., Miño, C., Ramírez-González, J., Viteri, C., Moity, N., et al. (2024). The impact of the COVID-19 pandemic on the Galapagos Islands' seafood system from consumers' perspectives. Sci. Rep. 14:1690. doi: 10.1038/s41598-024-52247-5
Cinner, J. E., Adger, W. N., Allison, E. H., Barnes, M. L., Brown, K., Cohen, P. J., et al. (2018). Building adaptive capacity to climate change in tropical coastal communities. Nat. Clim. Change 8, 117–123. doi: 10.1038/s41558-017-0065-x
Constable, A. L. (2017). Climate change and migration in the Pacific: options for Tuvalu and the Marshall Islands. Reg. Environ. Chang. 17, 1029–1038. doi: 10.1007/s10113-016-1004-5
Cutter, S. L. (1996). Vulnerability to environmental hazards. Prog. Hum. Geogr. 20, 529–539. doi: 10.1177/030913259602000407
Dessai, S., Adger, W. N., Hulme, M., Turnpenny, J., Köhler, J., and Warren, R. (2004). Defining and experiencing dangerous climate change. Clim. Change 64, 11–25. doi: 10.1023/B:CLIM.0000024781.48904.45
Dessai, S., and Hulme, M. (2004). Does climate adaptation policy need probabilities? Clim. Policy 4, 107–128. doi: 10.1080/14693062.2004.9685515
Dessai, S., and Hulme, M. (2007). Assessing the robustness of adaptation decisions to climate change uncertainties: a case study on water resources management in the East of England. Glob. Environ. Chang. 17, 59–72. doi: 10.1016/j.gloenvcha.2006.11.005
Downing, T. (2003). “Lessons from famine early warning and food security for understanding adaptation to climate change: toward a vulnerability/adaptation science?,” in Climate Change, Adaptive Capacity and Development, eds J. B. Smith, R. J. T. Klein, and S. Huq (London: Imperial College Press), 71–100. doi: 10.1142/9781860945816_0005
Eakin, H., and Luers, A. L. (2006). Assessing the vulnerability of social-environmental systems. Annu. Rev. Environ. Resour. 31, 365–394. doi: 10.1146/annurev.energy.30.050504.144352
El-Zein, A., and Tonmoy, F. N. (2015). Assessment of vulnerability to climate change using a multi-criteria outranking approach with application to heat stress in Sydney. Ecol. Indic. 48, 207–217. doi: 10.1016/j.ecolind.2014.08.012
Engle, N. L. (2011). Adaptive capacity and its assessment. Glob. Environ. Chang. 21, 647–656. doi: 10.1016/j.gloenvcha.2011.01.019
Eriksen, S., Schipper, L., Scoville-Simonds, M., Vincent, K., Adam, H., Brooks, N., et al. (2021). Adaptation interventions and their effect on vulnerability in developing countries: help, hindrance or irrelevance? World Dev. 141:105383. doi: 10.1016/j.worlddev.2020.105383
Eriksen, S. H., and Kelly, P. M. (2007). Developing credible vulnerability indicators for climate adaptation policy assessment. Mitig. Adapt. Strateg. Glob. Chang. 12, 495–524. doi: 10.1007/s11027-006-3460-6
Eriksen, S. H., Nightingale, A. J., and Eakin, H. (2015). Reframing adaptation: the political nature of climate change adaptation. Glob. Environ. Chang. 35, 523–533. doi: 10.1016/j.gloenvcha.2015.09.014
Escobar-Camacho, D., Rosero, P., Castrejón, M., Mena, C. F., and Cuesta, F. (2021). Oceanic islands and climate: using a multi-criteria model of drivers of change to select key conservation areas in Galapagos. Reg. Environ. Chang. 21:47. doi: 10.1007/s10113-021-01768-0
Fazey, I., Kesby, M., Evely, A., Latham, I., Wagatora, D., Hagasua, J.-E., et al. (2010). A three-tiered approach to participatory vulnerability assessment in the Solomon Islands. Glob. Environ. Change 20, 713–728. doi: 10.1016/j.gloenvcha.2010.04.011
Folke, C., Colding, J., and Berkes, F. (2002). “Synthesis: building resilience and adaptive capacity in social–ecological systems,” in Navigating Social-Ecological Systems: Building Resilience for Complexity and Change, eds C. Folke, F. Berkes, and J. Colding (Cambridge: Cambridge University Press), 352–387.
Ford, J., Keskitalo, E. C., Smith, T., Pearce, T., Berrang-Ford, L., Duerden, F., et al. (2010). Case study and analogue methodologies in climate change vulnerability research. WIREs Clim. Chang. 1, 374–392. doi: 10.1002/wcc.48
Ford, J., Smit, B., and Wandel, J. (2006a). Vulnerability to climate change in the Arctic: a case study from Arctic Bay, Canada. Glob. Environ. Chang. 16, 145–160. doi: 10.1016/j.gloenvcha.2005.11.007
Ford, J., Smit, B., Wandel, J., Allurut, M., Shappa, K., Ittusarjuat, H., et al. (2008). Climate Change in the Arctic: Current and Future Vulnerability in Two INUIT Communities in Canada. London: The Royal Geographical Society. doi: 10.1111/j.1475-4959.2007.00249.x
Ford, J., Smit, B., Wandel, J., and MacDonald, J. (2006b). Vulnerability to Climate Change in Igloolik, Nunavut: What We Can Learn From the Past and Present. Cambridge: Cambridge University Press. doi: 10.1017/S0032247406005122
Ford, J. D., King, N., Galappaththi, E. K., Pearce, T., McDowell, G., and Harper, S. L. (2020). The resilience of indigenous peoples to environmental change. One Earth 2, 532–543. doi: 10.1016/j.oneear.2020.05.014
Ford, J. D., and Smit, B. (2004). A framework for assessing the vulnerability of communities in the canadian arctic to risks associated with climate change. Arctic 57, 325–454. doi: 10.14430/arctic516
Fowler, H. J., Blenkinsop, S., and Tebaldi, C. (2007). Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int. J. Climatol. 27, 1547–1578. doi: 10.1002/joc.1556
Füssel, H.-M. (2004). Coevolution of the Political and Conceptual Frameworks for Climate Change Vulnerability Assessments. Berlin: Potsdam and Oldenburg.
Füssel, H.-M. (2005). Vulnerability in Climate Change Research: A Comprehensive Conceptual Framework. UC Berkeley: University of California International and Area Studies.
Füssel, H.-M. (2007). Vulnerability: A generally applicable conceptual framework for climate change research. Glob. Environ. Chang. 17, 155–167. doi: 10.1016/j.gloenvcha.2006.05.002
Füssel, H.-M., and Klein, R. J. T. (2006). Climate change vulnerability assessments: an evolution of conceptual thinking. Clim Chang. 75, 301–329. doi: 10.1007/s10584-006-0329-3
Füssel, H. M. (2010). How inequitable is the global distribution of responsibility, capability, and vulnerability to climate change: a comprehensive indicator-based assessment. Glob Env. Chang. 20:9. doi: 10.1016/j.gloenvcha.2010.07.009
Garschagen, M., and Romero-Lankao, P. (2015). Exploring the relationships between urbanization trends and climate change vulnerability. Clim. Change 133, 37–52. doi: 10.1007/s10584-013-0812-6
Gaworek-Michalczenia, M. F., Sallu, S. M., Di Gregorio, M., Doggart, N., and Mbogo, J. (2022). Evaluating the impact of adaptation interventions on vulnerability and livelihood resilience. Clim. Dev. 14, 867–883. doi: 10.1080/17565529.2021.2018987
Haasnoot, M., Brown, S., Scussolini, P., Jimenez, J. A., Vafeidis, A. T., and Nicholls, R. J. (2019). Generic adaptation pathways for coastal archetypes under uncertain sea-level rise. Environ. Res. Commun. 1:71006. doi: 10.1088/2515-7620/ab1871
Haasnoot, M., Kwakkel, J. H., Walker, W. E., and ter Maat, J. (2013). Dynamic adaptive policy pathways: a method for crafting robust decisions for a deeply uncertain world. Glob. Environ. Change 23, 485–498. doi: 10.1016/j.gloenvcha.2012.12.006
Hallegatte, S. (2009). Strategies to adapt to an uncertain climate change. Glob. Environ. Change 19, 240–247. doi: 10.1016/j.gloenvcha.2008.12.003
Helmke, G. (2020). “Presidential crises in Latin America,” in The Politics of Institutional Weakness in Latin America, eds. D. M. Brinks, S. Levitsky, and M. V. Murillo (Cambridge: Cambridge University Press), 98–118.
Hinkel, J. (2011). “Indicators of vulnerability and adaptive capacity”: towards a clarification of the science–policy interface. Glob. Environ. Chang. 21, 198–208. doi: 10.1016/j.gloenvcha.2010.08.002
Hopkins, D. (2015). Applying a comprehensive contextual climate change vulnerability framework to New Zealand's tourism industry. Ambio 44, 110–120. doi: 10.1007/s13280-014-0525-8
Kelly, P. M., and Adger, W. N. (2000). Theory and practice in assessing vulnerability to climate change andfacilitating adaptation. Clim. Change 47, 325–352. doi: 10.1023/A:1005627828199
Keskitalo, E. C. H. (2009). Governance in vulnerability assessment: the role of globalising decision-making networks in determining local vulnerability and adaptive capacity. Mitig. Adapt. Strateg. Glob. Change 14, 185–201. doi: 10.1007/s11027-008-9159-0
Klein, R. J. T., and Möhner, A. (2011). The political dimension of vulnerability: implications for the green climate fund. IDS Bull. 42, 15–22. doi: 10.1111/j.1759-5436.2011.00218.x
Kooiman, J. (2003a). Governing as Governance. London: SAGE Publications Ltd. doi: 10.4135/9781446215012
Kundo, H., Brueckner, M., Spencer, R., and Davis, J. (2021). Mainstreaming climate adaptation into social protection: the issues yet to be addressed. J. Int. Dev. 33, 953–974. doi: 10.1002/jid.3567
Lee, H.-C., and Chen, H. (2019). Implementing the Sendai Framework for disaster risk reduction 2015–2030: disaster governance strategies for persons with disabilities in Taiwan. Int. J. Disaster Risk Reduct. 41:101284. doi: 10.1016/j.ijdrr.2019.101284
Leichenko, R. M., and O'Brien, K. L. (2002). The dynamics of rural vulnerability to clobal change: the case of southern Africa. Mitig. Adapt. Strateg. Glob. Change 7, 1–18. doi: 10.1023/A:1015860421954
Lemos, M. C., and Agrawal, A. (2006). Environmental governance. Annu. Rev. Environ. Resour. 31, 297–325. doi: 10.1146/annurev.energy.31.042605.135621
Leonard, S., Parsons, M., Olawsky, K., and Kofod, F. (2013). The role of culture and traditional knowledge in climate change adaptation: insights from East Kimberley, Australia. Glob. Environ. Change 23, 623–632. doi: 10.1016/j.gloenvcha.2013.02.012
Li, H.-M, Wang, X.-C., Zhao, X.-F., and Qi, Y. (2021). Understanding systemic risk induced by climate change. Adv. Clim. Change Res. 12, 384–394. doi: 10.1016/j.accre.2021.05.006
Matsuoka, Y., and Gonzales Rocha, E. (2021). The role of non-government stakeholders in implementing the Sendai Framework: a view from the voluntary commitments online platform. Prog. Disast. Sci. 9:100142. doi: 10.1016/j.pdisas.2021.100142
McCubbin, S., Smit, B., and Pearce, T. (2015). Where does climate fit? Vulnerability to climate change in the context of multiple stressors in Funafuti, Tuvalu. Glob. Environ. Change 30, 43–55. doi: 10.1016/j.gloenvcha.2014.10.007
McLaughlin, P., and Dietz, T. (2008). Structure, agency and environment: toward an integrated perspective on vulnerability. Glob. Environ. Change 18, 99–111. doi: 10.1016/j.gloenvcha.2007.05.003
Mehta, L., Srivastava, S., Adam, H. N., Alankar Bose, S., Ghosh, U., et al. (2019). Climate change and uncertainty from ‘above' and ‘below': perspectives from India. Reg. Environ. Change 19, 1533–1547. doi: 10.1007/s10113-019-01479-7
Metzger, M. J., Rounsevell, M. D. A., Van den Heiligenberg, H. A. R. M., Pérez-Soba, M., and Hardiman, P. S. (2010). How personal judgment influences scenario development. Ecol. Soc. 15. doi: 10.5751/ES-03305-150205
Mikulewicz, M. (2020). The discursive politics of adaptation to climate change. Ann. Am. Assoc. Geogr. 110, 1807–1830. doi: 10.1080/24694452.2020.1736981
Mills-Novoa, M. (2023). What happens after climate change adaptation projects end: a community-based approach to ex-post assessment of adaptation projects. Glob. Environ. Change 80:102655. doi: 10.1016/j.gloenvcha.2023.102655
Milman, A., and Arsano, Y. (2014). Climate adaptation and development: contradictions for human security in Gambella, Ethiopia. Glob. Environ. Change 29, 349–359. doi: 10.1016/j.gloenvcha.2013.11.017
Mudaliar, P. (2020). Polycentric to monocentric governance: power dynamics in Lake Victoria's fisheries. Environ. Policy Gov. 31, 1–14. doi: 10.1002/eet.1917
Neil Adger, W. (1999). Social vulnerability to climate change and extremes in coastal Vietnam. World Dev. 27, 249–269. doi: 10.1016/S0305-750X(98)00136-3
Nguyen, T. T. X., Bonetti, J., Rogers, K., and Woodroffe, C. D. (2016). Indicator-based assessment of climate-change impacts on coasts: a review of concepts, methodological approaches and vulnerability indices. Ocean Coast. Manag. 123, 18–43. doi: 10.1016/j.ocecoaman.2015.11.022
Nightingale, A. J. (2017). Power and politics in climate change adaptation efforts: struggles over authority and recognition in the context of political instability. Geoforum 84, 11–20. doi: 10.1016/j.geoforum.2017.05.011
Nilsson, A. E., Gerger Swartling, Å., and Eckerberg, K. (2012). Knowledge for local climate change adaptation in Sweden: challenges of multilevel governance. Local Environ. 17, 751–767. doi: 10.1080/13549839.2012.678316
O'Brien, K., Eriksen, S., Nygaard, L., and Schojolden, A. (2007). Why different interpretations of vulnerability matter in climate change discourses. Clim. Policy 7, 73–88. doi: 10.1080/14693062.2007.9685639
O'Brien, K., Eriksen, S., Schjolden, A., Nygaard, L., O'Brien, K., and Alfsen, K. (2004a). What's in a Word? Conflicting Interpretations of Vulnerability in Climate Change Research. Oslo: Center for International Climate and Environmental Research.
O'Brien, K., Leichenko, R., Kelkar, U., Venema, H., Aandahl, G., Tompkins, H., et al. (2004b). Mapping vulnerability to multiple stressors: climate change and globalization in India. Glob Env. Chang. 14, 303–313. doi: 10.1016/j.gloenvcha.2004.01.001
O'Neill, B. C., Kriegler, E., Riahi, K., Ebi, K. L., Hallegatte, S., Carter, T. R., et al. (2014). A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Clim. Change 122, 387–400. doi: 10.1007/s10584-013-0905-2
Oppenheimer, M. (2005). Defining dangerous anthropogenic interference: the role of science, the limits of science. Risk Anal. 25, 1399–1407. doi: 10.1111/j.1539-6924.2005.00687.x
Ostrom, E. (2010). Polycentric systems for coping with collective action and global environmental change. Glob. Environ. Change 20, 550–557. doi: 10.1016/j.gloenvcha.2010.07.004
Pearce, T. D., Ford, J. D., Laidler, G. J., Smit, B., Duerden, F., Allarut, M., et al. (2009). Community collaboration and climate change research in the Canadian Arctic. Polar Res. 28, 10–27. doi: 10.1111/j.1751-8369.2008.00094.x
Pearse, R. (2016). Gender and climate change. Wiley Interdiscip. Rev. Clim. Change 8:e451. doi: 10.1002/wcc.451
Pielke, R., Prins, G., Rayner, S., and Sarewitz, D. (2007). Lifting the taboo on adaptation. Nature 445, 597–598. doi: 10.1038/445597a
Pixley, K. V., Cairns, J. E., Lopez-Ridaura, S., Ojiewo, C. O., Dawud, M. A., Drabo, I., et al. (2023). Redesigning crop varieties to win the race between climate change and food security. Mol. Plant 16, 1590–1611. doi: 10.1016/j.molp.2023.09.003
Plummer, R. (2013). Can adaptive comanagement help to address the challenges of climate change adaptation? Ecol. Soc. 18, art2. doi: 10.5751/ES-05699-180402
Plummer, R., and Armitage, D. (2007). Charting the new territory of adaptive co-management. Ecol. Soc. 12. Available online at: http://www.jstor.org/stable/2626786
Plummer, R., and Armitage, D. (2010). Integrating Perspectives on Adaptive Capacity and Environmental Governance (Berlin: Springer Science & Business Media), 1–19. doi: 10.1007/978-3-642-12194-4_1
Prno, J., Bradshaw, B., Wandel, J., Pearce, T., Smit, B., and Tozer, L. (2011). Community vulnerability to climate change in the context of other exposure-sensitivities in Kugluktuk, Nunavut. Polar Res. 30:7363. doi: 10.3402/polar.v30i0.7363
Ranger, N., Reeder, T., and Lowe, J. (2013). Addressing ‘deep' uncertainty over long-term climate in major infrastructure projects: four innovations of the Thames Estuary 2100 Project. EURO J. Decis. Process. 1, 233–262. doi: 10.1007/s40070-013-0014-5
Räsänen, A., Juhola, S., Nygren, A., Käkönen, M., Kallio, M., Monge Monge, A., et al. (2016). Climate change, multiple stressors and human vulnerability: a systematic review. Reg. Environ. Chang. 16, 2291–2302. doi: 10.1007/s10113-016-0974-7
Rauken, T., Mydske, P. K., and Winsvold, M. (2015). Mainstreaming climate change adaptation at the local level. Local Environ. 20, 408–423. doi: 10.1080/13549839.2014.880412
Restemeyer, B., van den Brink, M., and Woltjer, J. (2017). Between adaptability and the urge to control: making long-term water policies in the Netherlands. J. Environ. Plan. Manag. 60, 920–940. doi: 10.1080/09640568.2016.1189403
Ribot, J. (2014). Cause and response: vulnerability and climate in the anthropocene. J. Peasant Stud. 41, 667–705. doi: 10.1080/03066150.2014.894911
Robinson, S. (2019). Mainstreaming climate change adaptation in small island developing states. Clim. Dev. 11, 47–59. doi: 10.1080/17565529.2017.1410086
Rounsevell, M. D. A., and Metzger, M. J. (2010). Developing qualitative scenario storylines for environmental change assessment. Wiley Interdiscip. Rev. Clim. Change 1, 606–619. doi: 10.1002/wcc.63
Schipper, E. L. F., Tanner, T., Dube, O. P., Adams, K. M., and Huq, S. (2020). The debate: is global development adapting to climate change? World Dev. Perspect. 18:100205. doi: 10.1016/j.wdp.2020.100205
Schipper, L., Thomalla, F., Vulturius, G., Johnson, K., and Klein, R. (2014). Climate Change and Disaster Risk Reduction. Stockholm: Stockholm Environment Institute.
Schoemaker, P., and van der Heijden, A. J. M. (1993). Strategic planning at Royal Dutch/Shell. Strateg. Chang. 2, 157–171. doi: 10.1002/jsc.4240020307
Schröter, D., Polsky, C., and Patt, A. G. (2005). Assessing vulnerabilities to the effects of global change: an eight step approach. Mitig. Adapt. Strateg. Glob. Change 10, 573–595. doi: 10.1007/s11027-005-6135-9
Scoville-Simonds, M., Jamali, H., and Hufty, M. (2020). The hazards of mainstreaming: climate change adaptation politics in three dimensions. World Dev. 125:104683. doi: 10.1016/j.worlddev.2019.104683
Sen, A. (1981). Poverty and Famines: An Essay on Entitlement and Deprivation. Oxford: Clarendon Press. Available online at: http://www.amazon.com/Poverty-Famines-Essay-Entitlement-Deprivation/dp/0198284632/ref=sr_1_1?s=books%5Candie=UTF8%5Candqid=1310678684%5Candsr=1-1
Serrao-Neumann, S., Schuch, G., Cox, M., and Low Choy, D. (2019). Scenario planning for climate change adaptation for natural resource management: insights from the Australian East Coast Cluster. Ecosyst. Serv. 38:100967. doi: 10.1016/j.ecoser.2019.100967
Shitangsu, P. (2014). Vulnerability concepts and its application in various fields: a review on geographical perspective. J. Life Earth Sci. 8:20150. doi: 10.3329/jles.v8i0.20150
Smit, B., Burton, I., Klein, R. J. T., and Wandel, J. (2000). An anatomy of adaptation to climate change and variability. Clim. Change 45, 223–251. doi: 10.1023/A:1005661622966
Smit, B., and Pilifosova, O. (2003). “From adaptation to adaptive capacity and vulnerability reduction,” in Climate Change, Adaptive Capacity and Development, eds J. B. Smith, R. J. T. Klein, and S. Huq (London: Imperial College Press), 9–28. doi: 10.1142/9781860945816_0002
Smit, B., and Wandel, J. (2006). Adaptation, adaptive capacity and vulnerability. Glob. Environ. Change 16, 282–292. doi: 10.1016/j.gloenvcha.2006.03.008
Smucker, T. A., Wisner, B., Mascarenhas, A., Munishi, P., Wangui, E. E., Sinha, G., et al. (2015). Differentiated livelihoods, local institutions, and the adaptation imperative: assessing climate change adaptation policy in Tanzania. Geoforum 59, 39–50. doi: 10.1016/j.geoforum.2014.11.018
Star, J., Rowland, E. L., Black, M. E., Enquist, C. A. F., Garfin, G., Hoffman, C. H., et al. (2016). Supporting adaptation decisions through scenario planning: enabling the effective use of multiple methods. Clim. Risk Manag. 13, 88–94. doi: 10.1016/j.crm.2016.08.001
Thomas, K., Hardy, D., Lazrus, H., Mendez, M., Orlove, B., Rivera-Collazo, I., et al. (2019). Explaining differential vulnerability to climate change: a social science review. Wiley Interdiscip. Rev. Clim. Change 10:e565. doi: 10.1002/wcc.565
Tonmoy, F. N., El-Zein, A., and Hinkel, J. (2014). Assessment of vulnerability to climate change using indicators: a meta-analysis of the literature. Wiley Interdiscip. Rev. Clim. Change 5, 775–792. doi: 10.1002/wcc.314
Tran, T. A., Pittock, J., and Tran, D. D. (2020). Adaptive flood governance in the Vietnamese Mekong Delta: a policy innovation of the North Vam Nao scheme, An Giang Province. Environ. Sci. Policy 108, 45–55. doi: 10.1016/j.envsci.2020.03.004
Tschakert, P., van Oort, B., St. Clair, A. L., and LaMadrid, A. (2013). Inequality and transformation analyses: a complementary lens for addressing vulnerability to climate change. Clim. Dev. 5, 340–350. doi: 10.1080/17565529.2013.828583
Turner, B. L., Kasperson, R. E., Matson, P. A., McCarthy, J. J., Corell, R. W., Christensen, L., et al. (2003). A framework for vulnerability analysis in sustainability science. Proc. Natl. Acad. Sci. U. S. A. 100, 8074–8079. doi: 10.1073/pnas.1231335100
van Aalst, M. K., Cannon, T., and Burton, I. (2008). Community level adaptation to climate change: the potential role of participatory community risk assessment. Glob. Environ. Change 18, 165–179. doi: 10.1016/j.gloenvcha.2007.06.002
Viteri Mejía, C., Rodríguez, G., Tanner, M. K., Ramírez-González, J., Moity, N., Andrade, S., et al. (2022). Fishing during the “new normality”: social and economic changes in Galapagos small-scale fisheries due to the COVID-19 pandemic. Marit. Stud. 21, 193–208. doi: 10.1007/s40152-022-00268-z
Warsame, A. A., Sheik-Ali, I. A., Jama, O. M., Hassan, A. A., and Barre, G. M. (2022). Assessing the effects of climate change and political instability on sorghum production: empirical evidence from Somalia. J. Clean. Prod. 360:131893. doi: 10.1016/j.jclepro.2022.131893
Watts, M., and Bohle, H.-G. (1993). The space of vulnerability: the causal structure of hunger and famine. Prog. Hum. Geogr. 17, 43–67. doi: 10.1177/030913259301700103
Whitney, C. K., Bennett, N. J., Ban, N. C., Allison, E. H., Armitage, D., Blythe, J. L., et al. (2017). Adaptive capacity: from assessment to action in coastal social-ecological systems. Resil. Alliance. 22. doi: 10.31230/osf.io/sxcb9
Wise, R. M., Fazey, I., Stafford Smith, M., Park, S. E., Eakin, H. C., Archer Van Garderen, E. R. M., et al. (2014). Reconceptualising adaptation to climate change as part of pathways of change and response. Glob. Environ. Chang. 28, 325–336. doi: 10.1016/j.gloenvcha.2013.12.002
Wisner, B. (1976). Man-Made Famine in Eastern Kenya: The Interrelationship of Environment and Development. Institute of Development Studies, University of Sussex. Available online at: https://books.google.com.ec/books?id=JrgJAQAAIAAJ
Wisner, B. (2020). Five years beyond sendai—can we get beyond frameworks? Int. J. Disaster Risk Sci. 11, 239–249. doi: 10.1007/s13753-020-00263-0
Wisner, B., Blaikie, P., Cannon, T., and Davis, I. (2003). At Risk: Natural Hazards. Routledge Abingdon.
Work, C., Rong, V., Song, D., and Scheidel, A. (2019). Maladaptation and development as usual? Investigating climate change mitigation and adaptation projects in Cambodia. Clim. Policy 19, S47–S62. doi: 10.1080/14693062.2018.1527677
Zurba, M., Maclean, K., Woodward, E., and Islam, D. (2018). Amplifying Indigenous community participation in place-based research through boundary work. Prog. Hum. Geogr. 43, 1020–1043. doi: 10.1177/0309132518807758
Zurba, M., Petriello, M. A., Madge, C., McCarney, P., Bishop, B., McBeth, S., et al. (2022). Learning from knowledge co-production research and practice in the twenty-first century: global lessons and what they mean for collaborative research in Nunatsiavut. Sustain. Sci. 17, 449–467. doi: 10.1007/s11625-021-00996-x
Keywords: adaptive capacity, planning tools, vulnerability, climate change, adaptation
Citation: Cáceres R, Wandel J, Pittman J and Deadman P (2024) Insights intended to improve adaptation planning and reduce vulnerability at the local scale. Front. Clim. 6:1345921. doi: 10.3389/fclim.2024.1345921
Received: 28 November 2023; Accepted: 12 February 2024;
Published: 28 February 2024.
Edited by:
Bao-Jie He, Chongqing University, ChinaReviewed by:
Alex O. Awiti, World Agroforestry Centre, KenyaMercy J. Borbor-Cordova, ESPOL Polytechnic University, Ecuador
Copyright © 2024 Cáceres, Wandel, Pittman and Deadman. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Renato Cáceres, r2cacere@uwaterloo.ca