Ecological Indicators 125 (2021) 107527 Contents lists available at ScienceDirect Ecological Indicators journal homepage: www.elsevier.com/locate/ecolind Turning the wheel away from biophysical indicators in coastal zone management: Towards a stakeholder-based systemic framework David J. Smith *, Beatriz Rodríguez-Labajos Autonomous University of Barcelona (UAB), Edifici ICTA-ICP, Carrer de les Columnes s/n, Campus de la UAB, 08193, 08193 Cerdanyola del Vallès, Barcelona, Spain A R T I C L E I N F O A B S T R A C T Keywords: Coastal zone management is a pressing matter, especially in developing countries, which are highly vulnerable to Indicators the effects of climate change. Human systems are underrepresented in the vast array of indicators aimed at Systemic assisting coastal zone management decisions. Clearly, there is room to better capture natural and human system Coastal zones relationships and interactions in coastal area assessments. A case in point is the well-known Coastal Hazard Climate change Monitoring Wheel (CHW). Hence three main objectives guide this paper: (i) Analysing the existing set of indicator themes Coastal zone management and categories in coastal areas; (ii) Contrasting this set of indicators with the perceived needs of local coastal Framework stakeholders from a developing country; and (iii) Proposing indicator categories to be included as part of a Quadruple helix stakeholders systemic coastal zone management framework. To this end, we undertook an automated content analysis of 1116 peer-reviewed articles on the subject matter. The analysis and a stringent set of criteria led to 40 articles that were reviewed to identify suitable indicators. In parallel, field research in Ghana allowed for a set of indicators from the quadruple helix stakeholders operating in coastal zones to be elicited. Contrasting the two sets of in­ dicators resulted in three situations. The first involves 14 indicator categories that co-occur in the literature and the detected needs from local coastal stakeholders. In the second situation, the categories mentioned in the literature were those not mentioned at local level. A third situation appeared when the local coastal stakeholders mentioned categories of indicators that were not identified in the reviewed literature. After examining each case, we advocate for the indicators in the first situation to be incorporated into the current coastal indicator moni­ toring frameworks (for example by upgrading the CHW). The unique contribution of this paper is the combi­ nation of literature and stakeholder-based indicator sub-categories that should be added to the current set of coastal monitoring frameworks. 1. Introduction accelerated sea-level rise and extreme weather events (Stronkhorst et al., 2018). More than half of the world’s population live up to 200 km inland Coastal areas are consequently progressively affected by climate from the coastline, a number that is set to double by 2025 (Inácio et al., change (Appelquist and Balstrøm, 2015; Appelquist and Halsnæs, 2015; 2018; Micallef et al., 2018). This stands to reason as coastal zones Kronen et al., 2010; Zhu et al., 2010). The disruptive impacts are contain the most productive habitats around the globe (Eriksen and particularly challenging for developing countries where planning in Silva, 2009) adding to the attraction for human settlement taking coastal development is often lacking (Wong et al., 2014). Further com­ advantage of livelihood opportunities in these areas (Barragán and de pounding this issue, coastal migration has largely taken place in flood Andrés, 2015). and cyclone-prone areas exacerbating the impacts from climate change However, the latest report from the Intergovernmental Panel on (de Sherbinin et al., 2011). Climate Change (IPCC) suggests that the global mean sea level rise is Natural and human systems in coastal areas are extensively entwined accelerating (Oppenheimer et al., 2019). Moreover, non-climatic as paired socio-ecological systems, yet they are often measured sepa­ anthropogenic drivers –including rapid urbanisation in coastal areas rately (Stojanovic et al., 2016). Typically, the natural systems of coastal and growth of megacities are adding to the pressure on coastal com­ areas include ecosystems and detailed biophysical attributes (Wong munities. Specifically with regards to exposure and vulnerability to the et al., 2014). Meanwhile, the human systems encompass the built * Corresponding author. E-mail addresses: david.smith@weandb.org (D.J. Smith), Beatriz.Rodriguez@uab.cat (B. Rodríguez-Labajos). https://doi.org/10.1016/j.ecolind.2021.107527 Received 7 August 2020; Received in revised form 15 January 2021; Accepted 10 February 2021 Available online 2 March 2021 1470-160X/© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). D.J. Smith and B. Rodríguez-Labajos Ecological Indicators 125 (2021) 107527 environment, economic activities (e.g., tourism, aquaculture, fisheries) Table 1 and the formal and informal institutions that organize human activities Indicator frameworks, models and approaches in coastal areas. (e.g., policies, laws, customs, norms, and culture). Focus Framework/model/approach Reference These human systems are critical as they drive many of the impacts Social Community Wellbeing index Buot and Cardenas (both environmental and social) and the changes that are seen at the (CWBi) (2016) local level in coastal areas. The drivers for these human systems involve Multi-dimensional Poverty Index Alkire and Santos a combination of social, economic, and institutional factors including (MPI) (2010) taxes and subsidies, aesthetics and recreational attractiveness of the Community Based Management Baines (1982) coast, as well as increased mobility (Bagstad et al., 2007). Interface between Drivers-Pressures-Ecosystem Kelble et al. (2013) Identifying both the natural and human-related changes in coastal Social and Services-Response (DPSER) Biophysical model areas is essential in order to effectively manage them. Developing Multi-Scale Integrated Analysis Giampietro et al. (2009) countries have a greater challenge in this regard, since data, capacity, of Societal and Ecosystem expertise and economic resources are limited; further, coastal pop­ Metabolism (MUSIASEM) ulations in these countries are generally growing more rapidly and Socio Ecological Systems at Murphy (2015) haphazardly (Appelquist and Balstrøm, 2014). Coastal Areas In order to make sense of these changes, indicators with the ability to Biophysical Ecosystem health (in relation to Costanza and Greer gather and present data in a relatively straightforward manner are coastal areas) (CEH) (1995) Coastal Vulnerability Index Thieler and Hammar- required. Only then, can complex systems or phenomena be appreciated Klose (1999) in a way that is reasonably simple to understand by coastal zone man­ Coastal Hazard Wheel Appelquist and Halsnæs agers (Choobchian et al., 2015). Indicators are useful for sharing the (2015) results of technical analyses or for monitoring the characteristics of RISC-KIT Coastal Hazard Van Dongeren et al. these natural and human systems. They also enable comparisons across Assessment module (2018) Coastal erosion risk assessment Narra et al. (2017) sustainability criteria or indeed across regions, as it so happens within Smartline Lins-de-Barros and the fisheries sector for example (Le Gallic, 2002). Muehe (2013), Sharples Over the years, a plethora of indicators have been developed to give et al. (2009) insight, monitor and manage coastal areas. However, the majority of Systemic Integrated approach to Magpayo (1995) coastal area indicators relate to the biophysical systems, with the human community-based coastal systems (for e.g. socio-economic, economic, governance, culture, norms resources management etc.) requiring a more integrated or holistic focus (Becken et al., 2014; Community Capitals Framework Flora and Flora (2008) Integrated Coastal Zone Sorensen (1993) Biedenweg et al., 2017; King et al., 2014). Evaluating indicators in Management isolation provides a portion of the whole picture. Thus, a systemic Community Based Coastal Maliao et al. (2009) framework is required to help guide environmental decision making Resource Management (Werner et al., 2014). Nguyen et al. (2016) stress the importance of combining social and biophysical systems in an integrated framework, especially in relation to policy-driven assessments towards adaptation coastline and in identifying hazard hotspots (Appelquist and Balstrøm, measures in coastal areas. 2015). Numerous frameworks, models, and approaches try to make sense of The lack in the consideration of the human systems within the these abundance of indicators to better manage and understand the overall assessment is a major shortcoming of the CHW framework. changes taking place at coastal areas. Table 1 features a non-exhaustive Indeed, its proponents already detected the need to add the human list of approaches divided into four categories according to their focus system to their framework: “supplementing the physical CHW assess­ ((i). social, (ii) interface between social and biophysical, (iii) biophysi­ ment with socioeconomic data may in many cases be relevant for cal, (iv) systemic). This list evidences the lack of an approach that en­ improving the information base for coastal planners and managers. This compasses all aspects of the indicator assessments at coastal areas. would provide CHW users with a combined picture of physical hazards Indeed, what is clear from the literature is that there is a general lack of and societal activities which could be relevant for supporting long-term successful implementation of the different approaches (Suinyuy et al., planning decisions.”(Rosendahl Appelquist and Halsnæs (2015):PP 9). 2016). There also seems to be a poor integration of the human system However, to date, the incorporation of this type of data has not been aspects of economic, political and governance facets within the majority included in any methodological development or practical implementa­ of the indicator approaches. tion of the CHW framework. The Coastal Hazard Wheel (CHW) featured in Table 1 (Appelquist Wider research also calls for the incorporation of human systems into and Balstrøm, 2015) is a recently developed indicator-based framework these types of frameworks and assessments. Howe et al. (2014) identify that has raised significant interest at the practical level for its ease of research needs in the interplay between socio-economic factors, human implementation. As a rapid assessment tool to coastal hazards, it re­ well-being and ecosystems. Calhoun et al. (2016) suggest that under­ quires low or no primary data collection (Appelquist and Halsnæs, standing the social-ecological system requires the consideration of the 2015). Examples of its implementation exist for India (Appelquist and social, cultural, historical, and legal/policy aspects as well. Vugteveen Balstrøm, 2015), Timor Lest, and Malta (Micallef, Micallef and Galdies, et al. (2015) call for the development of indicators that identify the (2018)). As evidence of its institutional significance, different inter­ processes of social, economic and ecological subsystems for integrated governmental organisations have adopted the CHW, including the management strategies in social-ecological systems. United Nations Industrial Development Organisation (UNIDO), the Clearly, ecosystem analysts need to move away from thinking of United Nations Environment Programme (UNEP) (Appelquist Rosendahl ecosystem assessments as decision-making tools and treat them rather as et al., 2016) and the Climate Technology Centre and Network (CTCN) an opportunity to understand and analyse the nature-society (i.e. natural (CTCN, 2017). and human system) relationships (Lele et al., 2013). In the same vein, Developed as a method to address coastal management issues, the there have been calls for indicator sets at coastal areas to be more CHW has a specific focus on the biophysical elements, with outcomes of consistent, comprehensive and complete and to thus form part of the the assessments indicating where further interventions are required overall Sustainability Development Goals assessments (Griggs et al., (Appelquist, 2013). The method therefore assists regional planners and 2014). decision-makers in obtaining an overview of the hazard profile of the Therefore, we can observe that there is a clear call to bring dedicated 2 D.J. Smith and B. Rodríguez-Labajos Ecological Indicators 125 (2021) 107527 human system indicators into the current coastal area assessments to as “big literature” (Nunez-Mir et al., 2016). enhance management decisions and approaches, as well as to better A further significant challenge in the analysis of the identified and understand the natural and human system relationships. This article selected literature is that the vast majority of articles involve qualitative therefore focusses on three main objectives aiming at pursuing this call: outcomes in the form of narrative reviews (Koricheva et al., 2013). To overcome both these challenges we used Automated Content Analysis 1) To analyse the existing set of indicator themes and categories in (ACA), i.e., algorithms that enable ‘concept mapping’, to ascertain the coastal areas. thematic composition of our body of literature. Themes in literature 2) To contrast this set of indicators with the perceived needs of local emerge from the frequency at which words and concepts appear and the coastal stakeholders from a developing country (Ghana) relationships among them (Nunez-Mir et al., 2016). 3) To propose a set of indicator categories to be included as part of a The software program chosen to perform the analysis was Lex­ systemic coastal zone management framework that takes it further imancer (Leximancer, 2019), which has been abundantly applied to than just the natural systems. ecological research (Cretchley et al., 2010; Grech et al., 2002; Knott et al., 2019; McCallen et al., 2019; Nunez-Mir et al., 2016; Penn- This paper thus provides the methods to which this investigation was Edwards, 2010; Sullivan et al., 2018; Wavrek et al., 2017). Apart from undertaken followed by a section on the results, the discussion and the the ability to perform ACA, Leximancer also provides a measure of the final conclusions that were drawn up and the suggestions for further associations between concepts, which is an important aspect when research in this field. looking to compare indicators in the literature. This step unveiled key themes, terms associated with those themes, and their connection to the 2. Methods word “indicator(s)”. After removing 21 words without substantial rele­ vance (e.g., “different”; “results”; “paper”; etc.), we identified 36 rele­ A research framework (Fig. 1) was devised to facilitate the systematic vant words from the ACA literature analysis. collection of data and its subsequent analysis. The framework was Next, we selected the articles that included the term “indicators” as guided by the three main objectives of this paper. The secondary data the main theme, together with other theme words that emerged from the (scientific literature) and primary data (focus groups) collection was ACA. The process yielded 296 articles whose abstracts were then undertaken before their subsequent analysis using supporting software. reviewed against the following inclusion criteria: - Based on original research, and not reviews or meta-analysis; 2.1. Eliciting indicators from the scientific literature - Explicitly identifying indicators, with specific focus on social indicators; A systematic evaluation of the peer-reviewed literature started with - Based on empirical studies (case studies); the first set of keywords: coast* AND environ* AND system* AND in­ - Focused on coastal regions; dicator* in the scientific databases Scopus, Google Scholar and Web of - Local focus (not national, regional or global); Science (February 2019). The first search strings were followed by a host - Case studies undertaken in developing countries of others, which eventually totalled a combination of 38 different - The articles would need to be 10 years old or younger keyword strings. This resulted in 1116 articles that were identified as relevant to this research. The sheer number of relevant articles is indeed The particular focus on the social indicators is due to the perceived symptomatic of the current challenge facing ecological research in that gap in the literature in measuring social indicators at coastal areas in extensive literature exists on the subject, which is currently referred to Fig. 1. The Research Framework. 3 D.J. Smith and B. Rodríguez-Labajos Ecological Indicators 125 (2021) 107527 comparison to measuring biophysical indicators. This research is con­ developed and imported into MAXQDA, which facilitated the coding of cerned in covering the gap on ’social’ indicators, without neglecting its the transcripts grouping them according to the different types of in­ relationship to all the other indicators. However, we realise that with the dicators and indicator categories. These codes were further grouped into specific focus on the social indicators in the literature the biophysical social, socio-economic, economic, biophysical, systemic, governance issues, for example, may be under-represented, but the concern here is and built environment. Grouping in this manner allowed for a com­ on the systemic indicators for coastal zone management (and the parison to be undertaken with the results from the literature analysis. perceived under-representation of social indicators within these sys­ temic indicators) and not with the state of the ecosystem. 2.3. Assessment of indicators This revealed a total of 40 articles that attained these requirements and were thus subjected to a full review. The indicator categories, sub- The process described above yielded two sets of indicators for local categories and individual indicators were then pulled out of each of coastal management, one set from the case studies in the scientific these articles and included into a large Excel database. literature and the other from the stakeholders perspective that are For practical terms, we grouped the indicators under the following currently facing the challenges of holistic coastal zone management in topics: “Biophysical”, “Economic”, “Socio-economic”, “Social”, “Built their local area. In order to assess and analyse these two sets, the in­ Environment”, “Systemic” and “Governance”. The grouping in this dicators were grouped into categories, sub-categories and lists of indi­ manner was based on approaches undertaken by other researchers, for vidual indicators using a spreadsheet (Excel). Their comparison example, Abdullaev et al. (2009). unveiled indicator categories absent in the existing literature. 2.2. Eliciting indicators from stakeholders 3. Results Two focus groups were held in Accra, Ghana, in March of 2019. 3.1. Literature insights of indicator themes and categories Ghana is a suitable location for our enquiry as it fits perfectly within the empirical criteria we used to select the articles, i.e. Ghana is a coastal The content analysis, using Leximancer, of 1116 article abstracts area in a developing country that is heavily affected by climate change from the original dataset (Fig. 2) revealed a number of interesting out­ impacts. Additionally, the first author has extensive work experience comes. It shows that studies regarding coastal systemic management and a network of contacts in the country that facilitated bringing focusing on the term ‘indicator’ connects to six main themes. The most together local relevant stakeholders into a focus group setting. frequently mentioned theme was ‘ecosystem’ (4269 mentions or ‘hits’). The focus group was chosen as a research technique as it employs “a Clearly, this shows that the literature related to systemic coastal zone guided, interactional discussion as a means of generating rich details of management indicators accentuates the notion of ecosystem services, as complex experiences and the reasoning behind [an individual’s] actions, well as ecosystem-based management approaches, assessments and beliefs, perceptions and attitudes” (Powell and Single, 1996: PP. 499). frameworks with particular emphasis on marine and fisheries aspects. The interest for this research was in gathering the perceptions and The following most common theme was ‘development’ (3699 hits) knowledge from local stakeholders and ensuring that viewpoints could which has a strong link to the systems theme which in turn links to the be exchanged between the quadruple helix stakeholders that ensures a management of ecosystems theme. The development theme further re­ wide range of opinions (Yun and Liu, 2019). This meant involving in­ lates to human, environmental, natural, ecological, social and economic dustry, academia, government and civil society from the coastal region themes, signaling a clear focus and connection in the literature for both in Ghana. human and natural systems in relation to coastal area development. We conducted two focus groups ensuring a manageable number of Interestingly enough, the development sphere relates to the ‘changes’ informed stakeholders in each session (8 and 5 participants respec­ sphere (3049 hits) through the terms ‘local’ and ‘impacts’, pointing to tively). To ensure the representativeness of the informed stakeholder local coastal areas as a place of environmental and social change. groupings the following criteria were used: (i) The stakeholders had to Looking further into the ‘changes’ sphere, the terms ‘climate’, ‘com­ be from Ghana; (ii) The stakeholders had to belong to one of the munity’ and ‘water quality’ point to relevant aspects in local coastal following stakeholder groups: NGOs; Farmer Organisation; Youth areas. Groups; Women Groups; Government Institution; Traditional Author­ ‘Changes’ also relate to the ‘fishing’ sphere (1197 hits) through the ities and (iii) The stakeholders had to have a relation to coastal zones. term ‘results’. Therefore, a high number of case studies analyzing Working together with a local umbrella organization we recruited the change, focus on fishing and show results using indicators. Interestingly, informed stakeholders. in the ‘fishing’ sphere the terms ‘time’ and ‘production’ are connected to The stakeholders were tasked with providing their opinions on in­ ‘indicators’ showing us the importance that the literature places on in­ dicators related to systemic (natural and human systems) for environ­ dicators that reflect time spent fishing and the subsequent effects on fish mental management in coastal areas in Ghana. The protocol for the production. Focus Groups outlined the main objectives and a set of guiding questions The terms in the ‘forest’ sphere (262 hits), ‘forest’ and ‘land’, are to help focus the discussions around the following objectives: both connected with the terms ‘areas’ (in the ‘change sphere’) and ‘in­ dicators’ (in the ecosystem sphere). This positions forest lands in coastal 1. To define a set of criteria in order to choose practical natural and areas as places of ecosystemic change that the indicators seem to be human system indicator (sub)categories that show the overall health monitoring. Meanwhile the ‘urban’ sphere (168 hits) is the least frequent of the environmental system. in the literature, connecting with the term ‘regional’ (in the ‘develop­ 2. To determine the needs and perspectives of indicators at local coastal ment’ sphere). areas in Ghana. Fig. 2 offers an insight into the topics that academic research has focused its interest on over the last ten years with regards to coastal To analyse the data from the focus groups the recorded conversations systemic management and indicators. With the aim of advancing to­ were transcribed verbatim and then coded using the software program wards a systemic approach, using indicators for environmental man­ MAXQDA (MAXQDA, 2020). MAXQDA provides functions especially agement in coastal areas, we selected the terms (as described in the adapted for qualitative data analysis of focus group data (Saillard, methodology) according to the well-established indicator categories of: 2011). Furthermore MAXQDA provides intuitive access to the focus Social; Economic; Governance; Biophysical and Systemic (Li et al., group transcripts as well as to statements and contributions made by 2018) (Table 2). Admittedly, this categorization forces choices in some individual participants (Kuckartz and Rädiker, 2019). A code book was overlapping categories. However, this step was fundamental for 4 D.J. Smith and B. Rodríguez-Labajos Ecological Indicators 125 (2021) 107527 Fig. 2. Graphic representation of main themes in the coastal management literature: (a) number of hits per theme; (b) relationship of the term ‘indicator’ with other terms. Source: Own elaboration using Leximancer. in Table 2. Evident from the first full article review was that a further Table 2 category of ‘built environment’ was required, and thus it was added to Indicator category and its associated terms as a base for the classification the classification framework. The grouping of indicators into the cate­ framework. gory of “built environment” at coastal areas was based on the ap­ Indicator Associated words from Leximancer analysis proaches from Buot and Dulce (2019), Tefe (2012) and Van Eijck et al. category (2014). The category “built environment” considers the human-made Social Community; social; human; environment, however at the coastal zones this indicator set does not Economic Economic Governance – take into account the urban context as this would be subject to an Biophysical Ecological; environment/environmental; fishing/fisheries, entirely different set of indicators. marine; water; species; land; urban; soil; natural; forest; An extensive list of individual indicators was extracted for each main biophysical indicator category. Analogous indicators – the indicators that had Systemic Framework; spatial; model; sustainable; system; changes; similar features to each other and thus comparable – were grouped ecosystem services; management; time; approach; regional; coastal; resources together. A frequency count of the times that analogous indicators were mentioned in an indicator category is visually represented in Fig. 3A. This revealed that Social was the indicator category with the highest advancing to the next step: to provide a convergent focus for the full frequency of related indicators (63% of all the listed indicators). Ex­ article review on articles that are related to the subject matter. amples of social categories can be found in Choobchian et al. (2015), Table 2 confirms, through the array of topics, that current research Dacks et al. (2018), Marín-Monroy and Ojeda-Ruiz de la Peña (2016) screened through content analysis concentrates on the biophysical as­ and Mollah (2016) that trace aspects such as togetherness; livelihoods; pects of coastal area management. Still, many terms fall under the sys­ access to basic services; security; health and education levels. They all temic category, where a number of holistic management frameworks highlight the importance the analysed literature has placed on com­ and indicators are used to support environmental decision-making munity indicators. processes at local level (Loomis and Paterson, 2014; Werner et al., The Biophysical category (14% of all the listed indicators) delivers a 2014). The governance category did not reveal any other associated host of indicators from the analysed literature. They range from the term and the economic category only revealed the associated term of specific (e.g., reduction of emissions of industrial sulphur dioxide (Meng ‘economic’. and Chi, 2018) to the more general, for instance the Biodiveristy index Using the selection criteria described in the methodology yielded 40 (Rakhmanissazly et al., 2018) and the Coastal Hazard Wheel (Appelquist articles that were subjected to a full review. Indicators were extracted and Balstrøm, 2015)) highlighting the vastness of this area of investi­ from each of these articles (with the particular focus on social in­ gation and the need to specify locally relevant indicators. dicators) and classified according to the indicator categories presented The Socio-Economic category followed in frequency, with 13% of 5 D.J. Smith and B. Rodríguez-Labajos Ecological Indicators 125 (2021) 107527 Fig. 3. Frequency of indicators mentioned in the literature (A) and those mentioned in the field data (B). all the listed indicators. Adger (1999); Tian et al. (2018); Buot and Dulce highlight the complexity of implementation in practical terms. (2019) are examples of how socio-economic indicators can be used, i.e., The analysed literature thus reveals a variety of entry points to better in relation to coastal livelihoods and coastal economies; food provision; portray the processes involved in the management of coastal regions, income stability and housing. Meanwhile, a host of authors (Clements, with a focus away from developed countries according to the OCED 2009; Dannevig and Aall, 2015; Dogliotti et al., 2014; King et al., 2014; definition (United Nations, 2005). We acknowledge the diversity of the Thaler and Levin-Keitel, 2016) show the importance of the indicator so-called “developing countries” that could be divided into several sub- ’level of food autonomy’, highlighting the relevance of self-subsistence at categories, from least developed, transition to emergent economies. We community level in coastal areas in developing countries. have further addressed this point in the discussion. The Built Environment (3% of all the listed indicators) from the analysed literature shows indicators related to aspects such as road infrastructure; water and light infrastructure; state of agricultural 3.2. Indicators from the bottom up infrastructure (Buot and Dulce, 2019; Camill et al., 2012; Ghisellini et al., 2016; McCarter et al., 2018). These indicators highlight the The perspective from the local level stakeholders provides an insight relevance of essential structures to livelihoods at local level. into the potential indicators that are relevant to monitor and control the The Economic indicator category (3% of all the listed indicators) natural and human systems at local coastal areas. The coding of the focusses on the fishing and tourism sector, as could be expected at transcripts from the focus groups thus disclosed a greater need for coastal regions. This entails indicators of fisheries household income governance, systemic and economic indicators at local level in Ghana (Miswar et al., 2018); fisheries contribution; market price of fish; income than those that have emerged from the literature review. The coded from fishing; share of catches per person (Choobchian et al., 2015; categories are represented in Fig. 3B. Biophysical (26% of all the coded Kronen et al., 2010) and tourism and recreation income (Choobchian indicators) and Governance (25% of all the coded indicators) were the et al., 2015; Tian et al., 2018). Indicators in relationship to household categories with the most frequently mentioned indicators by the local economies also appear in the analysed literature: some examples include quadruple helix stakeholders. These were followed by the categories three or more income sources; savings ratio; ownership asset and Systemic (16%), Socio-Economic (7%), Built Environment (8%), Eco­ household income as some examples from Kronen et al., (2010), nomic (9%) and Social (9%). Choobchian et al., (2015) and Dacks et al., (2018). Diving deeper into the sub-codes mentioned within each category, Examples of indicators within the Governance category (3% of all the analysis disclosed 35 sub-categories of indicators Fig. 4. Within the the listed indicators) focus on institutional aspects: institutional stability category ‘Built Environment’ Climate Affected Structures was the most (Mollah, 2016); environmental services of institutional ecosystems frequently mentioned item by the focus group participants (6,19% of all (Zaldívar-Jiménez et al., 2010); total sustainability of institutional the listed sub categories). A participant from the Fisheries Commission criteria (Choobchian et al., 2015); fishing tools policy (Choobchian gave insight into the reason for this: “along the coast it [climate change] et al., 2015); land management policies (Roy et al., 2018) and protective affects a lot of infrastructure houses and things in my community. A lot of areas including coastal protection and species protection (Tian et al., houses have been destroyed.” 2018). This highlights the relevance the literature has placed on an in­ Within the Biophysical category ‘changing rainfall pattern’ was most tegrated or holistic look at policies, but also the importance placed on frequently mentioned with 5.15% of the total mentioned items. “About the need for institutions to be stable and sustainable in developing the rain, we also have periodic drought, for example, in the first rain the countries. farmer thinks ‘ok let me start preparing for farming’ and then all of a sudden Finally, the Systemic category of indicators (1% of all the listed the rain breaks so there are alternating issues of drought and flooding”, indicators) from the analysed literature was the least featured. Examples comments a local private company participant. include: cooperative’s roles; total sustainability of coastal management Community Associations (5.15% of the total mentioned items) were criteria, as well as indicators related to frameworks (e.g., Energy Sys­ most frequently mentioned within the category Governance. A partici­ tems Theory (EST) and Emergy Analysis (EA)) (Berrios et al., 2017). Also pant from the Fisheries Commission provides insight into the reason for within the systemic category we found indicators of central tendency this by talking about equipment for fishing: “two or three of them [fish­ and dispersion measurement (Bandoc et al., 2014), ecosystem approach ermen] should come together [cooperatives] and have a stronger vessel to (Engler, 2015) and Community Based Management (Borges et al., 2017; work with”. Boyd and Charles, 2006; Courtney and White, 2000; Lawson et al., 2010; Within the Economic category the most frequently mentioned sub- Pomeroy et al., 1997; Sherman, 2014). These indicators provide a category was ‘climate affected incomes’. A participant from a farmer relation to theories, approaches, analysis or management models which association explains why: “I have 5 acres of land. I’m not getting the same harvest as before as a result of the climate and the weather. Last year there 6 D.J. Smith and B. Rodríguez-Labajos Ecological Indicators 125 (2021) 107527 Fig. 4. Categories and their sub categories of indicators from the focus groups, with the percentage of mentions of a sub-category in relation to every other sub-category. were no crops and the mango it doesn’t bear fruit; this has affected my that they can speak out on at the district level”. income” Under the Social category the sub-category of ‘Social Information Education (4.12% of the total mentioned items) was the most Exchange’ had the highest frequency of mentions with 3.09% of the total frequently mentioned sub-category within the Socio-Economic category. sub-category mentions. “It depends on what you want to communicate. In The same participant from the farmer association gives insight into this: the oyster community, most of the community do not read or write. Then you “Until the government changes the policy that at a certain age children should need to be careful with the kind of information that you share - you should be made to go to school and shouldn’t be seen loitering around the villages - have some positive communication as opposed to negative communication, because school is better, its free - but until that policy is made, we will have instead of showing pictures of “don’t do this” show pictures of “do, do this”, trouble with the children in the villages as the elders and leaders cannot force stated by a participant from the private company. them to go to school”. Other than the frequency of times a sub-category is mentioned it is Within the Systemic category both with 4.12% of the total mentioned important to observe their interaction, as it can signal groupings of in­ categories are the sub-categories of ‘holistic fisheries management’ and dicators of that are of interest for management or monitoring. Fig. 5 ‘information exchange’. On the topic of holistic fisheries management a shows the sub-categories mentioned together and their the frequency of participant from a company supporting farmer associations explains: “… times mentioned (the number in brackets). so we asked the oyster fishermen what they wanted to do, and they said that The code map (Fig. 5) is developed through the multidimensional they wanted to have greater income. So, of course, what we did is we put that scaling method (Bazeley, 2009) which is used to position the codes on into a holistic management context with measures to show where it fits. So we the map given the distances between them. The intersections of the don’t want to harvest more, we want to add value to the little harvest they codes are placed in accordance with the number of times two codes have have. For example, if I am harvesting three but I am getting the same income been assigned to a segment together. In this case our interest was to level that I was getting [when I was harvesting two], there is no motivation know which codes intersected (co-occurred) in a segment of the tran­ to go in to harvest more. We help them to understand this”. The need for a scripts from both focus groups. This allows us to know which indicators sub-category of Information Exchange becomes apparent in the words of could potentially be correlated together allowing for indicators to be a participant from the Peasant Famers Association of Ghana: “…for handled together, either in terms of joint measure or for selecting one as example, if the farmers have issues with chemical fertilizers, this is an issue a signal for a cluster. Fig. 5. Clustering of the co-occurrence of codes mentioned from both focus group transcriptions. *The code colours match those of the indicator categories in Fig. 3. 7 D.J. Smith and B. Rodríguez-Labajos Ecological Indicators 125 (2021) 107527 The code map can be clustered into three clusters of codes (i.e. in­ more of the brine water coming up, so it affects the soil quality. Furthermore, dicators) that have intersected in the transcripts. In intersected codes within this cluster, holistic community management co-occurred with cluster 1, Systemic Holistic Fisheries management was central to Economic Environmental Information Exchange. A social advocate participant, Information Exchange and Socio-Economic Income from farming. This is after listing several types of climate and market-related information and evident from the reflection from a social advocate participant who services provided to farmers and communities, he reasoned: “…what I mentioned: “one of the other things that is affecting the local fishermen is the think ESOKO [Digital Solutions for Agriculture and Data Collection] lack of technology or the lack of understanding of the devices to detect the needs to do is to add more environmental information about the coastal area weather patterns. For instance, the fishermen are already set to go out fishing as well as economic information and social information and they would need but all of a sudden there is a heavy wind from the sea. So that has disrupted to provide this information in the local dialects in order to solve the high social their activities for the day […] What is clear is that they do not have access to needs of those places…” this information that can help them to plan ahead and thus they have lost out on their economic activities of that day. I believe that if the fishermen are 3.3. Contrasting the literature and field indicator categories equipped with these modern technologies, communications and devices they will know the effects the weather will have on their activities and this will also The two components of Fig. 3 described individually in the sections help them to plan better.” above can be now compared side by side. We note that the social cate­ From cluster 2, participants from the focus groups highlighted the gory (Fig. 3A) has the greatest representation meanwhile the systemic relationship between the following indicators: Climate Affected Structures category was the least represented from the analysed literature. Mean­ (Built Environment), Forced Climate Migrations (Social), Ability to go to while, the analysis of the data from the focus group participants (field School (Social) and Education (Socio-economic), indicating that the one data) reveals an even spread between the indicator categories, with affects the other. The intersection of these codes is evident from the systemic proving to be the category the participants showed slightly reflection from an education youth group participant that mentioned: “I more importance towards. Here we note the relevance of bottom-up vs a would like to touch on education and coastal communities as climate change top-down approaches where a significantly higher importance was has already affected the infrastructure by destroying some local schools. placed on the social category from the field data than the top-down Students have then not been able to go to school in their community and they literature analysis (a frequency of 63% and 15% respectively). have to travel quite a distance to another community to go to the school The difference between the perspectives of academic research and there”. local stakeholders creates a valuable opportunity to assess the state and Within cluster 3, unsurprisingly, water quantity co-occurred with prospects of indicators for systemic coastal area management. In this water quality. A representative from a local development consultancy respect, Fig. 6 offers a visual representation of the subcategories of stated “along the coast there is some fresh patch of water on top of the salt coastal zone indicators by combining insights from the literature and water. But with climate change, now that level of freshwater is being infil­ from the field data. This visual representation aims at reinforcing the trated by the salt. This creates a combination of things. […] Normally if it range of indicators included in coastal indicator frameworks, in order for rains then the aquifer is recharged, but with the lack of rain, we now have the natural and human systems to be taken into account together. Fig. 6. Homogenised literature and field sub-category coastal zone indicators. 8 D.J. Smith and B. Rodríguez-Labajos Ecological Indicators 125 (2021) 107527 We created a classification system that sorts the indicators into five the potential indicator categories from the literature and the current situations according to their saliency in both the literature and in the indictor frameworks, there may still be potential indicators that need to field. A colour code qualifies each situation. With 20 or more mentions be taken into account from a local perspective – at least from the evi­ of a certain sub-category in the literature and if that sub-category was dence obtained from the case study in Ghana. In this sense, it reiterates mentioned (presence) in the focus groups, the sub-category was col­ the need to have indicators that encompass a wide range of aspects but oured green; if its salience in the literature was less frequent, between 1 that ultimately take the local level needs into account. Table 5 provides and 19 mentions, and was still mentioned (presence) in the focus groups, the sub-categories that were mentioned from the field data but that did the subcategory was then coloured light green. If, however it appears in not have any mentions from the literature. the literature but was absent in the field, it was coloured light yellow (when it is abundantly mentioned in the literature, with at least 20 4. Discussion mentions) or orange (when it is less mentioned in the literature, with 19 mentions or less). If there was no mention of the sub-category from the Climate change impacts are currently referred to as a climate crisis literature but there was a mention of it (presence) in the field data, it was (Brugger and Crimmins, 2015; Hoppe et al., 2013; Navarro, 2018). Some coloured red. countries across the globe are better prepared than others to cope with Therefore, Fig. 6 helps us to distinguish three different scenarios in the impending climate change impacts. For instance, Bangladesh is terms of the indicators for systemic coastal area management. The first purported to be one of the most vulnerable countries to climate change scenario is a co-occurrence of the literature analysis with the identified in the world (Minar et al., 2013), however it is better prepared than most needs from local coastal stakeholders. There is a total of 14 analogous developed countries in terms of adaptation and mitigation measures. As indicator subcategories that were mentioned in both the literature and in Bangladesh, West Africa - specifically Ghana - is going to be one of the the focus groups, across all the indicator categories (see examples in more climate vulnerable developing countries affected by coastal zone Table 3). These could be the first candidates towards an expansion of the impacts (Sylla et al., 2016), this determined our choice of empirical current existing frameworks vis-à-vis becoming more encompassing of reference. Our analysis provides a fined-grained identification of in­ the aspects beyond just the biophysical or social elements currently dicators from the literature and from the field that are relevant for the focussed on in the literature. management of coastal areas of developing countries that are highly The second scenario is where we have the sub-categories mentioned vulnerable and/or that are currently affected by climate change (and in the literature but not mentioned at the local Ghanaian level. In this extreme weather) impacts. case, there are 12 sub-categories that have emerged from the literature While negative impacts will manifest on the biophysical and built that at local level, in Ghana, were not considered by the stakeholders. environments, it is society that will bear the brunt of these impacts This outcome is crucial as it shows us that a first approximation to the (Adger et al., 2005; Azhoni et al., 2018; Clements, 2009; Odemerho, local stakeholders needs to be undertaken to know what is important to 2015; Rasul and Sharma, 2016). Our results mirror the idea that the way be considered in each local coastal community. In other words, armed in which different shorelines and marine environments are managed, with a full set of sub-categories, a researcher can approach a local and what they are managed for, should be a reflection of what society community to discover from the sub-categories which have relevance for wants from those environments (Loomis and Paterson (2014). There­ them to measure and monitor in terms of their local coastal management fore, the measurement and monitoring of climate change effects and of the natural and human system needs. The differences in the types of coastal management should include not only the natural systems but the sub-categories mentioned in the literature also reveals the encompassing human systems as well. nature of the literature case study data. A number of categories from the Thus, it is important that the integration between the natural and literature expose the types of indicators that could potentially be more human systems relies not only on the scientific advancement in this field commonly used in least developed, transition and emergent countries but the practical implementation thereof. Therefore, screening the than in Ghana. For instance, coastal infrastructures indicators may not literature to identify the academic advancement, has been an important emerge from the local stakeholders in Ghana as infrastructure is not seen element of this research, however, the contrast with local stakeholder as an issue that may be a more significant issue in other developing needs is vital to ensure that the entire process of developing a systemic countries. Table 4 provides the sub-categories mentioned from the framework is not only guided by the theoretical approaches that would literature that did not have any mentions from the field data, with some have difficulty to be implemented. examples. Unsurprisingly 83% of all the indicators identified in the literature The third scenario is where the local Ghanaian coastal stakeholders and 70% of the indicators identified in the field refer to domains outside have mentioned sub-categories of indicators that were not uncovered in the physical environments and thus emphasizes this human dimension. the 40 articles that were subjected to a full literature review. This case Accordingly, we contribute to the idea that a holistic set of indicators shows us that although a researcher may believe to have uncovered all at coastal regions with a focus on the local level is well-suited to aid Table 3 Combined mentions in the literature and field data of the indicator sub-categories with examples of locally (Ghana) defined indicators. Category Sub-Category Indicator example (from the Ghana focus groups) Social Community Togetherness Number of associations that are present in the community Communication Number of information exchange events (meetings, presentations etc) held in the community. Community Education Number of children that have the ability to go to school. Socio-economic Community livelihood What is the trend in the economic spending power Systemic Management Is there a community-based management plan in place? Governance Cooperatives Do cooperatives exist at local level (fishing, canoe sharing etc.?) Control Are closed fishing seasons implemented? Policies Do policies exist against beach sand mining? Economic Income Number of community members that are changing their principle income stream Built Environment Infrastructure Number of infrastructures destroyed by climatic events over the last 10 years and the number rebuilt since. Biophysical Climatic Conditions Rainfall patterns over the last 10 years. Water Changes in the lagoon salinity levels. Pollution Tons of plastic present in the lagoon in 1 year Fishing Change in fish sizes and in fish catch 9 D.J. Smith and B. Rodríguez-Labajos Ecological Indicators 125 (2021) 107527 Table 4 Sub-categories from the literature not mentioned in the field data. Category Sub-Category Indicator example Social General Community Demographic - percentage of population below 6 years of age Information - percentage of dependent population Mollah (2016) Community Access to basic services - percentage of community access to health services Nemes (2005) - percentage of community that has access to water Alamarah Tamimi et al. (2007), Biedenweg et al. (2017), Dondeynaz et al. (2012) Community Knowledge Utilization of local knowledge on resource management Biedenweg et al. (2017), Miswar et al. (2018) Community Security Number of homes and farms located in areas of floods or landslides Dondeynaz et al. (2012), Hove et al. (2016) Community Health body mass index/Human Development Index Biedenweg et al. (2017), Ghisellini et al., 2016; Kwasi et al., 2011) Socio- Household Livelihood Number of families with credit support and insurance Buot and Dulce (2019), Matzdorf et al. (2014), Rakhmanissazly Economic et al. (2018) Systemic Institutional Total sustainability of institutional criteria Choobchian et al. (2015) the literature but not mentioned at the local level and scenario 3: local Table 5 Ghanaian coastal stakeholders mentioned sub-categories of indicators Sub-categories from the field data not mentioned in the literature. that were not mentioned in the literature) offer insights in terms of Category Sub-Category Indicator example (from the Ghana focus implementation, rather than on expanding current indicator frame­ groups) works. These last two scenarios imply that coastal management indi­ Social Adaptation Number of adaptive measures that have been cator frameworks should be adapted to each local situation. They show brought in that affect the community (i.e. after a us that coastal zone indicator frameworks uncovered in the literature school was destroyed by a storm, the kids stayed at home). need to be adapted to the natural and human systems at local coastal Systemic Information Full systemic information available to farmers / areas. Farmer access to information regarding the systemic management of the local area / Is 5. Conclusion information available to be used by farmers? Eg. smartphones, climate data, fishing data etc. Technology Do fishermen have access to technologies that can This paper has detailed the process of discerning, accessing and allow them to manage all their fishing aspects in analysing a complex set of indicator data that has exposed indicator an integrated manner (for e.g. weather devices, categories and sub-categories. The paper has furthermore contrasted radios, communication technology etc.) these results with the perceptions and needs of the local quadruple helix Economic Income Number of community members changing economic activities (i.e. from fishing to farming) stakeholders from the coastal areas in Ghana. Finally, a set of sub- / Changes in rain fed crops to irrigated crops categories has been proposed to be included within the current moni­ Built Adaptation Number of recent changes made to the built toring/hazard assessment frameworks that combines the natural and Environment environment in response to climate change human systems. impacts that improve the community livelihood Literature analysis is no substitute to local assessments and the Mitigation Number of well-developed landing beaches in the local fishing community that can support larger subsequent understanding of local conditions. Then again, local assess­ vessels ments are no substitute to a literature analysis. This is no more evident Biophysical Ocean Changes in sea water temperature than shown in our results where the literature focusses predominantly Temperature on social sub-categories of indicators, meanwhile at the local level there Soil Changes in soil salinity is a greater integration of these natural and human systems. The unique contribution of this paper is the combination of literature and decision makers. The choice of the right indicators expands their in­ stakeholder-based indicator sub-categories that should be added to the formation base on what society wants and how to protect society from current set of coastal monitoring frameworks - such as the Coastal climate change impacts. Hazard Wheel - to ensure that the natural and human systems are A recently implemented CHW framework in West Africa as part of a considered holistically. In other words, our methodological process of UNIDO funded and CTCN managed project highlighted some of the combining both a top-down (literature) and bottom-up (local Ghanaian shortcomings of the CHW framework (CTCN, 2017). The report high­ coastal stakeholders) indicator identification has provided the platform lights that even at its first evaluation phase, the CHW would benefit for the inclusion of local expert knowledge based on internationally greatly from having a set of rapid social, economic and systemic as­ accepted indicators for coastal zone management. This insight provides sessments, with the possibility to expand the list of potential manage­ a salient call to field analysts and the donors or policy makers that ment options of the CHW to include governance or political commission the work to take into account the value of local experts and implications. local knowledge when devising the natural and human system indicators A combination of literature and local stakeholder-based sub-category for coastal zone management. indicators - obtained from Ghana - has allowed us to define three sce­ Researchers at coastal zones should continually drive to be multi­ narios for uncovering indicator sub-categories that could be included as disciplinary, focusing on the interconnectedness and the knock-on ef­ part of the current set of measuring and monitoring indicators for nat­ fects of one system on another. An observation from one of the ural and human systems at local coastal areas. The first scenario (a co- participants of the focus groups provides the reasoning for this, where occurrence of the literature analysis with the identified needs from she described how an extreme storm destroyed a local school. This local Ghanaian coastal stakeholders) is the one we promote to be resulted in the children no longer able to go to that school meanwhile, incorporated into the current coastal indicator monitoring frameworks those that could, had to travel to the next village to attend school. All (for example by upgrading the CHW – the framework advocated for use participants seemed to have a similar experience to this one as this in developing country contexts). This could be by including for instance observation was backed up with anecdotes of how those children that the sub-category “Community Togetherness” by measuring the number could no longer attend school spent their days loitering around the of associations that are present in the community. villages, some turning to crime. From these statements, there is no The other two scenarios (scenario 2: sub-categories mentioned in clearer evidence of how the natural system has impacted the human 10 D.J. Smith and B. Rodríguez-Labajos Ecological Indicators 125 (2021) 107527 system and the very reason why both systems need to be measured and Berrios, F., Campbell, D.E., Ortiz, M., 2017. Emergy evaluation of benthic ecosystems influenced by upwelling in northern Chile: contributions of the ecosystems to the monitored and included in the current coastal frameworks that are regional economy. Ecol. Modell. 359, 146–164. devoid of these combined indicators. Biedenweg, K., Harguth, H., Stiles, K., 2017. The science and politics of human well- To build in these sub-categories into the frameworks currently being: A case study in cocreating indicators for puget sound restoration. Ecol. Soc. 22 available we propound to focus further research on integrating the https://doi.org/10.5751/ES-09424-220311. Borges, R., Ferreira, A.C., Lacerda, L.D., 2017. Systematic planning and ecosystem-based human and natural system indicators prioritised from a stakeholder base management as strategies to reconcile mangrove conservation with resource use. of data that is easily obtainable. Furthermore, there is a strong need to Front. Mar. Sci. 4, 353. investigate the concept of weighting or indeed non-weighted indicators Boyd, H., Charles, A., 2006. Creating community-based indicators to monitor sustainability of local fisheries. Ocean Coast. Manag. 49, 237–258. and subcategories in function of their importance. Finally, we propose Brugger, J., Crimmins, M., 2015. Designing institutions to support local-level climate that further work needs to take place in the visualisation of the collected change adaptation: Insights from a Case Study of the U.S Cooperative Extension indicator information to provide managers with stronger coastal zone System. Weather. Clim. Soc. 7, 18–38. https://doi.org/10.1109/CEC.2011.5949892. Buot, M., Dulce, M.Z., 2019. An index to determine community wellbeing along coastal management tools. community in Leyte. Philippines. Environ. Asia 12, 56–67. https://doi.org/ 10.14456/ea.2012.23. M.M. Buot V.R. Cardenas Community wellbeing indices: implications to policy CRediT authorship contribution statement development, in: 13 2016 Change?, College, Laguna (Philippines). Calhoun, S., Conway, F., Russell, S., 2016. Acknowledging the voice of women: David J. Smith: Conceptualization, Methodology, Validation, Implications for fisheries management and policy. Mar. Policy 74, 292–299. Camill, P., Hearn, M., Bahm, K., Johnson, E., 2012. Using a boundary organization Formal analysis, Investigation, Writing - original draft, Visualization, approach to develop a sea level rise and storm surge impact analysis framework for Project administration, Funding acquisition. Beatriz Rodríguez-Laba­ coastal communities in Maine. J. Environ. Stud. Sci. 2, 111–130. https://doi.org/ jos: Writing - review & editing, Supervision. 10.1007/s13412-011-0056-6. Choobchian, S.H., Kalantari, K., Asadi, A., Taghavi Motlagh, S.A., 2015. Measurement and comparison of different dimensions of sustainable coastal fishing management in Beach Seine cooperatives in Guilan. J. Agric. Sci. Technol. 17, 1463–1472. Declaration of Competing Interest Clements, R., 2009. The economic cost of climate change in Africa. Pan African Clim, Justice Alliance. Costanza, R., Greer, J., 1995. The Chesapeake Bay and its watershed: a model for The authors declare that they have no known competing financial sustainable ecosystem management? Barriers Bridg. Renew. Reg. Ecosyst. C. S. interests or personal relationships that could have appeared to influence Holling S. Light. eds., Chapter 4, pp. 169-213 45. the work reported in this paper. Courtney, C.A., White, A.T., 2000. Integrated coastal management in the Philippines: Testing new paradigms. Coast. Manag. 28, 39–53. Cretchley, J., Rooney, D., Gallois, C., 2010. Mapping a 40-year history with Leximancer: References Themes and concepts in the journal of cross-cultural psychology. J. Cross. Cult. Psychol. 41, 318–328. CTCN West African coastal classification, hazard management and standardized Abdullaev, I., Kazbekov, J., Jumaboev, K., Manthritilake, H., 2009. Adoption of communication scheme utilizing the Coastal Hazard Wheel [WWW Document] integrated water resources management principles and its impacts: Lessons from https://www.ctc-n.org/technical-assistance/projects/west-african-coastal- Ferghana Valley. Water Int. 34, 230–241. https://doi.org/10.1080/ classification-hazard-management-and 2017 accessed 6.4.20. 02508060902843710. Dacks, R., Ticktin, T., Jupiter, S.D., Friedlander, A., 2018. Drivers of fishing at the Adger, W.N., 1999. Exploring income inequality in rural, coastal Viet Nam. J. Dev. Stud. household scale in Fiji. Ecol. Soc. 23 https://doi.org/10.5751/ES-09989-230137. 35, 96–119. https://doi.org/10.1080/00220389908422593. Dannevig, H., Aall, C., 2015. The regional level as boundary organization? An analysis of Adger, W.N., Brown, K., Hulme, M., 2005. Redefining global environmental change. climate change adaptation governance in Norway. Environ. Sci. Policy 54, 168–175. Glob. Environ. Chang. 15, 1–4. https://doi.org/10.1016/j.gloenvcha.2004.12.002. https://doi.org/10.1016/j.envsci.2015.07.001. Alamarah Tamimi, A.R., Isayed, A.A., Mughli, M.A., 2007. Using socio-economic de Sherbinin, A., Castro, M., Gemenne, F., Cernea, M.M., Adamo, S., Fearnside, P.M., indicators for integrated water resources management: Case study of Palestine, Krieger, G., Lahmani, S., Oliver-Smith, A., Pankhurst, A., Scudder, T., Singer, B., Tan, Water Resources in the Middle East: Israel-Palestinian Water Issues - From Conflict to Y., Wannier, G., Boncour, P., Ehrhart, C., Hugo, G., Pandey, B., Shi, G., 2011. Cooperation. https://doi.org/10.1007/978-3-540-69509-7_34. Preparing for Resettlement Associated with Climate Change. Science (80-.). 334, 456 Alkire, S., Santos, M.E., 2010. Acute multidimensional poverty: A new index for LP – 457. https://doi.org/10.1126/science.1208821. developing countries. United Nations Dev. Program. Hum. Dev. Rep. Off. Backgr, Dogliotti, S., García, M.C., Peluffo, S., Dieste, J.P., Pedemonte, A.J., Bacigalupe, G.F., Pap. Scarlato, M., Alliaume, F., Alvarez, J., Chiappe, M., Rossing, W.A.H., 2014. Co- Appelquist, L.R., Balstrøm, T., 2015. Application of a new methodology for coastal multi- innovation of family farm systems: A systems approach to sustainable agriculture. hazard-assessment & management on the state of Karnataka, India. J. Environ. Agric. Syst. 126, 76–86. https://doi.org/10.1016/j.agsy.2013.02.009. Manage. 152, 1–10. https://doi.org/10.1016/j.jenvman.2014.12.017. Dondeynaz, C., Carmona Moreno, C., Céspedes Lorente, J.J., 2012. Analysing inter- Appelquist, Lars, 2013. Generic framework for meso-scale assessment of climate change relationships among water, governance, human development variables in hazards in coastal environments. J. Coast. Conserv. 17 (1), 59–74. https://doi.org/ developing countries. Hydrol. Earth Syst. Sci. 16, 3791–3816. https://doi.org/ 10.1007/s11852-012-0218-z. 10.5194/hess-16-3791-2012. Appelquist, L.R., Balstrøm, T., 2014. Application of the Coastal Hazard Wheel Engler, C., 2015. Beyond rhetoric: Navigating the conceptual tangle towards effective methodology for coastal multi-hazard assessment and management in the state of implementation of the ecosystem approach to oceans management. Environ. Rev. 23, Djibouti. Clim. Risk Manag. 3, 79–95. https://doi.org/10.1016/j.crm.2014.06.002. 288–320. Appelquist, L.R., Halsnæs, K., 2015. The Coastal Hazard Wheel system for coastal multi- Eriksen, S., Silva, J.A., 2009. The vulnerability context of a savanna area in Mozambique: hazard assessment & management in a changing climate. J. Coast. Conserv. 19, household drought coping strategies and responses to economic change. Environ. 157–179. https://doi.org/10.1007/s11852-015-0379-7. Sci. Policy 12, 33–52. https://doi.org/10.1016/j.envsci.2008.10.007. Appelquist Rosendahl, L., Balstrøm, T., Nicholls, R.J., Linham, M.M., Spensley, J., Flora, C.B., Flora, J.L., 2008. Communities: Legacy and Change, 3rd ed. Westview Press. Bjørnsen, P.K., Lloyd, G.J., Jeppesen, G., Vestergaard, O., 2016. The Coastal Hazard Ghisellini, P., Cialani, C., Ulgiati, S., 2016. A review on circular economy: The expected Wheel decision-support system - Quick Start Guide. transition to a balanced interplay of environmental and economic systems. J. Clean. Azhoni, A., Jude, S., Holman, I., 2018. Adapting to climate change by water management Prod. 114, 11–32. https://doi.org/10.1016/j.jclepro.2015.09.007. organisations: Enablers and barriers. J. Hydrol. 559, 736–748. https://doi.org/ Giampietro, M., Mayumi, K., Ramos-Martin, J., 2009. Multi-scale integrated analysis of 10.1016/j.jhydrol.2018.02.047. societal and ecosystem metabolism (MUSIASEM): An Outline of Rationale and Bagstad, Kenneth J, Stapleton, Kevin, D’Agostino, John R., 2007. Taxes, subsidies, and Theory. Energy 34, 313–322. insurance as drivers of United States coastal development. Ecol. Econ. 63 (2–3), Grech, M.R., Horberry, T., Smith, A., 2002. Human error in maritime operations: 285–298. https://doi.org/10.1016/j.ecolecon.2006.09.019. Analyses of accident reports using the Leximancer tool, in: Proceedings of the Baines, C., 1982. Community involvement in creative ecology: some national problems of Human Factors and Ergonomics Society Annual Meeting. Sage Publications Sage CA: local significance., An ecological approach to urban landscape design. Workshop. Los Angeles, CA, pp. 1718–1721. Bandoc, G., Mateescu, R., Dragomir, E., Golumbeanu, M., Comanescu, L., Nedelea, A., Griggs, D., Smith, M.S., Rockström, J., Öhman, M.C., Gaffney, O., Glaser, G., Kanie, N., 2014. Systemic approach of the impact induced by climate changes on hydrothermic Noble, I., Steffen, W., Shyamsundar, P., 2014. An integrated framework for factors at the Romanian Black Sea Coast. J. Environ. Prot. Ecol. 15, 455–467. sustainable development goals. Ecol, Soc, p. 19. Barragán, J.M., de Andrés, M., 2015. Analysis and trends of the world’s coastal cities and Hoppe, R., Wesselink, A., Cairns, R., 2013. Lost in the problem: The role of boundary agglomerations. Ocean Coast. Manag. 114, 11–20. https://doi.org/10.1016/J. organisations in the governance of climate change. Wiley Interdiscip. Rev. Clim. OCECOAMAN.2015.06.004. Chang. 4, 283–300. https://doi.org/10.1002/wcc.225. Bazeley, P., 2009. Integrating data analyses in mixed methods research. Hove, T., Derman, B., Manzungu, E., 2016. Land, farming and IWRM: A case study of the Becken, S., Mahon, R., Rennie, H.G., Shakeela, A., 2014. The tourism disaster middle Manyame sub-catchment. Water Altern. 9, 531–548. vulnerability framework: An application to tourism in small island destinations. Nat. Hazards 71, 955–972. 11 D.J. Smith and B. Rodríguez-Labajos Ecological Indicators 125 (2021) 107527 Howe, C., Suich, H., Vira, B., Mace, G.M., 2014. Creating win-wins from trade-offs? Murphy, D.W.A., 2015. Theorizing climate change,(im) mobility and socio-ecological Ecosystem services for human well-being: A meta-analysis of ecosystem service systems resilience in low-elevation coastal zones. Clim. Dev. 7, 380–397. trade-offs and synergies in the real world. Glob. Environ. Chang. 28, 263–275. Narra, P., Coelho, C., Sancho, F., Palalane, J., 2017. CERA: An open-source tool for https://doi.org/10.1016/j.gloenvcha.2014.07.005. coastal erosion risk assessment. Ocean Coast. Manag. 142, 1–14. Inácio, M., Schernewski, G., Nazemtseva, Y., Baltranaitė, E., Friedland, R., Benz, J., 2018. Navarro, T., 2018. Water reuse and desalination in Spain–challenges and opportunities. Ecosystem services provision today and in the past: A comparative study in two J. Water Reuse Desalin. 8, 153–168. Baltic lagoons. Ecol. Res. 33, 1255–1274. https://doi.org/10.1007/s11284-018- Nemes, G., 2005. Integrated rural development-The concept and its operation. IEHAS 1643-8. Discuss, Pap. C. Kelble D. Loomis S. Lovelace W. Nuttle P. Ortner P. Fletcher G. Cook J. Lorenz (Jerry), Nguyen, T.T.X., Bonetti, J., Rogers, K., Woodroffe, C.D., 2016. Indicator-based Boyer, J., The EBM-DPSER conceptual model: integrating ecosystem services into the assessment of climate-change impacts on coasts: A review of concepts, DPSIR framework PLoS One 8 2013 e70766 10.1371/journal.pone.0070766. methodological approaches and vulnerability indices. Ocean Coast. Manag. 123, King, M.F., Renó, V.F., Novo, E.M.L.M., 2014. The concept, dimensions and methods of 18–43. https://doi.org/10.1016/j.ocecoaman.2015.11.022. assessment of human well-being within a socioecological context: A Literature Nunez-Mir, G.C., Iannone, B.V., Pijanowski, B.C., Kong, N., Fei, S., 2016. Automated Review. Soc. Indic. Res. 116, 681–698. https://doi.org/10.1007/s11205-013-0320- content analysis: addressing the big literature challenge in ecology and evolution. 0. Methods Ecol. Evol. 7, 1262–1272. https://doi.org/10.1111/2041-210X.12602. Knott, J., LaRue, E., Ward, S., McCallen, E., Ordonez, K., Wagner, F., Jo, I., Elliott, J., Odemerho, F.O., 2015. Building climate change resilience through bottom-up adaptation Fei, S., 2019. A roadmap for exploring the thematic content of ecology journals. to flood risk in Warri. Nigeria. Environ. Urban. 27, 139–160. https://doi.org/ Ecosphere 10, e02801. 10.1177/0956247814558194. Koricheva, J., Gurevitch, J., Mengersen, K., 2013. Handbook of meta-analysis in ecology Oppenheimer, M.B.C., Glavovic, J., Hinkel, R., van de Wal, A.K., Magnan, A., Abd- and evolution. Princeton University Press. Elgawad, R., Cai, M., Cifuentes-Jara, R.M., DeConto, T., Ghosh, J., Hay, F., Isla, B., Kronen, M., Vunisea, A., Magron, F., McArdle, B., 2010. Socio-economic drivers and Marzeion, B., Meyssignac, Z., Sebesvari, B., 2019. Sea Level Rise and Implications for indicators for artisanal coastal fisheries in Pacific island countries and territories and Low-Lying Islands. Coasts Commun. their use for fisheries management strategies. Mar. Policy 34, 1135–1143. https:// Penn-Edwards, S., 2010. Computer Aided Phenomenography: The Role of Leximancer doi.org/10.1016/j.marpol.2010.03.013. Computer Software in Phenomenographic Investigation. Qual. Rep. 15, 252–267. Kuckartz, U., Rädiker, S., 2019. Analyzing Focus Group Data, in: Analyzing Qualitative Pomeroy, R.S., Pollnac, R.B., Katon, B.M., Predo, C.D., 1997. Evaluating factors Data with MAXQDA: Text, Audio, and Video. Springer International Publishing, contributing to the success of community-based coastal resource management: the Cham, pp. 201–217. https://doi.org/10.1007/978-3-030-15671-8_15. Central Visayas Regional Project-1 Philippines. Ocean Coast. Manag. 36, 97–120. A.A. Kwasi L. Larbi P, B.A., atrick Kwabena Ofori-Danson, Impacts of Coastal Inundation Powell, R.A., Single, H.M., 1996. Focus Groups. Int. J. Qual. Heal. Care 8, 499–504. Due to Climate Change in a Remote Sens. 3 2011 2029 2050 10.3390/rs3092029. https://doi.org/10.1093/intqhc/8.5.499. Lawson, E.T., Schluchter, W., Gordon, C., 2010. Using the paired comparison Rakhmanissazly, A., Permatasari, A.I., Peranginangin, E.C., 2018. Edco-Tourism; A methodology to assess environmental values in the coastal zone of Ghana. J. Coast. coastal management program to improve social economics. IOP Conf. Ser. Earth Conserv. 14, 231–238. Environ. Sci. 116 https://doi.org/10.1088/1755-1315/116/1/012038. B. Le Gallic Fisheries Sustainability Indicators: The OECD experience., in: Joint Rasul, G., Sharma, B., 2016. The nexus approach to water–energy–food security: An Workshop EEA-EC DG Fisheries-DG Environment on“ Tools for Measuring option for adaptation to climate change. Clim. Policy 16, 682–702. https://doi.org/ (Integrated) Fisheries Policy Aiming at Sustainable Ecosystem” 2002 Brussels, 10.1080/14693062.2015.1029865. Belgium. Roy, S., Roy, M.M., Jaiswal, A.K., Baitha, A., 2018. Soil arthropods in maintaining soil Lele, S., Springate-Baginski, O., Lakerveld, R., Deb, D., Dash, P., 2013. Ecosystem health: thrust areas for sugarcane production systems. Sugar Tech 20, 376–391. services: Origins, contributions, pitfalls, and alternatives. Conserv. Soc. 11, 343–358. Saillard, E.K., 2011. Systematic versus interpretive analysis with two CAQDAS packages: Leximancer, 2019. Leximancer. NVivo and MAXQDA. Forum Qualitative Sozialforschung/Forum. Qualitative Social Li, Yi, Kappas, M., Li, Y., 2018. Exploring the coastal urban resilience and transformation Research. of coupled human-environment systems. J. Clean. Prod. 195, 1505–1511. https:// Sharples, C., Mount, R., Pedersen, T., Lacey, M., Newton, J., Jaskierniak, D., Wallace, L., doi.org/10.1016/j.jclepro.2017.10.227. 2009. The Australian coastal smartline geomorphic and stability map version 1: Lins-de-Barros, F.M., Muehe, D., 2013. The smartline approach to coastal vulnerability project report. Prep. Geosci. Aust. Dep. Clim. Chang. by Sch. Geogr. Environ. Stud. and social risk assessment applied to a segment of the east coast of Rio de Janeiro Univ. Tasmania, Hobart. State. Brazil. J. Coast. Conserv. 17, 211–223. Sherman, K., 2014. Toward ecosystem-based management (EBM) of the world‫ ׳‬s large Loomis, D.K., Paterson, S.K., 2014. Human dimensions indicators of coastal ecosystem marine ecosystems during climate change. Environ. Dev. 11, 43–66. services: A hierarchical perspective. Ecol. Indic. 44, 63–68. https://doi.org/ Sorensen, J., 1993. The international proliferation of integrated coastal zone 10.1016/j.ecolind.2013.12.022. management efforts. Ocean Coast. Manag. 21, 45–80. https://doi.org/10.1016/ Magpayo, N., 1995. Integrated approach to community-based coastal resources 0964-5691(93)90020-Y. management. In: Visayas-Wide CB-CRM and Fisheries Co-Management Conference. Stojanovic, T., McNae, H.M., Tett, P., Potts, T.W., Reis, J., Smith, H.D., Dillingham, I., ECOTECH Center, Lahug, Cebu City, pp. 4–7. 2016. The “social” aspect of social-ecological systems. Ecol. Soc. 21. Maliao, R.J., Pomeroy, R.S., Turingan, R.G., 2009. Performance of community-based Stronkhorst, J., Levering, A., Hendriksen, G., Rangel-Buitrago, N., Appelquist, L.R., 2018. coastal resource management (CBCRM) programs in the Philippines: A meta- Regional coastal erosion assessment based on global open access data: A case study analysis. Mar. Policy 33, 818–825. for Colombia. J. Coast. Conserv. 22, 787–798. https://doi.org/10.1007/s11852-018- Marín-Monroy, E.A., Ojeda-Ruiz de la Peña, M.Á., 2016. The role of socioeconomic 0609-x. disaggregated indicators for fisheries management decisions: The case of Magdalena- Suinyuy, N., Xue, X., Banyouko Ndah, A., 2016. Exploring the challenges of Almejas Bay. BCS. Mexico. Fish. Res. 177, 116–123. https://doi.org/10.1016/j. implementing integrated coastal management and achieving sustainability within fishres.2016.01.009. the cameroon coastline. Rev. Gestão Costeira Integr./J. Integr. Coast. Zo. Manag. 16 Matzdorf, B., Biedermann, C., Meyer, C., Nicolaus, K., Sattler, C., Schomers, S., 2014. https://doi.org/10.5894/rgci648. Paying for Green? 207. Sullivan, K., Thomas, S., Rosano, M., 2018. Using industrial ecology and strategic MAXQDA, 2020. MAXQDA. management concepts to pursue the Sustainable Development Goals. J. Clean. Prod. McCallen, E., Knott, J., Nunez-Mir, G., Taylor, B., Jo, I., Fei, S., 2019. Trends in ecology: 174, 237–246. Shifts in ecological research themes over the past four decades. Front. Ecol. Environ. Sylla, M.B., Nikiema, P.M., Gibba, P., Kebe, I., Klutse, N.A.B., 2016. Climate Change over 17, 109–116. West Africa: Recent Trends and Future Projections, in: Yaro, J.A., Hesselberg, J. McCarter, J., Sterling, E.J., Jupiter, S.D., Cullman, G.D., Albert, S., Basi, M., Betley, E., (Eds.), Adaptation to Climate Change and Variability in Rural West Africa. Springer Boseto, D., Bulehite, E.S., Harron, R., Holland, P.S., Horning, N., Hughes, A., International Publishing, Cham, pp. 25–40. https://doi.org/10.1007/978-3-319- Jino, N., Malone, C., Mauli, S., Pae, B., Papae, R., Rence, F., Revo, O., Taqala, E., 31499-0_3. Taqu, M., Woltz, H., Filardi, C.E., 2018. Biocultural approaches to developing well- M.K. Tefe Framework for integrating indigenous and scientific knowledge for being indicators in Solomon Islands. Ecol, Soc, p. 23. transportation planning in developing countries 2012 https://doi.org/10.14188/ Meng, B., Chi, G., 2018. Evaluation index system of green industry based on maximum j.2095-6045.2012.06.011. information content. Singapore Econ. Rev. 63, 229–248. https://doi.org/10.1142/ Thaler, T., Levin-Keitel, M., 2016. Multi-level stakeholder engagement in flood risk S0217590817400094. management-A question of roles and power: Lessons from England. Environ. Sci. Micallef, S., Micallef, A., Galdies, C., 2018. Application of the Coastal Hazard Wheel to Policy 55, 292–301. https://doi.org/10.1016/j.envsci.2015.04.007. assess erosion on the Maltese coast. Ocean Coast. Manag. 156, 209–222. https://doi. E.R. Thieler E.S. Hammar-Klose National assessment of coastal vulnerability to sea-level org/10.1016/j.ocecoaman.2017.06.005. rise 1999 US Atlantic Coast. Minar, M.H., Hossain, M.B., Shamsuddin, M.D., 2013. Climate change and coastal zone Tian, H., Lindenmayer, D.B., Wong, G.T.W., Mao, Z., Huang, Y., Xue, X., Lindenmayer, D. of Bangladesh: vulnerability, resilience and adaptability. Middle-East J. Sci. Res. 13, B., Wong, G.T.W., Mao, Z., Huang, Y., Xue, X., 2018. A methodological framework 114–120. for coastal development assessment: A case study of Fujian Province. China. Sci. Miswar, E., Natasya, D., Irham, M., Aprilla, R.M., Agustina, S., Affan, J.M., 2018. Total Environ. 615, 572–580. https://doi.org/10.1016/j.scitotenv.2017.09.309. Analysis of social and economic aspects of management of marine and coastal United Nations, 2005. Standard country or Area Codes for Statistical Use [https://stats. resources based on EAFM (Ecosystem Approach to Fisheries Management) method in oecd.org/glossary/detail.asp?ID=6326]. Series M, No. 49, Rev. 4 (United Nations Banda Aceh City. IOP Conf. Ser. Earth Environ. Sci. 216 https://doi.org/10.1088/ Publ. Sales No. M.98.XVII.9). 1755-1315/216/1/012034. Van Dongeren, A., Ciavola, P., Martinez, G., Viavattene, C., Bogaard, T., Ferreira, O., Mollah, S., 2016. Assessment of flood vulnerability at village level for Kandi block of Higgins, R., McCall, R., 2018. Introduction to RISC-KIT: Resilience-increasing Murshidabad district, West Bengal. Curr. Sci. 110, 81–86. https://doi.org/10.18520/ strategies for coasts. Coast. Eng. 134, 2–9. cs/v110/i1/81-98. 12 D.J. Smith and B. Rodríguez-Labajos Ecological Indicators 125 (2021) 107527 Van Eijck, J., Romijn, H., Smeets, E., Bailis, R., Rooijakkers, M., Hooijkaas, N., P.P. Wong I.J. Losada J.-P. Gattuso J. Hinkel A. Khattabi K.L. McInnes Y. Saito A. Verweij, P., Faaij, A., 2014. Comparative analysis of key socio-economic and Sallenger 2014. Coastal systems and low-lying areas, in: Field, C.B., V.R. Barros, D.J. environmental impacts of smallholder and plantation based jatropha biofuel Dokken, K.J.M., M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, production systems in Tanzania. Biomass Bioenergy 61, 25–45. https://doi.org/ R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and 10.1016/j.biombioe.2013.10.005. L.L.W. (Eds.), Climate Change, Impacts, Adaptation, and Vulnerability 2014 Vugteveen, P., Rouwette, E., Stouten, H., van Katwijk, M.M., Hanssen, L., 2015. Cambridge University Press Cambridge, United Kingdom and New York, NY, USA Developing social-ecological system indicators using group model building. Ocean 361 409. Coast. Manag. 109, 29–39. Yun, J.J., Liu, Z., 2019. Micro- and macro-dynamics of open innovation with a Wavrek, M., Heberling, J.M., Fei, S., Kalisz, S., 2017. Herbaceous invaders in temperate quadruple-helix model. Sustainability 11, 3301. https://doi.org/10.3390/ forests: a systematic review of their ecology and proposed mechanisms of invasion. su11123301. Biol. Invasions 19, 3079–3097. Zaldívar-Jiménez, M.A., Herrera-Silveira, J.A., Teutli-Hernández, C., Comín, F.A., Werner, S.R., Spurgeon, J.P.G., Isaksen, G.H., Smith, J.P., Springer, N.K., Gettleson, D.A., Andrade, J.L., Molina, C.C., Ceballos, R.P., 2010. Conceptual framework for N’Guessan, L., Dupont, J.M., 2014. Rapid prioritization of marine ecosystem services mangrove restoration in the Yucatán Peninsula. Ecol. Restor. 28, 333–342. and ecosystem indicators. Mar. Policy 50, 178–189. https://doi.org/10.1016/j. Zhu, D.-S., Zhang, J.-Y., Liao, W.-G., Shi, X.-X., Cheng, H.-G., Li, Y., 2010. A key marpol.2014.03.020. ecological indicator system for water project planning and design. Shuikexue Jinzhan/Adv. Water Sci. 21, 560–566. 13