The Role of Meso-level Organizations in Climate Adaptation for Small-Scale Producers in Sub-Saharan Africa-insights from four African Countries

The Role of Meso-level Organizations in Climate Adaptation for Small-Scale Producers in Sub-Saharan Africa-insights from four African Countries | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Analysis The Role of Meso-level Organizations in Climate Adaptation for Small-Scale Producers in Sub-Saharan Africa-insights from four African Countries Darlington Sibanda, Eric Welch, Hallie Eakin, Awulatu Abigail Apuryinga, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6937506/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This analysis examines the meso-level organizations (MLOs) that are core climate change adaptation (CCA) actors responsible for interweaving micro-level rural community needs with macro-level policy and finance intentions, using qualitative data from four countries in Africa: Ghana, Kenya, Malawi, and South Africa. Findings show that MLOs involved in CCA comprise a complex group of organizational actors that operate across geographies and social contexts, and manifest substantially different capacities and functions, which create dependencies and opportunities for synergy that form the basis of partnering and networking critical for carrying out CCA. Because MLOs bridge macro-level policy/finance and micro-level CCA beneficiaries they have greater influence on CCA than is currently recognized. Findings generate insights about the vulnerability of the organizations in the CCA meso-level and the potential implications of changes in financial support will have for ultimate beneficiaries Earth and environmental sciences/Climate sciences/Climate change/Climate-change impacts Scientific community and society/Agriculture climate change adaptation meso-level organization small-scale producer organization attributes farming communities Ghana Kenya Malawi South Africa Figures Figure 1 Figure 2 Figure 3 Introduction This analysis generates an empirically-based foundation for advancing understanding of intermediary organizations – i.e., “meso-level organizations” or MLOs – that implement planned adaptation interventions for small scale producers (SSPs). MLOs, which include civil society, media, private sector and government organizations, play critical roles in planned adaptation by connecting farmers to resources, knowledge, and policy frameworks while promoting equitable, localized, and scalable solutions (Figure 1). Greater transparency and understanding of MLOs can improve the effectiveness and intelligent scaling of investments (1) . This is particularly important as more attention shifts towards enabling CCA in increasingly resource constrained environments. The study extends limited existing work (2-4) to capture a more comprehensive set of organizational attributes, functions and capacities. We ask: How can we describe MLOs involved in CCA activities targeting SSPs?; What are the institutional settings in which MLOs operate?; and What are the roles, functions and capacities that MLOs describe as central to CCA work? We make use of interview data collected from representatives of 70 MLOs in Kenya, Malawi and Ghana, South Africa in 2023 (see methods section). Interviews captured organizations’ missions, functions, capacities, funding sources, target beneficiaries and other elements. We organize our findings in four main sections: (1) broad profiles; (2) climate change adaptation mission and effort; (3) institutional settings, including funding source and targeted beneficiaries; and (4) functions and capacities. Where valuable, we provide country-level comparisons. Appendices present data on traditional characteristics of MLOs including geographic scope, age, size, and qualitative examples from interviews. Results MLO broad profiles, climate change adaptation commitment and work A first step to understanding the roles of MLOs in CCA is to gain a sense of their size, geographic scope, time in operation, as well as the sector in which they operate. These characteristics can provide some insight into their relative experience and operational orientation. For example, the time in operation provides insights into the organization’s level of experience and stability in relation to CCA. Older organizations may be more central in a network and more influential either at the micro- or macro-level. Variation of new and established MLOs is also indicative of the dynamic nature of the population of organizations and the potential for influx of new technologies, knowledge or innovative approaches as the imperative of adaptation increases. This is important because it provides insights into the readiness and potential leadership of MLOs to undertake CCA initiatives. Findings show that MLOs are typically of moderate size (figures AF1 to AF4). About one-quarter (26%) of interviewed MLOs are small (less than ten employees), while just under half (44%) have ten to fifty employees, and another one-third are larger than 50 up to 250 employees. A final group (8%) are very large with over 250 employees. MLO size varies by country. Organizations are larger on average in Kenya than in Malawi or Ghana. Notably, 15% of organizations in Kenya have more than 250 employees, compared to 5% in Ghana and 4% in Malawi. In all countries, most MLOs range between ten and fifty employees. In terms of time in operation, few MLOs in the study were young; only 17% were less than 15 years old. Half have been active for 15 to 30 years, while another one-third (31%) have operated for more than thirty years. Most MLOs in the study operate in multiple geographic domains within the country, with only 12.5% reporting operations in a single domestic location. Additionally, about half operate in multiple countries in Africa and about one-third have activities in continents other than Africa. This supports the idea that a substantial proportion of these organizations have been operating for some time across wide geographical, cultural, economic and political domains. The MLO landscape includes different types of organizations. Guided by literature, the project defined distinct types of MLOs to guide our analysis to code the interviews (5-7). Results (table 1) show that local non-profit / community-based organizations (NPO/CBO) are the most common type of MLO, followed by International NPO, government organizations, and private sector organizations. Findings show comparatively few parastatal organizations, universities, companies or other international organizations (international multilateral or bilateral). As the MLOs in our study were selected because of their known involvement in CCA (see methods section), future work should ensure a fully representative sample of organizations conducting CCA work, even if such work is incidental to their primary missions (e.g., value chain actors involved indirectly in climate resilient agriculture). The table in appendix AT1 provides more detail by illustrating three types of organizations interviewed: local NGOs/CBOs, international NGOs, and private sector entities. --- Place Table 1 Here ---- Overall, the findings show that the profiles of the MLOs that make up this review are larger, older and have a greater domestic geographic range than might be expected. This indicates that many MLOs are relatively stable, experienced and have relatively expansive footprints across diverse localities. The findings also suggest that many organizations may have moved into the adaptation space from other missions or focal areas. MLO climate change adaptation commitment and work As investment in climate change adaptation programs and projects has increased in recent decades (8, 9), the organizational landscape has also strategically shifted to align its work. The extent to which organizations identify CCA as a core mission captures centrality of CCA in its overall work portfolio and provides insight into mobilization of organizational capacity for CCA. Investigating the overlap of CCA with other areas of focus, such as agricultural development or agroecology, helps understand the range of MLO portfolios, identify areas of cross-learning, and discern areas of specialization. Here we examine three indicators of MLO CCA work orientation coded from our interviews: thematic focus of MLO work, MLO commitment to CCA as a core mission, and CCA activity undertaken by the MLO. The coding protocol defined several areas of thematic focus including CCA, business or entrepreneurship, gender, equality, youth empowerment, conservation or environment, climate science, communication, and disaster and risk management, among others. Reflecting the fact that MLO engagement in CCA for small scale farmers was a selection criterion for the study, 59% of MLOs responded that CCA was a thematic focus of the work they do, and 50% indicated a primary focus on agricultural development. Other areas of thematic foci were environment and conservation (38%), women, gender and equality (29%), disaster and risk management (12%), communication and information technology (12%), youth empowerment (12%), and business and entrepreneurship (12%). Fifty percent of the respondents identified additional areas of thematic focus not specifically presented here. Most of the MLO have multiple, overlapping mission orientations and work across multiple domains, potentially integrating CCA in different activities. Relatively few MLOs (15%) mentioned only one thematic focus; 35% mentioned two, 24% described three thematic focal areas, and 11% named four or more. Although this complexity likely has many determinants – prior experience, opportunity environment, funder and policy demands – it is broadly indicative of the reality of integrated problem solving needed for CCA work with SSPs. It is also possible that cross-theme learning benefits MLOs and facilitates strategic positioning of new work. Our second indicator is a four-category ordinal measure that captures the extent of MLO commitment to CCA as a mission. The four categories are: limited, moderate, strong and core CCA commitment. Perhaps unsurprising given our selection criteria, findings show that 10% of the participating organizations had a limited CCA mission, while one-quarter (26%) have a moderate focus and over one-third (39%) have a strong focus. Only one-quarter (25%) of organizations have CCA as a core mission. Hence, the CCA mission of most organizations overlaps with other areas of commitment. Table 2 shows that Kenya and South Africa have more MLOs reporting CCA as a core mission as compared to Malawi and Ghana. Examples presented in appendix AT2 provide additional qualitative detail by presenting one organization with a low level CCA mission and another with a core CCA mission. --- Place Table 2 Here ---- Finally, the interviews captured the profile of diverse climate change work activities in which MLOs are involved. Table 3 shows that just 30% are involved in CCA awareness and education, 25% in policy or advocacy, 22% in smart agriculture practices, and 14% each in agroecology and climate and information systems. --- Place Table 3 Here ---- Institutional Setting Given our interviewee selection criteria, as expected the interview data show that most MLOs target SSPs as a key beneficiary (77%), although some MLOs focus on specific social groups, such as women and youth, or on other types of actors in the system as part of their CCA work. For example, 10% of the MLOs identified women as a general targeted beneficiary, while another 10% targeted youth, indicating that they work to advance women and youth issues more generally including at meso- and macro-levels. In addition, 13% of MLOs identify government actors as their target beneficiaries. These findings suggest that some MLOs influence vertically or horizontally to effect change. Appendix AT3 provides further detail with examples of MLOs influence orientation, with some facing vertically up or down, and others facing horizontally toward other MLOs. The source of funding of an MLO for CCA can provide some insight into the importance of particular financial flows and institutional dependency relations between the meso- and macro-level. MLOs are often shaped by institutional context (10-12). Specifically, the source of funding likely shapes the orientation of CCA activities in which MLOs engage. The coding protocol defined several categories of MLO funding, including multilateral, bilateral, international NPO, government, private sector and other sources. Overall, of the 70 total MLOs, 15 had undetermined funding. Of the remaining 55 MLOs, 23 (42%) were found to have only one source of funding, while 32 (58%) identified bilateral funding as a funding source. Seven of the 23 of the single source MLOs (30%, 13% overall) are dependent only on bilateral funding, while 30 (55%) are dependent on multilateral funding. Notably, given the recent elimination of USAID support, 27 out 70 (39%) organizations mentioned that they received funding from USAID. A country-level breakdown (figure 2) shows that MLOs in Ghana, Kenya and Malawi are most dependent on multilateral, bilateral and international NPOs for funding. For instance, 63% of MLOs in Ghana and 50% in Kenya reported that they were funded by International NPOs. Multilateral and bilateral funding sources provide funding for most MLOs in Ghana, Kenya and Malawi. In South Africa, close to 40% MLOs reported bilateral partners to be their main source of funding. --- Place Figure 2 Here ---- MLO Capacities and Functions Capturing MLO perceptions of their capacities and functions in CCA offers insight into the practical demands of CCA work and the resources mobilized to support. Table 4 provides descriptions of the key capacities identified in this study. Capacities are distributed across organizations such that the highest commonly reported capacity, agriculture development capacity, is found in less than 40% of the MLOs. Other key MLO capacities reported include in-house gender expertise, gender policy/strategy and infrastructure capacity. Fewer MLOs reported to rely on external monitoring and evaluation expertise (2%). --- Place Table 4 Here ---- Drawing from literature (13-15), this study identified the following key functions performed by MLOs. Findings (appendix AF5) show that the majority of the MLOs reported that they performed trainer or educator functions (88%). Other common functions are advocacy (57%), knowledge interpretation (52%) and convener (49%), all highlighting MLO roles as intermediaries. Notably, in our data, training and knowledge interpretation often referred to gender sensitivity training or support for climate information services (CIS). Some of the less common functions are related to specific products and services including, technology producer (10%), village savings and loans (7%), and risk insurance (3%). Despite studies showing that technology and related innovations are critical for CCA targeting SSPs (16, 17), few MLOs identify this function. Importantly, our study shows that MLOs rarely perform a single function, and they tend to learn towards combination of functions (e.g MLOs which perform knowledge producer function, can also be involved as knowledge interpreters and trainers). Regardless of whether an MLO has specific expertise or organizational capacity, they can find themselves performing specific functions in relation to CCA projects and programs. Ideally, these functions do correspond to specific capacity profiles, and to the different sectors and beneficiary orientations of the organization. Our data (Figure 2) indicate that local NPO/CBOs and, to a lesser extent, international NPOs, perform a greater variety of functions compared to other MLO types. Private sector and university/research have a strong presence in knowledge production, technology production, and risk insurance. On the other hand, multilateral and bilateral MLOs are active in finance supply, training/education, and resource distribution functions, suggesting they are more likely to be playing the role of coordinating and executing agencies. --- Place Figure 3 Here ---- Appendix AT4 presents examples of a private business entity and local CBO/NPO involved in gender and CIS efforts. While the primary motivation of private entities is profit, there is commitment to addressing equity issues such as gender. AT4 also demonstrates that technology innovation related to CIS is central to private entities while local CBO/NPO focuses on community engagement, capacity building and advocacy. It is reasonable to expect a positive relationship between functions and capacities, where organizations with more capacity can take on more functions. It is possible that the relationship between capacities and functions is endogenous, such that organizations taking on additional functions will gain experience and learn, giving it new capacities. As expected, we find a relatively tight relationship between the number of MLO capacities and the number of MLO functions (see figure in appendix AF6). The qualitative examples in appendix AT5 provide more detailed qualitative examples of mixtures of MLO capacities and functions. The variation in capacity and function across MLOs may create opportunities for niche-oriented bundling or gap identification needed for partner identification and collaboration. Discussion This work provides a baseline characterization of the organizational landscape and serves as a foundation for improving understanding of the constellation of MLOs working on CCA in sub-Saharan Africa and laying the groundwork for future research. MLOs are generally capable and stable actors that are likely more influential for enabling climate change adaptation than currently recognized. Most of the organizations interviewed had relatively long histories, were moderately sized and worked across national and international locations suggesting a wealth of experience that may constitute a significant asset in efforts to enhance locally-led adaptation work. Interview respondents often described their movement into CCA from other humanitarian, agricultural development, environmental or social missions as new funding opportunities arose, and as climate change impacts affected their core mission and beneficiaries. These prior experiences likely inform their CCA work and create synergies with other development objectives — which could be a powerful way to address SDG tradeoffs and synergies (18). The MLO role of knowledge broker supports the development of innovative practices and adaptive approaches, ultimately enhancing agricultural productivity and supporting more informed decision-making processes (19, 20). The diversity of other functions and high variation of capacities and specializations among MLOs suggest that they are strategic about the CCA roles they play and the skills they offer, playing to strengths, creating opportunities for partnering and generating interest from funders. These findings support prior studies anticipating the critical linkages MLOs play in CCA (2, 3, 21). It is also evident that while all of our interviewees were involved in CCA for agricultural development (as a selection criteria), the orientation of their activities varied, with some more oriented towards macro-level (finance and policy), while others orient towards meso-level organizations or micro-level SSPs. Although more refined analysis is needed, the evidence suggests that MLOs are likely finding strategic niches in the CCA organizational landscape, playing complementary functions and roles with distinct capacities. Overlapping and competitive positions in this landscape are also likely; redundancies could potentially enhance system level resilience for CCA, but in the absence of coordination could also lead to inefficiencies and ineffectiveness. Although MLOs have diverse capacities and play important functions as intermediaries in CCA efforts, they are also vulnerable. Most of the MLOs in climate change adaptation are civil society organizations that self-identify as local NGOs or CBOs, and although some are larger, over 40% have fewer than 20 employees. This suggests they may have fewer available resources to bridge funding gaps. Additionally, MLOs are highly reliant on one or two bilateral or multilateral funding sources, which, as recent policy shifts in the United States have demonstrated, can put them in precarious financial circumstances. Given their vulnerability, it is likely that the next few years will witness high levels of competition among MLOs for ever- scarcer funding. In face of perceived unsustainable philanthropic and donor funding schemes, many international donors and multilateral institutions are leaning into greater private sector participation in CCA, with the expectation that returns on investment in more climate resilient development will provide broader and more sustained benefits (22). Nevertheless, we found relatively few MLOs identified with the private sector in our sample. While this may be an artefact of the sampling approach and research design, it also is consistent with research that has identified risks for private sector actors to engage in CCA, associated with political and economic instability, inadequate regulatory environment, and lack of trust create high barriers to entry (7, 23). In the near future, MLO capacities on the one hand and vulnerabilities on the other are likely to shape climate change adaptation impacts on the ground, especially for rural farm-dependent communities. The study shows that most MLOs have multiple ‘mission orientations’ of which climate change adaptation is only one. Given their skills and strategic capabilities, agile organizations may redirect their focus in the near term, away from CCA, toward areas that provide better funding opportunities. Some MLOs may cease operating. Nevertheless, the current dynamics of the international funding environment may also motivate some international donors to double-down on efforts to enhance the autonomy and vitality of national and sub-national organizational networks and value chains involved in CCA. Either way, understanding the capacities and potential vulnerabilities of the organizational landscape for CCA will be critical to avoid cascading negative impacts on SSPs. ONLINE METHODS This paper is part of a larger research project entitled Accelerating Climate Adaptation via Meso-level Integration (ACAMI). We undertook 78 interviews with representatives of meso-level organizations from Ghana, Kenya, Malawi and South Africa. These four countries are significantly impacted by climate change and facing pressing development challenges such as poverty and inequality (18, 24). In Ghana, Kenya and Malawi, SSPs play a significant role in agriculture production and other related socio-economic benefits. MLO representatives were drawn from a new relational database (RD) which was designed and developed by the ACAMI project team. This RD contains 195 MLOs, 109 projects and 192 contact people from Ghana, Kenya, Malawi and South Africa. The process of developing the RD started with a scoping exercise of projects, MLOs and organizational contacts involved in the implementation of climate change adaptation targeted as SSPs in the period 2015-2023 in the four selected countries. We made the best effort to reach out to any and all implementing organizations affiliated with internationally and nationally funded adaptation initiatives. Methods table MT1 below shows the criteria for selection of MLOs and associated projects to include in the RD. The criteria outlined above was complemented with a codebook (Supplementary Material), which provided the parameters, categories and subsets used in populating the ACAMI RD. This protocol guided the removal of duplicates as well as ensuring that entries were properly captured on the RD. Various strategies were used to identify MLOs for the paper (figure MF1). The initial stage involved selection of MLOs and projects from the Transforming Social Inequalities through Inclusive Climate Action (TSITICA) project database (For more details about the TSITICA project, visit https://tsitica.uct.ac.za/). The TSITICA database contains both CCA and Mitigation projects implemented during the period 2000 to 2020 in Ghana, Kenya and South Africa. The distribution of projects in the TSITICA database is Ghana=126; Kenya=157 and South Africa =652. From this database, ACAMI team drew an initial list of CCA projects, focusing on projects from 2015 to 2020. Mitigation projects and other projects which did not meet the criteria (Table M1) were excluded. Malawi was not part of the TSITICA project, so the ACAMI team searched for funder websites and other known sources. In addition, specialized databases were acquired for Malawi with the assistance of the ACAMI project advisory board member. These include: (i) Malawi Adaptation Inventory; (ii) Malawi Stakeholder Mapping and (iii) Database of Development partners working in the Agriculture Sector. Other databases accessed to expand the inventory of MLOs and projects for all four countries included the Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA), Bill & Melinda Gates Foundation (BMGF), Adaptation Fund, and Climate Funds Update (CFU), among others. Furthermore, in the context of South Africa, contacts from the Department of Forestry, Fisheries and the Environment provided an updated centralized database from MLOs, projects and contact people were selected and added to the RD. During this stage of developing the RD, data were captured from the databases and complemented by publicly available information such as websites. After initially capturing data on three separate MS Access files, they were merged at a later stage. For analytical purposes, we drew from literature some normative categorizations of MLOs (13-15, 25). As demonstrated by the earlier discussion of organizational theory, these categories are only useful as analytical tools, because organizations are much more complex and constantly adapting to their environment and at the same time changing it. Using the information from the RD, MLO representatives were selected and contacted in each country. In total, 78 interviews with MLO representatives and experts were conducted both virtually and in-person in Ghana, Kenya, Malawi and South Africa between October 2023 and January 2024. The duration of these interviews was usually between an hour and 2 hours. Follow-up interviews were arranged and conducted with MLO representatives depending on the need and availability. For the purposes of this landscape analysis, 4 expert interviews were excluded and only 74 interviews with MLO representatives were considered. Because three of the interviews were follow-ups, the total number of MLOs interviewed is 70. Interview transcripts were imported into MAXQDA for qualitative thematic analysis. MAXQDA was selected for its robust capabilities in managing, coding, and analyzing large volumes of qualitative data, as well as its advanced tools for visualizing code relationships and supporting collaborative analysis (26, 27). A detailed codebook was developed iteratively prior to coding, with multiple rounds of trial coding conducted to ensure intercoder reliability across the geographically dispersed team. Once all coding was completed, SPSS statistical software was used to conduct the descriptive analysis presented in this paper. Results were presented using simple graphs, tables and other relevant charts. Our study relies primarily on qualitative interviews, introducing some uncertainty regarding variable interpretation and interviewer perspectives. However, we conducted enough interviews to ensure a clear understanding of the data. While semi-structured interviews offer depth and flexibility, they are challenging to standardize and analyze, as their success depends on the interviewer’s ability to probe effectively while maintaining focus. As a result, the depth and breadth of responses vary. To mitigate this, we provided multiple rounds of interviewer training and conducted interviews in pairs to enhance complementarity and accountability. Additionally, since interviews were conducted with employees within organizations, responses may have been influenced by their specific roles and tasks, potentially leading to variations if another employee from the same organization were interviewed. 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West African Journal of Applied Ecology. 2018;26:56-72. Kuckartz U, Rädiker S. Analyzing qualitative data with MAXQDA: Springer; 2019. Gizzi MC, Rädiker S. The practice of qualitative data analysis: Research examples using MAXQDA: BoD–Books on Demand; 2021. Tables Tables are available in the Supplementary Files section. Additional Declarations There is NO Competing Interest. Supplementary Files TableMT1andFigureM1.docx APPENDICES.docx Tables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6937506","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Analysis","associatedPublications":[],"authors":[{"id":482213132,"identity":"c4f7c59d-be7a-46be-b708-226bec7373b3","order_by":0,"name":"Darlington 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University","correspondingAuthor":false,"prefix":"","firstName":"Eric","middleName":"","lastName":"Welch","suffix":""},{"id":482213134,"identity":"757c769b-552a-4050-9c74-a929d3a64176","order_by":2,"name":"Hallie Eakin","email":"","orcid":"","institution":"School of Sustainability, Arizona State University","correspondingAuthor":false,"prefix":"","firstName":"Hallie","middleName":"","lastName":"Eakin","suffix":""},{"id":482213135,"identity":"bf04b29f-312c-4550-8517-f9d5d3012e2b","order_by":3,"name":"Awulatu Abigail Apuryinga","email":"","orcid":"","institution":"Independent Consultant","correspondingAuthor":false,"prefix":"","firstName":"Awulatu","middleName":"Abigail","lastName":"Apuryinga","suffix":""},{"id":482213136,"identity":"92d84c5b-3cd7-4fc1-a9e1-beb2ae8656db","order_by":4,"name":"Nadine Methner","email":"","orcid":"","institution":"African Climate \u0026 Development Initiative, University of Cape Town","correspondingAuthor":false,"prefix":"","firstName":"Nadine","middleName":"","lastName":"Methner","suffix":""},{"id":482213137,"identity":"71f3cc67-05d3-4f45-ad3b-24a4b34426cd","order_by":5,"name":"Ekua Semuah Odoom","email":"","orcid":"","institution":"African Climate \u0026 Development Initiative, University of Cape Town","correspondingAuthor":false,"prefix":"","firstName":"Ekua","middleName":"Semuah","lastName":"Odoom","suffix":""},{"id":482213138,"identity":"01192e06-98d4-4df5-90a9-b62a9e334f2b","order_by":6,"name":"Washington Kanyangi","email":"","orcid":"","institution":"Africa Research \u0026 Impact Network","correspondingAuthor":false,"prefix":"","firstName":"Washington","middleName":"","lastName":"Kanyangi","suffix":""},{"id":482213139,"identity":"cfe8292f-2588-420e-b3f6-89218f73c57a","order_by":7,"name":"Ruth Magreta","email":"","orcid":"","institution":"Lilongwe University of Agriculture and Natural Resources, Africa Centre of Excellence in Agricultural Policy Analysis, Lilongwe, Malawi","correspondingAuthor":false,"prefix":"","firstName":"Ruth","middleName":"","lastName":"Magreta","suffix":""},{"id":482213140,"identity":"c040017d-a86d-4bea-ae55-cbd0e53a55cd","order_by":8,"name":"Mattia Caldarulo","email":"","orcid":"","institution":"Department of Public Policy, Rochester Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Mattia","middleName":"","lastName":"Caldarulo","suffix":""}],"badges":[],"createdAt":"2025-06-20 09:30:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6937506/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6937506/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86264684,"identity":"8e868f80-be4c-450b-8294-4c18625a870c","added_by":"auto","created_at":"2025-07-08 15:28:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":323024,"visible":true,"origin":"","legend":"\u003cp\u003eVisualizing Meso-Level Organizations\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6937506/v1/263c3959a40d788f48232a41.png"},{"id":86264689,"identity":"13a44c8f-db94-4f3d-a394-0485f60e198d","added_by":"auto","created_at":"2025-07-08 15:28:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":306045,"visible":true,"origin":"","legend":"\u003cp\u003eClimate Change Adaptation Funding Source by Country, with Data Definitions\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6937506/v1/635794e5a778d5245b351caa.png"},{"id":86264956,"identity":"9de461ca-31e9-44dc-8d9d-b512aa75a719","added_by":"auto","created_at":"2025-07-08 15:36:26","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":181434,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of Functions, Local NPOs Compared to International NPOs\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6937506/v1/1a0081a27133fb8ddcb30a3b.png"},{"id":94729964,"identity":"2156bf55-fca4-4866-8ae9-f276cab61fbd","added_by":"auto","created_at":"2025-10-30 07:05:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1142404,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6937506/v1/6430f240-ae84-4eb4-81ef-d60c8f4a093a.pdf"},{"id":86264685,"identity":"286a9a6d-b42b-4e86-933f-7787f3084ed3","added_by":"auto","created_at":"2025-07-08 15:28:26","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":217759,"visible":true,"origin":"","legend":"","description":"","filename":"TableMT1andFigureM1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6937506/v1/1f5aa999d82e2d6cb19c3867.docx"},{"id":86264686,"identity":"f2fc257a-6247-47c3-9b60-40f0cdcac188","added_by":"auto","created_at":"2025-07-08 15:28:26","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":586635,"visible":true,"origin":"","legend":"","description":"","filename":"APPENDICES.docx","url":"https://assets-eu.researchsquare.com/files/rs-6937506/v1/480cd91df0fe983e0919a51c.docx"},{"id":86264687,"identity":"5648d8f3-0675-4928-8ebb-2b6afa96734e","added_by":"auto","created_at":"2025-07-08 15:28:26","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1013084,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-6937506/v1/fbbca46228ddb2fce39f3c84.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"\u003cp\u003eThe Role of Meso-level Organizations in Climate Adaptation for Small-Scale Producers in Sub-Saharan Africa-insights from four African Countries\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThis analysis generates an empirically-based foundation for advancing understanding of intermediary organizations \u0026ndash; i.e., \u0026ldquo;meso-level organizations\u0026rdquo; or MLOs \u0026ndash; that implement planned adaptation interventions for small scale producers (SSPs). MLOs, which include civil society, media, private sector and government organizations, play critical roles in planned adaptation by connecting farmers to resources, knowledge, and policy frameworks while promoting equitable, localized, and scalable solutions (Figure 1). Greater transparency and understanding of MLOs can improve the effectiveness and intelligent scaling of investments (1) . This is particularly important as more attention shifts towards enabling CCA in increasingly resource constrained environments.\u003c/p\u003e\n\u003cp\u003eThe study extends limited existing work (2-4) to capture a more comprehensive set of organizational attributes, functions and capacities. We ask:\u0026nbsp;How can we describe MLOs involved in CCA activities targeting SSPs?; What are the institutional settings in which MLOs operate?; and What are the roles, functions and capacities that MLOs describe as central to CCA work?\u003c/p\u003e\n\u003cp\u003eWe make use of interview data collected from representatives of 70 MLOs in Kenya, Malawi and Ghana, South Africa in 2023 (see methods section). \u0026nbsp;Interviews captured organizations\u0026rsquo; missions, functions, capacities, funding sources, target beneficiaries and other elements. We organize our findings in four main sections: (1) broad profiles; (2) climate change adaptation mission and effort; (3) institutional settings, including funding source and targeted beneficiaries; and (4) functions and capacities. Where valuable, we provide country-level comparisons. Appendices present data on traditional characteristics of MLOs including geographic scope, age, size, and qualitative examples from interviews. \u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cu\u003eMLO broad profiles, climate change adaptation commitment and work\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eA first step to understanding the roles of MLOs in CCA is to gain a sense of their size, geographic scope, time in operation, as well as the sector in which they operate. These characteristics can provide some insight into their relative experience and operational orientation. For example, the time in operation provides insights into the organization\u0026rsquo;s level of experience and stability in relation to CCA. Older organizations may be more central in a network and more influential either at the micro- or macro-level. \u0026nbsp;Variation of new and established MLOs is also indicative of the dynamic nature of the population of organizations and the potential for influx of new technologies, knowledge or innovative approaches as the imperative of adaptation increases. This is important because it provides insights into the readiness and potential leadership of MLOs to undertake CCA initiatives.\u003c/p\u003e\n\u003cp\u003eFindings show that MLOs are typically of moderate size (figures AF1 to AF4). About one-quarter (26%) of interviewed MLOs are small (less than ten employees), while just under half (44%) have ten to fifty employees, and another one-third are larger than 50 up to 250 employees. \u0026nbsp;A final group (8%) are very large with over 250 employees. \u0026nbsp;MLO size varies by country. \u0026nbsp;Organizations are larger on average in Kenya than in Malawi or Ghana. \u0026nbsp;Notably, 15% of organizations in Kenya have more than 250 employees, compared to 5% in Ghana and 4% in Malawi. In all countries, most MLOs range between ten and fifty employees. In terms of time in operation, few MLOs in the study were young; only 17% were less than 15 years old. Half have been active for 15 to 30 years, while another one-third (31%) have operated for more than thirty years. \u0026nbsp; Most MLOs in the study operate in multiple geographic domains within the country, with only 12.5% reporting operations in a single domestic location. Additionally, about half operate in multiple countries in Africa and about one-third have activities in continents other than Africa. \u0026nbsp; This supports the idea that a substantial proportion of these organizations have been operating for some time across wide geographical, cultural, economic and political domains.\u003c/p\u003e\n\u003cp\u003eThe MLO landscape includes different types of organizations. \u0026nbsp; Guided by literature, the project defined distinct types of MLOs to guide our analysis to code the interviews (5-7). \u0026nbsp;Results (table 1) show that local non-profit / community-based organizations (NPO/CBO) are the most common type of MLO, followed by International NPO, government organizations, and private sector organizations. Findings show comparatively few parastatal organizations, universities, companies or other international organizations (international multilateral or bilateral). As the MLOs in our study were selected because of their known involvement in CCA (see methods section), future work should ensure a fully representative sample of organizations conducting CCA work, even if such work is incidental to their primary missions (e.g., value chain actors involved indirectly in climate resilient agriculture). \u0026nbsp;The table in appendix AT1 provides more detail by illustrating three types of organizations interviewed: local NGOs/CBOs, international NGOs, and private sector entities.\u003c/p\u003e\n\u003cp\u003e--- Place Table 1 Here ----\u003c/p\u003e\n\u003cp\u003eOverall, the findings show that the profiles of the MLOs that make up this review are larger, older and have a greater domestic geographic range than might be expected. \u0026nbsp;This indicates that many MLOs are relatively stable, experienced and have relatively expansive footprints across diverse localities. The findings also suggest that many organizations may have moved into the adaptation space from other missions or focal areas.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eMLO climate change adaptation commitment and work\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eAs investment in climate change adaptation programs and projects has increased in recent decades (8, 9), the organizational landscape has also strategically shifted to align its work. \u0026nbsp; The extent to which organizations identify CCA as a core mission captures centrality of CCA in its overall work portfolio and provides insight into mobilization of organizational capacity for CCA. \u0026nbsp;Investigating the overlap of CCA with other areas of focus, such as agricultural development or agroecology, helps understand the range of MLO portfolios, identify areas of cross-learning, and discern areas of specialization.\u003c/p\u003e\n\u003cp\u003eHere we examine three indicators of MLO CCA work orientation coded from our interviews: thematic focus of MLO work, MLO commitment to CCA as a core mission, and CCA activity undertaken by the MLO. \u0026nbsp;The coding protocol defined several areas of thematic focus including CCA,\u0026nbsp;business or entrepreneurship, gender, equality, youth empowerment, conservation or environment, climate science, communication, and disaster and risk management, among others. \u0026nbsp; Reflecting the fact that MLO engagement in CCA for small scale farmers was a selection criterion for the study, 59% of MLOs responded that CCA was a thematic focus of the work they do, and 50% indicated a primary focus on agricultural development. Other areas of thematic foci were environment and conservation (38%), women, gender and equality (29%), disaster and risk management (12%), communication and information technology (12%), youth empowerment (12%), and business and entrepreneurship (12%). Fifty percent of the respondents identified additional areas of thematic focus not specifically presented here. Most of the MLO have multiple, overlapping mission orientations and work across multiple domains, potentially integrating CCA in different activities. Relatively few MLOs (15%) mentioned only one thematic focus; 35% mentioned two, 24% described three thematic focal areas, and 11% named four or more. Although this complexity likely has many determinants \u0026ndash; prior experience, opportunity environment, funder and policy demands \u0026ndash; it is broadly indicative of the reality of integrated problem solving needed for CCA work with SSPs. It is also possible that cross-theme learning benefits MLOs and facilitates strategic positioning of new work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur second indicator is a four-category ordinal measure that captures the extent of MLO commitment to CCA as a mission. The four categories are: limited, moderate, strong and core CCA commitment. Perhaps unsurprising given our selection criteria, findings show that 10% of the participating organizations had a limited CCA mission, while one-quarter (26%) have a moderate focus and over one-third (39%) have a strong focus. \u0026nbsp;Only one-quarter (25%) of organizations have CCA as a core mission. \u0026nbsp;Hence, the CCA mission of most organizations overlaps with other areas of commitment. Table 2 shows that Kenya and South Africa have more MLOs reporting CCA as a core mission as compared to Malawi and Ghana. Examples presented in appendix AT2 provide additional qualitative detail by presenting one organization with a low level CCA mission and another with a core CCA mission. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e--- Place Table 2 Here ----\u003c/p\u003e\n\u003cp\u003eFinally, the interviews captured the profile of diverse climate change work activities in which MLOs are involved. Table 3 shows that just 30% are involved in CCA awareness and education, 25% in policy or advocacy, 22% in smart agriculture practices, and 14% each in agroecology and climate and information systems.\u003c/p\u003e\n\u003cp\u003e--- Place Table 3 Here ----\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eInstitutional Setting\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eGiven our interviewee selection criteria, as expected the interview data show that most MLOs target SSPs as a key beneficiary (77%), although some MLOs focus on specific social groups, such as women and youth, or on other types of actors in the system as part of their CCA work. \u0026nbsp; For example, 10% of the MLOs identified women as a general targeted beneficiary, while another 10% targeted youth, indicating that they work to advance women and youth issues more generally including at meso- and macro-levels. In addition, 13% of MLOs identify government actors as their target beneficiaries. These findings suggest that some MLOs influence vertically or horizontally to effect change. \u0026nbsp;Appendix AT3 provides further detail with examples of MLOs influence orientation, with some facing vertically up or down, and others facing horizontally toward other MLOs.\u003c/p\u003e\n\u003cp\u003eThe source of funding of an MLO for CCA can provide some insight into the importance of particular financial flows and institutional dependency relations between the meso- and macro-level. MLOs are often shaped by institutional context (10-12). Specifically, the source of funding likely shapes the orientation of CCA activities in which MLOs engage. The coding protocol defined several categories of MLO funding, including multilateral, bilateral, international NPO, government, private sector and other sources. Overall, of the 70 total MLOs, 15 had undetermined funding. Of the remaining 55 MLOs, 23 (42%) were found to have only one source of funding, while 32 (58%) identified bilateral funding as a funding source. Seven of the 23 of the single source MLOs (30%, 13% overall) are dependent only on bilateral funding, while 30 (55%) are dependent on multilateral funding. Notably, given the recent elimination of USAID support, 27 out 70 (39%) organizations mentioned that they received funding from USAID.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA country-level breakdown (figure 2) shows that MLOs in Ghana, Kenya and Malawi are most dependent on multilateral, bilateral and international NPOs for funding. For instance, 63% of MLOs in Ghana and 50% in Kenya reported that they were funded by International NPOs. Multilateral and bilateral funding sources provide funding for most MLOs in Ghana, Kenya and Malawi. In South Africa, close to 40% MLOs reported bilateral partners to be their main source of funding.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e--- Place Figure 2 Here ----\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eMLO Capacities and Functions\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eCapturing MLO perceptions of their capacities and functions in CCA offers insight into the practical demands of CCA work and the resources mobilized to support. Table\u0026nbsp;4 provides descriptions of the key capacities identified in this study. Capacities are distributed across organizations such that the highest commonly reported capacity, agriculture development capacity, is found in less than 40% of the MLOs. Other key MLO capacities reported include in-house gender expertise, gender policy/strategy and infrastructure capacity. Fewer MLOs reported to rely on external monitoring and evaluation expertise (2%).\u003c/p\u003e\n\u003cp\u003e--- Place Table 4 Here ----\u003c/p\u003e\n\u003cp\u003eDrawing from literature (13-15), this study identified the following key functions performed by MLOs.\u0026nbsp;Findings (appendix AF5) show that the majority of the MLOs reported that they performed trainer or educator functions (88%). Other common functions are advocacy (57%), knowledge interpretation (52%) and convener (49%), all highlighting MLO roles as intermediaries. Notably, in our data, training and knowledge interpretation often referred to gender sensitivity training or support for climate information services (CIS). Some of the less common functions are related to specific products and services including, technology producer (10%), village savings and loans (7%), and risk insurance (3%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDespite studies showing that technology and related innovations are critical for CCA targeting SSPs (16, 17), few MLOs identify this function. Importantly, our study shows that MLOs rarely perform a single function, and they tend to learn towards combination of functions (e.g MLOs which perform knowledge producer function, can also be involved as knowledge interpreters and trainers).\u003c/p\u003e\n\u003cp\u003eRegardless of whether an MLO has specific expertise or organizational capacity, they can find themselves performing specific functions in relation to CCA projects and programs. Ideally, these functions do correspond to specific capacity profiles, and to the different sectors and beneficiary orientations of the organization. Our data (Figure 2) indicate that local NPO/CBOs and, to a lesser extent, international NPOs, perform a greater variety of functions compared to other MLO types. Private sector and university/research have a strong presence in knowledge production, technology production, and risk insurance. On the other hand, multilateral and bilateral MLOs are active in finance supply, training/education, and resource distribution functions, suggesting they are more likely to be playing the role of coordinating and executing agencies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e--- Place Figure 3 Here ----\u003c/p\u003e\n\u003cp\u003eAppendix AT4\u0026nbsp;presents examples of a private business entity and local CBO/NPO involved in gender and CIS efforts. While the primary motivation of private entities is profit, there is commitment to addressing equity issues such as gender. AT4 also demonstrates that technology innovation related to CIS is central to private entities while local CBO/NPO focuses on community engagement, capacity building and advocacy.\u003c/p\u003e\n\u003cp\u003eIt is reasonable to expect a positive relationship between functions and capacities, where organizations with more capacity can take on more functions. It is possible that the relationship between capacities and functions is endogenous, such that organizations taking on additional functions will gain experience and learn, giving it new capacities. As expected, we find a relatively tight relationship between the number of MLO capacities and the number of MLO functions (see figure in appendix AF6). \u0026nbsp;The qualitative examples in appendix AT5 provide more detailed qualitative examples of mixtures of MLO capacities and functions. The variation in capacity and function across MLOs may create opportunities for niche-oriented bundling or gap identification needed for partner identification and collaboration.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis work provides a baseline characterization of the organizational landscape and serves as a foundation for improving understanding of the constellation of MLOs working on CCA in sub-Saharan Africa and laying the groundwork for future research.\u0026nbsp;MLOs are generally capable and stable actors that are likely more influential for enabling climate change adaptation than currently recognized. Most of the organizations interviewed had relatively long histories, were moderately sized and worked across national and international locations suggesting a wealth of experience that may constitute a significant asset in efforts to enhance locally-led adaptation work. Interview respondents often described their movement into CCA from other humanitarian, agricultural development, environmental or social missions as new funding opportunities arose, and as climate change impacts affected their core mission and beneficiaries. These prior experiences likely inform their CCA work and create synergies with other development objectives \u0026mdash; which could be a powerful way to address SDG tradeoffs and synergies (18).\u003c/p\u003e\n\u003cp\u003eThe MLO role of knowledge broker supports the development of innovative practices and adaptive approaches, ultimately enhancing agricultural productivity and supporting more informed decision-making processes (19, 20). The diversity of other functions and high variation of capacities and specializations among MLOs suggest that they are strategic about the CCA roles they play and the skills they offer, playing to strengths, creating opportunities for partnering and generating interest from funders.\u0026nbsp;These findings support prior studies anticipating the critical linkages MLOs play in CCA\u0026nbsp;(2, 3, 21).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIt is also evident that while all of our interviewees were involved in CCA for agricultural development (as a selection criteria), the orientation of their activities varied, with some more oriented towards macro-level (finance and policy), while others orient towards meso-level organizations or micro-level SSPs. Although more refined analysis is needed, the evidence suggests that MLOs are likely finding strategic niches in the CCA organizational landscape, playing complementary functions and roles with distinct capacities. Overlapping and competitive positions in this landscape are also likely; redundancies could potentially enhance system level resilience for CCA, but in the absence of coordination could also lead to inefficiencies and ineffectiveness.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAlthough MLOs have diverse capacities and play important functions as intermediaries in CCA efforts, they are also vulnerable. Most of the MLOs in climate change adaptation are civil society organizations that self-identify as local NGOs or CBOs, and although some are larger, over 40% have fewer than 20 employees. This suggests they may have fewer available resources to bridge funding gaps. \u0026nbsp;Additionally, MLOs are highly reliant on one or two bilateral or multilateral funding sources, which, as recent policy shifts in the United States have demonstrated, can put them in precarious financial circumstances. Given their vulnerability, it is likely that the next few years will witness high levels of competition among MLOs for ever- scarcer funding.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn face of perceived unsustainable philanthropic and donor funding schemes, many international donors and multilateral institutions are leaning into greater private sector participation in CCA, with the expectation that returns on investment in more climate resilient development will provide broader and more sustained benefits (22). Nevertheless, we found relatively few MLOs identified with the private sector in our sample. While this may be an artefact of the sampling approach and research design, it also is consistent with research that has identified risks for private sector actors to engage in CCA, associated with political and economic instability, inadequate regulatory environment, and lack of trust create high barriers to entry (7, 23). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the near future, MLO capacities on the one hand and vulnerabilities on the other are likely to shape climate change adaptation impacts on the ground, especially for rural farm-dependent communities. The study shows that most MLOs have multiple \u0026lsquo;mission orientations\u0026rsquo; of which climate change adaptation is only one. Given their skills and strategic capabilities, agile organizations may redirect their focus in the near term, away from CCA, toward areas that provide better funding opportunities. Some MLOs may cease operating. \u0026nbsp;Nevertheless, the current dynamics of the international funding environment may also motivate some international donors to double-down on efforts to enhance the autonomy and vitality of national and sub-national organizational networks and value chains involved in CCA. Either way, understanding the capacities and potential vulnerabilities of the organizational landscape for CCA will be critical to avoid cascading negative impacts on SSPs. \u003c/p\u003e"},{"header":"ONLINE METHODS","content":"\u003cp\u003eThis paper is part of a larger research project entitled \u003cem\u003eAccelerating Climate Adaptation via Meso-level Integration\u003c/em\u003e (ACAMI). We undertook 78 interviews with representatives of meso-level organizations from Ghana, Kenya, Malawi and South Africa. These four countries are significantly impacted by climate change and facing pressing development challenges such as poverty and inequality (18, 24). In Ghana, Kenya and Malawi, SSPs play a significant role in agriculture production and other related socio-economic benefits. MLO representatives were drawn from a new relational database (RD) which was designed and developed by the ACAMI project team. This RD contains 195 MLOs, 109 projects and 192 contact people from Ghana, Kenya, Malawi and South Africa.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe process of developing the RD started with a scoping exercise of projects, MLOs and organizational contacts involved in the implementation of climate change adaptation targeted as SSPs in the period 2015-2023 in the four selected countries. We made the best effort to reach out to any and all implementing organizations affiliated with internationally and nationally funded adaptation initiatives. Methods table MT1 below shows the criteria for selection of MLOs and associated projects to include in the RD.\u003c/p\u003e\n\u003cp\u003eThe criteria outlined above was complemented with a codebook (Supplementary Material), which provided the parameters, categories and subsets used in populating the ACAMI RD. This protocol guided the removal of duplicates as well as ensuring that entries were properly captured on the RD.\u003c/p\u003e\n\u003cp\u003eVarious strategies were used to identify MLOs for the paper (figure MF1). The initial stage involved selection of MLOs and projects from the Transforming Social Inequalities through Inclusive Climate Action (TSITICA) project database (For more details about the TSITICA project, visit https://tsitica.uct.ac.za/). The TSITICA database contains both CCA and Mitigation projects implemented during the period 2000 to 2020 in Ghana, Kenya and South Africa. The distribution of projects in the TSITICA database is Ghana=126; Kenya=157 and South Africa =652. \u0026nbsp;From this database, ACAMI team drew an initial list of CCA projects, focusing on projects from 2015 to 2020. Mitigation projects and other projects which did not meet the criteria (Table M1) were excluded. Malawi was not part of the TSITICA project, so the ACAMI team searched for funder websites and other known sources.\u003c/p\u003e\n\u003cp\u003eIn addition, specialized databases were acquired for Malawi with the assistance of the ACAMI project advisory board member. These include: (i) Malawi Adaptation Inventory; (ii) Malawi Stakeholder Mapping and (iii) Database of Development partners working in the Agriculture Sector. Other databases accessed to expand the inventory of MLOs and projects for all four countries included the Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA), Bill \u0026amp; Melinda Gates Foundation (BMGF), Adaptation Fund, and Climate Funds Update (CFU), among others. Furthermore, in the context of South Africa, contacts from the Department of Forestry, Fisheries and the Environment provided an updated centralized database from MLOs, projects and contact people were selected and added to the RD. During this stage of developing the RD, data were captured from the databases and complemented by publicly available information such as websites. After initially capturing data on three separate MS Access files, they were merged at a later stage.\u003c/p\u003e\n\u003cp\u003eFor analytical purposes, we drew from literature some normative categorizations of MLOs (13-15, 25). As demonstrated by the earlier discussion of organizational theory, these categories are only useful as analytical tools, because organizations are much more complex and constantly adapting to their environment and at the same time changing it.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUsing the information from the RD, MLO representatives were selected and contacted in each country. In total, 78 interviews with MLO representatives and experts were conducted both virtually and in-person in Ghana, Kenya, Malawi and South Africa between October 2023 and January 2024. The duration of these interviews was usually between an hour and 2 hours. Follow-up interviews were arranged and conducted with MLO representatives depending on the need and availability. For the purposes of this landscape analysis, 4 expert interviews were excluded and only 74 interviews with MLO representatives were considered. Because three of the interviews were follow-ups, the total number of MLOs interviewed is 70.\u003c/p\u003e\n\u003cp\u003eInterview transcripts were imported into MAXQDA for qualitative thematic analysis. MAXQDA was selected for its robust capabilities in managing, coding, and analyzing large volumes of qualitative data, as well as its advanced tools for visualizing code relationships and supporting collaborative analysis (26, 27). A detailed codebook was developed iteratively prior to coding, with multiple rounds of trial coding conducted to ensure intercoder reliability across the geographically dispersed team. \u0026nbsp;Once all coding was completed, SPSS statistical software was used to conduct the descriptive analysis presented in this paper. Results were presented using simple graphs, tables and other relevant charts.\u003c/p\u003e\n\u003cp\u003eOur study relies primarily on qualitative interviews, introducing some uncertainty regarding variable interpretation and interviewer perspectives. \u0026nbsp;However, we conducted enough interviews to ensure a clear understanding of the data. While semi-structured interviews offer depth and flexibility, they are challenging to standardize and analyze, as their success depends on the interviewer\u0026rsquo;s ability to probe effectively while maintaining focus. As a result, the depth and breadth of responses vary. To mitigate this, we provided multiple rounds of interviewer training and conducted interviews in pairs to enhance complementarity and accountability. Additionally, since interviews were conducted with employees within organizations, responses may have been influenced by their specific roles and tasks, potentially leading to variations if another employee from the same organization were interviewed. \u0026nbsp;Because data presented here represent a snapshot, single point in time, care should be taken into interpretation. \u0026nbsp;It is possible that these organizations have engaged in other types of CCA activities in the past. While this paper presents quantitative angle of the data, analysis of the qualitative data will be presented elsewhere.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAgrawal A, Gans J, Goldfarb A. Exploring the Impact of Artificial Intelligence: Prediction versus Judgment. Information Economics and Policy. 2019;47.\u003c/li\u003e\n \u003cli\u003ePetzold J, Hawxwell T, Jantke K, Gonçalves Gresse E, Mirbach C, Ajibade I, et al. A global assessment of actors and their roles in climate change adaptation. Nature Climate Change. 2023;13(11):1250-7.\u003c/li\u003e\n \u003cli\u003eChaudhury AS, Ventresca MJ, Thornton TF, Helfgott A, Sova C, Baral P, et al. Emerging meta-organisations and adaptation to global climate change: Evidence from implementing adaptation in Nepal, Pakistan and Ghana. Global Environmental Change. 2016;38:243-57.\u003c/li\u003e\n \u003cli\u003eHarris NL, Gibbs DA, Baccini A, Birdsey RA, de Bruin S, Farina M, et al. Global maps of twenty-first century forest carbon fluxes. Nature Climate Change. 2021;11(3):234-40.\u003c/li\u003e\n \u003cli\u003eD'Haen S, Nielsen J. Contemplating Climate Change at local Government. On-the-ground Politics of Adaptation Delivery in Tanzania. 2017. p. 25-36.\u003c/li\u003e\n \u003cli\u003eOmukuti J. Challenging the obsession with local level institutions in country ownership of climate change adaptation. Land Use Policy. 2020;94:104525.\u003c/li\u003e\n \u003cli\u003eZoetbrood A. Private Sector Involvement in Climate Adaptation: Studying the Role and Level of Engagement of the Private Sector in Public-Private Partnerships for Food Security in the Global South and its Justice Implications: Utrecht University; 2022.\u003c/li\u003e\n \u003cli\u003eSavvidou G, Aaron A, Kulthoum O-M, and Trisos CH. Quantifying international public finance for climate change adaptation in Africa. Climate Policy. 2021;21(8):1020-36.\u003c/li\u003e\n \u003cli\u003e(UNEP) UNEP. Come hell and high water : As fires and floods hit the poor hardest, it is time for the world to step up adaptation actions. Nairobi; 2024.\u003c/li\u003e\n \u003cli\u003eMubaya CP, Mafongoya P. The role of institutions in managing local level climate change adaptation in semi-arid Zimbabwe. Climate Risk Management. 2017;16:93-105.\u003c/li\u003e\n \u003cli\u003eTaylor A. Institutional inertia in a changing climate: Climate adaptation planning in Cape Town, South Africa. International Journal of Climate Change Strategies and Management. 2016;8:194-211.\u003c/li\u003e\n \u003cli\u003eAllan JI, and Hadden J. Exploring the framing power of NGOs in global climate politics. Environmental Politics. 2017;26(4):600-20.\u003c/li\u003e\n \u003cli\u003eYomo M, Villamor GB, Aziadekey M, Olorunfemi F, Mourad KA. Climate change adaptation in Semi-Arid Ecosystems: A case study from Ghana. Climate Risk Management. 2020;27:100206.\u003c/li\u003e\n \u003cli\u003eTahiru A, Sackey B, Owusu G, Bawakyillenuo S. Building the adaptive capacity for livelihood improvements of Sahel Savannah farmers through NGO-led adaptation interventions. Climate Risk Management. 2019;26:100197.\u003c/li\u003e\n \u003cli\u003eBaudoin M-A, Ziervogel G. What role for local organisations in climate change adaptation? Insights from South Africa. Regional Environmental Change. 2017;17(3):691-702.\u003c/li\u003e\n \u003cli\u003eDaouda O, Bryant CR. Analysis of Power Relations among Actors and Institutions in the Process of Agricultural Adaptation to Climate Change and Variability from the Diffusion of Innovations Perspective. In: Bryant CR, Sarr MA, Délusca K, editors. Agricultural Adaptation to Climate Change. Cham: Springer International Publishing; 2016. p. 27-51.\u003c/li\u003e\n \u003cli\u003eKühl HS, Bowler DE, Bösch L, Bruelheide H, Dauber J, Eichenberg D, et al. Effective Biodiversity Monitoring Needs a Culture of Integration. One Earth. 2020;3(4):462-74.\u003c/li\u003e\n \u003cli\u003eIPCC. Climate Change 2023: Synthesis Report. Geneva, Switzerland: IPCC; 2023.\u003c/li\u003e\n \u003cli\u003eCrane TA, Roncoli C, Hoogenboom G. Adaptation to climate change and climate variability: The importance of understanding agriculture as performance. NJAS - Wageningen Journal of Life Sciences. 2011;57(3):179-85.\u003c/li\u003e\n \u003cli\u003eRumore D, Schenk T, Susskind L. Role-play simulations for climate change adaptation education and engagement. Nature Climate Change. 2016;6(8):745-50.\u003c/li\u003e\n \u003cli\u003eDirect P. The Nine Roles that Intermediaries Can Play in International Cooperation. 2023.\u003c/li\u003e\n \u003cli\u003eSongwe V, Stern N, Bhattacharya A. Finance for climate action: scaling up investment for climate and development. Addis Ababa: United Nations. Economic Commission for Africa 2022.\u003c/li\u003e\n \u003cli\u003eBiagini B, Miller A. Engaging the private sector in adaptation to climate change in developing countries: importance, status, and challenges. Climate and Development. 2013;5(3):242-52.\u003c/li\u003e\n \u003cli\u003eTrisos CH, Adelekan IO, Totin E, Ayanlade A, Efitre J, Gemeda A, et al. Africa. Cambridge, UK and New York, NY, USA: Cambridge University Press; 2022.\u003c/li\u003e\n \u003cli\u003eAbass R, Mensah, A., \u0026amp; Fosu-Mensah, B. The role of formal and informal institutions in smallholder agricultural adaptation: The case of lawra and nandom districts, Ghana. . West African Journal of Applied Ecology. 2018;26:56-72.\u003c/li\u003e\n \u003cli\u003eKuckartz U, Rädiker S. Analyzing qualitative data with MAXQDA: Springer; 2019.\u003c/li\u003e\n \u003cli\u003eGizzi MC, Rädiker S. The practice of qualitative data analysis: Research examples using MAXQDA: BoD–Books on Demand; 2021.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables are available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"climate change adaptation, meso-level organization, small-scale producer, organization attributes, farming communities, Ghana, Kenya, Malawi, South Africa","lastPublishedDoi":"10.21203/rs.3.rs-6937506/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6937506/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This analysis examines the meso-level organizations (MLOs) that are core climate change adaptation (CCA) actors responsible for interweaving micro-level rural community needs with macro-level policy and finance intentions, using qualitative data from four countries in Africa: Ghana, Kenya, Malawi, and South Africa. Findings show that MLOs involved in CCA comprise a complex group of organizational actors that operate across geographies and social contexts, and manifest substantially different capacities and functions, which create dependencies and opportunities for synergy that form the basis of partnering and networking critical for carrying out CCA. Because MLOs bridge macro-level policy/finance and micro-level CCA beneficiaries they have greater influence on CCA than is currently recognized. Findings generate insights about the vulnerability of the organizations in the CCA meso-level and the potential implications of changes in financial support will have for ultimate beneficiaries","manuscriptTitle":"The Role of Meso-level Organizations in Climate Adaptation for Small-Scale Producers in Sub-Saharan Africa-insights from four African Countries","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-08 15:28:22","doi":"10.21203/rs.3.rs-6937506/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4c83524c-43b3-4e89-ad2f-2dd8696a1332","owner":[],"postedDate":"July 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51228390,"name":"Earth and environmental sciences/Climate sciences/Climate change/Climate-change impacts"},{"id":51228391,"name":"Scientific community and society/Agriculture"}],"tags":[],"updatedAt":"2025-10-30T04:40:27+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-08 15:28:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6937506","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6937506","identity":"rs-6937506","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}