Agroecology is increasingly recognized as a pathway for agricultural transformation that can mitigate environmental harms and improve social equity. Yet, the lack of broad-scale assessments that track agroecological indicators in distinct contexts has been identified as a challenge to scaling agroecology out and up. Here, we identify and assess indicators of agroecology based on the Food and Agriculture Organization’s 10 Elements of Agroecology and Tool for Agroecology Performance Evaluation. We created an agroecological index representing the status of agroecological practices and outcomes on farms in Brazil and mapped the results at the municipal level (the smallest autonomous administrative territorial unit in Brazil) using data from the 2017 agricultural census. We found that the extent of agroecological practice across Brazil’s 26 states exhibited strong spatial variability. Within states with low average levels of agroecological practice, we identified “bright spots” of agroecology, or municipalities that performed better than their state average. Bright spot analyses may provide insights on how other municipalities could improve their agroecological status, as well as illustrate potential factors inhibiting agroecological transitions elsewhere. Based on the analysis of local contexts through a literature review, we found that bright spots corresponded to areas with highly visible activities of grassroots farmer networks and nongovernmental organizations, access to public policies and programs, proximity to urban markets, and maintenance of traditional agricultural practices. This suggests that additional institutional investment and support should be directed toward strengthening these enabling factors for agroecology.
While a large diversity of agricultural systems exists at the global level, the drive toward production gains and efficiency has led to an increasingly industrialized agricultural sector. Industrial forms of agriculture contribute to a number of ecosystem disservices (Power, 2010; Foley et al., 2011; Campbell et al., 2017) and social and public health crises (Food and Agriculture Organization [FAO] et al., 2021). These negative outcomes have led to renewed calls for redesigned, territorially embedded agrifood systems that provide affordable, accessible, nourishing, and culturally appropriate food for all, while improving social equity, respecting planetary boundaries, and enhancing ecosystem services at multiple scales (McGreevy et al., 2022).
Scholars, civil society actors, governments, and intergovernmental organizations have increasingly highlighted the transformative potential of agroecology as an alternative to the industrial agrifood paradigm: “Rather than tweaking the practices of unsustainable agricultural systems, agroecology seeks to transform food and agricultural systems, addressing the root causes of problems in an integrated way and providing holistic and long-term solutions” (FAO, 2018, p. 2). Agroecology is commonly described as a science, a practice, and a social movement (Wezel et al., 2009), and as a way of life (James et al. 2023). As a science and practice, agroecology entails applying place-based, experiential, and/or scientific knowledge to agricultural systems in order to produce food while maintaining or enhancing ecosystem functions (Wezel et al., 2009; Méndez et al., 2013; Vandermeer and Perfecto, 2013). Additionally, agroecology is rooted in agrarian movements’ calls to rectify the power imbalances at play within the global agrifood system, which benefit corporate actors at the expense of human well-being and environmental health (Patel, 2009; Wittman, 2011; Bezner Kerr et al., 2022).
Despite the promise of agroecology, there remains a need to “develop practical, scientifically grounded and comprehensive performance metrics, and indicators of agriculture and food systems as a basis for assessment, policy implementation, and investment decisions” (High Level Panel of Experts, 2019, p. 24). Indeed, a major challenge in assessing transitions to agroecology is understanding how to measure and monitor agroecological practice, progress, and performance across space and time in a way that is responsive to specific ecological and cultural contexts yet facilitates comparison, while also respecting farmers’ and researchers’ time and resource constraints. Such an approach is useful for developing broad-based evidence on agroecological transitions and their ability to contribute to more sustainable agrifood systems.
In addition, what societies decide to measure (or not) not only reflects their assumptions, values, and goals but also influences behavior and policy. The agricultural census, as a standardized and standard-setting instrument for documenting and assessing agricultural development, is one tool through which “the moral economy [of agriculture] is produced and reproduced” (Busch, 2000, p. 274). A narrow focus on productivity and income assumes that yield, efficiency, and profit are the only things worth measuring, at the expense of the many other socioecological functions and services that agroecosystems provide (Anderson et al., 2021). Linking the power of agricultural standards and governance of agricultural assessment with a process to measure multiple practices, processes, and outcomes has the potential to help unlock the transformative potential of agroecology at multiple scales by (re)defining “success” and the purpose of the agrifood system (Méndez et al., 2013; Anderson et al., 2021; James, 2022).
To leverage existing data, facilitate comparison, and account for the multifunctionality of agriculture, here we use the FAO’s 10 Elements of Agroecology framework (FAO, 2018; Barrios et al., 2020). We adapt its Tool for Agroecology Performance Evaluation (TAPE; FAO, 2019; Mottet et al., 2020) to provide a baseline assessment of agroecological indicators at the municipal level (Brazil’s smallest autonomous administrative territorial unit) across Brazil, using data from the 2017 Censo Agropecuário (Agricultural Census; Instituto Brasileiro de Geografia e Estatística [IBGE], 2017). Drawing inspiration from work on “bright spots” (Cinner et al., 2016) of multifunctional agriculture (Frei et al., 2018), we calculate municipal agroecological indices based on the census data and then spatialize the results to identify “bright spots” of agroecology—defined here as municipalities where index-based agroecological scores are higher than the average for a state with otherwise low municipal scores. We also provide a counterexample of “dull spot” municipalities in the highest-scoring state, with agroecological scores below the municipal average for that state. Bright spot analyses may provide opportunities for learning how other municipalities could advance agroecological transition processes, while dull spots could identify possible barriers to agroecological transitions. Lastly, we conduct a literature review to identify the roles of local actors, institutions, and geographic conditions in influencing the practice of agroecology in these relatively high- and low-scoring municipalities. Our overall study objectives are (1) to test the efficacy of a modified TAPE approach for assessing agroecological implementation across diverse contexts using publicly available census data and (2) to identify bright spots of agroecological implementation and possible factors that may influence agroecological scores.
Methodological background: Agroecology at the FAO
In 2018, the Committee on Agriculture (COAG; FAO’s governing body) urged FAO to strengthen the normative, science- and evidence-based work on agroecology, as well as develop metrics, tools, and protocols to evaluate the contribution of agroecology to agrifood system sustainability (Loconto and Fouilleux, 2019; Mottet et al., 2020). The Committee on World Food Security (CFS, 2021) also recommended that FAO “establish, improve and apply comprehensive performance measurement and monitoring frameworks” to encourage the adoption of agroecology.
Along with COAG’s request and CFS’s recommendations came the need for defining, monitoring, and evaluating agroecology (including both practices and outcomes) on the basis of a common understanding. Agroecological data are often collected at localized (e.g., community and household-level) scales, which can limit cross-context comparisons and relevance to larger scale policymaking (Mottet et al., 2020; Wittman et al., 2020). To address the need for comparability and to build broad-based consensus among scientists, practitioners, and civil society with respect to defining and operationalizing agroecology (thereby ensuring its approach does not dilute or misrepresent the tripartite nature of agroecology), FAO’s 10 Elements of Agroecology were developed. This framework emerged from a comprehensive review and synthesis of the agroecology literature; a consensus-building process with 1,400 participants from civil society, government, academia, and the private sector at a series of regional meetings from 2015 to 2017; and consultations with academics and FAO practitioners (FAO, 2018; Barrios et al., 2020). The 10 Elements of Agroecology were supported by the Member States of FAO in 2019 and now represent a common framework to “[guide] countries to transform their food and agricultural systems” (FAO, 2018, p. 2) and assess and compare the indicators of agroecological practice, progress, and performance.
To facilitate the construction of a large-scale evidence base for agroecology and to answer the call from Member States, FAO also took a participatory approach to develop a tool, TAPE, for assessing agroecology based on the 10 Elements framework (Bicksler et al., 2023). The development of TAPE involved a systematic review of existing sustainable agriculture indicator frameworks, a “multi-stakeholder consultation phase based on a review and prioritization of over 70 indicators by more than 450 participants,” and the formation of a technical working group tasked with finalizing a framework and indicator-based tool that could be operationalized globally (Mottet et al., 2020, p. 3).
Applying TAPE involves a multistep process comprised of 2 major assessment phases: The first step, Characterization of Agroecological Transition (CAET), “provides a diagnostic on where the [agroeco]system stands in terms of its transition toward sustainability” (Mottet et al., 2020, p. 3). In other words, this step aims to characterize progress toward agroecology in a particular context, which could range from the farm scale to broader spatial scales (such as municipalities). Subsequent steps take a mixed qualitative–quantitative approach to assess how agroecology shapes outcomes in the given context for a subset of the Sustainable Development Goals, including food security and nutrition status (Mottet et al., 2020). Our analysis uses CAET, the first step of TAPE, to characterize the status of agroecological transitions in Brazilian municipalities according to the 10 Elements. This approach enables the provision of an overall “territorial snapshot” of agroecological progress on farming systems (Mottet et al., 2020). Underpinning CAET is the assumption that:
Units belonging to the same territory are more similar to each other than units in different territories. Therefore, it is hoped that the majority of differences between observations (variance) belonging to the same territorial group should come from their level of application of practices. This methodology can be adapted to any level of analysis; in fact, the generic terms “region” or “territory” may refer here to different strata such as a municipality, a watershed, a province, an administrative region, or any other defined area. (Mottet et al., 2020, p. 5)
We take a new approach by using CAET to assess the status of agroecological transitions at the municipal level across Brazil using publicly available data from the 2017 agricultural census. We seek to investigate whether and how agricultural census data can be used to assess the implementation of agroecology, given that farm-level data collection is often both expensive and time-consuming (for both researchers and participants) and considering that agricultural census data are often used to set policy at national and international levels. The Brazilian case offers a unique opportunity to derive data that mirror questions from CAET because the agricultural census data made available by IBGE contain relatively detailed information about practices relevant to agroecology. That is, the IBGE agricultural census provides a more comprehensive suite of data that encompasses not only outcomes (e.g., yield) and demographic information (e.g., age or gender) but also includes data on practices that are relevant to agroecology (e.g., crop rotation, agroforestry, seed-saving). Considering that Member States of FAO, including Brazil, have approved the 10 Elements of Agroecology to guide FAO’s work and to promote the operationalization of these Elements for assessing agroecological transitions, our approach to linking the CAET indices with existing agricultural census data could be useful and replicated to measure progress toward agroecology across diverse contexts and over time.
Materials and methods
We used publicly available data that were collected by IBGE (2017) for the most recent agricultural census. Agricultural census data are collected every 5–10 years by enumerators who administer questionnaires to farming households, defined as any farming unit that is partially or entirely dedicated to subsistence or commercial agricultural activities, regardless of size, ownership, land access, or geography (IBGE, 2019). The data are then aggregated to the municipal level before being made publicly available, facilitating population-level analysis of farms.
The lead author manually compared the IBGE agricultural census tables to the CAET indices used to describe each of the 10 Elements (as outlined in detail by Mottet et al., 2020 [Supplemental Material]) and compiled the relevant data in Table 1. For all but 3 Elements—Culture and Food Traditions, Co-creation and Sharing of Knowledge, and Circular and Solidarity Economy—we were able to obtain at least one indicator from the 2017 census tables that was relevant to the respective CAET index. Nonetheless, census data allowed us to cover only 47% of CAET’s indices to describe the 10 Elements of Agroecology. All indicators were either percentage-based (e.g., the percentage of farms that use a given agroecological practice per municipality) or were normalized from 0 to 100. Indicators within each Element index were then summed to calculate the average Element score. When only a few farmers (typically 3 or fewer) used a certain practice or were represented for a certain variable in a municipality, they were not reported in the census to ensure farmer anonymity (IBGE, 2018). As an example of how this was treated in our analysis, if 3 indicators were identified for an Element in the agricultural census, but a given municipality only had data available for two of the indicators and did not report data on the third in order to protect farmer anonymity, the average score was calculated from the 2 indicators for which there was available data for that Element. Then, all Element scores were averaged to calculate an overall agroecological index per municipality for which data were available (n = 5,563). Lastly, we mapped the overall index scores and each Element index at the municipal level across Brazil using the “geobr” package in the statistical software R (R Core Team, 2022).
|10 Elements .||CAET Indices .||Agricultural Census Data (Table Number) .|
|6. Culture and food traditions|
|7. Co-creation and sharing of knowledge|
|8. Human and social values|
|9. Circular and solidarity economy|
|10. Responsible governance|
|10 Elements .||CAET Indices .||Agricultural Census Data (Table Number) .|
|6. Culture and food traditions|
|7. Co-creation and sharing of knowledge|
|8. Human and social values|
|9. Circular and solidarity economy|
|10. Responsible governance|
Numbers in parentheses refer to table numbers from the census. CAET = Characterization of Agroecological Transition; TAPE = Tool for Agroecology Performance Evaluation.
We then averaged the municipal scores for each state to identify the states with the highest and lowest average overall agroecological scores. Importantly, while we will refer to these results as “agroecological scores” throughout, they should more appropriately be understood as proxy agroecological scores given that we have not directly measured these indicators, and some indicators and Elements have no data whatsoever. In the 5 states characterized by the lowest agroecological scores (approximately 20% of Brazil’s federative units—26 states and 1 federal district), we identified “bright spot” municipalities, defined as municipalities that were more than 1 standard deviation (SD) above the state average. We then conducted an exploratory review of the academic and grey literature (in English and Portuguese) on agroecology and agricultural production in the 2 highest-scoring municipalities in each state to provide insights on the possible conditions contributing to their higher scores within an overall low-scoring context. While not the focus of our analysis, we also provide a counterexample by identifying “dull spot” municipalities in the overall highest-scoring agroecological state, defined as municipalities that were more than 1 SD below the state average. We similarly conducted a literature review on agricultural production in these 2 lowest-scoring municipalities to identify potential negative drivers or pressures that hinder agroecological transitions. States provide administrative boundaries that are shared by municipalities located within them and share some regional geographic and sociopolitical conditions (e.g., states and municipalities each set their own nested policy agendas and budgets for agricultural extension work). Given some of these commonalities, differences between municipalities should therefore reflect differences in the innovation and implementation of agroecological practices and processes. Overall, this methodology allows us to explore the efficacy of using an indicator-based approach rooted in census data and CAET to identify municipalities that could serve as examples showcasing opportunities and barriers in agroecological implementation.
Results and interpretation
The state of Acre (AC) has the highest average agroecological score (41.15; Supplemental Table 1). In general, this reflects relatively high scores in the state for the Elements of Efficiency (i.e., use of only organic fertilizers), Recycling (i.e., seed-saving and to a lesser extent, seed exchange), and Human and Social Values (i.e., family farming and to a lesser extent, on-farm residence; Figure 1). In contrast, the states with the lowest average agroecological scores were Paraná (PR, 27.71), Mato Grosso (MT, 28.24), São Paulo (SP, 28.35), Mato Grosso do Sul (MS, 29.85), and Goiás (GO, 30.02; Supplemental Table 1). This reflects particularly low scores in these states for the Elements of Diversity (specifically, diversity in livestock and annual crop production), Efficiency (specifically, no use of agrochemicals for pest control and exclusive use of organic fertilizers), Resilience (particularly due to the low Diversity scores, which are included as a dimension of Resilience), Recycling (specifically, seed-saving and seed exchange), and Human and Social Values (specifically, relatively low scores for family farming, on-farm residence, and gender equity in farm-owning/operating; Figure 1).
Across the municipalities and states, Elements such as Efficiency and Recycling have among the highest scores, while Elements like Human and Social Values and Responsible Governance have among the lowest. This is consistent with the Efficiency-Substitution-Redesign (or ESR) framework (Hill, 1985) and subsequent literature building upon it, including Gliessman’s 5 levels of food systems change (Gliessman, 2016). These frameworks state that efficiency-based practices/processes (e.g., reducing external input-use) are often (but not necessarily) among the first to be used in agroecological transitions, while practices/processes that aim to redesign or transform food systems (e.g., those related to good governance and improving social equity) often take more time to implement due to their complexity.
Overall, the mean scores across the states did not vary widely and are fairly low, ranging between 27.71 and 41.15 on a 100-point scale (Supplemental Table 1). This could in part be attributed to limited data availability, given that census data provided information on only about 47% of CAET indices and with 3 Elements not represented. However, it is also consistent with the fact that Brazilian government programs generally favor agricultural modernization; for example, organic agriculture remains marginal in Brazil, with less than 1.5% of farms reporting that they were organic in the 2017 agricultural census (IBGE, 2019). As another example, Brazil’s Food Acquisition Programme—a structured demand program that incentivized family farmers to produce organically or agroecologically—only reached 3% of family farmers, and only 2% of the purchased food was certified as organic/agroecological at the program’s peak performance (James et al., 2022). The government also promotes agriculture largely as an economic growth strategy, with government support and investment encouraging the production of export-oriented commodities like soy, beef, and poultry (Sencébé et al., 2020). Although mean state scores did not vary widely, there was wider variability at the municipal level, with the highest-scoring municipality (Osasco, SP) scoring 61.48 and the lowest-scoring municipality for which we have complete information (Paiçandu, PR) scoring 15.40.
High-scoring municipalities in GO, MS, and MT
Because the states of GO, MS, and MT are all located in Brazil’s Centre-West, we will discuss them together. Ecologically, this region of Brazil is largely dominated by the Cerrado (savanna) and Pantanal (wetland) ecosystems and was historically viewed as unsuitable for agriculture due to acidic, highly weathered soils that have low fertility (Derli and Antonio, 1998). However, during the Green Revolution in the 1970s, there was a large increase in state-sponsored research, development, and investment in the Cerrado, which has transformed this region—and Brazil—into an agricultural powerhouse, particularly for export-oriented agricultural commodities like soy and beef as well as cotton and sugarcane (Brannstrom et al., 2008; Blesh and Wittman, 2015; Capellesso et al., 2016; Coy et al., 2020). Intensive agricultural production by agribusiness in the Cerrado and along the Amazon frontier has raised significant and well-documented environmental concerns related to deforestation, biodiversity loss, and land degradation, as well as human rights concerns related to land rights and public health (Martinelli et al., 2010; Oliveira, 2013; Thomas et al., 2014; Song et al., 2021). Yet within this overall unfavorable context for agroecology, some municipalities emerged as bright spots by scoring notably better than their state averages (Figure 2a–c).
The bright spot municipalities in GO (mean state score: 30.02) are largely clustered in the northeastern part of the state (Figure 2a). Among these bright spots, the highest-scoring municipalities are Cavalcante (45.96) and Teresina de Goiás (45.29; Figure 3), which are neighboring municipalities located in the center north of the state in the Chapada dos Veadeiros region.
Active in these municipalities is an agroecological network called Rede Pouso Alto Agroecologia (Pouso Alto Agroecology Network), which was founded in 2014 to consolidate the efforts of numerous local organizations that had already been promoting agroecology in the years prior (Rede Pouso Alto Agroecologia, n.d.b.). The organizations that make up Rede Pouso Alto Agroecologia aim to improve rural well-being and the quality of life of rural people by strengthening agroecology and supporting traditional peoples in maintaining biocultural heritage through extrativismo (sustainable harvesting; Rede Pouso Alto Agroecologia, n.d.a.). They carry out an array of activities with producers, ranging from providing trainings and organic certification, supporting business plans and farm management, fundraising to help farmers obtain equipment, and hosting native seed fairs; they also conduct public campaigns to promote agroecological and organic foods among consumers (Rede Pouso Alto Agroecologia, n.d.b.). The network works with and forges alliances among a range of rural peoples, with a specific emphasis on serving traditional peoples (populações/povos tradicionais)—a designation in Brazil used to describe social groups with a relationship to sustainable territorial development, including family farmers, Indigenous peoples, ribeirinhos (river dwellers), extratavistas (harvester-gatherers), and quilombolas (Afro-Brazilians descended from people who escaped slavery).
As Rede Pouso Alto Agroecologia states, “within the network, the Kalunga quilombolas play a prominent role in maintaining and supplying traditional foods, genetic resources, and associated production methods” (Rede Pouso Alto Agroecologia, n.d.b.). Cavalcante is home to the largest Kalunga community in the Kalunga territory, which covers the municipalities of Cavalcante, Teresina de Goiás, and Monte Alegre. Here, the Kalunga produce food using traditional methods, without inorganic fertilizers and other agrochemicals (Slow Food Brasil, 2020), as reflected in their relatively high score for Efficiency. They mainly grow a diversity of crops and livestock for home consumption or to barter and exchange with other community members, as is perhaps reflected in relatively higher scores for Diversity and Recycling, but also sell surplus production through local markets or the Kalunga association (Slow Food Brasil, 2020). Among these communities, agroecology may provide an alternative agricultural development pathway that relies less on external markets and more on internal community resources and relationships (Tiburcio, 2007; Medina et al., 2021).
Mato Grosso do Sul
Of the bright spots (Figure 2b) we identified in MS (mean state score: 29.85), our analysis points to the municipalities of Ladário (42.99) and Guia Lopes da Laguna (38.16) as the highest-scoring municipalities in the state (Figure 4).
We located little detailed information about agroecology and sustainable agriculture in Guia Lopes da Laguna in our literature review, although our analysis indicates that its highest scores relate to the Elements of Efficiency (driven by 91% of farmers reporting no use of agrochemicals and 67% of farmers reporting use of only organic fertilizers) and Recycling (driven by 80% of farmers reporting that they save seed). As a result, we focus here on the municipalities of Ladário and Corumbá (37.73), which is the next highest-scoring municipality. Both are located in the extreme northwest of the state.1 In both municipalities, more than 90% of the population lives in urban areas, but both have assentamentos (agrarian reform settlements) with diversified production of crops and livestock—particularly dairy and beef cattle, but also bee-keeping—for home consumption and income generation (da Conceição, 2016). Scholars have noted how public procurement programs, including the National School Feeding Program (Programa Nacional de Alimentação Escolar [PNAE]), have increasingly incentivized settlement farmers in the area to grow more horticultural products due to the possibility of better financial returns (Martins et al., 2018). Additionally, the participatory guarantee system (PGS) Associação de Produtores Orgânicos do Estado de Mato Grosso do Sul (Association of Organic Producers in the State of Mato Grosso do Sul) has been active in these municipalities since 2000 (da Conceição, 2016). PGS programs can play an important role in facilitating agroecological transitions and enhancing the Element of Circular and Solidarity Economy by providing a way for local producers to certify one another as agroecological in a manner that is more cost-effective and less bureaucratic for small-scale farmers than third-party certification (Brancher, 2004). Nonetheless, documenting the information necessary for certification is still a challenge for some of the settlement farmers (Martins et al., 2018).
While access to public programs, the quality of local infrastructure and education, soil type and fertility, and land use history vary considerably among the 8 assentamentos present in these 2 municipalities, scholars have noted the overall important role that these settlements play in advancing agroecology in the region (Cuyate et al., 2011; da Conceição, 2016). In some cases, younger members of the settlements who temporarily left to study agroecology at technical schools or university have returned to promote agroecological practices, and in other cases, settlement farmers were encouraged to experiment with agroecology through interactions with government or university-based extension agents who were knowledgeable about agroecology, provided guidance, and offered workshops and trainings (Cuyate et al., 2011; da Conceição, 2016; Carbunck et al., 2018; da Costa and Feiden, 2020), likely enhancing Co-creation and Sharing of Knowledge. In qualitative research carried out with two of the assentamentos, members generally indicated that their primary motives for participating in the agroecological transition had to do with their involvement with local social movements, nongovernmental organizations (NGOs), unions, or associations, and their desire to produce healthier foods (da Conceição, 2016).
The bright spot municipalities in MT are relatively distributed around the state, largely near other state borders (Figure 2c). Várzea Grande (41.13) and Nossa Senhora do Livramento (39.88) were the highest-scoring municipalities in MT in our analysis (Figure 5), with scores notably higher than the mean state score (28.24).
Várzea Grande and Nossa Senhora do Livramento are located in the Baixada Cuiabana, a cluster of 14 municipalities in the south-central part of MT that include and surround the capital city, Cuiabá. Operating in these municipalities is Rede de Cooperação Solidária de Mato Grosso (Mato Grosso Solidarity Cooperation Network), which takes a participatory action research approach to advancing agroecology and family farming in order to improve conservation of natural resources, food security, and income in accordance with solidarity economy principles (Recoopsol, n.d.). This area has some of the highest rates of organic production in the state, which may be reflected in these municipalities’ higher scores for Efficiency (Sebrae, 2016); however, much of the production remains uncertified (Araújo, 2017).
Scholars have noted how traditional peoples have contributed to tree, crop, nonconventional food plant (plantas alimentícias não convencionais, PANCs), and medicinal plant diversity in this area for both subsistence and commercialization, including through the National School Feeding Program (PNAE), likely contributing to higher scores for Diversity (Bortoluzzi et al., 2019; Paraguassu et al., 2019; Laranja et al., 2020). Other reasons this region appears to have scored well include the presence of urban agroecological farms, including Terra Estrela in Várzea Grande, which has become an exemplar of organic marketing in the region. This is largely due to its success in opening an organic store, developing a contract with a local supermarket, and organizing local organic farms to create a model similar to a community-supported agriculture (CSA) initiative, linking growers with supportive consumers to provide some stability for participating farmers (Pantaleão et al., 2014; Naime, 2016; Araújo, 2017). In this way, Terra Estrela may play a role in bolstering the Element of Circular and Solidarity Economy, which was not captured in the census data but could be a driver of agroecology in these high-scoring municipalities.
High-scoring municipalities in SP
SP, one of the Brazil’s most important agricultural states, has an agricultural and historical context that differs substantially from that of the Centre-West. During Brazil’s colonial period, the state was dominated by coffee and sugarcane plantations that relied on the exploited labor of people who were enslaved (Gonçalves, 2017; Luna and Klein, 2018). These histories still inform the SP landscape: There continues to be industrial, export-oriented production of sugarcane, coffee, oranges, corn, and soy; there is intensive use of agrochemicals to manage monocultures; and land inequality is high.
Against this backdrop (mean state score: 28.35), bright spots in SP largely appear clustered along the coast (Figure 2d). The highest-scoring municipality is Osasco (61.48) followed by Mauá (49.18; Figure 6), which are both part of the metropolitan area of the capital city of SP. According to our analysis, Osasco scored well due to having a high percentage of farms with horticultural production (Diversity Element), and all farms here reported using only organic fertilizers and not using any agrochemicals (Efficiency Element), probably in part due to higher urban demand for organic foods. Additionally, all farms here reported access to government credit programs (Resilience Element), likely due to having fairly good access to services as an urban municipality, and equity in land distribution is relatively high (Governance Element). However, there was a lack of data for some indicators in Osasco; for example, data were not reported for the indicators of seed-saving and seed exchange (Recycling Element), nor for diversity in temporary (annual) production (Diversity Element). In addition, the publicly available census data do not provide information on the number of livestock for Osasco due to farmer confidentiality, which prevents us from calculating SIDI for livestock (although this is probably low). Mauá received high scores for horticultural production (Diversity Element), although data were also not reported for temporary (annual) or livestock production, which could influence its score for this Element. There was a high use of crop rotation among farms and all farms reported protecting water sources (Synergies Element). Additionally, Mauá scored highly on the use of organic fertilizers and nonuse of agrochemicals (Efficiency Element), and all farms here reported having access to credit (Resilience Element).
That such highly urbanized municipalities emerged as bright spots points to the role that cities and urban areas can play in agroecological transitions (Justo, 2020). For example, Osasco is home to Instituto AUÁ, an NGO with the goal of promoting community-based environmental projects and a solidarity economy in the greater SP area. Since its founding in 1997, the NGO has advocated for agroecology as a pathway for sustainable development that can support family farmers (Instituto AUÁ, 2016a). It has since expanded in a number of ways; for example, since 2014, it has been running its Banca Orgânica project, which operates similarly to a CSA model (Instituto AUÁ, 2016a). Additionally, Instituto AUÁ organizes numerous urban gardens for community members and for schools, encouraging youth environmental education across Osasco. The group has partnered with the Urban Agriculture Program of Osasco’s Department of Social Development, Work and Inclusion (SDTI) to support local community members in building gardening skills while also generating some income for the participants, who are often socially marginalized (Instituto AUÁ, 2016a). The horticultural products and medicinal plants that participants grow are then sold on-site or at the local organic market. According to their 2016 Annual Report, that year alone of the program involved 7 urban gardens growing more than 30 horticultural and medicinal species and trained 50 local residents in urban agroecology (Instituto AUÁ, 2016b). Together, Instituto AUÁ and SDTI have published a manual for urban vegetable gardeners, focused on agroecological production techniques as well as how to market and sell products in the city (Instituto AUÁ, 2016b). It is possible that these activities and initiatives have helped to lay the groundwork for the Element of Circular and Solidarity Economy, one of the enabling Elements (along with Responsible Governance) that can help the other Elements to take root.
Similarly, Mauá is home to the Ideia Natural (n.d.) collective, which serves the larger SP region by providing programming on environmental education, agroecological and artisanal production and processing, sustainable tourism, and the solidarity economy. The collective hosts an “Experimental Laboratory of Permaculture and Periurban Agroecology,” which supports producer–consumer linkages and colearning, while providing opportunities for workers to generate some income (Ideia Natural, n.d.). Ideia Natural also partners with other local groups like the rural–urban consumer collective, which is a consumer cooperative that removes intermediaries and links supportive eaters with organic farmers to strengthen rural–urban connections and provide “a food supply that guarantees the human right to adequate food, free of pesticides …that promotes fair trade and preserves communities and traditional cultures, the environment, and human health” (Coletivo CRU-SOLO, n.d.).
High-scoring municipalities in PR
In PR, particularly in the interior of the state, soy and corn production dominate; it is the second-largest producer of grains in Brazil after MT (IBGE, 2020). In addition, PR has a strong animal agriculture sector: It is the national leader in poultry production (hosting a quarter of Brazil’s poultry) and the second-largest national producer of milk, hogs, eggs, farmed fish (particularly tilapia), and honey (IBGE, 2020). The highly specialized and industrialized production in this area contributes to PR’s fairly low municipal-level diversity, its reliance on agrochemicals and synthetic fertilizers, and high land inequality relative to the other 2 states in the southern region.
Within these broader conditions (mean state score: 27.71), bright spots in PR appear concentrated in the eastern and south-central regions (Figure 2e). The coastal municipality of Paranaguá (44.80) received the highest score for agroecology in PR, followed by the eastern municipality of Itaperuçu (44.73; Figure 7). Paranaguá scored well on indicators such as land use diversity and proportion of farms protecting rivers and streams (both Synergies Element), proportion of farms that don’t use agrochemicals (Efficiency Element), proportion of farms that save seed (Recycling Element), proportion of farms accessing government credit programs (Resilience Element), and proportion of farms where the owner–operator resides on-farm (Values Element). It also scored relatively high for the proportion of farms that are part of farmers’ associations (Governance Element). It scored less well on youth involvement in agriculture (Values Element), proportion of farms with agroforestry (Synergies Element), and proportion of farms practicing horticulture (Diversity Element), likely because this region is primarily focused on field crop and livestock production. Itaperuçu scored well for indicators on use of only organic fertilizers and no use of agrochemicals (Efficiency Element), on-farm residence (Values Element), and proportion of farms accessing government credit programs (Resilience Element), while having relatively low scores for land equity (Governance Element), proportion of farms with horticultural production (Diversity Element), and proportion of farms practicing agroforestry (Synergies Element)—again, likely because of the investment in field crop and livestock production in this area.
Paranaguá is one of the oldest settlements in PR and is situated along the Bay of Paranaguá. The municipality’s ecologically sensitive location has resulted in the municipal government’s efforts to implement an environmental conservation policy, which may contribute to the enabling Element of Responsible Governance. The policy involves promoting rural tourism, reforestation, soil conservation, sustainable aquaculture, and organic agriculture, while also promoting mangrove preservation (Municipio de Paranaguá, 2019; Articulação Nacional de Agroecologia, 2020). Paranaguá has also been part of an interinstitutional “Agroecology Hub” that started in 1999, involving 7 municipalities and participating institutions ranging from local city halls, state governmental bodies, NGOs, and farmers’ associations (Mendes do Amaral, 2007). The aim of the Hub was to provide “a permanent forum for discussion and implementation of integrated actions aimed at local development, with an emphasis on agroecology and family farming” (Mendes do Amaral, 2007, p. 1731). Outcomes associated with the Hub included various workshops to support farmers in transitioning to organic farming methods and standards, in line with organic and environmental legislation, the certification of over 200 farmers practicing agroecology, support for regionally focused commercialization, and encouraging farmers’ involvement with the agroecology PGS Rede Ecovida (Mendes do Amaral, 2007).
Itaperuçu is located within an hour’s drive of the state capital, Curitiba, likely increasing access to markets; more than half of the state’s certified organic producers are located in the capital region (Silva et al., 2018). Additionally, Itaperuçu’s high scores could be linked to a progressive local government, which has instituted public policies and programs that speak to Responsible Governance. For example, a policy initiative called Itaperuçu Sustentável (Sustainable Itaperuçu) aims “to strengthen the economy in an ecological way based on cycle tourism, agroecology and waste management” (Mandato Goura, 2019). By linking agroecological producers along a sustainable tourism route, the policy aims to support the livelihoods of local agroecological farmers and encourage production of agrochemical-free foods. In addition, the program Produção Agroecológica Integrada e Sustentável (Integrated and Sustainable Agroecological Production) is funded and implemented here through a partnership between the Banco do Brasil Foundation, the National Bank for Economic and Social Development, and the National Union of Cooperatives of Family Agriculture and Solidarity Economy (UNICAFES, 2014) in conjunction with local partners, including Itaperuçu’s Secretariat of Agriculture and the Environment and the local rural workers’ union. This program provided training to 17 local farm families on agroecological production methods, the development of cooperatives, and collective marketing, with a primary focus on improving food security for the participating families and a secondary focus on income generation (UNICAFES, 2014), potentially contributing to the Elements of Co-creation and Sharing of Knowledge as well as Circular and Solidarity Economy in the municipality.
Finally, Itaperuçu has also received a contract through the Assistência Técnica e Extensão Rural (Technical Assistance and Rural Extension) policy to encourage and scale out PGS (Ministério do Desenvolvimento Agrário e Agricultura Familiar, 2017). The decentralized PGS Rede Ecovida (EcoLife Network) is already very active in this municipality and region, as are a number of other PGS (Centro Paranaense de Referência em Agroecologia, 2017). For example, the Associação para o Desenvolvimento da Agroecologia no Paraná (Association for the Development of Agroecology in Paraná [AOPA]) is located in this area and provides direct support to farmers who make up the Maurício Burmester do Amaral nucleus of Rede Ecovida (a farmer nucleus is made up of smaller, more localized groups of Rede Ecovida farmers; Brancher, 2004; Silva et al., 2018; AOPA, n.d.). Scholars describe AOPA, founded in 1995, as “the best and most well-recognized institution in the region” for agroecology and a “historical reference” and “pioneer” of agroecology in the state (Silva et al., 2018). AOPA hosts an associated cooperative (COAOPA, 2022) that helps market agroecological foods, and it was a founder of Rede Ecovida’s innovative alternative marketing system, the Southern Circuit for the Circulation of Agroecological Foods. The Southern Circuit distributes and trades Rede Ecovida products across all 3 southern states based on solidarity economy principles of regional cooperation and embeddedness, social justice, appropriate economic valuation, and transparency (Magnanti, 2008). Given the reputation and success of AOPA and Rede Ecovida in the area, extension agents from the PR government’s Empresa de Assistência Técnica e Extensão Rural (Enterprise for Technical Assistance and Rural Extension) entered into a partnership with AOPA to learn from their experience and better understand the specific needs of agroecological farmers, which included technical support with production planning and identifying marketing channels (Silva et al., 2018). This collaboration has now resulted in the design of 2 new courses for extension agents (on the principles of agroecology and on homeopathy), creating opportunities for extension agents to better serve agroecological and organic farmers in the area, possibly further expanding the sector (Silva et al., 2018). These initiatives highlight the potential influence of bright spots on scaling out agroecology.
Low-scoring municipalities in AC
Lastly, we used our method to identify low-scoring municipalities in a state otherwise characterized by overall higher scores for agroecology. The state with the average overall highest agroecological score was the Amazonian state of AC (41.15), located in Brazil’s North. While agricultural expansion over the past 3 decades has increasingly put the ecological integrity of the Amazon at risk, with expansion of export-oriented cattle and grain monocultures being major drivers of deforestation, land grabs, and human rights abuses (Oliveira, 2013; Kehoe et al., 2019), Amazônia also has a long history of agricultural and ecological use by Indigenous and traditional peoples, whose complex subsistence strategies include traditional fire management, development of terra preta (Amazonian dark earth, an Indigenous technique to build fertility in low-fertility rainforest soils), extrativismo (sustainable harvesting and gathering of native products, like açai, Brazil nuts, and rubber), and polyculture agroforestry (Glaser, 2007; Maezumi et al., 2018). These management practices have not only shaped tree species domestication and the current forest composition (i.e., the “hyperdominance” of edible tree species; Maezumi et al., 2018) but also strongly influenced domestication of crops like manioc, squash, beans, rice, and even maize (Watling et al., 2017; Watling et al., 2018; Koch et al., 2019). In short, many of these traditional practices and their legacies remain on the landscape and are in use by local peoples today.
AC in particular has “a long tradition of agroforestry and resource management …over millennia” (Watling et al., 2017, p. 1871), and 63% of AC has a protected land status (designated as Indigenous territories or as conservation units; de Souza Nascimento et al., 2021). In our analysis, AC scored well on the Elements of Efficiency (for not using agrochemicals and for using only organic fertilizers), Recycling (particularly for saving seed), and Human and Social Values (particularly for family farming and owner–operator on-farm residence, while also scoring relatively high for the percentage of both women- and youth-run farms). Yet within this overall context, dull spots of agroecology were concentrated in the southeastern corner of AC along the border with Rondônia (Figure 2f), which is one of the most deforested Amazonian states. Specifically, the lowest-scoring municipalities were Senador Guiomard (33.41) and Acrelândia (34.25; Figure 8). These municipalities have the highest density of roads in AC and have been targets of decades of government programming to fuel economic growth and settlement (Salgado et al., 2014; de Souza Nascimento et al., 2021).
Senador Guiomard’s scores for annual crop diversity (Diversity Element); land use diversity, water protection, and native forest preservation (Synergies Element); nonuse of agrochemicals and use of organic fertilizers (Efficiency Element); and farmers’ association membership (Governance Element) were among the lowest in the state. This reflects the fact that 94% of Senador Guiomard’s total agricultural area is used for animal production (primarily a split of cattle and chickens), while 86% of its annual crop production area is used for maize (IBGE, 2019). A possible factor influencing Senador Guiomard’s score could be its strategic geographic location; as stated in an official government investment report, the municipality is connected to the now-concluded Interoceanic Highway, “which connects Brazil to ports on the Pacific coast, thereby connecting Acre with Andean markets, the US west coast and Asian markets … and contributes to Brazilian exports and the development of Brazil’s Northern Region” (RENAI et al., n.d., p. 80). In light of this, Senador Guiomard has been designated as an “Export Processing Zone,” which confers an industrial area designation with special tax and other incentives and benefits in order to increase exports and attract investment (Ministry of Industry Foreign Trade and Services, n.d.; RENAI et al., n.d.). This designation has been granted for 20 years and will be renewable for another 20 years after the initial period is completed (RENAI et al., n.d.), with likely negative implications for its agroecological status into the future.
Acrelândia, which neighbors Senador Guiomard, has also been characterized by intensive deforestation and subsequent installation of pasture (de Freitas et al., 2012). It is therefore now similarly dominated by animal production, with almost 80% of its total agricultural area dedicated to animal agriculture, again largely cattle and chicken production (IBGE, 2019). Of its area in annual crop production, over 70% is dedicated to maize, and of its area in perennial crop production, almost 94% is dedicated to banana and coffee (IBGE, 2019). These patterns help to explain its low scores for annual crop diversity (Diversity Element), land use diversity (Synergies Element), and for nonuse of agrochemicals and use of organic fertilizers (Efficiency Element). Acrelândia is similarly positioned at the nexus of the interoceanic highway and other formal and informal roads, and such proximity has long been linked to settlement and agricultural expansion that spurs deforestation in the Amazon (Fearnside, 1987; Alves, 2002; Laurance et al., 2002; Barber et al., 2014) and in AC specifically (de Souza Nascimento et al., 2021).
Implications: Insights into potential factors influencing agroecological success
Our analysis used existing Brazilian census data to identify municipalities with high agroecological index scores relative to their context, which can provide insights into the conditions that may advance agroecological transitions. Our literature review points to the following factors as potentially influencing higher agroecological scores: highly active grassroots farmer networks and NGOs; proximity to urban areas and markets; access to public policies, programs, and trainings; and maintenance of traditional and cultural agricultural practices. These factors suggest that a mix of bottom-up activities (through farmer networks and place-based agroecological practices) and structural policy supports (through progressive public programs and market incentives) could be key to scaling out agroecological transitions (Mier y Terán Giménez Cacho et al., 2018; Blesh et al., 2023). In contrast, disabling conditions for agroecology include the expansion of simplified commercial agriculture with a profit-based export orientation (Ioris, 2018; Anderson et al., 2021).
Involvement with grassroots farmer networks and NGOs is often discussed in the agroecology literature as a key feature for scaling out agroecology across communities (Rosset and Martínez-Torres, 2012; Hart et al., 2016; Mier y Terán Giménez Cacho et al., 2018) and contributes to the Elements of Responsible Governance and Co-creation and Sharing of Knowledge. In our study, participation in social movements, networks, or local NGO activities featured strongly in all bright spot municipalities, indicating that these factors may play an integral role in encouraging and supporting agroecological transitions through place-based horizontal knowledge exchange and capacity-building. Agroecology networks like Rede de Cooperação Solidária in MT’s Baixada Cuiabana and Rede Ecovida in Paranaguá and Itaperuçu, PR actively promote farmer-to-farmer knowledge sharing and provide local marketing opportunities for participating farmers. In Osasco, SP, a local NGO (Instituto AUÁ) promotes community-based projects to engage youth through environmental education programs and train local and low-income community members on organic urban agriculture, which supports residents in acquiring new skills and generates livelihood opportunities.
As has also been discussed in the agroecology literature, bright spot cases were located in proximity to urban areas. This proximity strengthens rural–urban relations, enhances access to markets, and serves to re-embed or reterritorialize food systems in the pursuit of larger scale food-systems change, enhancing the Element of Circular and Solidarity Economy (Gliessman, 2016; Vaarst et al., 2018; James and Bowness, 2021). As part of the SP metropolitan area, farmers in Osasco, SP, have better access to resources and services like credit and also have more marketing opportunities, particularly due to Instituto AUÁ’s focus on providing marketing and distribution training. The municipalities of Várzea Grande and Nossa Senhora do Livramento in MT are located in the Baixada Cuiabana as part of a cluster of municipalities surrounding MT’s capital city of Cuiabá. Here, urban agroecological farms like Terra Estrela serve as models for other farms in the region and have generated overall greater support for agroecology by opening a store for organic products and organizing local farms to create a CSA-like model that benefits agroecological farmers as well as eaters.
Proximity to urban areas can also enhance farmers’ access to public policies, programs, and trainings, which can play an important role in supporting transitions to agroecology through Responsible Governance (Wittman and Blesh, 2015; Chappell, 2018; Giraldo and McCune, 2019; Valencia et al., 2019). In Itaperuçu, PR, local programs like the Integrated and Sustainable Agroecological Production program provided local farmers with training on agroecological production methods, cooperative development, and marketing, while the Sustainable Itaperuçu initiative provided agroecological farmers with an extra income opportunity through agritourism. In MT’s Baixada Cuiabana and the municipalities of Ladário and Corumbá in MS, farmers have benefited from accessing national public policies like PNAE, which acts as a mediated market to support and incentivize organic production. These findings indicate that government support can be important for scaling out agroecology but is most effective when it supports place-based initiatives (e.g., linking agroecological farmers with sustainable rural tourism through Sustainable Itaperuçu) and is joined up with other local or national policy priorities (e.g., improving youth food security through PNAE). An important factor to note is that access to public policies is not uniform across Brazil (Grisa and Schneider, 2014; McKay and Nehring, 2014), which will require reducing geographic, class-based, and racial bias in the distribution of public resources and services.
Place-based agroecological knowledge
Lastly, we found that place-based and traditional agricultural practices serve as an important basis for amplifying agroecology. This has also been discussed widely by social movements and in the scholarly literature and links to the Elements of Co-creation and Sharing of Knowledge and Culture and Food Traditions (Vandermeer and Perfecto, 2013; Altieri et al., 2015; Nyéléni International Forum for Agroecology, 2015; High Level Panel of Experts, 2019; Morgan and Trubek, 2020; Utter et al., 2021). In the Baixada Cuiabana of MT, in Ladário and Corumbá in MS, and in Cavalcante and Teresina de Goiás in GO, traditional peoples (including extrativistas, quilombolas, and family farmers) have played an integral role in stewarding agrobiodiversity and biocultural heritage and in promoting management methods that do not rely on synthetic external inputs, enhancing the Elements of Diversity, Recycling, Efficiency, and Resilience. Sharing knowledge about place-based agricultural methods through participatory learning in social networks could build upon and expand the potential of these practices.
Limitations and future directions
Although Brazil has one of the most comprehensive agricultural censuses in the world, there are several limitations to our analysis. First, because the agricultural census data are aggregated to the municipal level, we could not assess the co-occurrence of different agroecological indicators at the level of specific farm agroecosystems, which is an important next step for understanding how management systems (and relationships among their component practices) affect agroecosystem and landscape-level sustainability.
Second, the 2017 Brazilian agricultural census data allowed us to cover only about 47% of CAET’s indices to describe the 10 Elements of Agroecology, which presents a major limitation to more holistically understanding the breadth of agroecology. For example, the Brazilian agricultural census does not explicitly capture agroecological variables related to the Elements of Culture and Food Traditions, Co-creation and Sharing of Knowledge, and Circular and Solidarity Economy. This points to important data gaps and limitations with respect to using the agricultural census data for measuring the full breadth of agroecology, especially social, cultural, and economic factors that reflect farmers’ access to important off-farm resources, networks, and knowledge systems that support agroecological transitions (Morgan and Trubek, 2020; Utter et al., 2021). These Elements may also help to differentiate agroecology from other forms of alternative agriculture (e.g., certified organic agriculture) that share some overlap in terms of on-farm management practices. To enable more robust and holistic quantitative assessments of agroecology in the future, agricultural census data could better account for these missing Elements and their indices. For example, Co-creation and Sharing of Knowledge (Element 7) could be assessed by gathering information about whether and from which sources farmers receive and/or share agroecological knowledge, and about farmers’ level of engagement in informal or grassroots networks (which could be assessed according to a Likert-type scale).
In addition, several of the other Elements have census data available for relatively few indices. For example, we only identified data for one of the 4 indices for the Recycling Element: management of seeds and breeds, with notable gaps for key agroecological practices that could fall in this category, such as use of on-farm compost, cover crops, and details on management of animal manure and crop residues. Therefore, while our analysis represents a first step toward assessing agroecology at a broad scale, using a more encompassing and complete set of indices and Elements will lead to a more realistic and holistic assessment of the practice of agroecology in Brazil. Indeed, had a larger suite of agroecological indicators been captured in the agricultural census data, or verified through on-the-ground TAPE data collection, then perhaps the average state scores would have exhibited greater variation.
While these data limitations constrain the validity of our results, we were able to capture important social, cultural, and economic dimensions of agroecology through indicators identified for the Elements of Resilience, Human and Social Values, and Responsible Governance, and the overall patterns for agroecological implementation across Brazil are consistent with what we would expect based on our knowledge of historical agricultural development in the country (e.g., the Centre-West states being highly influenced by Green Revolution modernization strategies). The possibility of interpreting existing census data in conjunction with other evidence (e.g., literature, on-farm research using TAPE, participatory validation, etc.) could complement and deepen future analyses in this area and open space for understanding drivers of agroecology and determining interventions in a participatory manner (Bicksler et al., 2023).
Applying the growing body of scientific knowledge on agroecology to make relatively straightforward changes to how data are collected and calculated in agricultural censuses would improve researchers’ abilities to more aptly assess agroecological indicators and characterize agroecology moving forward, which is necessary for agroecological approaches to receive greater policy support in line with FAO Member States’ commitments. While making changes to agricultural censuses follows a specific process and can also be influenced by shifting governmental administrations and their priorities, the FAO is already supporting countries in this effort and has a leadership position in this regard, as its World Programme for the Census of Agriculture helps to inform countries’ agricultural censuses. There is therefore an opportunity for the FAO and its partners working on agroecology to support the inclusion of more robust data on agroecology.
Because of challenges associated with the Brazilian census questionnaire changing over time and because temporal analysis was beyond the scope of our analysis, our findings represent only a snapshot in time. Future work could use time series data to explore, to the extent possible, how trends in agroecological status change over time, and to link the level of agroecological transition to key outcomes, such as food security, health, and perceptions of well-being (the objective of TAPE Step 2). Although CAET does not weight indicators, future work could also consider whether or not weighting certain data inputs or indicators would make sense in terms of their perceived importance for each Element. Additionally, while we undertook a more descriptive exploration of enabling conditions for agroecology, future research could employ quantitative techniques (e.g., regression analysis) to assess the relative importance of potential determinants of farm management practices and explore additional possible explanatory factors (such as ecoregions, state, municipal area, population size, etc.), which could lead to more generalizable statements on drivers.
Finally, while a coarse-scale indicator-based approach and literature review can facilitate cross-context comparisons, it may also privilege certain ways of knowing and obscure complex realities. To this end, future research could investigate the drivers and outcomes of agroecology by integrating qualitative and quantitative explorations of the on-the-ground experiences of farmers and other stakeholders in municipalities that have higher or lower agroecological scores relative to their geographic context, as proposed in TAPE Step 3. For example, a remaining question is to what extent high-scoring states or municipalities are characterized by agroecology “by design” (i.e., driven by farmer choice) or “by default” (i.e., out of necessity due to a lack of access to resources or alternative options). While our study included income as an indicator (Resilience Element) and while states in the Northeast and North regions have the lowest farm household incomes on average (perhaps indicating agroecology “by default”), scholars have found that income is not a consistent predictor of rural peoples’ livelihood strategies or environmental behaviors in this context. For example, farmers’ options and decision-making are heavily influenced by social and historical factors (including factors like identity and social prestige), alternative and noneconomic values (including lifestyle and security), and other assets and capabilities (Garrett et al., 2017). Therefore, undertaking on-the-ground, mixed-methods assessments would help further explain the “conditionality” of agroecological scores (Magliocca et al., 2018; Sampson et al., 2021), lending important insights for how to design context-appropriate policy instruments and interventions that can foster a more sustainable and just food system.
The objectives of this analysis were 2-fold: (1) to adapt and test the ability of FAO’s TAPE (specifically, the CAET step) to be used with publicly available agricultural census data to assess indicators of agroecology at a territorial scale and (2) to identify and evaluate high-scoring, bright spot agroecological municipalities in Brazil and provide a counter-example of low-scoring, dull spot municipalities. We also aimed to understand potential drivers of more or less advanced agroecological status through a complementary literature review. The identified drivers could, in turn, be tested in future causal analysis, to provide a more detailed understanding of the diversity of place-based factors that can foster agroecological transitions. Even with existing data limitations, CAET proved useful for assessing and detecting variation in agroecological practices and processes on farms in Brazil. We also found that a bright/dull spots approach can support investigations of agroecological transitions by helping to illuminate potential drivers and inhibitors of agroecological implementation. Our approach can serve as a model for using existing census data to evaluate agroecological indicators in other contexts to develop broad-based evidence on scaling agroecology. We also recommend extending the scope of data collection for public agricultural censuses, given that existing census data do not capture some important Elements. This would facilitate more holistic assessments of agroecology at a large scale and help drive agroecology-inspired policy toward more transformative change.
We found that, in general, agroecological scores were highest among states in Brazil’s Northeast and North regions such as AC and lowest in the industrialized agricultural states of PR, SP, and Brazil’s Centre-West, aligning with historical and ongoing production patterns in these areas. Our literature review supports prior research on agroecological transitions (e.g., Mier y Terán Giménez Cacho et al., 2018; Anderson et al., 2021; Blesh et al., 2023), providing additional empirical evidence that enabling conditions that may advance progress toward agroecology include involvement with grassroots farmer networks and NGOs; access to supportive public policies, programs, and trainings; proximity to urban areas and markets for local, organic, and agroecological foods; and maintenance of traditional and cultural agricultural practices. This suggests that additional investment and support should be directed toward strengthening grassroots groups, agroecology-oriented public policies, organic markets, and place-based ecological knowledge in order to continue scaling out agroecology.
Data accessibility statement
The authors used Instituto Brasileiro de Geografia e Estatística (2017) agricultural census data, which are publicly available. The authors can make additional information or data available upon reasonable request.
The supplemental files for this article can be found as follows:
Supplemental Table 1. Average agroecological scores per state and region (DOC).
The authors would like to thank Zia Mehrabi, Jeff Liebert, Rodrigo de Campos Macedo, and members of UN FAO’s TAPE team for fruitful conversations and/or feedback.
DJ acknowledges funding from the Vanier Canadian Graduate Scholarship and PEO International. DJ, NR, and HW acknowledge funding from SSHRC Insight Grant 435-2016-0154. CL was funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 796451 (FFSize).
The authors declare no competing interests.
Contributed to conception and design: DJ, JB, CL, NR, HW.
Contributed to acquisition of data: DJ.
Contributed to analysis and interpretation of data: DJ, JB, CL, NR, HW.
Drafted the article: DJ.
Revised the article: DJ, JB, CL, NR, AJB, AM, HW.
Approved the submitted version for publication: DJ, JB, CL, NR, AJB, AM, HW.
A note on geography: Somewhat uniquely, the small municipality of Ladário is entirely surrounded by the very large municipality of Corumbá.
How to cite this article: James, D, Blesh, J, Levers, C, Ramankutty, N, Bicksler, AJ, Mottet, A, Wittman, H. 2023. The state of agroecology in Brazil: An indicator-based approach to identifying municipal “bright spots.” Elementa: Science of the Anthropocene 11(1). DOI: https://doi.org/10.1525/elementa.2023.00011
Domain Editor-in-Chief: Alastair Iles, University of California Berkeley, Berkeley, CA, USA
Knowledge Domain: Sustainability Transitions
Part of an Elementa Special Feature: Principles-based Approaches in Agroecology