The State of Local Food Systems and Integrated Planning and Policy Research: An Application of the Climate, Biodiversity, Health, and Justice Nexus

Abstract

Food systems are difficult to model, given the challenge of defining socially desirable food system outcomes. Research that aims to advance agri-food systems must reveal opportunities for integrated food systems planning and assess its outcomes. The climate, biodiversity, health, and justice (CBHJ) nexus provides such a lens, and it is a potentially useful tool for understanding how (or whether) food systems planning and policy studies employ a systems-based, integrated perspective. Further, it may be used to identify how agri-food systems planning and policy engage with local objectives and co-benefits related to climate change adaptation and mitigation, biodiversity conservation, community health, and social justice. This research proposes an indicator framework to operationalize the CBHJ nexus, by undertaking a scoping review of over one hundred local agri-food planning and policy studies. Outcomes from this work reveal the nature and degree to which agri-food systems research adopts a systems lens that comprehensively models resilience, sustainability, and justice. Outcomes related to biodiversity, procedural justice, and mental wellbeing were not common in the dataset. Recommendations from the work include guidance on how the nexus can broaden the quantitative and qualitative data-driven measurements of food system outcomes. Future work is required to define appropriate CBHJ outcomes and their possible measurements across scales beyond just local levels.

1. Introduction

Food systems are complex, characterized by interdependencies and relationships among environmental, social, economic, and political factors and actors [1] (Hinrichs, 2014). Interactions among food system components produce outcomes that are difficult to predict, govern, or deliberately achieve [2]. For example, the development of community gardens in a city can produce social benefits, such as local access to food and community gathering spaces; however, it can also result in gentrification and the social justice issues associated with gentrification [3]. Adding to the complexity, food systems are multi-scalar in nature, where issues and opportunities occur at and produce effects across different levels of governance [4]. This complexity makes food systems planning and governance highly challenging, particularly in light of dynamic and unpredictable global pressures such as climate change, urbanization, and shifting consumption patterns.

Although a challenging task, determining how to conduct planning processes and develop policies that contribute to sustainable and resilient food systems is a priority for local governments and communities across the world. The COVID-19 pandemic put this priority into stark relief, as it demonstrated the ways in which global food systems are highly vulnerable to disturbances and shocks [5]. Accordingly, the pandemic served as a lesson on how efforts are needed to strengthen food supply chains and local food systems resilience [6,7]. In the face of emerging and on-going global challenges such as climate change and geopolitical conflict, the need for robust and effective local food system planning and governance has become increasingly more critical for community sustainability and resilience [8].

Early scholarly efforts in food systems planning at local and regional scales include Pothukuchi and Kaufman’s (1999) seminal work on the need to integrate food systems into urban planning agendas [9]. Their work set the stage for a growing body of research and policy advocacy in this area [10,11,12]. The Milan Urban Food Policy Pact (2015) further signaled the importance of local and regional food system planning, as it was designed to galvanize efforts among municipalities worldwide to adopt policies and practices aimed at fostering sustainable local food systems [13]. Such local systems are often referred to as “city-region” food systems, as they encompass contiguous urban, peri-urban, and rural areas that engage in high-intensity local food production and urban agriculture [14].

City-region food systems are conceptually grounded in principles and goals around building self-reliant and resilient local economies while simultaneously addressing broader social and environmental goals. For instance, scholars such as Blay-Palmer (2018) and Mougeot (2000) frame city-region food systems (and local–regional scales, more generally) as crucial sites for innovation, experimentation, and policy development to improve the resilience and equitability of food systems [14,15]. Accordingly, the city-region food system has been recognized as an appropriate planning scale for strengthening the resilience of urban and peri-urban areas [16,17]. At this scale, developing plans for achieving such goals is critical, as cities are typically supported by net imports of food and (thus) are vulnerable to supply disruptions.

To be successful, local food system planning and policy require robust indicators for measuring their outcomes. Multiple frameworks exist to measure agri-food system performance; however, these often operate at a global scale to align with worldwide initiatives such as the United Nations Sustainable Development Goals (SDGs). For instance, Allen et al. (2019) identify indicators capable of capturing the wide-ranging dynamics of global food systems, from production and distribution to consumption and waste management [18]. While such global frameworks are essential, they often overlook the nuances and specificities of food systems operating at local and regional scales. Therefore, despite the rising interest in city-region food systems, a gap remains in the availability of rigorous, comprehensive indicator frameworks for examining the performance and effectiveness of food systems plans and policies in local and regional contexts.

Developing a robust and accessible suite of indicators for local and regional scales is critical to ensure that local plans and policies are effectively aligned with concrete food systems (and broader community sustainability) objectives. Such indicators can be selected and/or explored in further research using an integrated planning lens [19]. While global models provide valuable insights and benchmarks for food systems development and policy, they often fail to capture the specific challenges and opportunities associated with local and regional food systems. Indicator frameworks for city-region food systems should mirror the comprehensiveness of the global frameworks discussed above, but also account for unique local dynamics such as land-use constraints, cultural factors, and governance structures. Local food systems planning is place-based, with no one-size-fits-all approach to its planning, development, and policy-making [20]; however, a comprehensive indicator framework is a valuable tool for communities that can be adapted to their local contexts and needs.

This paper seeks to advance the practice of local and regional food system planning by reviewing scholarly literature (1) to identify quantitative, local–regional food system indicators, (2) to reveal gaps in measurement, and (3) to develop an indicator framework for modeling local-regional food system outcomes. The research aims to address gaps in the development and application of indicator frameworks for supporting local and regional food system planning and policy. Researchers and practitioners can build on this work to develop indicator systems for providing actionable insights for guiding policy, enhancing collaboration across sectors, and fostering adaptive management strategies.

Theoretical Framework

This research uses systems thinking and an integrated planning lens in its examination of food systems outcomes and indicators. Systems thinking is a means for understanding how a set of interacting components operate as a whole (such as in agri-food systems), as well as how these components are interconnected with a variety of social, economic, and environmental factors [21]. System thinking involves the recognition that any planning and policy decisions to manage socio-ecological systems produce unintended and often unpredictable outcomes, which can be beneficial and/or detrimental [22]. Systems thinking can be applied to support integrated community sustainability planning, as this form of planning requires recognizing how relationships among social, environmental, and economic factors shape local issues and affect strategies and policies for addressing these issues [23]. Integrated approaches to local food systems planning and (broadly) sustainable community development are essential for ensuring that local development and planning approaches use a multi-faceted and interdisciplinary lens to effectively and appropriately engage with complex socio-ecological systems.

Newell (2023) proposed the climate-biodiversity-health (CBH) nexus framework (see Figure 1) for supporting research and practice in integrated community sustainability planning [24]. Building (and aiming to improve) upon the work done on the food-energy-water nexus framework [25,26], the CBH framework can support integrated planning by situating actions and strategies in the context of clear sustainability goals (i.e., climate action, biodiversity conservation, and community health), rather than focusing on ambiguous goals and objectives of planning subsystems, such as food, energy, and water systems. The climate component of the CBH framework refers to climate change mitigation and adaptation. The biodiversity component refers to habitat conservation and wildlife health and wellbeing. The health component refers to both physical and mental health. The framework can be applied to a variety of planning challenges and priorities; for example, Ghadiri et al. (2024) applied the framework to a case study in the Comox Valley region of British Columbia, Canada, finding it to be useful for comprehensively illustrating among a range of objectives, actions, strategies for food system planning [27].

The CBH framework draws from systems thinking to explore the interactions among goals and associated strategies for pursuing sustainability. Specifically, it foregrounds interaction and unpredictability into systems modeling efforts, recognizing that the pursuit of CBH dimensions and subdimensions can unintentionally affect other dimensions and sub-dimensions. For example, the implementation of community gardens may contribute to mental health benefits as well as increased pollinator habitat/health. The implementation of a vertical farming operation may contribute to climate adaptation goals but may detract from climate mitigation, given its intensive energy demands. CBH planning allows for place-based determination of relevant goals and assessments of their unpredictable interactions and outcomes.

Newell et al. (2023) further developed the CBH nexus to include justice-related considerations (CBHJ) [28]. While incorporating justice into the nexus framework requires further refinement and application, it is nevertheless important for gaining an understanding of both the equitable/inequitable receipt of outcomes of strategies and actions (i.e., distributive justice) and who are involved in (or missing from) efforts toward arriving at those outcomes (i.e., procedural justice). The addition of the ‘justice’ component posthoc strengthens the framework, allowing for a deeper assessment of the social component of sustainability within integrated food systems planning efforts—a component deemed lacking through testing and application with community partner organizations [28]. The justice dimension and its associated sub-dimensions are key for more comprehensive assessments of food system indicators and outcomes, where food access and participation in food system governance are now considered key dimensions of food security and food system development [29]. The CBHJ nexus provides a useful lens for developing a food systems planning and policy indicator framework that can be applied to support integrated planning, as it comprehensively responds to the critical sustainability challenges of the modern age.

This research asks the following: What CBHJ outcomes does the local–regional food system’s planning literature model? Related to this question, the research also asks how CBHJ indicators may be operationalized to inform integrated planning.

2. Materials and Methods

This research used systematic scoping methods, which involve a systematic approach to extract the literature and a qualitative coding approach to examine it, with the goal of identifying key themes from and directions for research [30]. In this study, the systematic scoping exercise consisted of coding and extracting CBHJ-related indicators from the academic literature comprising empirical studies of local and regional food systems. This method was selected for this review-based study rather than a more traditional quantitative systematic approach, as it enabled an exploration of the terrain of modeling local agri-food performance indicators, rather than infer statistical trends in their scope and/or prevalence.

The goal of the systematic scoping exercise was to create a comprehensive indicator framework, which can be adapted and used by communities to support their local place-based planning and policy needs. To this end, a search strategy was used that targeted the literature within three databases: Web of Science, Scopus, and PubMed. These search engines were chosen for their rigor and replicability within the literature [31]. The following search terms were used to identify relevant empirical studies: (a) (“local food” OR “regional food”) AND (model OR quantify*) AND (“plan*”); (b) (“local food” OR “regional food”) AND (empirical) AND (“climate change” OR “biodiversity” OR “health” OR “justice”); (c) (“local food” OR “regional food”) AND (empirical) AND (“plan*”); (d) (“local food OR regional food” AND scenario AND empirical). provides the results of the search.

The researchers selected for empirical publications that include qualitative, quantitative, as well as semi-quantitative indicators of food systems outcomes. The researchers excluded studies exploring national or global scale indicators, as well as those falling outside the boundaries of a ‘city region’ [14]. The inclusion criteria for the final set of papers used for the analysis involved papers that were (1) published in 2015 or later (i.e., following the publication of the Milan Urban Food Policy Pact), (2) written in English, and (3) peer-reviewed. The exclusion criteria related to papers that (1) do not document an empirical study, (2) do not present quantitative or qualitative data or measures/indicators of CBHJ outcomes, (3) focus exclusively on rural areas rather than regions with urban and peri-urban spaces, and (4) do not focus on local or regional levels. The inclusion and exclusion criteria are summarized in

Table 1. Summary of inclusion and exclusion criteria.

Inclusion Criteria	Published in 2015 or later Written in English Peer-reviewed
Exclusion Criteria	Non-empirical studies (e.g., theoretical, conceptual, or review papers) No reported qualitative or quantitative indicators or measures relevant to CBHJ No focus on urban or peri-urban food systems No focus on local/regional scale (i.e., only national or global)

. After applying the inclusion and exclusion criteria, a total of 122 papers were identified and included in the analysis (Figure 2).

2.1. Analysis

The research analysis phase followed a deductive approach. Deductive approaches involve the use of predefined analytical frameworks or theories to code data, as opposed to inductive approaches which involve the use of open coding to identify new or emergent themes and generate theory [32,33]. The researchers applied the CBHJ framework to generate a predefined set of codes, per deductive coding procedures [34]. Specifically, codes labeled ‘climate’, ‘health’, ‘biodiversity’, and ‘justice’ and their associated sub-dimensions (see Figure 1) were applied to examine each study. Relevant indicators and actions for food system planning were coded according to each respective dimension and sub-dimension.

Following the initial phase of coding and categorization, the researchers identified indicators that were coded to multiple CBHJ sub-dimensions. The linkages across dimensions and sub-dimensions were informed by studies that use integrated systems mapping approaches to identify interactions between food system components, issues, and interventions [35,36]. The linkages and comprehensive list of local–regional agri-food indicators were prepared in a modified Venn diagram format, which serves as an indicator framework that can be applied to city-regional contexts and can be used to support integrated food systems planning (Figure 3). Thus, indicators could potentially span a total of fifteen areas, some of which overlapped with two or more CBHJ dimensions (i.e., climate–biodiversity–health, climate–biodiversity–justice, climate–biodiversity, climate–justice, climate–health, etc.).

2.2. Limitations

The researchers acknowledge three key limitations to this study. First, by focusing exclusively on peer-reviewed literature, CBHJ indicators from gray literature and non-governmental or international governmental organizations are not captured. Such an analysis of alternative sources of literature, while potentially important and substantive, proved out of scope (given the large number of potential sources). While this is a limitation and may under-report the actual number of possible indicators, the peer-reviewed literature reports on scientifically robust and established protocols for measuring indicators of agri-food system performance. Additionally, the goal of this paper was to provide a generalized indicator framework from which communities can undertake place-based assessments of local–regional goals and priorities. This exercise aims to bridge academic rigor with practical applicability, creating a tool that can be adapted and inform place-based discussions—not a complete and comprehensive list of indicators that may stymie accessibility.

Second, we acknowledge that our analysis neglects the literature not written in English, which may lead to an under-reporting of indicators. This is important to note as environmental values vary culturally, and language captures unique perceptions of local environments and places [37]. Future work that assesses geographical differences in indicators and goals for food system development is required to address this gap. This research represents a high-level analysis of peer-reviewed literature on agri-food system performance; however, future research is required to adapt the proposed high-level indicator framework to various local contexts across the globe.

A final gap in our analysis concerns the reliability of our indicator selection and coding approach. Indicator coding and selection was primarily performed by the lead author. To minimize the potential for bias, coding results were continuously discussed within the authorship team in an iterative and reflexive process. Further to this, indicators were not assigned relative weights or importance. This approach was taken intentionally to minimize the potential for author bias, and to align the research with its practical goals for application in integrated planning contexts where indicator weights can be assigned via community consultation.

3. Results

A variety of methodological approaches were identified through the reviewed literature. These include geospatial analyses of potential site locations for food assets (e.g., food hubs, distribution centers, urban agriculture sites, etc.). This involves assessing site location suitability using multi-criteria decision -making techniques and spatial statistics to characterize the optimal placement for these assets, such as community gardens [38]. Other spatial studies explore the relationship between food environments and human health, particularly focusing on spatial patterns in obesity and cardiovascular disease [39,40]. Food desert analyses serve as a cross-over between these respective methodological approaches, where food deserts—areas of low access to healthy foods—are factored into food asset site suitability models, with the goal of driving healthier food and physical health outcomes. Finally, some spatial studies use life cycle assessment models, which include research on potential environmental outcomes for specific technologies like controlled environment growing [41] and analyses that more broadly explore urban metabolism and resource circularity [42,43].

As identified through the literature review, research in food systems planning also involves qualitative and mixed-methods approaches. Some of these studies use systems thinking, mapping interactions among food system components using data from focus groups and/or interviews [36,44]. Other studies conduct policy and document analyses to assess local food policy initiative outcomes and approaches [45]. Overall, fewer studies that employ qualitative approaches were identified in the dataset than studies that use quantitative methods. However, all studies coded as indicating and/or modeling justice-related considerations employ qualitative methods (aside from the spatial studies on food deserts).

3.1. CBHJ Thematic Analyses

The following sections present the results of the CBHJ indicator extraction and analysis, and these results are summarized in

Table 2. Indicators and relevant actions per CBHJ dimension extracted from the initial coding.

CBHJ Dimensions	Indicators	Specific Measures/Sub-Indicators	Relevant Actions
Climate (mitigation)	- Farm-to-fork distance - Global warming potential per crop unit - Soil quality - Clean-tech adoption	- Energy used across life cycle stage [41] - Transportation distance: farm/processor to supermarket, consumer to supermarket [46] - Soil organic matter and aggregate stability [47] - Nutrient circularity [48] - Adoption of e-vehicles for food distribution [49]	- Green energy for indoor crop production [41] - Resource circularity and circular economic development [38] - Research scale and place-specific practices increasing soil health/fertility [50]
Climate (adaptation)	- Food self-sufficiency ratio - Available farm type diversity - Available product diversity - Disaster readiness - Water efficiency - Crop and livestock disease risk - Technology adoption	- Number and type of locally produced foods [35] - Ratio of potential productive land/available production infrastructure to dietary demand [51] - Capacity of emergency food reserves: number of paid staff; distance traveled (clients/volunteers); food assets, finances, potential food demand, demographics (e.g., low income), and additional services offered [52] - Input and population-specific disaster management/food security plans for vulnerable peoples [53] - Disease vector access to crop or livestock [54] - Blue water use and grey water generation minimization in local food production [55] - Area planted using controlled environment technology [56]	- Incorporation of food production assets (e.g., small-scale urban vertical farming) in newly built residential units [51] - Shift to regional and seasonal diets [57] - Increase urban agricultural projects [44] - Diversify farm types/operational models to cope with uncertainty [58]
Biodiversity (habitat protection)	- Land availability for healthy diets - Demand for local environmental resources - Quantity and quality available farmland - Agricultural land in production - Agricultural productivity (yield) - Loss of agricultural land	- Agri-food yields/land use intensity [42] - Agri-food imports - Loss of peri-urban agricultural land over time [43] - Environmental carrying capacity (per capita) by industry, including agriculture [59]	- Farmland preservation [35] - Reduce land footprint by shifting to vegetarian diets, reduce food waste, and reduce overconsumption per person [57]
Biodiversity (wildlife health and welfare)	- Pollinator health - Lower trophic community health in agricultural soils	- Wild bee species richness and evenness [60] - Macro-invertebrate and microbial population diversity in soil [47]	- Encourage diversified garden planting [60]
Health (mental)	- Economic contribution of local–regional food systems - Social capital - Place-based food cultural identity	- Job creation in agri-food sector [38] - Cost of local produce by season across year [56] - Value-added production [38] - Cost of last-mile logistics [61] - Programs available for community relationship building [62] - Number of farmers pursuing direct-to-consumer sales [63] - Perceptions of trust and transparency in food systems [64] - Participation in cooperative networks/professional associations [65] - Agritourism development [66]	- Payments to farmers for ecosystem service provisioning [44] - Public funding for home gardening skills development [67] - Community engagement and place-based program development [64]
Health (physical)	- Cardiovascular health - Individual health indicators - Food desert prevalence - Ratio of healthy to unhealthy food retail - Food skills program prevalence and effectiveness - Contaminant exposure	- Number of new patients entering cardiovascular programs [40] - Probability of obesity [39,68] - Pollution hazard index for production site suitability [69] - Body mass index - Proportion of low- and high-density of lipoprotein cholesterol - Heavy metals in soils [70] - Pesticide residues on food products [71]	- Sustainable procurement [36] - Incentives for cheap, healthy food provisioning at supermarkets [36] - Regulations around unhealthy food advertising [36] - Increasing availability of healthy local food [39,45] - Increase walkability of cities [68] - Job creation through local food enterprise [38] - Creation of local certification/branding systems [44]
Justice (distributional)	- Land consolidation - Healthy food economic access - Access to community food programming - Inequitable labour practices - Institutional provisioning of local–regional foods	- Farmland ownership by demography [72] - Extent of unpaid or underpaid labour in local agri-food systems [73] - Wait times for community gardens [74] - Hospital procurement of local agri-foods [75] - Access to public transit in/around local and regional food assets [76]	- Compensation of farmers for adoption of best management practices [44]
Justice (procedural)	- Decision-making inclusivity - Increasing public agency	- Number and heterogeneity of actors involved in local food planning [77] - Facilitating collaboration and engagement [78]	- Creation of shared spaces for dialogue [62]

. Food system planning-related indicators (and associated references) are described with relevant actions for developing local and regional agri-food systems. The relative prevalence and study of indicators in the literature with respect to the different CBHJ areas are also described below, with specific attention provided to conspicuous indicator gaps.

3.1.1. Climate

Climate-related food systems indicators were well represented within the dataset (n = 41 total papers included climate-related indicators). The studies primarily focused on climate change mitigation considerations by modeling greenhouse gas emissions from the transport of food products within local and regional areas, with the purpose of this research being to reveal ways of optimizing supply routes in terms of reducing emissions [43,79]. Some studies compared the relative emissions of centralized versus decentralized distribution chains for entire regions as well as single businesses/operations like food hubs or logistics companies [61]. A key focus of climate mitigation in the context of decentralized versus centralized distribution chains is toward developing circular food economies that revalorize waste [48]. Other studies modeled life cycle emissions of individual farms, with such studies particularly focusing on controlled environment facilities [41]. Methodologies to determine food system process emissions and carbon mitigation opportunities are well-developed developed and established.

Indicators related to climate change adaptation indicators were less common than those related to climate change mitigation in the dataset. These indicators were less quantifiable and more challenging to identify than indicators related to climate change mitigation, as they are measures of resilience and capacity to respond to climate-related disturbances. Such indicators include the diversity of farming practices, capturing how diversifying business and operational models can improve resilience in the face of climate impacts and disaster events [58]. Adaptation and adaptive capacity, as indicators of agrifood systems, are higher-level heuristics. Such indicators require the establishment of proxy measures described above.

Other indicators relate to a capacity for withstanding disaster events and exogenous shocks, and these are discussed in studies that model local food self-sufficiency under different scenarios of diet, trade, and development. Examples of such research include Hansen et al.’s (2020) estimates of available food stocks from commercial food providers within a region in Germany, in face of supply chain disruptions [80]. Some studies propose current and target food self-sufficiency ratios as indicators for climate change adaptation [48,81,82]. Food self-sufficiency assessments include considerations around available arable land, a justifiable delineation of the area across which food self-sufficiency is measured, and estimates of production potential, yield, and potential demand. Finally, climate change adaptation indicators include considerations related to water use efficiency, with climate change expected to impact water availability and quality in areas across the world. One such study explored water stress and utilization of reclaimed water as key indicators of climate change adaptation [83].

3.1.2. Biodiversity

Biodiversity-related indicators were less common within the dataset (n = 26 mentioned biodiversity conservation and enhancement or wildlife health as objectives for local food system planning). When mentioned, it was most often in the context of pollination and seed dispersal as ecosystem services [84], and the only metrics related to the wildlife wellbeing sub-dimension of the CBHJ nexus involved the community composition of insects and wild pollinators. For example, Lanner et al. (2019) assessed species richness of wild bees within community gardens to find that urban agriculture sites are beneficial to biodiversity [60]. Based on these findings, they recommend increasing flower and crop diversity within food production sites to accommodate diverse pollinator species. Similarly, Chappell et al. (2016) found that economic support for sustainable agri-food practices was correlated with higher species diversity of ground-foraging ants [85]. Such assessments of biodiversity are thus highly limited, reflecting a narrow focus on key species.

Direct indicators related to the habitat conservation and preservation as a CBHJ sub-dimension were not as common within the dataset; however, several studies examined factors associated with habitat conservation, namely land sparing opportunities from higher-yield and localized food production (n = 17). In these cases (and similar to the climate change adaptation indicators), metrics related to food self-sufficiency and yield intensity can be used as indicators of habitat conservation potential, with research highlighting land-sparing opportunities where high yields result in a decreased need for agricultural expansion [86,87]. Similar to concerns raised with adaptation-related indicators, these measures are proxies/substitutes for biodiversity conservation as a higher-order goal.

3.1.3. Health

The majority of papers within the dataset modeled human health indicators (n = 75), with a subset drawn from the field of epidemiology, employing measures related to cardiovascular health, body mass index, measures of fitness, and dietary habits. In particular, the relationship between food environments and human health was frequently found to be an object of study. For example, Alonge et al. (2023) measured relationships between obesity and the quality of food environments, using the presence of fast food retailers within an area and odds of obesity as variables [39]. Similar studies measured the relationship between access to unhealthy food and physical health [68,88] (e.g., Bivoltsis et al., 2019; Jiang et al., 2022). Other studies adopted multi-criteria decision-making methodologies to identify poor food environments and to inform the placement of local food infrastructure, such as community gardens and farms, as well as supermarkets and health food stores [69,89]. Research methodologies that explore the link between physical health and the food environment are well-established and replicated in the academic and non-academic literature.

Some of the health-related studies in the dataset involve modeling scenarios of dietary change with respect to food production systems and foodshed performance. These studies argue for improving agri-food production practices to achieve community adherence to dietary guidelines. For example, Cuttler et al. (2019) assessed the cost of a ‘healthy food basket’ in line with Lancet dietary guidelines and how the cost can vary within a region [90]. Similarly, Ghosh (2021) modeled the potential of an area to achieve food and dietary self-sufficiency as per recommended healthy diets [67]. As a final example, Marrero et al. (2020) examined the relationship between local food purchasing and dietary quality in an island state with high import dependence [91]. These studies demonstrate the interconnections between food self-sufficiency and dietary quality as a component of physical health.

The indicators and measures of mental health found within the dataset were predominantly related to economic wellbeing, rather than the multitude of other mental health dimensions present within the CBHJ framework (e.g., place attachment, social capital). Organizational and operational costs of doing business may be considered indicators of livelihood and thus mental health. Job creation within local food economies may also serve as a proxy for mental health and wellbeing. The researchers also included implementation and management of food literacy programming as an indicator for mental health, given their potential to further social capital and community among participants. A select number of studies (n = 4) also explored trust and participation/relationship building as key outcomes for local food systems planning. Arriving at measures of mental wellbeing and health are challenging to model at aggregated local/regional levels, requiring in-depth qualitative research. Proxy measures, especially those related to financial health and wellbeing, are most commonly employed.

3.1.4. Justice

Justice as a CBHJ dimension was well represented within the dataset (n = 44 mentioned social justice-related indicators). Indicators relevant to justice (specifically distributional justice, related to food access) and health were the most common among these papers. The most commonly identified type of study that related to justice focused on distributional justice, that is, research on how low-quality food environments and food deserts are situated in areas of poverty and affect access to healthy foods for the local demographics [69]. Other papers focus on justice considerations for particular stakeholder groups. For example, studies such as that by Liu et al. (2024) work on the effects of concentration and consolidation of agri-food inputs and resources such as land examine justice and equity considerations among farmers [92]. Other justice-related studies include Tuler et al.’s (2020) research on the perceptions of regional food system planners, finding that they view ownership of capital (e.g., land, technology) by demography as an important but challenging indicator to capture in decision-support tools that are used by planners [72].

In terms of procedural justice indicators, increasing the variety and number of actors participating in agri-food governance decisions is a strategy [77]. Removing barriers to such participation is important for supporting procedural justice in food systems, and this is particularly crucial for disaster management planning [53] to ensure diverse groups are involved in strategies for maintaining food security in the face of disaster events and supply disruptions. Some aspects of procedural justice are difficult to capture as an indicator; for example, Domingo et al. (2023) highlight the importance of relationship and trust building for facilitating local food planning with First Nations communities [62].

3.1.5. Quantitative vs. Qualitative Indicators

To arrive at a comprehensive framework, the researchers included both quantitative and qualitative measures/indicators of food system performance, which were recorded in the peer-reviewed literature. The search strategy yielded mainly quantitative indicators; however, some studies included more qualitative considerations. For example, trust and relationship building are key outcomes to consider in food system planning [62]. Such qualitative indicators may be challenging to operationalize in integrated planning contexts, requiring purposive and in-depth interviews, surveying, or workshops. Similarly, agri-food system resilience-related indicators that are more qualitative in nature (e.g., agro-ecosystem integrity, or decent livelihoods) may be challenging to capture and operationalize across scales [93].

3.1.6. Summary

Among all the CBHJ sub-dimensions, physical health indicators were found to appear most frequently in the dataset. Climate change mitigation was also a well-studied CBHJ sub-dimension, particularly in terms of greenhouse gas emissions from food production and transportation of food products across supply chains (e.g., from consumer to supermarket, farmer to processors, etc.). Biodiversity and procedural justice-related indicators appeared least frequently in the dataset. In some cases, these indicators did not directly measure the CBHJ factor, such as how the land-sparing potential of high-yield agriculture opens opportunities for habitat conservation and rewilding efforts. In other cases, variables and indicators are difficult to define; for instance, the relationship and trust building required for effective participatory governance are difficult to quantify or assess but are nevertheless crucial to procedural justice.

3.2. Indicator Framework

From the extracted list of indicators, the researchers highlighted interlinkages between single indicators and multiple CBHJ dimensions where present (see Figure 4 for a summary of the results). Linkages were deduced through studies in the dataset that employed integrated systems mapping to highlight interactions across dimensions and sub-dimensions. CBHJ dimensions and their areas of overlap are highlighted via different colors, using a modified Venn-diagram. This analysis reveals opportunities for integrated food system planning to arrive at co-benefits—that is, indicators that capture multiple CBHJ dimensions. Such an indicator framework can be used to support communities and local food system planners to triage and prioritize actions (and their associated measurements) likely to generate the most beneficial outcomes.

Three areas of high overlap among CBHJ outcomes with respect to related indicators were identified in this study: health–justice, health–climate, and climate–biodiversity. Specifically, the overlap was found with indicators that (respectively) related to the sub-dimensions of physical health and distributional justice, physical health and climate adaptation, and climate adaptation and habitat conservation. This section reviews those areas of overlap, indicating how certain indicators used in food systems studies can be framed in terms of relating to multiple CBHJ sub-dimensions.

Studies on food access, quality of local food environments, and/or multi-criteria decision-making for identifying sites for developing local food assets in poor food environments most often included indicators spanning multiple CBHJ domains. This type of research typically examines the relationships between indicators for distributional justice (e.g., access, income, and poverty) and physical health indicators (e.g., body mass index, dietary habits). In some cases, these studies spatially analyze indicators related to high access to unhealthy foods or low access to healthy foods. This health–justice overlap demonstrates how local strategies and interventions that address physical health and distributional justice (specifically, equitable access to healthy food) can achieve co-benefits relevant to the CBHJ framework.

Another relatively common area of overlap was between physical health and climate change adaptation. Several studies (n = 18) explored the feasibility of reterritorializing food systems and/or supporting stronger food self-sufficiency, with a focus toward healthy food provisioning. Assuming that the development of stronger regional systems can serve as a buffer against food system disturbances and supply shocks, integrating healthy food provisioning and local supply strategies (e.g., not just supply stocks of grains or non-perishables) can serve as a goalpost for food system’s development and planning.

The final area of major overlap observed in the dataset involves climate change adaptation and habitat conservation. Indicators that measure local and regional food self-sufficiency are useful for assessing climate change adaptation capacity, as they reflect the local potential for maintaining food supply and flows in face of global supply chain disruptions. These indicators also capture land-sparing considerations, as high-yield local food production can decrease agricultural land expansion. Measures such as land use intensity (e.g., kg crop/area) and local–regional logistics efficiencies (e.g., number farm deliveries to supermarkets/day) can be used to infer the adaptive capacity and land sparing potential [80,94].

4. Discussion

This study conducted a systematic scoping exercise on research designed to support local and regional food systems planning. The climate, biodiversity, health, and justice (CBHJ) framework was applied as an integrated planning lens for analyzing this literature and identifying relevant indicators for improving CBHJ outcomes through local and regional food systems development. The analysis extracted a set of indicators related to each of the CBHJ outcome areas, as well as areas where multiple indicators are examined in concert in local and regional food system models. The following discussion presents our findings in the context of socio-ecological systems and integrated planning literature.

4.1. Indicator Gaps

The analysis identified relatively few indicators related to biodiversity, mental health, and procedural justice. It is somewhat surprising that there are not many indicators related to biodiversity, as food systems are tightly linked to ecological health and biodiversity [95]. Additionally, the indicators identified are quite specific in that they mainly relate to pollinators or indirect in that they concern land use intensity (i.e., land sparing potential). Opportunities exist for integrating local and regional food systems planning literature into existing debates and discussions of biodiversity and agri-food systems. For example, the relationship between agriculture and ecosystem services is well-described [96]. Applying a local and regional planning lens to plan for and measure ecosystem services that both are provided by urban and peri-urban agriculture and supports biodiversity requires further research and application [97]. Some scholars argue for the incorporation of ecosystem services into local agri-food planning and practice; however, few applications of such integration have been implemented [84]. Incorporating indicators and measures from ecosystem services as well as agroecological literature that are relevant to agroecosystem health (e.g., abundance/biomass of agricultural products, species composition, taxonomic diversity, and functional diversity) could be one strategy to address this gap [98,99].

As noted, the land land-sparing can be used as an indirect way of measuring biodiversity outcomes; however, more research on and unpacking of assumptions that increased yield intensity and agri-food land connectivity will decrease the pressures of agricultural lands on natural areas. Studies have shown that market-led drivers of agri-food systems lead to land use extensification (i.e., bringing more land into production), where technology-driven intensification of existing agricultural lands may lead to land-sparing benefits [100]. However, only one study in the reviewed dataset [94] examined this issue, using a region in China as a case study and finding that policy incentives for regional food production and self-sufficiency can lead to increased use of greenhouse technologies (i.e., higher-yield agriculture).

Similar to biodiversity, few indicators related to mental health outcomes. Measures of mental health identified through this study represented indirect relationships between food systems and mental health, as they were primarily associated with the economic and financial wellbeing for farmers. Financial wellbeing is only one among a variety of measures of mental wellbeing, including spiritual, emotional, and social health. This lack of indicators is surprising considering it is well-recognized that workplace exposure to hazardous materials, climate variabilities, and poor physical health are all known risk factors contributing to poor farmer mental health [101]. Accordingly, indicators for the mental health and mental wellbeing for farm workers, temporary workers, and waged labor across agri-food supply chains are required. Field surveys, interviews, and ethnographic techniques can collect such data that are qualitative and more challenging to measure.

The research also identified a lack of indicators related to procedural justice. Only one paper provided clear indicators in this area [77]. However, many papers provided actions that directly addressed issues in governance and procedural justice [62,92]. Such findings reveal a gap in the literature, where despite a recognition that procedural justice is important for food system planning, few quantitative or qualitative measures have been established to ascertain its effectiveness or model its outcomes. Although not yet published as peer-reviewed literature, some practitioners and organizations are attempting to make progress in this area, such as with the Public Health Association of BC’s Just Food Systems Evaluation Framework [102]. Instruction can be taken from the literature exploring indicators of environmental (in)justice. Browne et al. (2022), by way of example, argue that demographics (e.g., income status), environmental conditions (e.g., exposure to toxins), physical health outcomes, and procedures (e.g., wait/response times for complaints) all combine to indicate and present environmental justice-related outcomes [103]. Studies regarding spatial variation in access to food and human health outcomes are a clear application of this framework to the context of food systems. However, other measures relevant to procedure (e.g., wait times and demand for food programs, establishment of local food-planning committees/governing bodies) may also provide potential indicators of procedural justice.

4.2. Scale

Important questions arise when considering and defining the scale models for local and regional food system analysis. Such questions include the following: What exactly are the boundaries of a ‘locality’ or ‘region’? This question in particular is explored and actively discussed within most of the modeling studies examined in this paper. There are also other questions and considerations beyond how to define a foodshed or appropriate area of analysis, such as, What should be the operational level and granularity of analysis for a food systems study? Most of the studies in this literature review assess outcomes and performance at the level of the region as a whole [42,57]; however, some studies explore outcomes at an organizational level, focusing on logistics efficiencies and performance for local food infrastructures like community hubs [104]. Other studies that employ an organizational focus in their analyses examine supply chain networks in ‘the middle’ of the production-to-consumption process, which facilitate distribution between local farmers and retailers [61].

There is relatively little research that examines and models food systems at the organizational/infrastructural level, particularly with respect to the food systems components and actors that exist in the middle of the food production to access/consumption suite of processes. Greater research attention to the middle suite of actors and networks that bring food from farm to fork is needed. Much of the literature in this dataset recommends actions related to the development of storage and distributional infrastructure [35]; yet, while indicators for agri-food system performance are well defined for upstream food system actors and components like farms, there is a lack of measures and indicators for the mid-stream processes [105].

4.3. Indicators and Actions for Sustainable Local and Regional Food Systems

There are many efforts to model food systems and assess indicators at large scales, including the United Nations Sustainable Development Goals and a variety of agri-food performance frameworks proposed in the literature [18,106]. However, there are fewer comprehensive approaches to assess agri-food system performance at local and regional levels presented in the planning literature. Numerous studies have explored indicators of all types for examining food systems issues and performances at small and/or regional scales of analysis [107]; however, this work typically focuses on one or few aspects of food systems (e.g., food access, food deserts, greenhouse gas emissions, food hubs, etc.) without engaging in a comprehensive analysis. This paper is a first step in the local and regional food systems planning literature to integrate agri-food performance measures and indicators into their models and integrated community sustainability planning and policy.

The CBHJ is a useful tool to begin this integration, as it can be used as a lens for revealing and recognizing the interplay among indicators where actions for local and regional food system planning generate unintended co-benefits and/or tradeoffs. Through this work, it is clear that local and regional food system planning and policy can result in significant co-benefits along with food availability, including improving community health, enhancing biodiversity, increasing local resilience, and others. Accordingly, local food plans, policies, and strategies can be designed to support multiple goals in tandem, such as improving the physical health of community members while providing greater food access for low-income and/or marginalized communities.

Future work is required to operationalize the indicator framework proposed in this research. Following integrated planning methodologies including workshops, community engagement, and iterative design of food systems action plans and strategies, the indicator framework can be a useful anchor around which these discussions are built. Concretizing possible actions through establishing common, measurable goals for food system development is a potentially useful strategy.

5. Conclusions

This paper uses the CBHJ framework to analyze the literature on local and regional food systems planning. Through a scoping literature review analytical process, key CBHJ-related indicators, gaps, and areas of overlap are identified. Indicators related to biodiversity, mental health, and procedural justice were least commonly found within the dataset, and in some cases, these indicators consist of indirect measurements, such as using the land-sparing potential as a proxy measurement for habitat conservation.

There are several limitations to this research. The sample set of papers is limited to the field of local and regional food system planning and/or performance measures. This study affords an exploration for opportunities to integrate the existing food system indicator literature with planning research. Additionally, while CBHJ offers a comprehensive framework to identify desirable outcomes within the planning domain, it is nevertheless limited in scope. This is especially apparent for economic indicators, where these may serve as a proxy for mental health (i.e., decreased financial stress) but are not captured on their own. Finally, indicators that are difficult to measure (e.g., connectedness with nature, aesthetics) and/or that may be culturally inappropriate to measure present limitations in this study.

There is an opportunity for further research into indicators for biodiversity-related ecosystem services that are pertinent for local and regional food systems, mental health risks (especially for agri-food workers), and procedural justice. More comprehensive measures and indicators within the local and regional planning literature are required to capture the performance of food system activities across the entire supply chain. Overall, the CBHJ framework demonstrates how local food systems planning can achieve multiple socio-ecological goals, emphasizing integrated strategies that address food access, health, and equity. The indicator framework proposed in this research should be operationalized to assess its effectiveness. This can be achieved by working within community contexts to select, weigh, and subsequently model indicators to support integrated food system planning.