# Water-cropland resources and agricultural management shape the main interactions with food self-sufficiency goals

Achraf Mamassi, Nicolas Guilpart, Lucile Muneret, Francesco Accatino

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Achraf Mamassi, Nicolas Guilpart, Lucile Muneret, Francesco Accatino. Water-cropland resources and agricultural management shape the main interactions with food self-sufficiency goals. Global Food Security, 2025, 44, pp.100841. 10.1016/j.gfs.2025.100841. hal-04985795

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# Water-cropland resources and agricultural management shape the main interactions with food self-sufficiency goals

Achraf Mamassi<sup>a, *, †</sup>, Nicolas Guilpart<sup>b</sup>, Lucile Muneret<sup>b</sup>, Francesco Accatino<sup>a</sup>

## ARTICLE INFO

### Keywords:

- Food self-sufficiency

- Factors

- Trade-off

- Synergy

- Food security

## ABSTRACT

Regional and national food policies must seek to attain equilibrium among social, economic, political, agricultural, and environmental factors. As a developmental objective, food self-sufficiency (FSS) responds to a region's need for increased autonomy and control over its own food supply. In this systematic review, we employed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol to assess the state of the art, then, we explored 109 final selected studies, focusing on the main interactions associated to achieving FSS goals. We found that FSS objectives can be realised through context-dependent interactions with 47 identified factors. The main limitations associated with attaining FSS goals emerge from the confluence of trade-offs with water and agricultural land. The positive interplay between FSS and agricultural management highlights the synergies that result from adopting advanced sustainable technologies and practices and optimizing resource-use efficiency, which holds promise for achieving FSS goals. We identified a shortage of studies focusing on food consumption, distribution, and access related factors, despite their relevance in promoting FSS and food security. We identified four primary developmental strategies rooted in local agricultural management practices, each aimed at addressing the achievement of FSS goals while mitigating associated trade-offs: cropland expansion/ cropland-water resource management, yield gap closure, cropping systems diversification/integrated crop management, and urban agriculture. In conclusion, identifying factors that limit or strengthen FSS can help to facilitate the transition away from siloed government strategies to arbitrate between different holistic development strategies according to local contexts.

## 1. Introduction

Food self-sufficiency (FSS), the ability of a country or region to produce enough food to meet its local population demand (FAO, 1999), has become a high-priority policy objective for governments seeking to control of their own food supplies and protect against international market fluctuations and other unpredictable challenges (Beltran-Peña et al., 2020; Clapp, 2015; Pradhan et al., 2014; Van Ittersum et al., 2016). Policymakers and researchers have taken an increasing interest in FSS as its relevance has grown: during the COVID-19 pandemic (FAO, 2021) which caused widespread supply chain disruptions and heightened food insecurity globally, and the Russian-Ukrainian war (FAO, 2022) which severely impacted global grain and fertilizer exports, threatening food availability in import-dependent regions. FSS has been recognised as an effective strategy for mitigating food insecurity by meeting local food demand through sustainable, locally adapted food

production systems (Beltran-Peña et al., 2020; Clapp, 2017). Nevertheless, only 33.5% of the global population achieves complete nutritional self-sufficiency through local production (Wassénius et al., 2023).

Governments adopt different strategies to meet their populations' food needs. On the one hand, they can adopt a fully trade-oriented approach to food procurement by creating networks of commercial partners (Clapp, 2015). On the other hand, they can opt for an FSS-oriented strategy by implementing trade barriers to restrict food imports while supporting the growth of their national agricultural sectors. Supporters of FSS-oriented policies defend the political right of states to protect themselves from the fluctuations of global food markets. Conversely, opponents focus on the costs associated with pursuing FSS and highlight the trade-offs involved, particularly when the politics of food protectionism restrain socio-economic and environmental benefits. This debate is ongoing as both approaches strongly depend on contextual factors, such as geographic, climate, economic, and socio-political

<footnote><sup>a</sup> University Paris-Saclay, AgroParisTech, INRAE, UMR SADAPT, 75005, Paris, France</footnote>

<footnote><sup>b</sup> University Paris-Saclay, AgroParisTech, INRAE, UMR Agronomie, 75005, Paris, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: achraf.mamassi@inrae.fr (A. Mamassi).</footnote>
conditions (Clapp, 2015).

Pursuing FSS goals can generate both synergies—positive in-
teractions that enhance sustainability—and trade-offs, where competing
demands create challenges (Clapp, 2017). These interactions stem from
various factors, referring to tangible elements (e.g., water, agricultural
land), dynamic circumstances (e.g., population growth), environmental
conditions (e.g., climate), and broader influences that plays a role in
shaping interactions with the targeted objectives of achieving FSS ob-
jectives (Table S1). Expanding agricultural land, addressing crop yield
gaps through the adoption of advanced technologies and management
practices, and optimizing resource-use efficiency may hold promise for
fulfilling FSS goals (Asseng et al., 2018; Davis et al., 2016). However,
these and other intensive agricultural strategies also entail trade-offs
and negative consequences, such as increasing global greenhouse gas
(GHG) emissions (Tilman et al., 2011) and depleting groundwater re-
sources (Luo et al., 2022) and biodiversity (Erb et al., 2016; Zhou et al.,
2023). Thus, identifying the factors that limit or strengthen efforts to
achieve FSS goals across multiple sectors can help to facilitate the
transition away from siloed strategies implemented by governments
towards more holistic development strategies. Moreover, assessing these
interactions can reveal contextual condition might have an influence.

The literature investigating the interactions of multiple factors with FSS spans multiple disciplines and shows that these relationships may be multi-lateral (i.e., the interaction that FSS objectives has at the same time with multiple factors, including as well interferences between factors). These factors' interactions with FSS have been systematically examined across research frameworks tailored to offer regional development strategies for specific regions of interest, incorporating key factors and context-specific dynamics to effectively address localised objectives. Analysing the co-occurrence of diverse factors in interaction with FSS can significantly facilitate their categorisation into clusters representing distinct research frameworks that usually consider those factors together in their analyses. Examples of such research frameworks include water-cropland resource allocation (Govoni et al., 2021), crop management systems (Luo et al., 2023), ecosystem services (Sun et al., 2023), and the water-energy-land nexus (Al-Thani et al., 2020). Identifying clusters of factors interacting with FSS and analysing them together not only aids in identifying the key factors of interest within each research framework but also highlights the geographical regions where these interactions are most pertinent. Such insights are crucial for refining scientific research goals (i.e., research frameworks) and ensuring that they align with regional priorities and local development strategies.

The literature still lacks extensive studies that thoroughly explore the
various types of factors spanning various sectors and their interactions
associated with achieving FSS. Additionally, the nature of those in-
teractions, their context dependency and complexity, and the in-
teractions among them have yet to be fully examined. To fill this gap, we
conducted a systematic review of the scientific literature addressing FSS
and its interactions with relevant factors. We specifically addressed the
following questions: i) What factors have been identified in the literature
as being in interaction with FSS? ii) What is the nature of the in-
teractions (i.e., positive, negative, or neutral) between these factors and
FSS? iii) What are the characteristics of each FSS-factor interaction,
including the contextual and the multi-lateral interactions with other
factors? And iv) how can analysing multi-lateral factor interactions
provide a foundation for identifying key research frameworks [i.e., the
type orientation adopted by a specific scientific community to investi-
gate the interactions of specific factors with the objective of FSS, as well
as the multilateral interactions between these factors (Table S1)] and, in
turn, how they shape the primary local agricultural development stra-
tegies to achieve FSS objectives? [i.e., from the perspective of imple-
menting an FSS policy, major local development agendas that are
increasingly focusing on agriculture and food production systems,
prioritizing strategies such as agricultural intensification to enhance
productivity (Table S1)].

## 2. Methods

We conducted a systematic scientific literature review to identify and characterize interactions between FSS and other factors, such as economic, social, environmental, or agronomic factors. We applied the standardised protocol “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) (Moher et al., 2009). Our analysis comprised three main steps: i) identifying, screening, and selecting peer-reviewed scientific papers from the literature; ii) structuring and filling a database with the relevant information extracted from the selected literature; and iii) performing descriptive statistics and cluster analysis on the constructed database to evaluate the reported interactions between FSS and other factors and to characterize the factors’ multi-lateral interactions and classification within the main research frameworks.

2.1. *Search strategy and paper selection*

In our initial literature scoping, we identified 1,257 documents (excluding duplicates) through our search of the Web of Science and Scopus databases in January 2024 (Fig. S1). We looked for peer-reviewed scientific papers in English studying, with any methods, with the interaction between FSS and other factors. The Boolean request was composed of the terms (“interaction” OR “trade-off” OR “compromise” OR “synergy” OR “nexus” OR “competition”) AND (“food” OR “feed”) AND (“self” OR “local”) AND (“sufficiency” OR “reliance” OR “supply” OR “foodshed”). Then, at each step of the PRISMA protocol, we established key inclusion and exclusion criteria (Table S2) to select relevant publications. Duplicate papers, review papers, and book chapters were excluded. Titles, abstracts, and keywords of the remaining articles were screened to retain those that met the predefined criteria. Afterwards, the full texts of the remaining articles were screened for eligibility. The document selection process, information on the data sources, and the classification results for the associated database are provided in the Supplementary database.

## 2.2. Dataset extraction and database construction

We reviewed the full texts of the 109 selected articles to extract and structure the information useful to our study. We extracted each article's general information (e.g., DOI, journal, publication year) and spatio-temporal context (e.g., study scale, the country or region investigated, FSS level) as well as the feed or food item (e.g., wheat, chicken) or group (e.g., cereal, meat) for which FSS was addressed, FSS indicators (e.g., self-sufficiency ratio [SSR]), the factors in interaction with FSS (e.g., a natural element or resource like water, a circumstance like population growth, a condition like weather, or an influence), the factors' indicators or measurements, the type of interaction between FSS and the factors (i. e., positive interactions/synergies, negative interactions/trade-offs, or neutral interactions that represent the absent or non-significant interactions or effect), and the methodologies implemented to analyse the interactions (e.g., data-driven analysis, scenario analysis, approach and methods, models, optimization). Information pertaining to these elements was compiled into an associated database (Supplementary database) and organised into two sheets: i) the “General Descriptive Dataset”, which links each article to its corresponding information (with one row per article), and ii) the “FSS vs. Factors Dataset”, which links each factor extracted from the articles to its relevant information (with one row per factor). In Table (S1), we define the key terms and concepts central to this database and the current article to enhance clarity and facilitate a seamless understanding of the text, underlying analyses, and derived results. More information and metadata for this database are reported in the “Metadata” included in the Supplementary database.
## 2.3. Descriptive statistics

To better understand the geographical distribution of key characteristics of FSS across the world's regions of interest, we mapped the number of selected papers by country, identified the main food items studied in each region, and assessed the level of FSS (i.e., self-sufficiency ratio "SSR"). The SSR was calculated using FAO Food Balance Sheets, based on a three-year average (2018–2020) of cereal and tubers import dependency ratios, which were inverted to derive the SSR for the countries represented in the published articles. Additionally, we defined, classified, and visualised the factors, the adopted nomenclature, and the frequency distribution of the presence of these factors in the studies. Also, the nature of the FSS-vs-factor interactions and their frequency across different factor groups were illustrated using a ring diagram. We presented further details on the characteristics of these interactions, including their nature and the interacting contextual factors. We used IBM SPSS Statistics v.25 (IBM Corp, 2017) for the cross-tabulation, frequency distribution, and mapping visualisations. Moreover, extracted data on the methods, approaches, and models used were further handled, analysed, and visualised as a Sankey diagram in R (R Core Team, 2023) using the ggsankey R package.

## 2.4. Cluster analysis

A cluster analysis was conducted to analyse the factors often analysed together in interaction with FSS. After identifying clusters, we examined the articles in each group to highlight the main interactions among the factors (e.g., how water-energy-land resources relate to FSS goals). This step helped us determine the primary research frameworks for each cluster and emphasise the nature of the interactions rather than just their co-occurrence. This approach aligns with a similar cluster analysis by Breure et al. (2024).

Outlined hereafter are the key steps of this cluster analysis: First, we used an unsupervised learning approach with a K-mode cluster algorithm (i.e., for categorical dataset) (Huang, 1998) to group articles by the factors' co-occurrence pattern or layout. Second, the number of clusters to be retained was predefined using the "gap statistic" algorithm (Tibshirani et al., 2001). Third, and after defining the clusters (n = 8), we visualised the distribution of the factors' appearance within each cluster. Fourth, and for each cluster, we utilized the relevant co-occurring factors types, the main scientific discipline of the articles, and information from the articles' titles and abstracts to elucidate the main characteristics of the cluster. Finally, we identified the research frameworks that were associated with the articles of each cluster and corresponded to the relevant conducted scientific analysis or evaluation and study aims and identified the regions of interest. The clustering analysis was performed using the following R packages: klaR (Weihns et al., 2005), cluster (Maechler et al., 2023), and factoextra (Kassambara and Mundt, 2020).

Examining the interactions among multiple factors established a foundation for identifying key research frameworks that align with regional priorities and local interests. These frameworks served as a guide for defining four core agricultural development strategies implemented to achieve FSS. In the present study, by leveraging the research frameworks (clusters) and their associated articles and information, we identified the key agricultural management strategies and shaped a discussion around the specific regions of interest, the key factors, and the context-specific nature of the interactions to address the localised objectives of FSS.

# 3. Results

## 3.1. Description of the selected studies

The database predominantly (90%) comprises articles from the last decade (2014–2024), with 58% published after 2020 (i.e., during and

after the COVID-19 pandemic), illustrating the research trend towards analysing FSS (Fig. S2). The studies are geographically distributed across 84 countries, with 24% taking place in China (Fig. 1a). FSS has mainly been assessed at the regional (52% of selected studies) and country scales (35%) but also at the global scale (3%) and over multiple scales in the same study (10%) (Supplementary Results [Fig. S3]). The database captures a wide range of FSS levels, including countries with very low levels (e.g., SSR = 0 mostly in Caribbean countries and Gulf countries) to very high levels (e.g., SSR = 4.3 in Ukraine) of FSS. More than 60% of the countries referenced in the reviewed articles exhibit local cereals insufficiency (SSR <0.85) (Clapp, 2017), the majority of which are located in sub-Saharan Africa, the Middle East and North Africa (MENA) region, southern Asia, and the Caribbean (Fig. 1c). Moreover, FSS was assessed for local staple food items (e.g., cereals, pulses, or tubers) in 91% of studies and for multiple food groups in 36% of studies (Fig. 1b). FSS was assessed for all food groups in regions or countries with the lowest levels of FSS (SSR <0.1) (e.g., Gulf countries) and those with the highest levels of FSS (SSR >2) (e.g., Nordic countries, Argentina) (Fig. 1b; Fig. 1c). Studies analysing FSS levels for individual staple foods focused on cereals: specifically, rice in sub-Saharan Africa and southern Asia and wheat in the MENA region. Research exploring the FSS levels for legumes was concentrated in European countries, such as France and Switzerland, and extended to examine soybean FSS across all of Europe and in China (Fig. 1b). Similarly, studies that analysed FSS levels for vegetables, fruits, and animal products predominantly focused on European countries, such as Spain and Germany, and the United States of America (USA).

Comprehensive details on the descriptive results of the reviewed studies are provided in the Supplementary Material. This includes: i) the scale of studies (e.g., regional level, national level etc.) (see supplementary result; Fig. S3); ii) the disciplinary and research communities engaged in studies (e.g., food science, agronomy science etc.) (see supplementary results; Fig. S4); iii) the applied analyses (e.g., status analysis, optimization analysis etc.), methodologies (e.g., modelling, data driven etc.), and tools utilized in studies (e.g., dynamic model, economic model, optimization algorithms etc.) (see supplementary results; Fig. S5); and iv) The FSS indicators employed in studies (e.g., FSS related indicators, food supply related indicators etc.) (see supplementary results; Fig. S6).

## 3.2. Conceptual framework of FSS-factor interactions

The conceptual framework in Figure (2) was developed based on the organization of factors extracted from the review of the literature, it further served as our guiding structure in the for conducting the subsequent meta-analysis. In particular, we i) harmonised the nomenclature of the factors and interactions identified in the literature (e.g., we standardised the name of a factor to "carbon/GHG emissions", replacing terms such as "CO₂ emissions", "GHG emissions", and "N₂O emissions", among others, that appeared in the different papers), ii) classified the individual factors into 17 thematic groups (definition in Table S1) to streamline the visualisation and interpretation of the results, and iii) categorized the factors' groups into three levels (definition in Table S1): (1) *high-level driving factors*, which impact the food system and FSS but are not generally impacted by FSS achievement, (2) *food system- and value chain-related factors*, which demonstrate a bilateral cause-effect relationship with FSS, and (3) *impacted factors*, which are impacted by the food system but do not influence FSS.

## 3.3. Identification of factors and their interactions with FSS

We identified a large number of factors in interaction with FSS (n = 47) (Fig. 2; Fig. 3), we organised in 17 distinct groups, which we further classified across three levels according to their interaction dynamics (Fig. 2; Fig. 3). A total of 308 interactions between FSS and other factors were analysed in the studies forming the database (Fig. S7). The
<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Descriptive geographical characteristics of the 109 studies included in the systematic review. a) Spatial distribution of reviewed articles frequency across studied countries; b) Spatial distribution for key studied food types (or items) across examined countries in the reviewed articles; c) Spatial distribution of self-sufficiency ratio (SSR) values across countries of reviewed articles. SSR calculation source: FAO Food Balance Sheets, 3-years average (2018–2020) data for cereals-tubers import dependency ratio (inverse of SSR) is converted to calculate the SSR for the countries of published articles. Six countries (Aruba, Bahrain, Bhutan Guadeloupe, Reunion Island and Qatar), “Europe” and “Overall world” did not have data to calculate SSR.</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** A conceptual framework highlights the interactions' web between FSS and the other factors. Illustrative organization of factors into semantic groups that were also categorized into three levels based on interactions dynamic (i.e., high-level driving factors, food system- and value chain-related factors, and impacted factors and outputs from the food system). The outer black arrows illustrate the long-term impact of low-level outputs on the food system and higher-level factors. Agricultural land is depicted as a resource type factor in cropland expansion, allocation and redistribution strategies and as an agronomic type factor under crop competitions and management strategies, as indicated by contextual studies. UA: urban agriculture; Practices: Management practices.</figcaption></figure>

majority of interactions (84%) involved factors integrated within the food system, as illustrated in Figure (3) and Figure (4). Some thematic groups were more frequently studied than others, with “agricultural land” being the most studied group (representing 22% of the 308 analysed interactions), followed by “water”, “management practices”, and “trade and market”.

The 47 factors were examined at different geographic scales (Supplementary database). At the regional level (i.e., administrative, watershed, and rural village areas), the factors were more diverse, and the key thematic groups of factors included “agricultural land”, “water”,

“management practices”, and “habitat quality/biodiversity”. “Urban agriculture” was a significant group of factors considered at the metropolitan scale (i.e., the regional level). At the national level, the primary thematic groups of factors studied were “agricultural land”, “water”, “climate, emissions/pollution”, “trade/market”, and “dietary patterns”. Finally, at the macro-regional (i.e., continental or multi-country) and global scales, the main factor groups analysed were “climate”, “agricultural land”, and “management practices”.

“Water”, “agricultural land”, “management practices”, and “climate” are critical groups of factors that have been extensively analysed in
<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Description of factors and their groupings. The Sankey diagram visually represents the classification of factors reviewed in the articles, showing the association of their frequency flows among various groupings and levels of interactions' dynamic with the FSS objective.</figcaption></figure>

island nations (e.g., Caribbean islands), sub-Saharan African countries, and the MENA region (Supplementary database). The analysis of interactions between “trade and market” group-related factors and FSS objectives has focused on geographic regions with the lowest FSS levels (SSR <0.1), such as Gulf countries and Caribbean islands, as well as on countries with the highest FSS levels (SSR >2), such as Ukraine, Argentina, and the Nordic region. Diets shifts and crop competition—particularly between bioenergy/no-food industrial crops and food crops—have been studied more frequently in European countries and China. Additionally, factors related to “population density”, “urbanisation”, and “urban agriculture” groups have been explored predominantly in a few developed countries, mostly in Europe and the USA.

### 3.4. Relationships between FSS and other factors

Among the 308 studied interactions, trade-offs were more frequent (63%) than synergies (30%) and neutral relationships (7%) (Fig. 4 and Fig. S7). The majority of factors (41 out of 47) were involved in a trade-off with FSS at least in one study. The most frequently involved factor groups in trade-offs are, in order of prevalence, “agricultural land” (22%) and “water” (13%), followed by “population density”, “trade and market”, and “habitat quality and biodiversity”. Approximately half of the factor types were involved in a positive relationship with FSS in at least one study. The factor groups frequently involved in synergies are “management practices” (25%), “agricultural land” (22%), and “urban agriculture” (9%).

### 3.5. Context dependency of FSS-factor interactions

We found that 28 factors demonstrated context-dependent interactions with FSS (Fig. 4 and Fig. S7), highlighted by the following examples.

The first example regards the availability of agricultural land and water resources. Addressing a population's food demand necessitates the availability of land allocated to agricultural activities and water resources as the primary factors in crop growth and production. The main contexts for trade-offs and negative relationships were related to regions suffering water and agricultural land resources scarcity and severe climate conditions. The second example regardsthe “management practices” group. The key factors are related to technological

advancement, fertilisation strategies, agricultural input use, and the adoption of sustainable farming practices—depends on the capacity of each management practice and technology to enhance crop productivity and resource-use efficiency, all while maintaining sustainable resource management, enhancing habitat quality, and preserving biodiversity. For instance, despite their demonstrated benefits for soil, water and land resources conservation, adopting organic, conservation, or carbon farming could manifest a changing nature of interaction with FSS due to their relatively low efficiency in sustaining or enhancing crop productivity (an FSS component) related to the minimal use of agricultural inputs in comparison to conventional cropping systems (Drofenik et al., 2023). The third example regards the choices made by actors and decision-makers regarding agricultural production systems and crop types—e.g., decisions on land distribution and agricultural land allocation—led to shifts in the nature of the interactions between FSS goals and “agricultural land” factors.

### 3.6. Characteristics of between-factors multi-lateral interactions within FSS objectvies

On average, three factors were considered simultaneously. Twenty-five articles (23%) analysed the interaction of only one factor with FSS, primarily including factors from the “urban agriculture”, “actors”, “food use”, and “trade/market” groups (Table S3). Thirty-three articles (30%) examined the interaction between two factors and FSS, with the most common pairs being “agricultural land” and “management practices” and “agricultural land” and “water” (Table S3). Thirty articles (29%) investigated three factors; the range of factors was diverse, typically including combinations from the “water”, “agricultural land”, “climate”, and “management practices” groups. Finally, 30 articles (29%) analysed more than three factors, two of which considered a maximum of six factors (Supplementary database). The binary co-occurrence matrix of factors (Table S3) reinforces the earlier findings of the predominance of food and agricultural production-related factors (production component of FSS)—particularly agronomic and resource-related factors—as central to interactions with FSS. Notably, “agricultural land”, “management practices”, and “water” frequently co-occurred, forming multi-lateral linkages not only within the agro-nomic and resource discipline but also with a broad spectrum of environmental, social, and economic factors. By contrast, other
<figure><img src="image_7.png" /><figcaption>Fig. 4. The nature of FSS vs. Factors interactions and their frequency among factors groups. The outermost ring, with varying degrees of brown, represents a classification of the 17 factors' groups by the levels of interactions' dynamic between the FSS objective factors. The three inner rings depict the nature of these interactions: green for positive, red for negative, and blue for neutral. The circles within these rings indicate the frequency of the contextual nature of factors in-teractions with FSS, using the same colors assigned to the 17 factors groups as shown in Figure (2). Details on the contextual nature of FSS versus factor interactions, including the drivers of these interactions (or their underlying reasons), are provided in Figure (S7).</figcaption></figure>

environmental, social, and economic factors, specifically those repre-
senting food distribution or consumption components, have been less
frequently examined in the literature, appearing in either isolated in-
teractions with FSS or multi-lateral interactions with other variables
(Table S3) (Supplementary database).

3.7. Clusters and research frameworks

We delineated eight primary clusters, and we defined each cluster's
associated research framework, main factors, and world regions of

interest (Fig. 5) (Table S4). Below, we provide main information on the
eight clusters.

* “Cluster 1” regroup research studies on the assessment of agricultural land allocation or redistribution, and cropland competition scenarios against the achievement of FSS objectives.

* “Cluster 2” includes studies on the multi-objective optimization of trade-offs between conservation goals, specifically, the compromises between the sustainable local food provision (i.e., FSS objective) and biodiversity preservation, resource conservation and habitat quality.
<figure><img src="image_8.png" /><figcaption>**Fig. 5.** The extracted eight clusters that represent scientific research frameworks: “Cluster 1: Evaluation of agricultural land allocation/redistribution and cropland competition scenarios”, “Cluster 2: Analysis of intensified agricultural production systems”, “Cluster 3: Analysis of sustainable food production systems”, “Cluster 4: Evaluation of crop management practices and optimization analysis”, “Cluster 5: Analysis of the water-energy-food-land (WEFL) nexus”, “Cluster 6: Analysis of urban agricultural systems”, “Cluster 7: Multi-objective optimization of trade-offs between ecosystem services” and “Cluster 8: Individual factors vs FSS interactions assessment.”. The relevant factors in multilateral interactions included in each research framework, and the four main agricultural management strategies (AMS) that directly address the contextual challenges and opportunities highlighted by the research frameworks (or clusters).</figcaption></figure>

* “Cluster 3” regroup research articles on the analysis of intensified agricultural production systems, and evaluation of crop yield gaps and cropland expansion strategies for understanding the status of food self-sufficiency and explore the potential attainment of FSS objectives

* “Cluster 4” encompasses research on the analysis of urban agricultural (UA) systems, highlighting their importance for developed countries (e.g., European countries, USA) to achieve vegetables, fruits and animal product self-sufficiency under cities’ population and industry pressures as well as limited resources.

* “Cluster 5” encompasses studies analyzing sustainable food production systems and assessing FSS status, objectives, and scenarios under the constraints of minimizing GHG emissions, pollution, and resource degradation (i.e., sustainability targets).

* “Cluster 6” regroup research studies on the evaluation of crop management practices prospective and the optimization analysis of crop management solutions for enhancing local food systems and achieving FSS objectives.

* “Cluster 7” includes research studies on the analysis of Water-*Energy*Food*Land (WEFL) nexus, specifically, the comprehensive status, scenarios and optimization analysis of water, energy, land and food nexus under the sustainable target of enhancing local food systems and achieving FSS objectives.

* “Cluster 8” regroups research studies on individual factors-vs.-FSS interactions assessment, for example: Trade/Market vs. FSS (e.g., local vs. imported food, market prices fluctuations, virtual cropland and water flows), food-use vs. FSS (e.g., Food waste/loss)

### 3.8. Local development startegies

The analysis of the multilateral interactions among factors within the FSS goals provided a robust foundation for identifying key research

frameworks, represented by clusters of factors co-analysed in their interactions with FSS. These research frameworks align closely with regional priorities and local interests, which, in turn, shape the primary agricultural development strategies designed to achieve FSS goals. Drawing on the insights from the eight identified clusters and their associated studies, we established four main agricultural management strategies (Fig. 5) that directly address the contextual challenges and opportunities highlighted by the research frameworks (or clusters).

i. *Cropland expansion or cropland-water resources management strategies:* related to the research frameworks and the relevant multilateral interactions involved in “Cluster 1: Evaluation of agricultural land allocation/redistribution and cropland competition scenarios” and “Cluster 5: Analysis of the water-energy-food-land (WEFL) nexus”.

ii. *Yield gap closure:* emerged from the research frameworks of “Cluster 2: Analysis of intensified agricultural production systems”, “Cluster 3: Analysis of sustainable food production systems”, and “Cluster 4: Evaluation of crop management practices and optimization analysis”.

iii. *Cropping systems diversification/Integrated crop management:* related to research frameworks of “Cluster 2: Analysis of intensified agricultural production systems”, “Cluster 4: Evaluation of crop management practices and optimization analysis” and “Cluster 7: Multi-objective optimization of trade-offs between ecosystem services”.

iv. *Urban agriculture:* aligned with “Cluster 6: Analysis of urban agricultural systems”.

## 4. Discussion

At various spatial scales, the achievement of FSS policy objectives is
challenged by its interactions with factors across diverse sectors. The key limitations to attaining FSS goals stem from water and agricultural land resource constraints, which adversely affect local food production. Conversely, the adoption of advanced sustainable technologies and optimised resource-use efficiency offer promising avenues for success. Notably, the agronomic and resource-related factors (related to the production component), dominate the discourse surrounding interactions with FSS achievement. By contrast, the economic, political, environmental, and social factors related to the food distribution and consumption components have been less frequently explored (Tables S3 and S4).

## 4.1. A diversity of interactions involving multiple sectors

Our organization of the 47 total factors into 17 thematic groups, which were further classified into three levels based on their interaction dynamics with FSS (Fig. 2), underscores this complexity of the interplay between FSS and other factors.

The key trade-offs arose between the objective of achieving staple FSS and two pivotal factors limiting local food production, water and agricultural land (Fig. 4). Moreover, the positive nature of the interactions between FSS goals and the management practices group of factors highlights the potential of advanced technologies and strategies for sustainability and resource-use efficiency in overcoming these limitations. Nevertheless, various factors (28 out of 47) displayed contextual interactions with achieving FSS goals. These factors may exhibit trade-offs, synergies, or neutral relationships with FSS depending on specific circumstances, including but not limited to spatiotemporal conditions and actors’ decisions. The contextual nature of most interactions arises from shifting spatiotemporal conditions. These shifts are driven by contextual variations in resource availability (e.g., water and agricultural land), climate parameters (e.g., temperature and rainfall), the impacts of climate change, and the economic statuses of countries. Additionally, context dependency is influenced by variations in decision-making by actors. These decisions include choices start from the farmers’ adoption of crop management practices and crop choices (e.g., fertilization methods, irrigation strategies, or levels of technology used) to policymakers implemented strategies for allocation of resources (e.g., water-use policies, land-use and allocation) (Fig. S7). The context dependency of the interactions further relies on shifts in dietary patterns and the adaptability of consumers (i.e., the local population), influenced by local traditions, population’s preferences and acceptance of dietary shifts. The efficiency of food utilisation, reflected in consumption levels and food waste, is another cause of context dependency. These factors together shape the complex interplay among diet, consumer practices, and the sustainability of food systems.

## 4.2. Agricultural management strategies as food production-driven solution for achieving FSS goals

Developing effective and balanced agricultural management strategies is crucial to ensuring efficient and sustainable local food production to meet the population's demands, all while maintaining sustainable resource management, high economic efficiency, and environmental control (Clapp, 2017). By examining the literature and the different factors involved, we analysed their interactions with FSS goals under the implementation of four main agricultural management strategies for achieving FSS goals: cropland expansion or cropland-water resources management, yield gap closure, cropping systems diversification/integrated crop management, and urban agriculture. We emphasized how these strategies function as critical interventions for enhancing and advancing FSS goals, highlighting the key interactions associated with them. Additionally, we addressed their role in mitigating trade-offs between certain factors and FSS objectives and conducted an in-depth examination of the factors and the contextual nature of the interactions underpinning these strategies.

### i. Cropland expansion or cropland-water resources management

Increasing FSS levels requires expanding the land allocated to agricultural activities. By prioritizing cultivating more agricultural land with staple and nutritionally essential crops, this strategy aims to bolster local food availability, improve self-reliance, and reduce dependence on imported agricultural commodities. However, most of the reported countries lack sufficient suitable agricultural land for expansion (e.g., islands [Russeil et al., 2023]), sufficient water resources to irrigate the additional cultivated land (e.g., sub-Saharan African countries [Van Ittersum et al., 2016]), or favourable climate conditions (e.g., MENA region [Asseng et al., 2018]) to sustain the growth of agricultural production on the expanded land. Furthermore, expanding cropland for nutritionally essential food production within the framework of countries' FSS policy may involve reallocating areas currently allocated to grasslands, forests or even resource-intensive crops; cash crops, non-food industrial crops or energy crop, which are more economically profitable. These cropping systems are often suited to the existing climatic conditions of these countries—e.g., cotton in sub-Saharan Africa (Hassan et al., 2000), fruit trees in MENA (Saidi et al., 2017), and oil palm in India and Southern Asia (Srinivasan et al., 2021)—and compete with essantial food crops for the same limited resources, which in turn impact staples self-sufficiency. Overall, the economic incentive creates a significant barrier to shifting towards staple or other essential food crops. Thus, targeted policies or subsidies are essential to make these crops financially attractive, enabling efforts to enhance regional food production and build resilience to market fluctuations. Expanding cropland for essential food production may require strategic management and sustainable repurposing of marginal lands. Moreover, optimizing land allocation to align with local FSS objectives could encompass not only the designation of specific cropland for particular food crops but also the integration of these crops through innovative practices such as crop rotation (Guilpart et al., 2022), intercropping and agroforestry (Burgess et al., 2022).

### ii. Yield gap closure.

The second agricultural strategy involves closing the crop yield gap through the adoption of advanced technologies and intensive cropping system management practices. Efficient and optimal fertilisation and irrigation, coupled with the use of adaptive management practices (e.g., cultivar selection, tillage, and pest and weed control) can ensure a higher crop yield and increase the capability of local food production systems to satisfy the demand of the local population (i.e., FSS goals) (Erb et al., 2016). When implemented effectively, these measures can significantly boost crop yields, positioning local production to better meet population food demands and the attainment of FSS goals. Modeling scenarios by Yuan et al. (2024) across 15 sub-Saharan African countries reveal that fully closing the current exploitable yield gap through enhancing fertilizer efficiency and optimizing irrigation practices could enable these nations to achieve complete rice self-sufficiency (i.e., the 15 countries' staple food). However, the adoption of this strategy must be supported by sufficient available water resources (Davis et al., 2016), the primary limiting factor of crop growth and production, or favourable local climate conditions for rainfed agricultural systems (Mamassi et al., 2022, 2023). Such intensive management also demands other substantial investments (e.g., infrastructure, irrigation schemes, roads, and supply chains), leading to high production costs (Lu and Van Ittersum, 2004). These costs may be economically unsustainable if the marginal expenses for additional inputs and labour do not result in the expected gross margin (i.e., FSS vs. economic efficiency trade-offs) (Wei et al., 2009). Also, within the yield gap closure strategy, the conventional application of agricultural inputs may amplify the GHG emissions from fossil fuel consumption and excessive fertiliser use and exacerbate water pollution from nitrate leaching (Tilman et al., 2011) and soil degradation due to salinity (Kopittke et al.,
2019). Furthermore, climate variability and climate change impacts pose significant challenges to global FSS objectives, primarily through its impact on crop yields, production stability, and the spatial distribution of agriculturally viable land (Kheir et al., 2024; Mamassi et., 2023; Peethani et al., 2024). Consequently, the yield gap closure strategy must be supported by context-appropriate, innovative and sustainable management practices and technologies to attain FSS goals while simultaneously ensuring climate resilience, sustainable resource management, enhancing habitat quality, and preserving biodiversity (Srinivasan et al., 2021; Zhou et al., 2023).

### iii. Cropping system diversification/Integrated crop management

From an FSS policy perspective, the cropping system diversification strategy allows export-dependent countries to improve their autonomy and control over the provision of various food types (not only the main exported items) and meet the local population's diverse dietary needs. Whilst, the strategic aim of import-dependent countries is to partially reduce dependency on imports by optimizing the use of their limited resources for the production of various local food types (Namany et al., 2019). Examples of export-dependent countries include Nordic nations (Karlsson et al., 2018; Osei-Owusu et al., 2019), Croatia (Tratnik et al., 2009), and Argentina (Auer et al., 2017), where cereals are the main exports (Osei-Owusu et al., 2019). Import-dependent countries; include Caribbean islands (Guell et al., 2022; Martin del Campo et al., 2023) and Gulf countries (Elmi et al., 2016; Namany et al., 2019), face unique challenges, such as a lack of resources (water for Gulf countries and cropland for Caribbean islands) and frequent extreme climate events (drought in Gulf countries and hurricanes in Caribbean islands). Overall, encouraging the local cultivation and consumption of diverse, climate-resilient crops through targeted policies that incentivize farmers can enhance both local population nutrition and sustainability. Complementary public awareness campaigns and collaborations with local markets are crucial for driving shifts in consumption patterns toward more diversified and healthful diets.

Adopting a cropping system diversification strategy within a prospective of FSS policy may entails trade-offs. First, certain countries typically possess resources that actually support the security of the current food supply (mainly staple foods). Hence, the resources required to diversify food production towards more resource-intensive production, such as vegetables and animal products, could strain the current cropping systems (Osei-Owusu et al., 2019). Second, a global concern related to this diversification strategy is its potential to disrupt trans-boundary food security and economic stability: when major exporters reduce the production of staple foods to boost production of other food types, the availability of these staples on the international market may decline. Such a reduction could trigger food crises and cause fluctuations in global market prices, a phenomenon economists refer to as “market distortion” (Clapp, 2015; Naylor and Falcon, 2010). Third, in countries with abundant livestock production, adopting an integrated crop management to include feed legumes spurred interest in analysing food versus feed competition. This scenario of adopting feed legumes FSS also reveals relevant contextual trade-offs in agricultural land requirements and economic profitability (Abdelkader and Elshorbagy, 2021) as well as synergies through the implementation of low-input and integrated sustainable management practices (Gebhardt et al., 2022), suitable climate conditions (Guilpart et al., 2022), and reduced GHG emissions and pollution (Liu et al., 2021). Research on feed legume self-sufficiency levels has been particularly concentrated in European countries, such as France (Jouan et al., 2020) and Switzerland (Keller et al., 2024), with significant attention given to soybean self-sufficiency across all of Europe (Guilpart et al., 2022) and China (Liu et al., 2021).

### iv. Urban agriculture

The worldwide rise in population density has intensified the food

demand and pressure on resources (Godfray et al., 2010) and is consistently accompanied by the expansion of urban areas and industrial activities (Sun et al., 2020). Urbanisation and industrialisation have led to a continuous reduction in peri-urban agricultural land and deterioration of regions' water resources (Qiu et al., 2022). Local food supply capacities have likewise continued to decline. Urban agriculture offers promising alternatives, as urban cropping systems, to face the evident challenges posed by population growth, urbanisation, and industrialisation. Implementing urban planning policies that integrate urban agriculture into city spaces—such as rooftop gardens, vertical farming, and community gardens—holds significant promise for improving the nutritional outcomes of metropolitan populations. It aims to regionalise food provision, bringing food production closer to where it is consumed and bridging the widening gap between local food supply and demand at a metropolitan scale. Within this strategy, interactions with FSS goals were examined in a few developed countries (Fig. 1a), mainly European countries (Monaco et al., 2017), the USA (Grewal and Grewal, 2012), and Australia (Ward, 2015). This research focused on integrating urban cropping systems containing vegetables, fruits, and certain animal products (e.g., fish and chicken) to improve these foods' partial FSS levels in populous cities. The synergies with FSS goals within the urban farming strategy were evident and included high resource-use efficiency (Small et al., 2019), the significant nutritional value of the cultivated food types (Ward, 2015), and reductions in household economic expenses (Grewal and Grewal, 2012) and the carbon footprint associated with transporting food (Small et al., 2019). However, the land, water, and energy requirements for urban agriculture are in direct competition with those of human domestic uses, which drives up the cost of urban food production (Small et al., 2019). Additionally, the limited potential of urban morphology and relevant farming systems to accommodate certain crop types poses a problem (Toboso-Chavero et al., 2023). Negative aspects may also include on-site GHG emissions and water, air, and soil pollution (Toboso-Chavero et al., 2023).

### 4.3. General lessons and limitations

FSS can be achieved through various pathways, each characterised by distinct trade-offs and synergies. Navigating the trade-offs requires identifying balanced, context-specific solutions across multiple dimensions and sectors—economic, political, social, and environmental—representing the best compromise between competing objectives. Furthermore, identifying strategies to foster synergies can enhance policymakers' capacities to simultaneously promote environmental sustainability, economic growth, social well-being, and resource management at regional and national scales.

This systematic review exploring the relationships between FSS and various factors has revealed the intricate contextual characteristics of these interactions. The context dependency of the nature of the interactions and the multi-lateral interactions among certain factors emphasise the necessity of predefining contextual conditions to support both qualitative and quantitative analysis of the nature of the interactions. Following a discussion of the major factors' groups (i.e., water, agricultural land, and management practices) and their interactions with FSS goals, we further analysed the interactions occurring under comprehensive agricultural strategies, highlighting these strategies' roles in supporting the achievement of FSS objectives, and examined the contextual trade-offs or synergies between certain factors and FSS goals.

This study selected search approach and systematic protocol, although executed with due diligence, may not be exhaustive, potentially leading to the exclusion of certain relevant studies. We exclusively concentrated on peer-reviewed and English language studies. This choice might surely be biased by the dominance of English as the primary language to study such extensive scientific topic. Also, during the screening step of the protocol (Table S2), our search was limited to the topic title, abstract and keywords, potentially, overlooking papers where
relevant terms appeared solely in the main text.

In this study, we described the qualitative nature of the interactions associated with achieving FSS goals but not the effect sizes of the influencing factors. Although we clearly define interactions as trade-offs, synergies, or neutral, the effects were not quantified; a positive or negative interaction may have a minimal or substantial effect. Thus, it is crucial to qualitatively assess these interactions while also highlighting the ranges of quantified impacts reported in the literature. Future research should focus on systematically quantifying these effects across multiple studies, potentially requiring the analysis of groups of factors according to their field (or sector) or spatiotemporal considerations in separate investigations.

## 5. Conclusion

FSS as a food policy or orientation, aligned with the United Nations' Sustainable Development Goal 2, Ending Hunger, aims to enhance autonomy and control over local food supplies. However, the implementation of such a food policy at the regional or national level must adapt to multidimensional factors and contextual conditions. Our results highlight the key trade-offs that arise between the objective of achieving FSS and two pivotal resources—water and agricultural land—as well as the strong positive interactions between FSS and management practices. The latter interactions underscore the transformative potential of advanced technologies and strategies that offer promising pathways for enhancing sustainability and resource-use efficiency, thereby overcoming existing challenges and driving progress towards FSS targets. Moreover, we showed the overt lack of studies focused on improving food consumption, distribution, and access to reach FSS targets. Finally, we identified four key developmental strategies based on agricultural management approaches to support the achievement of FSS objectives: cropland expansion or cropland-water resource management, yield gap closure, cropping systems diversification/integrated crop management, and urban agriculture. Those strategies that necessity actionable steps such as adopting context-specific agricultural practices and optimizing resource use to mitigate the relevant trade-off associated to FSS objectives, and ensure that interventions are closely in synergy with regional priorities and global Sustainable Development Goals (SDGs).

This systematic review confirms that the literature on interactions with FSS is heavily skewed towards agriculture and local food production component, with significantly less attention given to economic, political, and social factors associated with food consumption and distribution. This slant is contradictory to the critical role of the food consumption, distribution and access components in addressing food insecurity, particularly in fulfilling two dimensions of food security: food utilisation and stability. Further research in this direction can unlock potential policies that encourage a holistic approach towards FSS. Specifically, future studies could delve into the intricate interactions among distribution networks, access strategies, and consumption patterns within the broader context of production systems and environmental sustainability. Additionally, localized investigations are essential to unravel the socio-economic and cultural dynamics influencing food access, distribution, and consumption, particularly through the lens of FSS-oriented policy development.

### CRediT authorship contribution statement

**Achraf Mamassi:** Writing – original draft, Visualization, Software, Methodology, Formal analysis, Data curation, Conceptualization. **Nicolas Guilpart:** Writing – review & editing, Validation, Methodology, Conceptualization. **Lucile Muneret:** Writing – review & editing, Visualization, Validation, Methodology, Conceptualization. **Francesco Accatino:** Writing – review & editing, Writing – original draft, Validation, Supervision, Resources, Project administration, Methodology, Funding acquisition, Formal analysis, Conceptualization.

### Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests. Achraf MAMASSI reports financial support was provided by French National Research Agency. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### Acknowledgements

This work benefited from the French state aid managed by the ANR under the "Investissements d'avenir" programme with the reference ANR-16-CONV-0003.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.gfs.2025.100841.

### Data availability

Data will be made available on request.

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