Circular Economy Strategies in Sustainable Agriculture: Pathways to Climate Resilience and Decarbonization

Abstract

In the context of accelerating climate change and increasing pressure on natural resources, agriculture needs to rethink its operating models to ensure both sustainability and long-term stability. The circular economy (CE) is increasingly invoked as a possible solution, but its concrete contribution to the climate resilience of agricultural systems remains insufficiently integrated and often assessed in a fragmented manner. This study aims to analyze the role of circular strategies in strengthening the climate resilience of agriculture, through a systemic approach based on multiple indicators. The methodology is based on a structured and comparative analysis of recent scientific literature, complemented by a bibliometric and co-occurrence analysis of keywords, in order to identify the main research directions and evaluation methods used. The analyzed indicators cover dimensions related to soil, water, crop performance, energy and socio-economic resilience of farms. The results suggest that circular economy strategies may contribute to climate resilience through cumulative, and context-dependent effects, including improvements in soil quality, resource-use efficiency, and reduced dependence on external inputs. However, evidence regarding direct impacts on production stability and adaptive capacity remains heterogeneous and often indirect. The study contributes by proposing an integrated conceptual framework that highlights the systemic nature of climate resilience and its links to decarbonization pathways, providing a basis for future empirical research and policy development.

1. Introduction

Contemporary agricultural systems are at a critical juncture, being simultaneously among the sectors most exposed to the effects of climate change and, at the same time, important contributors to global greenhouse gas emissions (GHG). Rising average temperatures, increasing drought and extreme precipitation episodes, accompanied by soil degradation and biodiversity loss, are already affecting agricultural stability and productivity globally [1,2,3]. In parallel, agriculture and agri-food systems are considered responsible for a large share of carbon, methane and nitrous oxide emissions, generated through land-use changes, the application of synthetic fertilizers, the management of animal manure and energy consumption [4,5]. This context places agriculture in the center of climate change adaptation and decarbonization efforts, highlighting the need for a structural transformation in the way agricultural systems are designed and managed.

In order to address these gaps, this study is guided by the following research questions:

(i)

What types of circular economy strategies are most frequently applied in agricultural systems?

(ii)

Through which mechanisms do these strategies contribute to climate resilience?

(iii)

How do circular economy strategies support decarbonization processes in agri-food systems?

These questions structure the analytical framework of the study and guide the subsequent synthesis of the literature. In Figure 1, we present a conceptual scheme of the main directions discussed in this introduction. This was made in order to synthesize the ideas and facilitate understanding of the relationships between climate pressures, the limitations of linear agriculture, and the role of the CE in strengthening the resilience and decarbonization of agricultural systems.

Conventional agricultural models have been developed largely based on a linear logic of “extract-produce-consume-dispose”. This is characterized by intensive use of resources, dependence on external inputs and generation of significant amounts of waste. Although these systems have contributed to increasing agricultural production in the short term, they have led, over time, to the depletion of soil nutrients, a decrease in natural fertility and an increased vulnerability to climatic stresses [6]. In this context, CE has begun to be seen as an alternative framework capable of responding to the limitations of linear agriculture [7]. The latter proposes the closure of material cycles, the valorization of biological waste and the regeneration of natural capital [8,9]. Applied in agriculture, CE encourages practices such as nutrient recycling, composting, valorization of plant residues, the integration of crops with animal husbandry and the use of renewable energy sources [10,11,12].

In recent years, especially in the last decade, the concept of circular agriculture has been associated with the principles of sustainable and regenerative agriculture [5,8,13,14,15]. The focus has shifted from maximizing production to maintaining ecosystem functionality and soil health in the long term.

While a growing body of literature indicates that circular strategies can contribute to improved soil quality, water retention and biodiversity, the magnitude and consistency of these effects remain highly context-dependent and not yet fully comparable across different agro-climatic systems [16,17,18,19,20]. Moreover, existing studies often assess these benefits in isolation, without systematically linking resilience outcomes to emission reduction performance. These mechanisms are necessary for adapting to climate variability and reducing the risks associated with extreme events (such as prolonged droughts or flash floods). For example, an integrated analysis of circular approaches in agriculture highlights the role of circular nutrient management and integrated crop–livestock systems in strengthening the stability of agroecosystems [21].

In addition to adaptation benefits, CE in agriculture is indicated as a relevant tool for decarbonization [22,23,24,25,26]. Practices such as composting, use of organic fertilizers, recycling of agricultural residues and implementation of agroforestry are considered promising for reducing GHG. Also, they may contribute to carbon sequestration in soil and biomass. At the same time, the integration of renewable energy technologies and increased energy efficiency at the farm level tend to support the transition to low-carbon agri-food systems. These circular strategies may generate multiple benefits, combining a reduction in the carbon footprint with improved economic and social performance of farms.

Despite this, existing research often remains fragmented, focusing either on specific technological aspects or on isolated environmental or economic assessments. It does not provide an integrated picture of how circular economy strategies simultaneously contribute to climate resilience and to decarbonization of agricultural systems. In addition, there is no standardized methodological framework for evaluating circular strategies across studies, which leads to inconsistent results and limits the comparability of findings. The diversity of geographical contexts, methodologies used and types of agricultural systems analyzed makes it difficult to identify general conclusions on good practices, existing trade-offs and implementation barriers. In this regard, a structured literature synthesis that explicitly connects circular strategies with climate adaptation mechanisms and emission reduction trajectories becomes necessary.

Circular agriculture may also be interpreted within the planetary boundaries framework, particularly concerning biogeochemical nitrogen and phosphorus flows, land-system change, and biosphere integrity. By reducing synthetic fertilizer dependency and enhancing nutrient recycling, circular strategies directly address the transgression risks associated with nutrient overload. This broader Earth-system perspective strengthens the argument that circular agriculture is not only a sectoral adaptation tool but part of a global sustainability transition.

As illustrated in Figure 1, this review systematically links types of strategies, their underlying mechanisms, and their dual impact on climate resilience and decarbonization. By structuring the analysis across these three dimensions, the study addresses the lack of integrative frameworks identified in the previous literature.

This paper is structured to reflect the analytical framework introduced above. Section 3.2 and Section 3.3 examine the types of circular economy strategies and their implementation patterns, addressing the first research question. Section 3.4 and Section 3.5 analyze the mechanisms through which these strategies enhance climate resilience, corresponding to the second research question. Finally, Section 3.6, Section 3.7 and Section 3.8 focus on decarbonization-related aspects, systemic gaps, and integrative frameworks, addressing the third research question.

2. Methodology of Research

In order to properly analyze the role of circular economy strategies in the context of climate resilience and decarbonization in agriculture, this study adopted a structured review approach, informed by PRISMA 2020 guidelines [27]. Although the study follows the general workflow, it does so as a guiding structure for transparency in study selection. However, the objective is not to conduct a fully systematic review with formal meta-analysis or risk-of-bias assessment, but rather to provide an integrative and conceptually oriented synthesis of the literature on circular economy strategies in agriculture and their links to climate resilience and decarbonization.

The formal screening and selection process was conducted exclusively using the Web of Science Core Collection. Scopus and Google Scholar were used as supplementary sources to identify additional relevant studies and to ensure conceptual completeness during the synthesis phase, but they were not part of the formal inclusion flow.

The selection of the topic and keywords was carried out in an iterative manner, starting from the central concepts identified in the specialized literature and subsequently refined based on the preliminary results of the search. The main topic was defined as “agricultural and agri-food systems”. Following the initial search, 1415 documents were identified. The topic was combined with terms that explicitly reflect the dimensions of interest of the study, namely “climate resilience”, “decarbonization”, “agricultural circularity”, “carbon sequestration”, “circular agriculture” AND “circular economy”. The following Boolean search string was applied: (“agriculture” OR “agri-food system”) AND (“circular economy” OR “circular agriculture”) AND (“climate resilience” OR “adaptation” OR “decarbonization” OR “carbon sequestration” OR “greenhouse gas emission”). The search string was refined iteratively to balance sensitivity and specificity. This combination was chosen to capture both the perspectives of adaptation to climate change and those of reducing emissions, within a circular vision of agriculture. The use of logical operators of the “OR” and “AND” type allowed the controlled expansion of the set of results, while avoiding the inclusion of studies that have no direct link to the circular economy applied to agriculture.

A number of 77 articles were included in the qualitative synthesis (

Table A1. Review articles analyzed in detail and their contribution to the present study.

Nr.	Ref.	Author	Title
1	[20]	Boincean et al., 2026	Circular Economy and Sustainable Practices in Regenerative Agricultural Productivity
2	[28]	Thierfelder et al., 2018	Complementary Practices Supporting Conservation Agriculture in Southern Africa
3	[29]	Dagevos et al. 2021,	Circular Business Models and Circular Agriculture: Perceptions and Practices of Dutch Farmers
4	[30]	Velten et al. 2015	What Is Sustainable Agriculture? A Systematic Review
5	[31]	Nkoa, 2014	Agricultural Benefits and Environmental Risks of Soil Fertilization with Anaerobic Digestates: A Review
6	[34]	Paradelo et al., 2024	Potential and Constraints of Use of Organic Amendments from Agricultural Residues for Improvement of Soil Properties
7	[36]	Mehdizadeh et al., 2025	Agri-Waste Valorization: Pathways to Sustainable Bioenergy and Biochemical Innovation
8	[2]	Kabato et al., 2025	Towards Climate-Smart Agriculture: Strategies for Sustainable Agricultural Production, Food Security, and Greenhouse Gas Reduction
9	[3]	Sarfraz et al. 2023	Role of Agricultural Resource Sector in Environmental Emissions and Its Explicit Relationship with Sustainable Development: Evidence from Agri-Food System in China
10	[5]	Lakatos et al., 2025	Standardized Metrics in Regenerative Agriculture for Climate Change Adaptation and Mitigation
11	[6]	Telo da Gama et al., 2021	Assessing the Long-Term Impact of Traditional Agriculture and the Mid-Term Impact of Intensification in Face of Local Climatic Changes
12	[8]	Morseletto., 2020	Restorative and Regenerative: Exploring the Concepts in the Circular Economy
13	[12]	Selvan et al., 2023	Circular Economy in Agriculture: Unleashing the Potential of Integrated Organic Farming for Food Security and Sustainable Development
14	[14]	Schreefel et al., 2020	Regenerative Agriculture—the Soil Is the Base.
15	[17]	Sadiq et al., 2025	Conservation Agriculture for Sustainable Soil Health Management: A Review of Impacts, Benefits and Future Directions
16	[18]	Telo da Gama, 2023	The Role of Soils in Sustainability, Climate Change, and Ecosystem Services: Challenges and Opportunities.
17	[22]	Kazimierczuk et al., 2023	Decarbonization of Agriculture: The Greenhouse Gas Impacts and Economics of Existing and Emerging Climate-Smart Practices
18	[24]	Peng et al., 2025.	Circular Economy in Agriculture: A Systematic Literature Review
19	[26]	Kamyab et al., 2024	Carbon Dynamics in Agricultural Greenhouse Gas Emissions and Removals: A Comprehensive Review
20	[38]	Paini et al. 2022	Valorization of Wastes from the Food Production Industry: A Review Towards an Integrated Agri-Food Processing Biorefinery
21	[40]	Gupta et al., 2022	Biomass Conversion of Agricultural Waste Residues for Different Applications: A Comprehensive Review
22	[43]	Shanmugam et al., 2024	Crop–Livestock-Integrated Farming System: A Strategy to Achieve Synergy between Agricultural Production, Nutritional Security, and Environmental Sustainability
23	[44]	Lemaire et al., 2014	Integrated Crop–Livestock Systems: Strategies to Achieve Synergy between Agricultural Production and Environmental Quality
24	[45]	Farias et al., 2020	Integrated Crop-Livestock System with System Fertilization Approach Improves Food Production and Resource-Use Efficiency in Agricultural Lands
25	[47]	Getahun et al., 2024	Application of Precision Agriculture Technologies for Sustainable Crop Production and Environmental Sustainability: A Systematic Review
26	[48]	Aarif et al., 2025	Smart Sensor Technologies Shaping the Future of Precision Agriculture: Recent Advances and Future Outlooks
27	[52]	Cardenete et al., 2014	Agri-Food and Bio-Based Analysis in the Spanish Economy Using a Key Sector Approach
28	[60]	Al-Musawi, et. al., 2025	Utilizing Different Crop Rotation Systems for Agricultural and Environmental Sustainability: A Review
29	[61]	Puech, Stark, 2023	Diversification of an Integrated Crop-Livestock System: Agroecological and Food Production Assessment at Farm Scale
30	[74]	Sarker et al., 2018	Agricultural Management Practices Impacted Carbon and Nutrient Concentrations in Soil Aggregates, with Minimal Influence on Aggregate Stability and Total Carbon and Nutrient Stocks in Contrasting Soils
31	[87]	Dziedzic et al., 2022	International Circular Economy Strategies and Their Impacts on Agricultural Water Use
32	[91]	Mihrete, and Mihretu, 2025	Crop Diversification for Ensuring Sustainable Agriculture, Risk Management and Food Security
33	[92]	Sridhar et al., 2026	Crop Diversification Strategies for Sustainable Agriculture and Climate-Resilient Ecosystems
34	[95]	Matysik-Pejas et al., 2023	An Assessment of the Spatial Diversification of Agriculture in the Conditions of the Circular Economy in European Union Countries
35	[99]	Hassan et al., 2022	Improved and Sustainable Agroecosystem, Food Security and Environmental Resilience through Zero Tillage with Emphasis on Soils of Temperate and Subtropical Climate Regions: A Review.
36	[101]	Francaviglia et al., 2023	Conservation Agriculture and Soil Organic Carbon: Principles, Processes, Practices and Policy Options
37	[107]	Filonchyk et al., 2024	Greenhouse Gases Emissions and Global Climate Change: Examining the Influence of CO2, CH4, and N2O
38	[108]	Xing, Y. and Wang, X, 2024	Impact of Agricultural Activities on Climate Change: A Review of Greenhouse Gas Emission Patterns in Field Crop Systems
39	[110]	Ma et al., 2024	Nexus between Climate Change, Agricultural Output, Fertilizer Use, Agriculture Soil Emissions: Novel Implications in the Context of Environmental Management
40	[111]	Bathaei, and et Štreimikienė, 2023	Renewable Energy and Sustainable Agriculture: Review of Indicators.
41	[112]	Méndez Rodríguez et al., 2022	A Multidisciplinary Approach Integrating Emergy Analysis and Process Modeling for Agricultural Systems Sustainable Management—Coffee Farm Validation
42	[113]	Bergez et al., 2022	Integrating Agri-Environmental Indicators, Ecosystem Services Assessment, Life Cycle Assessment and Yield Gap Analysis to Assess the Environmental Sustainability of Agriculture
43	[120]	Murtaza et al., 2025	Biochar from Agricultural Waste as a Strategic Resource for Promotion of Crop Growth and Nutrient Cycling of Soil under Drought and Salinity Stress Conditions: A Comprehensive Review with Context of Climate Change
44	[115]	Silvestri et al., 2022	A Review of Energy-Based Indicators for Assessing Sustainability and Circular Economy in the Agri-Food Production
45	[126]	Whitton, and Carmichael, 2025	Systemic Barriers Preventing Farmer Engagement in the Agricultural Climate Transition: A Qualitative Study
46	[125]	Hilmi et al., 2024	Farmers’ Resilience to Climate Change through the Circular Economy and Sustainable Agriculture: A Review from Developed and Developing Countries
47	[123]	Sgroi, 2022	The Circular Economy for Resilience of the Agricultural Landscape and Promotion of the Sustainable Agriculture and Food Systems
48	[124]	Atanasovska et al., 2022	A. Research Gaps and Future Directions on Social Value Stemming from Circular Economy Practices in Agri-Food Industrial Parks: Insights from a Systematic Literature Review
49	[122]	Yang et al., 2023	Circular Economy Strategies for Combating Climate Change and Other Environmental Issues
50	[119]	Boudjabi et al., 2023	Enhancing Soil Resilience and Crop Physiology with Biochar Application for Mitigating Drought Stress in Durum Wheat (Triticum Durum)
51	[4]	Menegat et al., 2022	Greenhouse Gas Emissions from Global Production and Use of Nitrogen Synthetic Fertilisers in Agriculture
52	[7]	IaCOVIDou et al., 2021	A Systems Thinking Approach to Understanding the Challenges of Achieving the Circular Economy.
53	[10]	Apolo-Romero et al., 2025	Circular Economy Assessment of Biochar-Enhanced Compost in Viticulture Using Ecocanvas
54	[13]	Tindwa et al., 2024	Circular Regenerative Agricultural Practices in Africa: Techniques and Their Potential for Soil Restoration and Sustainable Food Production
55	[15]	Newton et al., 2020	What Is Regenerative Agriculture? A Review of Scholar and Practitioner Definitions Based on Processes and Outcomes
56	[16]	Anikwe, and Ife, 2023	The Role of Soil Ecosystem Services in the Circular Bioeconomy
57	[19]	Khan et al., 2024	Innovative Organic Fertilizers and Cover Crops: Perspectives for Sustainable Agriculture in the Era of Climate Change and Organic Agriculture
58	[104]	Landmann et al., 2023	Insect Diversity Is a Good Indicator of Biodiversity Status in Africa
59	[23]	Sroufe, and Watts, 2022	Pathways to Agricultural Decarbonization: Climate Change Obstacles and Opportunities in the US
60	[37]	Rațu et al., 2023	Application of Agri-Food By-Products in the Food Industry
61	[39]	Klein et al., 2021	Towards a Circular Bioeconomy? Pathways and Spatialities of Agri-Food Waste Valorisation
62	[46]	Ali et al., 2025	Circular Economy Advances with Artificial Intelligence and Digital Twin: Multiple-Case Study of Chinese Industries in Agriculture
63	[53]	Zucaro et al., 2017	Greenhouse Gas Emissions and Non-Renewable Energy Use Profiles of Bio-Based Succinic Acid from Arundo Donax L. Lignocellulosic Feedstock
64	[57]	Turmel et al., 2015	Crop Residue Management and Soil Health: A Systems Analysis
65	[58]	Liang et al., 2025	Integrated Management Practices Foster Soil Health, Productivity, and Agroecosystem Resilience.
66	[63]	Li et al., 2022	Enhancing Crop Productivity and Resilience by Promoting Soil Organic Carbon and Moisture in Wheat and Maize Rotation
67	[80]	Alharbi et al., 2024	Agricultural and Technology-Based Strategies to Improve Water-Use Efficiency in Arid and Semiarid Areas
68	[83]	Prasad, 2023	Sustainable Water Use in Agriculture—Circular Economy Approach
69	[90]	Vernooy, 2022	Does Crop Diversification Lead to Climate-Related Resilience? Improving the Theory through Insights on Practice.
70	[93]	Alletto et al., 2022	Crop Diversification Improves Cropping System Sustainability: An 8-Year on-Farm Experiment in South-Western France
71	[98]	Quintarelli et al., 2022	Cover Crops for Sustainable Cropping Systems: A Review.
72	[100]	Wang, 2022	Managing Land Carrying Capacity: Key to Achieving Sustainable Production Systems for Food Security.
73	[102]	Martínez-Mena et al., 2021	Long-Term Effects of Sustainable Management Practices on Soil Properties and Crop Yields in Rainfed Mediterranean Almond Agroecosystems
74	[106]	Zavalloni et al., 2025	Technological Innovations for Biodiversity Monitoring and the Design of Agri-Environmental Schemes.
75	[109]	Lin et al., 2025	Renewable Energy Consumption Efficiency, Greenhouse Gas Emission Efficiency, and Climate Change in Europe
76	[114]	Porter et al., 2009	The Value of Producing Food, Energy, and Ecosystem Services within an Agro-Ecosystem
77	[121]	Li et al., 2021	Role of Biochar in Improving Sandy Soil Water Retention and Resilience to Drought

Note: This table lists review-type scientific articles (including systematic, critical, and methodological reviews) used in the detailed synthesis supporting the proposed article framework.

). The reduction from the initial pool of 1415 records to the final sample of 77 studies resulted from a multi-stage screening process conducted in accordance with predefined inclusion and exclusion criteria. In the first stage, duplicate records and non-relevant documents were removed based on title and abstract screening. Subsequently, full-text screening was applied to assess the relevance of each study in relation to the objectives of this review, with particular attention to the focus on circular economy applications in agriculture and their link to climate resilience and decarbonization. Studies were excluded if they did not address these core themes, lacked sufficient methodological detail, were not peer-reviewed, or did not provide applicable empirical or conceptual contributions. This rigorous filtering process ensured that only studies directly aligned with the research scope and of sufficient methodological relevance were retained for the qualitative synthesis.

Inclusion criteria: English language documents, publication period between 2000 and 2026, peer-reviewed articles, explicit link to CE and agriculture and papers that discuss resilience OR decarbonization. The search was limited to articles published between 2000 and 2026 to capture both the early conceptual evolution of the circular economy in agriculture, as well as recent developments related to climate change and decarbonization.

Exclusion criteria: non-agricultural studies, editorials, conference abstracts, duplicates, irrelevant topics.

In order to address the methodological robustness of the included literature, a qualitative assessment of study quality was performed. The evaluation considered aspects such as clarity of research objectives, methodological transparency, type of study design, and the reliability of the evidence provided. Although no formal quantitative scoring system was applied, the classification of studies into conceptual, empirical, and review categories allowed for a general appraisal of the overall strength and limitations of the available evidence, which was taken into account when interpreting the results.

We refer to Figure 2 for the schematic of the research methodology.

Following the selection process, the included studies were analyzed using a thematic synthesis approach. The analysis focused on identifying recurring categories of circular strategies, their associated biophysical and socio-economic mechanisms, and the types of indicators used to assess climate resilience and decarbonization. Rather than applying a formal coding protocol, the synthesis was conducted iteratively, allowing the identification of dominant patterns, conceptual linkages, and research gaps across studies. Potential sources of bias and limitations inherent to individual studies were acknowledged and taken into account in the overall interpretation of the evidence.

To support the thematic selection and to obtain an overview of the conceptual structure of the analyzed literature, a bibliometric analysis of the co-occurrence of keywords was performed using the VOSviewer (version 1.6.20) software. The analysis was performed based on the keywords provided by the authors, setting a minimum threshold of five occurrences, in order to highlight only the dominant concepts and the relevant relationships between them. The results of the VOS analysis suggest the existence of well-defined thematic cores, centered around the concepts of agriculture, sustainability, management, circular economy and climate change. At the same time, it also suggested strong links with terms such as biodiversity, agroecology, governance and sustainable transitions. This structure reflects the interdisciplinary nature of the field and justifies the integrated approach adopted in the study. We refer to Figure 3 for the keyword analysis.

Thus, a central core of the network is dominated by terms such as “agriculture”, “sustainability” and “management”, indicating that most studies approach the circular economy from a systemic perspective. They seem focused on sustainable resource management and the transition of agricultural systems towards more efficient and resilient models. This cluster seems to functions as a conceptual convergence point, connecting the environmental, economic and institutional dimensions of circular agriculture.

A second major cluster is associated with concepts related to climate change and the environment, including terms such as “climate change”, “biodiversity”, “soil”, “water” and “vulnerability”. The presence of these keywords suggests that a significant part of the literature focuses on the impact of circular strategies on the functioning of agricultural ecosystems and their capacity to cope with climate stresses. This cluster reflects how these topics are commonly co-discussed in the literature, particularly in relation to climate resilience-related themes, such as improving soil health, conserving water and maintaining ecosystem services.

A well-defined thematic group is also represented by terms such as “circular economy”, “life cycle assessment”, “carbon”, “emissions” and “nitrogen”, reflecting that the literature is also focused on assessing the environmental impact and climate performance of circular farming systems. Studies associated with this cluster frequently use quantitative methods, in particular life cycle analysis (LCA), to assess the potential for reducing greenhouse gas emissions, resource efficiency and contribution to decarbonization. This thematic group is associated with the climate mitigation dimension of the circular economy and can provide the analytical basis for quantifying its benefits.

The VOS analysis also indicates the existence of a cluster focused on innovation and emerging technologies, characterized by terms such as “technology”, “digitalization”, “big data”, “internet of things” and “blockchain”. It reflects the growing interest in the role of digital solutions and smart technologies in facilitating the transition to circular farming, by optimizing resource flows, monitoring processes and increasing transparency in agri-food chains. Although this cluster is more peripheral compared to the traditional sustainability and environment cores, it points to recent and emerging research directions.

Overall, the distribution and interconnection of clusters highlighted by the VOS analysis suggests that CE in agriculture is approached as an integrative concept. It appears to be located at the intersection of sustainable resource management, climate resilience, decarbonization and technological innovation. This conceptual structure supports the relevance of the approach adopted in this study and justifies the need for a thematic synthesis that connects these research directions in a coherent framework. It should be emphasized that keyword co-occurrence analysis reflects thematic relationships within the literature and does not imply causal relationships or empirical validation of the concepts discussed.

The novelty of the methodological approach consists in combining a rigorous selection of the literature, structured based on the PRISMA principles, with an exploratory bibliometric analysis of the co-occurrence of keywords. The latter was carried out through VOSviewer, which allows not only an in-depth thematic synthesis of circular economy strategies in agriculture, but also a clearer understanding of the conceptual structure and emerging directions in the specialized literature on climate resilience and decarbonization. Future research could complement literature synthesis with system dynamics modeling or agent-based simulations to explore long-term circular transition pathways under different climate scenarios. Integrating bibliometric insights with dynamic simulation tools would allow stress-testing of circular strategies against projected temperature increases, water scarcity trends, and policy shocks. It is important to note that, due to the exploratory and integrative nature of this approach, no formal risk-of-bias assessment was performed. Therefore, the findings should be interpreted as a conceptual synthesis of the literature rather than as a quantitatively validated systematic review.

3. Results

3.1. General Characteristics of the Analyzed Literature

The analyzed corpus consists of articles published in international peer-reviewed journals indexed in major scientific databases, primarily covering sustainability, agriculture and environmental research fields. This indicates a growing scientific interest in the application of CE in agricultural and agri-food systems.

The analyzed corpus includes a combination of review articles, empirical studies, life cycle assessment analyses, and several case studies. Reviews play an important role in structuring the field, providing conceptual frameworks for circular agriculture and its relationship with climate resilience and decarbonization. In parallel, empirical studies contribute to quantifying the impact of circular strategies on environmental performance, especially through the use of the LCA methodology.

Regarding the agricultural fields addressed, a significant proportion of the studies focus on plant agriculture and integrated crop systems, with an emphasis on the circular management of nutrients, organic residues and biomass flows. The livestock sector is frequently analyzed in relation to nutrient recycling and emission reduction, while a smaller number of studies address the CE at the level of the entire agri-food chain. This progressive extension from the farm level to a food system perspective is highlighted in studies discussing circularity as a central element of the transition to sustainability.

From a methodological point of view, the reviewed literature reflects a clear orientation towards interdisciplinary approaches, combining quantitative assessments of environmental impact with conceptual analyses and case studies. Indicators related to soil health, water use and greenhouse gas emissions are the most frequently used to assess the contribution of circular strategies to climate resilience and decarbonization. Overall, these results suggest that the field of CE in agriculture is at a stage of maturation, but still requires integrated syntheses and better-defined comparative frameworks, aspects that are addressed to some extent in this study.

3.2. Types of Circular Economy Strategies and Trends Identified in Agriculture

The literature review indicates that CE strategies in agriculture are not applied through a single dominant approach, but rather through a set of complementary and context-dependent practices that show both convergence and variation across studies [28,29,30]. They are adapted to different types of agricultural systems, pedoclimatic contexts and levels of intensification. See Figure 4.

Several studies (e.g., Thierfelder et al. [28], Dagevos and de Lauwere [29], Boincean et al. [20]) converge in emphasizing that circular agriculture relies on combinations of practices rather than single interventions. While Thierfelder et al. [28] highlight the importance of context-specific adaptation in smallholder systems, Dagevos and de Lauwere [29] focus more on resource efficiency strategies in intensive systems, including biomass optimization and energy integration. In contrast, Boincean et al. [20] provide empirical evidence that long-term soil productivity benefits arise from the combined application of crop rotation and organic amendments, illustrating how complementarities between practices enhance system performance.

For example, analysis of Thierfelder et al. [28] highlights that in agricultural systems in southern Africa, the principles of circularity are applied through flexible combinations of practices such as crop rotation, maintaining crop residues on the soil, and integrating crops with livestock. The authors claim that there is no single solution applicable to all farms, and the effectiveness of practices depends on their adaptation to local soil, climate, and resource availability conditions, which supports the idea of circularity based on diversity and complementarity, not standardization.

The study by Dagevos and de Lauwere [29] analyzes CE in agriculture from a broader perspective, focusing on resource efficiency and reducing nutrient and energy losses. Through their study, they emphasize that circular strategies include a combination of practices such as recycling organic waste, using organic fertilizers, optimizing biomass flows and integrating renewable energies, applicable, especially in more intensive agricultural systems. Importantly, these strategies are presented as complementary, each contributing differently to sustainability objectives, without there being a dominant practice that alone ensures the transition to circularity.

Boincean et al. [20] emphasize that CE strategies in agriculture are not a singular tool, but an integrated set of complementary practices that need to be adapted to the local context and the specificities of agricultural systems in order to generate resilience and sustainability. The study presents the results of long-term experiments carried out in the Republic of Moldova and Romania, which demonstrate the value of combining several circular practices in crop rotation and soil management. They demonstrated that crop rotation diversified with perennial legumes and grasses in combination with the addition of composted organic matter led to a consistent increase in winter wheat production compared to variants without organic fertilization. They demonstrated that this combination of circular practices can reduce dependence on petrochemical inputs and support soil health in the long term.

These strategies are not universally applicable and their effectiveness depends on agro-climatic conditions, farm structure, and resource availability.

Also, from the conceptual analysis of Velten et al. [30], we deduce that CE in agriculture must be understood at the agri-food system level, not just at the farm level. The authors pointed out that circularity emerges from the interaction of multiple practices and actors, including collective waste management, cooperation between farms and processing units, and the development of local nutrient recycling networks. In this sense, CE is described as a gradual and contextualized process, which differs depending on the value chain structure, institutional framework, and regional conditions.

One of the most frequently encountered directions is represented by nutrient recycling strategies and circular management of organic matter. This is considered fundamental for the transition to more resilient and resource-efficient agricultural systems. Composting of agricultural residues, the use of manure, biogas digestate and other organic amendments are widely discussed as solutions to reduce dependence on synthetic fertilizers and to improve soil fertility, with positive effects on carbon storage and greenhouse gas emissions reduction [20,31,32,33,34,35].

A trend in the recent literature is the emphasis on the valorization of agricultural residues and by-products, both at farm level and along the agri-food chain [36,37,38,39,40,41]. Crop residues, straw, stalks or waste from food processing are increasingly seen as valuable resources, usable for the production of compost, bioenergy or bio-based materials. This approach apparently contributes not only to waste reduction, but also to closing carbon and nutrient cycles within agricultural systems. Thus, agricultural residues may play an important role in decarbonization strategies, especially when integrated into local CE systems. The integration of crop and livestock systems is another central strategy identified in the reviewed literature, often presented as one of the most mature forms of circular agriculture. Integrated crop-livestock systems allow for efficient nutrient reuse, reduce nitrogen and phosphorus losses, and help stabilize productivity under climate stress. These systems are often associated with increased resilience to climate variability and a reduced carbon footprint, especially when compared to specialized and intensive agricultural systems [42,43,44,45].

At the same time, the literature indicates a growing interest in the role of digital technologies and precision agriculture in supporting CE [46,47,48,49]. The use of sensors, soil and crop monitoring systems, and digital tools for input management allows for the optimization of fertilizer and water application, reducing losses and environmental impacts.

For instance, according to the study by Getahun et al. [47], digital technologies and precision agriculture are important in supporting CE. They can optimize the use of agricultural inputs, reducing nutrient and energy losses, and supporting adaptive crop management. At the same time, they may simultaneously contribute to resource efficiency, environmental protection, and the long-term sustainability of agricultural systems.

Beyond resource optimization, digital technologies may enable real-time Monitoring–Reporting–Verification (MRV) systems for circular performance. Blockchain-based traceability, remote sensing soil carbon monitoring, and AI-driven nutrient flow analysis could allow transparent accounting of circularity metrics at farm and regional scales. This creates the foundation for performance-based incentives, carbon market integration, and climate-aligned agricultural financing mechanisms.

Although these strategies are more commonly found in technologically advanced agricultural contexts, they are considered important enablers of circularity, in particular by increasing resource efficiency and reducing indirect emissions.

Another emerging direction is the integration of renewable energy sources into farms and agri-food systems, through the use of photovoltaic panels, biogas or other forms of bio-based energy [50,51,52,53]. This trend is often discussed in relation to farm energy autonomy and reducing dependence on fossil fuels, and is associated with benefits in terms of decarbonization. Integrating renewable energy production with circular biomass management can generate important synergies between economic and climate objectives.

A study conducted in Poland by Oleszek et al. [50] highlights that the integration of renewable energy sources into farms and agri-food systems is a key component of the transition to aCE. Their integration through the use of photovoltaic panels, biogas plants and other forms of bio-based energy contributes to reducing dependence on fossil fuels, hence valorizing agricultural waste and increasing the energy autonomy of the agricultural sector.

Overall, the reviewed literature suggests that current trends in CE in agriculture are moving towards increasingly integrated approaches. They combine nutrient recycling, waste valorization, mixed farming systems, digital technologies and renewable energy. See

Table 1. Strategies and emerging trends in agricultural systems.

CE Strategy	Practices Involved	Agricultural Context	Climate Resilience Contribution	Relevance for Decarbonization	Ref.
Diversified crop rotations	-crop diversification -inclusion of legumes	-low-input and smallholder systems	-improved soil structure -enhanced nutrient availability -reduced vulnerability to climate variability	-reduced dependence on synthetic fertilizers -lower indirect GHG emissions	[20,28]
Organic matter recycling	-composting -use of crop residues -manure application	-mixed farming systems	-increased soil organic carbon -better water retention and drought tolerance	-carbon sequestration in soils -reduced emissions from waste disposal	[20,31,32,33,34,35]
Integrated crop–livestock systems	-nutrient recycling manure management	-extensive and mixed systems	-enhanced nutrient cycling -improved system stability	-lower fertilizer-related emissions -improved resource efficiency	[42,43,44,45]
Residue retention and soil cover	-mulching -residue incorporation -reduced soil disturbance	-conservation agriculture systems	-protection against erosion	-increased soil carbon stocks -reduced fuel use	[31,32,33,34,35]
Renewable energy integration	-on-farm renewable energy use -bioenergy from residues	-medium- to large-scale farms -regional agri-food systems	-reduced exposure to energy price volatility	-direct reduction in fossil fuel use and CO2 emissions	[50,51,52,53]
System-level circular coordination	-regional nutrient loops -cooperation between farms and processors	-agro-food value chains and regional systems	-increased adaptive capacity through systemic resilience	-emission reductions through optimized material and energy flows	[30]

. However, the level of implementation and maturity of these strategies varies considerably across regions and types of farming systems. Many studies highlight the existence of economic, technical and institutional barriers that limit their scaling. These findings pave the way for detailed analysis of how circular strategies could effectively contribute to climate resilience and decarbonization processes, which are developed in the following sections.

3.3. Comparative Insights and Implementation Challenges of Circular Strategies

If we look from an analytical point of view at the literature, several cross-cutting aspects appear that are not always explicitly addressed in individual studies. First, trade-offs may arise between different circular economy strategies. For example, the valorization of agricultural residues for bioenergy can compete with their use for soil organic matter restoration, potentially affecting long-term soil fertility [54,55]. Similarly, intensification in certain approaches may reduce system diversity, which is a key component of resilience.

Second, the effectiveness of circular strategies varies significantly across agricultural contexts. Differences in farm size, resource availability, agro-climatic conditions, and technological capacity influence the feasibility and outcomes of implementation. As a result, strategies that are effective in highly industrialized farming systems may not be directly transferable to smallholder or resource-constrained contexts.

Third, several implementation barriers limit the adoption of circular practices, including high initial investment costs, limited access to finance, lack of technical knowledge, insufficient advisory services, and institutional fragmentation. These factors suggest that the transition toward circular agriculture is not solely a technical process, but also an economic and institutional one that requires enabling conditions at multiple governance levels.

3.4. Assessment of Circular Strategies to Climate Resilience

Circular economy strategies are widely associated with processes that may contribute to climate resilience by reorganizing resource flows so that nutrients, water and energy are maintained in the system for longer periods of time. Instead of a linear model based on external inputs and constant losses, circular practices aim to close biogeochemical cycles, especially at the soil level. For example, recycling organic residues and applying compost or biochar increase soil organic carbon content, a key indicator of long-term sustainability, as it is closely linked to fertility, structure and biological activity.

The use of biochar as a soil amendment is a concrete example of a circular strategy that enhances climate resilience in agriculture. Biochar, a carbonized product obtained from agricultural biomass, has the ability to modify the physical properties of the soil in a way that significantly improves the water retention available to plants. This makes it useful in mitigating the effects of drought and other water stresses. Edeh et al. [56] noted that the application of biochar can increase, on average, the available water content in the soil by over 28% (at application rates between 30–70 t/ha) and the soil’s water retention capacity by about 20%, which suggests a real improvement in resilience to drought conditions. Biochar applications have been reported to increase soil available water content, particularly at application rates ranging between approximately 10 and 40 t/ha, depending on soil type, crop system, and biochar properties. While these application rates demonstrate significant improvements under experimental and controlled conditions, they may be considered relatively high from a practical agrotechnical perspective, posing challenges in terms of economic feasibility, material availability, and logistics for large-scale farming systems. This is especially relevant in sandy soils where water retention problems are more acute. Compared to other residue-based practices such as residue retention or compost application, biochar is often reported as a more stable and long-term soil amendment. This is because of its persistence in soil and its stronger potential to improve water retention. However, its effectiveness remains highly dependent on soil type, feedstock characteristics, and pyrolysis conditions, making its outcomes more context-specific and less uniform across studies.

Among the circular strategies discussed, practices such as organic matter recycling and residue retention are supported by a relatively large body of long-term field experiments and are often associated with direct improvements in soil properties and water dynamics. In contrast, strategies such as biochar application, while showing strong potential in controlled conditions, tend to exhibit more variable outcomes depending on soil characteristics and implementation conditions. System-level strategies, including crop diversification and crop–livestock integration, seem to provide broader resilience benefits, although their effects are more complex and harder to isolate empirically.

The literature provides consistent evidence that CE strategies can contribute to climate resilience of agricultural systems [28,57,58,59]. A conceptual framework is presented in Figure 5 to illustrate the pathways through which circular practices contribute to climate resilience and sustainability in agriculture. This is achieved not through a single mechanism, but through a series of cumulative processes, which act on soil, water, biodiversity and the overall stability of production. In many cases, resilience does not appear immediately, but is built gradually, as circular practices are maintained and adapted to the local context.

One such mechanism is the improvement of soil health by recycling organic matter and maintaining plant residues. The study carried out by Thierfelder et al. [28] highlights that conservative agricultural practices, including keeping residues on the soil surface and diversified rotations, contribute to increasing soil structural stability and better water retention, reducing the vulnerability of crops to drought and climate variability. These effects are all the more relevant in semi-arid regions, where water scarcity is one of the main climate risks for agriculture.

Complementarily, the use of organic fertilizers and compost is often associated with a greater capacity of the soil to absorb climate shocks. A study by Dagevos and de Lauwere [29] indicates that agricultural systems that recycle nutrients at the farm or agri-food chain level tend to show higher resilience, due to reduced dependence on external inputs and increased soil organic carbon (SOC) content. In this context, circularity is not only a resource efficiency strategy, but also becomes a climate adaptation tool.

Diversification of agricultural systems reduces dependence on a single crop or a single type of input. Diversified rotations and the integration of legumes and mixed crop–livestock systems may contribute to the stabilization of production under variable climatic conditions [20,28,60,61,62]. These systems are less vulnerable to climatic fluctuations, as they distribute risk and maintain ecosystem functions even under stress. Thus, resilience appears as an emergent property of the system, not as the effect of a single intervention. The integration of digital technologies and precision agriculture complements these strategies through more adaptive resource management. Soil sensors, crop monitoring systems or decision support tools can allow for real-time adjustment of irrigation and fertilization, reducing losses and increasing the efficiency of water and nutrient use. This rapid response capacity is essential for climate resilience, especially in the context of the increasing frequency of extreme events.

From a systems ecology perspective, circular agricultural systems may be interpreted through the adaptive cycle framework (exploitation–conservation–release–reorganization). Circular strategies enhance the conservation phase by strengthening resource retention, while diversified systems increase the reorganization capacity following climate shocks. This panarchical interpretation suggests that circularity does not merely stabilize systems but increases their adaptive reconfiguration potential after disturbances, a dimension often overlooked in linear resilience assessments.

The effects of circular strategies are relatively well supported for biophysical indicators, although their translation into broader resilience outcomes remains less directly evidenced. Studies using long-term field experiments, comparisons between conventional and circular systems, as well as quantifiable indicators (such as soil organic carbon content, water retention capacity, yield stability or erosion reduction) make an important contribution to strengthening this aspect. For example, in the long-term experiments analyzed by Boincean et al. [20], diversified rotations and organic fertilization led to a stabilization of yields in years with uneven rainfall, demonstrating the ability of circular systems to cope with climate variability.

At the agri-food system level, resilience is also assessed by the ability to reduce dependence on external resources, especially fossil energy. The integration of renewable sources, such as biogas and photovoltaic panels, may contributes not only to decarbonization, but also to the economic stability of farms in the context of volatile energy markets. This economic stability is an integral part of climate resilience, as it can allows farmers to maintain sustainable practices even under external stress.

3.5. Indicators for Assessing Climate Resilience in Circular Systems

In terms of ways of assessing climate resilience, a number of indicators are frequently used in the literature to assess whether circular strategies have real effects on the sustainability and resilience of agricultural systems. In

Table 2. Key takeaway summarizing the main indicators for the assessment of climate resilience and sustainability of circular agricultural systems.

Category	Indicator	Evaluation	Main Relevance	Typical Evidence Type	Strengths	Limitations
Soil-related indicators	soil organic carbon content	analysis of total or particulate organic carbon; changes monitored over multi-year experiments	soil fertility, carbon sequestration, soil health	long-term field experiments, soil sampling studies	widely accepted, standardized, strong link to sustainability	slow to change, spatially variable, influenced by climate and management
	soil water holding capacity and plant-available water	soil moisture retention curves; field capacity and wilting point measurements	water regulation, drought resilience	laboratory soil physics analyses, field measurements	soil water regulation and plant drought resilience	requires controlled measurements, site-specific
	soil aggregate stability and bulk density	wet sieving methods for aggregate stability; core sampling for bulk density	soil structure, erosion resistance	physical soil analyses	good indicator of soil structure and erosion risk	sensitive to sampling methods and temporal variability
	nutrient availability (N, P, K) and nutrient use efficiency	soil nutrient tests; partial nutrient balances; yield-based nutrient efficiency indicators	nutrient cycling, productivity efficiency	soil testing, field trials, nutrient budgeting	direct agronomic relevance	nutrient availability fluctuates seasonally and spatially
Water-related indicators	water use efficiency (yield per unit of water input)	ratio of crop yield to total water input (rainfall + irrigation); field-scale water balance	water productivity, drought adaptation	field experiments, irrigation studies	simple, widely used, comparable across systems	does not capture temporal variability of water stress
	soil moisture dynamics under drought conditions	continuous soil moisture monitoring using sensors; comparison between management systems	drought resilience, water availability dynamics	sensor-based field monitoring	high temporal resolution	requires instrumentation, data-intensive
	irrigation water savings	comparison of irrigation volumes before and after adoption of water-saving practices	water conservation efficiency	farm-level comparisons	direct practical relevance	context-dependent, influenced by climate variability
Crop and system performance indicators	yield stability across years with variable climate conditions	multi-year yield datasets analyzed across contrasting climatic conditions	production stability, resilience	long-term field datasets	strong indicator of resilience	requires long-term datasets
	yield variability and coefficient of variation	statistical analysis of interannual yield variability	risk and stability of production	statistical analysis of yield records	quantitative and comparable	does not explain mechanisms
	crop productivity under stress conditions (drought, heat)	yield response measured under experimentally or naturally occurring stress events	adaptive capacity to climate extremes	experimental or observed stress conditions	direct measure of stress response	limited generalizability
Environmental indicators	reduction in soil erosion rates	field measurements or model-based estimates of erosion under different management practices	land degradation, soil conservation	field measurements, erosion models	important for long-term sustainability	model uncertainty
	biodiversity indicators (pollinators, soil biota, functional diversity)	species richness, abundance, and functional diversity indices at field or landscape level	ecosystem stability and services	field surveys, ecological assessments	captures ecological dimension	methodologically complex
	greenhouse gas emissions (CO2, N2O) per unit of output	Life Cycle Assessment, emissions intensity per unit of agricultural product	climate impact mitigation	lca studies	standardized methodology	requires assumptions and system boundaries
Resource and energy indicators	reduction in synthetic fertilizer and energy inputs	comparison of input quantities before and after adoption of circular practices	resource efficiency, input dependency	farm-level data analysis	simple and practical	does not capture indirect effects
	share of renewable energy in farm energy use	energy balance analysis, percentage of renewable sources in total farm energy consumption	energy sustainability, decarbonization	energy balance analysis	clear and interpretable metric	data availability dependent
	energy self-sufficiency of farming systems	ratio between on-farm energy production and total energy demand	system autonomy, resilience	energy accounting studies	reflects independence from external energy	sensitive to system boundaries
Socio-economic resilience indicators	dependence on external inputs	quantification of purchased inputs relative to total production costs	economic vulnerability	farm economic analysis	direct indicator of resilience	simplified representation of economic systems
	economic stability and cost variability over time	long-term analysis of production costs, income variability, and profitability	financial resilience	time-series economic data	captures long-term trends	requires longitudinal data
	adaptive capacity to climate and market shocks	farm-level resilience assessments during extreme climate events or market volatility	system resilience and adaptability	case studies, resilience assessments	integrates multiple dimensions	difficult to quantify consistently

, we summarized some of the main indicators for evaluating the contribution of circular practices to climate resilience. These indicators do not directly measure resilience outcomes in all cases, but rather capture key processes and conditions that are widely associated with increased system resilience.

3.5.1. Soil-Related Indicators

The first of the soil-related indicators is the content of soil organic carbon, which reflects both the health of the soil and its capacity to regulate hydrological processes and nutrient cycles [63,64,65,66]. Practices that increase soil organic matter, such as conservation agriculture or crop rotations that add organic matter, have been associated with significant increases in topsoil SOC, which can reduce the risk of water stress and support production during periods of low rainfall.

Another indicator is the soil’s water-holding capacity [67,68,69,70]. This indicates how much water the soil can store and deliver over the course of production cycles, directly influencing the availability of water for plants during droughts. Improving soil structure by increasing organic matter often leads to more developed macro- and mesopores, which increase access to soil water for roots and may contribute to resilience to water stress.

Indicators related to aggregate stability and bulk density are used to assess the cohesion of soil particles and the overall physical structure [71,72,73,74,75]. Soils with stable aggregates are better able to withstand erosion caused by heavy rainfall and provide better rooting conditions for plants, thus helping to maintain production under extreme climatic conditions. Measures that preserve soil structure or increase aggregate stability are considered to be beneficial for resilience to severe climatic events, for example by reducing nutrient losses and soil structure degradation after rainfall.

Last but not least, the availability of nutrients (nitrogen, phosphorus, potassium—N, P, K) and their use efficiency are important indicators for understanding how circular strategies affect soil fertility and the ability of plants to cope with climatic fluctuations [76,77,78,79]. Soils that maintain a stable level of biologically available nutrients can help plants to get through periods of climatic stress more easily, and practices that improve natural nutrient cycles, such as crop rotations and the use of organic fertilizers, are frequently associated with a better balance of these essential elements.

3.5.2. Water-Related Indicators

In addition to soil quality indicators, specific indicators related to soil water are used; they refer to its use and consumption efficiency, as water is one of the resources most affected by climate change. These indicators provide direct information on the capacity of an agricultural system to adapt to periods of drought or intense rainfall.

Water use efficiency (WUE) is one of the indicators. It refers to the amount of production (biomass or harvest) obtained per unit of water consumed [80,81,82,83]. Under climate change conditions, higher efficiency indicates that plants use the available water more efficiently, suggesting greater resilience to drought. The adoption of precision irrigation systems combined with renewable practices (e.g., mulching and crop rotation) can increase WUE by 15–30% compared to conventional systems, thus contributing to a more adaptive management of water resources.

Soil moisture dynamics is another circular indicator, which refers to how the soil holds and releases water over time and is used to assess how well an agricultural system can cope with climate variability [84,85,86]. By monitoring moisture in soil layers, research demonstrates that strategies that increase organic matter are associated with more stable moisture levels, reducing water stress on crops during periods of prolonged drought. Also in this category is irrigation water savings, which measures the reduction in the volume of water used for irrigation while maintaining the same productivity [87,88,89]. Circular practices that improve soil structure and water retention can reduce irrigation needs and, implicitly, vulnerability to water shortages during critical seasonal periods.

3.5.3. Crop and System Performance Indicators

Crop and agricultural system performance indicators allow us to quantify how circular strategies influence production stability and the ability to adapt to changing climates. One such indicator is yielding stability, which is usually measured by comparing yields in normal years to those in years with climate stress. Studies examining the impact of crop diversification suggest that systems with complex rotations or intercropping tend to have lower yield variability in the face of climate fluctuations, resulting in more predictable and stable production during periods of drought or extreme heat [60,90,91,92]. A related concept is the variation of yield, which points out how much production varies from one year to the next; lower values indicate higher resilience to variability in weather conditions [93,94,95].

Another important aspect of climate resilience is cropping productivity under stress conditions (drought, heat), assessed by comparing yields under normal conditions versus drought or heat extremes. For example, cover crops, particularly those that include legumes, have been associated with reduced yield losses under water stress and increased productivity in some regenerative farming systems [95,96,97,98]. This suggests that such circular practices can help establish production and adapt it to a changing climate.

In terms of environmental indicators, an important example is the reduction in soil erosion rates, which is closely linked to resource conservation and the ability of the agricultural system to sustain production in the long term. Practices such as zero tillage and the conservation of residues on the soil surface significantly reduce soil loss through erosion and improve ecosystem functions, thus contributing to maintaining soil health and resilience to intense rainfall [99,100,101,102].

Also in the category of environmental indicators are biodiversity indicators, such as the richness of pollinator species or the biotic diversity of the soil [103,104,105,106]. Strategies that encourage landscape diversification and include agroecological elements are associated with increased species diversity, which also supports the stability of production under variable climates, but also the provision of ecosystem services necessary for crop adaptation. Also, greenhouse gas emissions (CO₂, N₂O) per production unit are evaluated as indicators of the impact on climate change [107,108,109,110]; circular strategies that reduce synthetic inputs and increase soil carbon sequestration tend to have a more favorable emissions balance compared to conventional systems.

3.5.4. Environmental Indicators

In addition to these biogeophysical indicators, the literature also uses resource and energy indicators to reflect the efficiency of input use and how the integration of renewable sources influences the sustainability of agricultural systems [111,112,113,114,115]. Indicators such as the reduction in the use of synthetic fertilizers, the proportion of renewable energy in the total consumption of the farm or the energy autonomy of agricultural systems can allow the assessment of how farms reduce their dependence on fossil fuels and improve their energy performance. It can be seen that the increase in the share of renewable energy and energy efficiency is a positive signal for sustainability and adaptation, since the reduction in traditional energy consumption is directly related to the reduction in emissions associated with agricultural production.

To fully understand the climate resilience of circular systems, socio-economic indicators are also used [111]. They reflect how circular strategies affect dependence on external inputs, economic stability and the ability of the agricultural system to cope with external shocks. This type of indicator includes dependence on external inputs (such as industrial fertilizers or fuels), economic stability and variability of costs over time, but also the ability to adapt to climate and market shocks, which can be measured by assessing the financial performance of farms during periods of unfavorable climatic conditions or fluctuations in resource prices.

These indicators enable robust and multidimensional assessments of the performance of circular agricultural systems from the perspective of sustainability and climate resilience, demonstrating that these are not theoretical claims, but real, quantifiable and relevant effects for agricultural policies, farm management and climate change adaptation strategies.

While improvements in soil properties, water retention, and nutrient cycling are consistently reported across the literature, these indicators should be interpreted as enabling conditions for resilience rather than direct measures of production stability or adaptive capacity. In many cases, the link between biophysical improvements and actual resilience outcomes remains indirect, highlighting the need for more long-term and system-level empirical evidence.

3.6. Gaps Identified in the Literature

Although the literature on CE applied to agriculture has grown significantly in recent years, there are still many theoretical, methodological and application gaps. The latter limit the full understanding and effective application of the concepts at scale (Figure 6).

To provide a more structured perspective on the identified gaps, the selected core studies (77) were qualitatively classified according to their methodological approach, spatial and temporal scale, and the type of indicators considered (biophysical, environmental, and socio-economic).

From the analyzed corpus, the majority of studies focus on biophysical and environmental indicators, while a significantly smaller proportion incorporates socio-economic dimensions. In addition, most contributions are based on short-term experiments or local case studies, with relatively few longitudinal or large-scale analyses. Conceptual and review-type studies are also more frequent than fully empirical, multi-site investigations, indicating a predominance of context-specific evidence rather than generalizable frameworks.

A first significant aspect is the absence of integrated approaches that coherently unite all dimensions of the CE (social, economic and environmental) within agri-food systems, as well as the explicit link between them and climate resilience or decarbonization. The current literature tends to focus either on resource efficiency aspects or on specific techniques (e.g., waste recycling or energy recovery), but rarely deals with all three in a holistic and integrated way, which limits the ability to understand the complexity of these systemic transitions in agriculture.

Another significant gap we identified is the lack of large-scale, long-term empirical studies that robustly assess the real-world effects of circular strategies on climate resilience in different geographical and development contexts. For example, many works are based on local case studies or theoretical models, but there is a lack of longitudinal and internationally comparable data that would allow for the assessment of progress over time and the validation of conclusions at levels other than local or experimental levels.

Similarly, methodological differences and the lack of standardized assessment frameworks are a major problem. The scientific literature stresses that there is no clear consensus on indicators, measurement methods and protocols for assessing the impact of circular strategies on climate resilience and decarbonization, making it difficult to compare results and synthesize scientific evidence consistently. This methodological heterogeneity contributes to the fragmentation of knowledge and the difficulty of formulating coherent and adaptable policy recommendations to different contexts.

Another area relatively underexplored in the current literature is the social and behavioral dimension of the adoption of circular strategies in agriculture. While economic and environmental performance are often analyzed, aspects such as farmers’ attitudes, institutional barriers, cultural factors or the social implications of the transition to circular models are underestimated or remain underdeveloped in most studies. Specifically, the social value emerging from the practical implementation of circular strategies, such as the impact on rural communities, social equity or working conditions, seem largely unexplored, especially in the context of agro-eco-industrial parks or local cooperation systems.

Last but not least, there is a lack of solid theoretical frameworks that combine circularity with climate resilience and the decarbonization transition into a unified model of understanding and practice. In many papers, these concepts appear separately, without their interdependencies being systematically explored and with references to concrete policies or effective implementation mechanisms.

3.7. Proposed Conceptual Framework and Original Contribution of the Study

Building on the gaps identified in the literature, this study proposes an integrated conceptual framework (Figure 7) for analyzing the contribution of CE in agricultural systems. This study goes beyond a traditional review by positioning the literature synthesis as a basis for the development of an original, indicator-based conceptual framework. The novelty of the approach lies in the fact that the CE is not treated as an isolated set of practices or technologies, but as a systemic mechanism for reorganizing resource flows, assessed through quantifiable indicators and directly correlated with climate adaptation and long-term sustainability outcomes. Unlike Figure 5, which provides a general conceptual overview of the pathways linking circular economy strategies to climate resilience, Figure 7 advances this representation by structuring these relationships into an operational, indicator-informed framework. While Figure 5 emphasizes conceptual linkages, Figure 7 explicitly organizes circular strategies, underlying mechanisms, and resilience outcomes into a hierarchical and functionally interpretable model that can support analysis and comparison across studies. It illustrates a conceptual synthesis of the main novelty and contribution of this study, highlighting how circular economy strategies are operationalized as a system-level mechanism for enhancing climate resilience in agricultural systems. The figure is structured as a sequential framework that moves from the implementation of circular practices to measurable resilience outcomes, emphasizing the cumulative and long-term nature of these effects.

The proposed framework can be used as an analytical tool for classifying and comparing studies based on three interconnected levels: (i) the type of circular strategies implemented, (ii) the biophysical, environmental, and socio-economic mechanisms activated, and (iii) the resilience and sustainability outcomes assessed through quantifiable indicators. This structure allows researchers to map existing studies onto a common structure, identify which mechanisms are addressed, and evaluate the completeness or imbalance of empirical approaches across the literature.

At the first level, we present circular economy strategies as integrated management practices rather than isolated interventions. These include the recycling of organic residues, soil-oriented practices aimed at closing nutrient cycles, diversification of cropping systems, precision agriculture tools, and the integration of renewable energy sources. This framing reflects the study’s key premise that circularity in agriculture is primarily about reorganizing resource flows within the system. The second level illustrates resource retention and efficiency mechanisms, through which circular practices reduce losses of nutrients, water, and energy. By maintaining resources within the agricultural system for longer periods, these mechanisms increase buffering capacity against climatic variability and external shocks. This step explicitly connects circular strategies to underlying biophysical and socio-economic processes, addressing a gap frequently identified in the literature. The third level of the figure focuses on system buffering capacity, which emerges from improvements in soil health, water availability, biodiversity, energy autonomy, and production stability. Rather than depicting resilience as an immediate outcome, the figure emphasizes its emergent and cumulative character, built progressively through sustained circular management adapted to local conditions. Finally, we highlight climate resilience and sustainability outcomes, including reduced vulnerability to drought and extreme weather events, stabilized yields under variable climatic conditions, lower greenhouse gas emissions per unit of output, and enhanced socio-economic resilience at the farm and agri-food system levels. These outcomes are explicitly linked to quantifiable indicators commonly used in the literature, reinforcing the empirical grounding of the proposed framework.

We argue that circular strategies are often analyzed in a fragmented manner, either from the perspective of resource efficiency or emission reduction, without clearly highlighting how and through which concrete mechanisms they participate in increasing the capacity of agricultural systems to cope with climate variability. In this context, the framework proposed here introduces an explicit link between three levels of analysis: the circular strategies implemented, the biogeophysical and socio-economic mechanisms activated, and the measurable climate resilience and decarbonization outcomes.

Thus, CE strategies are grouped according to their functional role on the agricultural system: strategies aimed at closing the cycles of nutrients and organic matter (e.g., recycling of residues, use of compost and biochar), strategies aimed at optimizing the use of water and energy (precision irrigation, integration of renewable sources), and strategies oriented towards the diversification and integration of agricultural systems (complex rotations, mixed crop-livestock systems). This functional classification allows a clearer understanding of how circular practices may generate cumulative effects on the stability of the system.

An original element of the study is the emphasis placed on the gradual and emergent nature of climate resilience, which does not appear as an immediate result of a single intervention, but is built over time by maintaining and adapting circular strategies to the local context. In this sense, our proposed framework integrates indicators frequently used in the specialized literature (such as soil organic carbon content, water retention capacity, production stability, erosion reduction or energy autonomy), but places them in a coherent logic of assessing resilience, not only environmental performance.

Compared to existing circular economy–resilience models, which often treat circularity primarily as a set of resource efficiency practices or emission reduction strategies, the proposed framework explicitly integrates circular strategies with system-level mechanisms and resilience outcomes through an indicator-based perspective. This enables a more structured interpretation of how circular interventions propagate effects across soil, water, energy, and socio-economic dimensions, rather than considering these effects in isolation. For example, a given study can be positioned within the framework by identifying the circular strategies it addresses, the mechanisms it evaluates (e.g., soil health improvement, water retention, energy efficiency), and the type of resilience outcomes reported, allowing for systematic comparison across heterogeneous studies.

The study also contributes by integrating the socio-economic dimension in the assessment of climate resilience, an aspect often underrepresented in previous research. By including indicators on dependence on external inputs, economic stability and the capacity to adapt to market shocks, the proposed framework recognizes that climate resilience is not only a biophysical process, but also an economic and institutional one. Overall, the main contribution of this study consists in proposing an integrative framework that operationalizes the circular economy as a tool for climate adaptation and mitigation in agriculture, based on existing empirical evidence, quantifiable indicators and a systemic approach. This framework can serve as a basis for future empirical studies, for the development of resilience-oriented agricultural policies, and for the design of transition strategies towards sustainable and low-carbon agri-food systems.

3.8. Conceptual Operationalization of the Circularity–Resilience Coupling Index (CRCI)

To operationalize the systemic link between circularity and climate resilience identified in the preceding sections, this study introduces a conceptual composite Circularity–Resilience Coupling Index (CRCI). The index intended as an exploratory and integrative framework for linking circular economy strategies with climate resilience outcomes. Rather than representing a fully validated empirical model, the CRCI is proposed as a structured approach for organizing and interpreting multidimensional indicators across circularity and resilience domains.

The CRCI integrates weighted indicators across five key dimensions: (i) soil carbon dynamics, (ii) water-use efficiency and retention stability, (iii) energy autonomy and renewable energy share, (iv) nutrient circularity ratios, and (v) socio-economic adaptive capacity. By aggregating these dimensions into a single composite score, the index could enable comparative assessment across farms, regions, and agro-climatic contexts, addressing the current lack of standardized integrative metrics for evaluating circular agriculture from a resilience perspective.

The CRCI simultaneously captures the following: circularity performance (closure of material and energy loops), resilience performance (buffering capacity, stability and adaptive capacity) and the structural coupling between circularity and resilience.

Accordingly, the CRCI can be expressed as:

$$\mathrm{C}\mathrm{R}\mathrm{C}\mathrm{I}=({\mathrm{C}}^{\mathsf{\alpha }}\cdot {\mathrm{R}}^{\mathsf{\beta }})\cdot \mathsf{\Phi }$$

(1)

where:

• C = Circularity sub-index ∈ [0, 1]
• R = Resilience sub-index ∈ [0, 1]
• α, β = importance exponents (default 1)
• Φ = coupling factor ∈ [0, 1] penalizing weak translation + trade-offs

All components are bounded to the interval [0, 1], and aims to ensure comparability across farms, regions and agro-climatic contexts.

3.8.1. Construction of the Circularity Sub-Index (C)

Circularity is interpreted here as the degree to which material and energy flows are retained, recycled, and regenerated within the agricultural system boundaries. Circularity can be evaluated across five functional dimensions: d ∈ {N,B,W,E,M} (nutrients, biomass, water circularity, energy circularity, materials/by-products).

Indicator normalization

Each indicator x_j is normalized to a unit interval using min–max scaling.

For benefit-type indicators (higher values indicate better performance):

$${\mathrm{z}}_{\mathrm{j}}=\mathrm{c}\mathrm{l}\mathrm{i}\mathrm{p}\left({\displaystyle \frac{{\mathrm{x}}_{\mathrm{j}}-{\mathrm{L}}_{\mathrm{j}}}{{\mathrm{U}}_{\mathrm{j}}-{\mathrm{L}}_{\mathrm{j}}}},\mathrm{0,1}\right)$$

(2)

For cost-type indicators (lower values indicate better performance):

$${\mathrm{z}}_{\mathrm{j}}=\mathrm{c}\mathrm{l}\mathrm{i}\mathrm{p}\left({\displaystyle \frac{{\mathrm{U}}_{\mathrm{j}}-{\mathrm{x}}_{\mathrm{j}}}{{\mathrm{U}}_{\mathrm{j}}-{\mathrm{L}}_{\mathrm{j}}}},\mathrm{0,1}\right)$$

(3)

where: L_j and U_j are lower and upper benchmark bounds, aimed at ensuring values remain within [0, 1].

Dimension score aggregation

For circular dimension d, score is calculated as:

$${\mathrm{C}}_{\mathrm{d}}={\sum }_{\mathrm{j}\in \mathrm{d}}{\mathsf{\omega }}_{\mathrm{d}\mathrm{j}}{\mathrm{z}}_{\mathrm{j}},{\sum }_{\mathrm{j}\in \mathrm{d}}{\mathsf{\omega }}_{\mathrm{d}\mathrm{j}}=1$$

(4)

Cross-dimension aggregation

To avoid compensatory effects, a geometric mean is applied:

$$\mathrm{C}={\prod }_{\mathrm{d}}{\mathrm{C}}_{\mathrm{d}}^{{\omega }_{\mathrm{d}}},{\sum }_{\mathrm{d}}{\omega }_{\mathrm{d}}=1$$

(5)

This structure is intended to ensures that poor performance in one circular loop cannot be fully offset by strong performance in another.

3.8.2. Construction of the Resilience Sub-Index (R)

Resilience is conceptualized as a multidimensional buffering and adaptive capacity that emerges from biophysical stability and socio-economic robustness. Resilience is operationalized through five pillars, and CS is the variable related to climate stress: k ∈ {S,H,Y,D,A}.

• where:
• S: Soil buffering—SOC, structure, infiltration,
• H: Hydrological buffering—PAW, WHC, WUE stability,
• Y: Yield stability under variable climate,
• D: Diversity/functional redundancy—rotations, livestock integration, habitat,
• A: Adaptive and socio-economic capacity—input dependence, liquidity, knowledge access).

Each resilience dimension is computed as:

$${\mathrm{R}}_{\mathrm{k}}={\sum }_{\mathrm{j}\in \mathrm{k}}{\mathrm{V}}_{\mathrm{k}\mathrm{j}}{\mathrm{Z}}_{\mathrm{j}}{\mathrm{C}\mathrm{S}}_{\mathrm{j}},{\sum }_{\mathrm{j}\in \mathrm{k}}{\mathrm{V}}_{\mathrm{k}\mathrm{j}}=1$$

(6)

Aggregation across resilience pillars uses a geometric mean:

$$\mathrm{R}={\prod }_{\mathrm{k}}{\mathrm{R}}_{\mathrm{k}}^{{\mathsf{\eta }}_{\mathrm{k}}},{\sum }_{\mathrm{k}}{\mathsf{\eta }}_{\mathrm{k}}=1$$

(7)

Yield stability (Y).

Yield stability can be operationalized using complementary statistical measures that capture variability, shock resistance, and worst-case performance.

Yield stability is operationalized through complementary statistical indicators:

Inverse coefficient of variation

$$\mathrm{Y}{\mathrm{S}}_1=1-\mathrm{c}\mathrm{l}\mathrm{i}\mathrm{p}\left({\displaystyle \frac{{\mathrm{C}\mathrm{V}}_{\mathrm{y}}-{\mathrm{C}\mathrm{V}}_{\mathrm{m}\mathrm{i}\mathrm{n}}}{{\mathrm{C}\mathrm{V}}_{\mathrm{m}\mathrm{a}\mathrm{x}}-{\mathrm{C}\mathrm{V}}_{\mathrm{m}\mathrm{i}\mathrm{n}}}},\mathrm{0,1}\right)$$

(8)

$${\mathrm{C}\mathrm{V}}_{\mathrm{y}}={\displaystyle \frac{{\mathsf{\sigma }}_{\mathrm{y}}}{{\mathsf{\mu }}_{\mathrm{y}}}}$$

(9)

Stress-year yield ratio normalized to [0, 1].

$$\mathrm{Y}{\mathrm{S}}_2={\displaystyle \frac{{\overline{\mathrm{y}}}_{\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{s} \mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}\mathrm{s}}}{{\overline{\mathrm{y}}}_{\mathrm{n}\mathrm{o}\mathrm{r}\mathrm{m}\mathrm{a}\mathrm{l} \mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}\mathrm{s}}}}$$

(10)

Worst-year protection

$$\mathrm{Y}{\mathrm{S}}_3={\displaystyle \frac{{\mathrm{y}}_{10\%}}{{\mathsf{\mu }}_{\mathrm{y}}}}$$

(11)

3.8.3. Coupling Factor (Φ)

Beyond independent circularity and resilience performance, the CRCI explicitly evaluates whether circular practices effectively translate into resilience gains without generating unintended systemic trade-offs. This coupling dimension represents the core theoretical contribution of the index.

The coupling factor captures whether circularity effectively translates into resilience without generating systemic trade-offs.

$${\mathsf{\Phi }}_{\mathrm{C}\mathrm{o}\mathrm{u}\mathrm{p}\mathrm{l}\mathrm{i}\mathrm{n}\mathrm{g}}={\mathsf{\Phi }}_{\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{g}\mathrm{n}\mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t}}\ast {\mathsf{\Phi }}_{\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{d}\mathrm{e}\mathrm{o}\mathrm{f}\mathrm{f}}\ast {\mathsf{\Phi }}_{\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{f}\mathrm{i}\mathrm{c}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}$$

(12)

Alignment component

Compute a signed alignment score between circularity dimensions C_d and resilience dimensions R_k using an “expected mechanism matrix” M. M_kd ∈ [0, 1] expresses how strongly circular dimension d should drive resilience pillar k.

Predicted resilience from circularity:

$${\widehat{R}}_K={\displaystyle \frac{{\sum }_d{M}_{kd}{C}_d}{{\sum }_d{M}_{kd}}} ,{\sum }_{\mathrm{d}}{\mathrm{M}}_{\mathrm{k}\mathrm{d}}=1$$

(13)

Mismatch penalty:

$$∆={\sum }_{\mathrm{k}}{\mathsf{\eta }}_{\mathrm{k}}|{\mathrm{R}}_{\mathrm{k}}-{\widehat{\mathrm{R}}}_{\mathrm{k}}|$$

(14)

Alignment factor:

$${\mathsf{\Phi }}_{\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{g}\mathrm{n}\mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t}}=1-\mathsf{\Delta }$$

(15)

Trade-off penalty

Trade-off indicators t_m, e.g., nutrient surplus, residue over-extraction, biodiversity decline), are aggregated as:

$$\mathrm{T}={\sum }_{\mathrm{m}}{\mathrm{q}}_{\mathrm{m}}{\mathsf{\tau }}_{\mathrm{m}},{\sum }_{\mathrm{m}}{\mathrm{q}}_{\mathrm{m}}=1$$

(16)

Penalty function:

$${\mathsf{\Phi }}_{\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{d}\mathrm{e}\mathrm{o}\mathrm{f}\mathrm{f}}={\mathrm{e}}^{-\mathrm{\lambda }\mathrm{T}}$$

(17)

where λ controls strictness.

This structure is intended to ensure that circular strategies that improve resource efficiency at the expense of ecological integrity or nutrient balance are not rewarded disproportionately.

Verification penalty

If r_j represents indicator reliability:

$${\mathrm{R}\mathrm{e}\mathrm{l}}_{\mathrm{d}}={\sum }_{\mathrm{j}\in \mathrm{d}}{\mathsf{\omega }}_{\mathrm{d}\mathrm{j}}{\mathrm{r}}_{\mathrm{j}}$$

(18)

$$\mathrm{R}\mathrm{e}\mathrm{l}={\sum }_{\mathrm{d}}{\mathsf{\omega }}_{\mathrm{d}}{\mathrm{R}\mathrm{e}\mathrm{l}}_{\mathrm{d}}$$

(19)

$${\mathsf{\Phi }}_{\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{f}\mathrm{i}\mathrm{c}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}={\mathrm{R}\mathrm{e}\mathrm{l}}^{\mathsf{\gamma }}$$

(20)

3.8.4. Full CRCI Expression

$$\mathrm{C}\mathrm{R}\mathrm{C}\mathrm{I}={\left({\prod }_{\mathrm{d}}{\mathrm{C}}_{\mathrm{d}}^{{\mathsf{\omega }}_{\mathrm{d}}}\right)}^{\mathsf{\alpha }}\ast {\left({\prod }_{\mathrm{k}}{\mathrm{R}}_{\mathrm{k}}^{{\mathsf{\eta }}_{\mathrm{k}}}\right)}^{\mathsf{\beta }}\ast \left(1-∆\right)\ast {\mathrm{e}}^{-\mathsf{\lambda }\mathrm{T}}\ast {\mathrm{R}\mathrm{e}\mathrm{l}}^{\mathsf{\gamma }}$$

(21)

The final CRCI (

Table 3. Template indicator set, benchmark bounds, and illustrative weights for CRCI operationalization.

CRCI Component	Indicator (x_j)	Metric (Definition)	Unit	Type	Benchmarks (L_j; U_j)	Illustrative Weights
C: Nutrients (N)	x1	Nutrient circularity ratio = (recycled N + P)/(total N + P inputs)	–	Benefit	L = 0; U = 1	ωN1 = 1.00; ωN = 0.20
C: Biomass/OM (B)	x2	Organic matter recycling rate (share of residues/organic amendments returned to soil)	–	Benefit	L = 0; U = 1	ωB1 = 1.00; ωB = 0.20
C: Water (W)	x3	Water circularity ratio = (reused + captured water)/(total irrigation water)	–	Benefit	L = 0; U = 1	ωW1 = 1.00; ωW = 0.20
C: Energy (E)	x4	Renewable energy share = renewable energy/total farm energy	–	Benefit	L = 0; U = 1	ωE1 = 1.00; ωE = 0.20
C: Materials/by-products (M)	x5	By-product valorization rate = valorized by-products/total by-products	–	Benefit	L = 0; U = 1	ωM1 = 1.00; ωM = 0.20
R: Soil buffering (S)	x6	Soil organic carbon (SOC) stock or concentration (site-specific)	% or g kg−1	Benefit	L = SOCP10; U = SOCP90	vS1 = 1.00; ηS = 0.20
R: Hydrological buffering (H)	x7	Plant-available water (PAW) in root zone (site-specific)	mm or vol.%	Benefit	L = PAWP10; U = PAWP90	vH1 = 1.00; ηH = 0.20
R: Yield stability (Y)	x8	Yield variability (CVy = YS1, YS2, YS3) across years (lower is better)	–	Cost	L = CVyP10; U = CVyP90	vY1 = 1.00; ηY = 0.20
R: Diversity/redundancy (D)	x9	Normalized diversification index (e.g., crop diversity/rotation complexity)	–	Benefit	L = 0; U = 1	vD1 = 1.00; ηD = 0.20
R: Adaptive and socio-economic capacity (A)	x10	Input dependence ratio = purchased inputs/total costs (lower is better)	–	Cost	L = 0; U = 1	vA1 = 1.00; ηA = 0.20

) value therefore reflects not only aggregated circular and resilience performance, but also the structural coherence between them, adjusted for trade-offs and data reliability. The weights assigned to the different CRCI components are illustrative and are intended to reflect an equal importance assumption across dimensions in the absence of empirical calibration. This approach aims to ensure methodological neutrality and to avoid introducing subjective prioritization among system components. Future applications of the model may adjust these weights based on context-specific considerations or empirical calibration. A sensitivity analysis is recommended for future work to assess how variations in weighting schemes influence the stability and robustness of the CRCI results.

3.8.5. Reporting and Replicability Protocol

To ensure transparency and reproducibility, empirical applications of the CRCI should explicitly report the following: indicator definitions and data sources, normalization bounds (Lj, Uj), dimension weights (ωdj, ωd, ηk), the mechanism matrix M_kd, trade-off parameters (λ), and reliability exponent (γ). Figure 8 is intended to provide a simplified visual representation of the conceptual logic of the CRCI, rather than a finalized operational model.

This structured reporting enables cross-study comparability and supports the development of standardized circular-resilience metrics for agricultural policy and research.

While the CRCI (Figure 8) is presented here as a formal structure, its primary contribution within this study lies in demonstrating how circular economy assessment can move from fragmented indicators toward an integrated resilience-oriented evaluation logic. Empirical validation across agro-climatic contexts remains a priority for future research.

It is important to emphasize that the CRCI is not empirically validated within the scope of this study and should be interpreted as a conceptual framework rather than a predictive or operational tool. Its primary role is to illustrate how circularity and resilience dimensions can be systematically integrated, while future research is required to test its applicability across different agro-climatic contexts and to refine its parameters.

4. Discussion

Integration of CE strategies in agriculture is supported by current public policy frameworks, such as the European Union’s Farm to Fork strategies and the European Green Deal, which aim to reduce dependence on external inputs and increase the resilience of agricultural systems to climate change. The effective implementation of these policies can accelerate the adoption of good circular practices through financial support mechanisms, incentives for regenerative practices and tools for monitoring progress [116,117]. Furthermore, the link between circularity and public policies is becoming increasingly clear in contemporary rural development and sustainable agriculture strategies, such as environmental policies incorporated into the Common Agricultural Policy (CAP) and initiatives supporting the transition to regenerative and low-carbon systems. These policy orientations highlight the need to develop legislative and financial instruments capable of supporting the widespread adoption of circular practices and overcoming the economic and institutional barriers identified in the literature [118].

Despite the existence of supportive policy frameworks, the large-scale implementation of circular agriculture remains uneven. Barriers such as limited access to finance, insufficient technical advisory services, and fragmented institutional coordination continue to constrain adoption, particularly among smallholder and resource-limited farming systems. This suggests that policy support must go beyond strategic objectives and include targeted financial instruments, knowledge transfer mechanisms, and region-specific implementation strategies.

The implementation and scaling of circular agriculture beyond individual farms depend strongly on supportive policy frameworks and institutional arrangements. Existing policies (European Green Deal and the Common Agricultural Policy) provide a general strategic direction, but their effectiveness relies on the availability of targeted instruments, including financial incentives, subsidies for sustainable practices, and support for innovation and knowledge transfer. At the institutional level, barriers such as fragmented governance structures, limited coordination between stakeholders, and unequal access to advisory services can hinder the adoption of circular strategies. In many cases, farmers face uncertainties related to market access, profitability, and long-term returns on investment, which can slow down the transition.

Scaling circular agriculture also requires collective approaches that extend beyond the individual farm level, such as cooperatives, agro-eco-industrial parks, and local value chains that facilitate resource sharing, waste valorization, and circular flows between actors. These multi-level arrangements are essential for enabling systemic transitions and for embedding circular practices within broader agri-food systems rather than isolated farm-level interventions.

In this study, we have attempted to synthesize the literature to understand how circular economy strategies can contribute to climate resilience and agricultural sustainability. Looking at the results obtained and what has already been published, we can say that there is a reasonable consensus that CE is more than a collection of isolated practices; it is a way of redesigning agricultural systems to keep resources within production cycles and to reduce dependence on external inputs. This is supported by several studies, including those proving that recycling organic residues and applying amendments such as biochar can increase soil organic carbon content and its water retention capacity, with beneficial effects on drought resilience [119,120,121,122,123].

One of the main conceptual challenges that our study attempted to overcome is the fragmentation of the existing literature. Many studies focus on either environmental aspects, input efficiency, or specific techniques without integrating them into a broader framework that shows who draws the line, how, and why these practices influence climate resilience. In contrast, our results reinforce the idea that circular effects on resilience occur through a complex set of interconnected mechanisms—improving soil structure, optimizing water use, diversifying agricultural systems, and integrating renewable energies—rather than through a single factor.

Another important observation is that climate resilience does not emerge suddenly after implementing a circular strategy, but builds gradually as the positive effects accumulate. For example, in long-term experiments examining diversified rotations and organic soil management, yield stabilization has been observed even in years with uneven rainfall. This accentuates that circular strategies can counteract the effects of climate variability only after a sufficiently long period of adaptation and adjustment of practices [20]. This captures an element that the literature emphasizes less: resilience is a dynamic process, not an instantaneous outcome.

Furthermore, while there is consistent evidence of the benefits of circular strategies on physical indicators of soil, water or crop productivity, less of the literature addresses the impact of these strategies on socio-economic dimensions of resilience. Recent research suggests that farmers are often reluctant to adopt circular technologies not because of their inefficiency, but because of institutional barriers, initial costs and uncertainties about long-term benefits [124]. This points to an area of research where more empirical data is needed, not just theoretical models. Furthermore, the assessment of economic stability, costs and the capacity to adapt to market shocks remains inconsistent across studies, suggesting a clear need for standardized methodological frameworks.

In our view, it is noteworthy that most of the existing literature is concentrated in developed countries or agricultural systems with advanced infrastructure, while resource-limited and developing regions are underrepresented. This concentration limits the ability to extrapolate conclusions globally and to understand how circular strategies can be adapted to very diverse soil–climatic and socio-economic contexts. Comparative research that includes these regions is essential for a more robust understanding of how circularity can support climate resilience in vulnerable environments.

At the same time, although circular strategies also appear to contribute to decarbonization, more studies are needed to quantify the effects on greenhouse gas emissions per unit of product, using comparative methodologies such as life cycle analysis. Similarly, the integration of renewable energy sources on farms is only sporadically studied, although there is work demonstrating their potential to reduce dependence on fossil fuels and increase the economic stability of farms.

In practice, however, the transition towards circularity is rarely linear and often constrained by local institutional and economic realities. Despite the fact that numerous benefits of circular strategies for climate resilience are highlighted, the large-scale adoption remains challenging due to significant socio-economic and institutional barriers. In various contexts, farmers perceive circular transformations as economically risky, costly and dependent on access to finance, infrastructure and advisory services. These are factors that can inhibit the adoption of regenerative practices, especially in resource-limited farming systems. These obstacles are often documented in the recent literature, and highlight that perceived financial risk, lack of resources and gaps in institutional support are real barriers to the adoption of circular agriculture and climate adaptation strategies in many regions of the world. An example is the study by Hilmi et al. [125] on farmers’ perceptions and financial barriers, and on the other hand, there is the study by Whitton and Carmichael [126] that identifies structural and organizational constraints in the agricultural climate transition.

Nevertheless, circular strategies may generate unintended rebound effects. For example, increased biomass valorization for bioenergy could compete with soil carbon retention objectives if residue removal exceeds sustainable thresholds. Similarly, high-tech precision agriculture could increase energy demand through digital infrastructure, partially offsetting decarbonization gains. Therefore, circular transitions must be evaluated through system-wide carbon and nutrient balances to avoid problem-shifting across environmental domains.

The relationship between adaptation (climate resilience) and mitigation (decarbonization) in circular agriculture is characterized by both synergies and potential conflicts. Several circular practices generate co-benefits across these two objectives. For instance, increasing soil organic carbon enhances water retention and drought resilience while simultaneously contributing to carbon sequestration and greenhouse gas mitigation. Similarly, improving nutrient recycling reduces reliance on synthetic fertilizers, thereby lowering emissions associated with their production and use.

However, potential conflicts may also arise. The use of agricultural residues for bioenergy can support decarbonization goals, but may reduce the availability of organic matter returned to soils, potentially affecting soil health and long-term resilience. In addition, certain technology-intensive circular solutions may increase energy demand, partially offsetting mitigation gains. Empirical studies provide examples of these interactions, particularly in systems where integrated soil management and diversified cropping practices have been associated with both improved resource efficiency and reduced emissions per unit of output. These observations underscore the need for integrated assessment approaches that consider adaptation and mitigation simultaneously, rather than treating them as separate objectives.

Furthermore, we argue that the implementation of circular practices can generate socio-economic trade-offs that are not yet fully understood or systematically quantified in the literature [127]. For example, the transformation of conventional models to circular models can require high initial costs and pressures on the farm economy, and the benefits become visible only in the long term. This phenomenon discourages widespread adoption in the absence of clear financial support mechanisms, public policies and responses adapted to the local context, aspects also reported in analyses of barriers to the adoption of circularity in agriculture.

Based on our findings, our study suggests that a more systematic integration of circular practices with agricultural, climate and socio-economic performance indicators can facilitate the development of better-informed policies and more effective implementation strategies. This is particularly relevant in a global context where climate change is intensifying and the need to adapt and transform agricultural practices is becoming increasingly urgent. In practice, however, no single framework can fully reflect the complexity of local farming realities, and the effectiveness of circular economy indicators depends strongly on local environmental conditions, farm structure and socio-economic constraints. Thus, a key limitation of this study is that the proposed framework remains indicative rather than exhaustive, since circular economy indicators could have different meanings and levels of relevance in contrasting agro-climatic and socio-economic contexts, particularly between highly industrialized and resource-limited farming systems.

A key contribution of this study Is the recognition that circular economy strategies could generate simultaneous benefits for both climate resilience and decarbonization, although these relationships are often complex and context-dependent. For instance, increasing soil organic carbon through organic amendments not only enhances water retention and drought buffering capacity, but also contributes to carbon sequestration. However, such synergies are not universal, and certain practices can create tensions between adaptation and mitigation objectives, particularly when resource use, energy demand, or economic costs are unevenly distributed. This highlights the need for integrated assessment frameworks capable of capturing both synergies and trade-offs between resilience and decarbonization pathways.

Overall, the literature suggests that circular economy strategies should not be interpreted as isolated technical solutions, but rather as components of a broader systemic transition in agriculture. Their effectiveness depends not only on biophysical processes, but also on socio-economic conditions, institutional frameworks, and long-term adaptation pathways. This systemic perspective reinforces the need to move beyond fragmented assessments toward integrative and context-sensitive approaches. It also explains why results reported in the literature remain heterogeneous and sometimes difficult to generalize across regions.

5. Conclusions

The literature review conducted in this study highlights the growing importance of circular economy strategies in strengthening the climate resilience of agricultural systems, especially in a context marked by increasing climate stress and pressure on natural resources. The synthesized results stresses that circular interventions do not act in isolation, but through a combination of mechanisms that simultaneously influence soil functioning, water use, agricultural production stability and farm energy performance.

From the perspective of the biophysical environment, circular practices directly contribute to improving soil quality, increasing organic carbon content and water retention capacity, which are essential aspects for mitigating the effects of drought and climate variability. At the same time, the integration of circular strategies at the agricultural system level has important implications for resource efficiency. Reducing dependence on synthetic fertilizers, recycling nutrients and using renewable energy sources, such as biogas or photovoltaics, can contribute not only to reducing the carbon footprint, but also to increasing the energy autonomy of farms. These aspects are increasingly relevant for the economic resilience of agricultural holdings.

While circular economy strategies are often associated with multiple environmental and resilience benefits, their effects are not universally positive and may involve important trade-offs. For example, increased biomass valorization for bioenergy may reduce the availability of organic residues for soil carbon accumulation if not carefully managed. Similarly, the adoption of advanced digital technologies could improve resource efficiency but can also increase energy demand and investment costs. These findings suggest that circular strategies should be evaluated within system-wide boundaries, rather than being assumed as inherently sustainable.

At the same time, the study also highlights the current limits of research. Although the ecological benefits of circular strategies are relatively well documented, the assessment of the socio-economic dimensions of resilience remains fragmented and uneven. Indicators such as income stability, the ability to adapt to market shocks or dependence on external inputs are still insufficiently integrated into existing analytical frameworks, despite their importance for the large-scale adoption of circular practices. In this context, the main contribution of the study consists of proposing an integrated approach to assessing climate resilience, which correlates environmental indicators, agricultural performance, energy and socio-economic dimensions in a unified framework. Such an approach allows not only a more realistic assessment of the effects of circular strategies, but also a better substantiation of decisions at the level of agricultural policies and farm management.

In our view, circular economy strategies are a promising tool for increasing climate resilience and sustainability of agri-food systems, but their efficiency depends on how they are adapted to the local context and on the ability to evaluate them through relevant and comparable indicators. Future research should focus on longitudinal studies, on the integration of regions less represented in the current literature and on the development of standardized methodologies that reflect the real complexity of agricultural systems in the face of climate change.

Ultimately, CE strategies in agriculture should not be interpreted solely as efficiency-enhancing tools but as systemic redesign principles capable of reshaping agroecosystem metabolism. Their transformative potential lies in reorganizing material and energy flows in alignment with ecological limits, thereby enabling agriculture to shift from being a net climate stressor to becoming a stabilizing component of the Earth system.