1 Introduction

The inevitable climate change events, such as frequent flooding, extreme heat, and uncertain precipitation patterns, have challenged crop production and agricultural growth (Carraro 2016; IPCC 2023). The detrimental effect of climate change on global crop production has been well documented (e.g., Challinor et al. 2014; Kuwayama et al. 2019; Lachaud et al. 2021; Miller et al. 2021; Schmitt et al. 2022). For example, the Latin America and the Caribbean study by Lachaud et al. (2021) showed that climate change reduces farm productivity by 9.03–12.7% in 2015–2050. Analyzing a half-decade panel dataset, Amale et al. (2022) demonstrated that delayed monsoon onset harms crop production in India.

The COVID-19 pandemic and burgeoning global population have notably surged food demand. As of 2020, global hunger afflicts around 720–811 million people (FAO). The advent of the COVID-19 pandemic has further exacerbated hunger and food insecurity. In addition, the global population is projected to surpass 9 billion by approximately 2037, primarily concentrated in low- and lower-middle-income countries. As highlighted by Lipper et al. (2014), a minimum of a 60% increase in agricultural production is imperative to cater to the expanding global populace’s sustenance requirements. Ensuring the well-being of 9 billion people without hunger necessitates an augmentation in agrifood output while embracing sustainable development principles.

The detrimental ramifications of global climate change and the confluence of heightened agricultural production imperatives urge farmers to embrace climate-smart agricultural (CSA) practices that mitigate climate-induced adversities. A substantial body of literature has delved into the effects of climate-smart agriculture with a focus on different identified CSA practices (e.g., Adonadaga et al. 2022; Neuenschwander et al. 2023; Zizinga et al. 2022). For example, Fentie and Beyene (2019) found that adopting row planting amplifies maize yield and commercialization intensity in Ghana. Examining agricultural reduction prospects in South Asia, Aryal et al. (2020) highlighted that soil, water, and nutrient management practices can potentially mitigate greenhouse gas (GHG) emissions, contributing to climate change mitigation. Zizinga et al. (2022) conducted field experiments to scrutinize the efficacy of CSA practices, focusing on mulching at varying thicknesses (0, 2, 4, and 6 cm). They found that CSA practice adoption increases maize yield and water use efficiency, and the largest effect occurred at a 6 cm mulch depth. Nevertheless, these studies have focused on a single CSA practice, which may yield divergent outcomes across different locations.

As underscored by FAO (2021), climate-smart agriculture constitutes innovations aligned with three goals: (a) sustainably increase agricultural productivity and incomes; (b) adapt and build the resilience of people and agrifood systems to climate change; and (c) reduce or, where possible, avoid greenhouse gas emissions. Few studies have synthesized the literature regarding the impact of CSA adoption on the achievements of the three goals associated with the promotion of climate-smart agriculture (e.g., Dinesh et al. 2015; Hamidov et al. 2018; Jamil et al. 2023; Kaczan et al. 2013; Partey et al. 2018). For example, Dinesh et al. (2015) synthesized 19 CSA case studies, assessing the efficacy of interventions aligned with three CSA goals. Their analysis highlighted intervention effectiveness contingent on specific contexts. Hamidov et al. (2018) scrutinized 20 agricultural adaptation cases across Europe, gauging the influence of climate change adaptations on soil functions. Findings suggest that most adaptations enhance soil conditions, while their impact on biodiversity remains uncertain. Jamil et al. (2023) investigated CSA practices, including agroforestry, crop rotation, diversification, laser leveling, and advanced agronomic soil enhancement and water retention methods. They highlighted the importance of those practices in promoting climate adaptation.

The reviews mentioned above help enrich our understanding of the economic and environmental effects of CSA adoption and underscore the site-specific nature of climate change impacts on agricultural production. However, findings from selected practices or regions in those literature review studies lack generalizability. In addition, we cannot conclude a one-fit-all CSA (either row planting or adjusting crop calendars) for achieving the goal for other countries and regions. Thus, a comprehensive review of literature detailing CSA practices is imperative to discern effective CSA approaches for diverse crops and regions. Besides, achieving the three CSA objectives could result in synergies or trade-offs (e.g., Chavula 2021; Dinesh et al. 2015; Jagustović et al. 2021; Ogola and Ouko 2021; Tilahun et al. 2023). Yet, delineating effective CSA strategies for each goal is pivotal due to regional variations in prioritizing these goals. This distinction equips policymakers to craft targeted strategies and interventions aligned with their primary objectives.

The objective of the present study is to review a body of collected literature and summarize their findings on the effects of CSA adoption on farm productivity and incomes, resilience, and greenhouse gas emissions, covering the three goals of climate-smart agriculture. Our contributions to the existing literature encompass three aspects. Firstly, our review discerns the effects of CSA adoption based on the three goals intrinsic to climate-smart agriculture. This makes our study stand as one of the limited systematic syntheses of CSA-related literature. Secondly, we comprehensively delineate multiple dimensions to chart CSA adoption’s impacts within each goal. Specifically, our analysis delves into the literature regarding the effects of CSA adoption on farm productivity and incomes, focusing on (1) crop yields and productivity, (2) incomes, and (3) technical and resource use efficiency – all aligning with CSA goal 1. In addition, we categorize the impacts of CSA adoption on resilience into (1) food consumption, dietary diversity, and food security and (2) production risk and vulnerability, which align with goal 2 of climate-smart agriculture. In the context of the goal 3, we examine impacts on (1) GHG emissions and (2) soil quality. Lastly, our study extends its purview to encompass diverse geographical locations, in contrast to the prevailing trend of concentrating on singular countries or regions. Encompassing Asia, Africa, Europe, and North America, our review enhances understanding and furnishes practical implications across varied landscapes.

The structure of this study unfolds as follows: In Section 2, we explain the procedure of literature collection and selection. Section 3 reviews the literature examining the effects of CSA adoption on farm productivity and incomes. Section 4 reviews the literature estimating the impact of CSA adoption on resilience, while Section 5 reviews the literature on the implications of CSA adoption for greenhouse gas emissions. Finally, we present concluding remarks in Section 6.

2 Literature collection and selection

This study employs the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to comprehensively review the existing literature concerning the effects of CSA adoption. Adhering to the PRISMA methodology (Moher et al. 2015; Schaub et al. 2023), our approach entails a four-step process: defining the research question, locating pertinent literature based on established criteria, excluding non-relevant studies, and summarizing the findings to mitigate identification biases. To gather literature, online searches were conducted using Google Scholar, ScienceDirect, and Web of Science. Keywords including “climate-smart agricultural practices”, “impact of adopting climate-smart agricultural practices”, and “effects of adopting climate-smart agricultural practices” were employed. The article types include peer-reviewed journal articles, working papers, and reports. We screened articles from 2013 onwards and excluded those that did not focus on the impact of CSA adoption. The workflow is shown in Fig. 1.

Fig. 1
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Flow diagram of the literature selection

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In the first stage, 3,029 papers were identified, and the subsequent elimination of 537 duplicates resulted in a refined pool of 2,492 for screening based on titles and abstracts. In the second stage, applying exclusion criteria led to removing 1,846 papers not directly aligned with the specified search terms, narrowing the scope to 646. Following the exclusion of three inaccessible papers, a comprehensive assessment of the remaining 643 was conducted in the third step, emphasizing research design considerations and variable relevance. The final focus was honed on 107 papers, removing 536 irrelevant publications.

Among the selected articles, 60 scrutinize CSA adoption’s impact on farm productivity. A total of 33 focused on income and resilience, respectively. A total of 25 articles focus on the effect of CSA adoption on GHG emissions (Fig. 2). The CSA practices are defined broadly in the selected papers. The identified practices include, such as adjusting crop calendars (Wang et al. 2022), adopting organic fertilizers and maize-legume intercropping (Maggio et al. 2022), and implementing row planting and drought-tolerant maize varieties (Martey et al. 2020). These practices, divergent from conventional agricultural methods, embody intelligence in adapting to climate change, collectively known as “climate-smart agriculture.”

Fig. 2
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Distributions of literature selection. Note: The reference may overlap across categories

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3 Impacts of CSA adoption on farm productivity and incomes

The first CSA goal is to achieve sustainable increases in agricultural productivity and incomes. Prior research has extensively explored the direct influence of CSA adoption on indicators related to farm productivity and incomes. In addition, some studies have delved into the role of CSA adoption in enhancing both technical and resource use efficiency – a practical pathway for bolstering farm productivity and incomes.

3.1 Impacts on crop yields and productivity

We collected 31 studies investigating the influence of CSA adoption on crop yields and productivity (see Table 8 in the Appendix). These studies affirm a positive and statistically significant association between CSA adoption and crop yields or productivity. However, Gorst et al. (2018) presented an exception, demonstrating that adopting CSAs like altered crop timing, crop switching, and conservation technologies significantly boost rice productivity in Pakistan, while its impact on wheat productivity remains statistically insignificant. It is important to note that direct comparisons of the yields or productivity-enhancing effects across existing studies are inconvincible due to variations in CSA categories, crop types, and contextual settings. Nevertheless, the collective evidence supports the assertion that CSA adoption effectively contributes to a crucial facet of the first CSA objective – sustainable improvement of agricultural productivity.

The CSAs explored in the literature exhibit diversity across various countries and regions, complicating the identification of representative CSAs. Nonetheless, we have constructed a typology of five representative CSA groups, organized according to input management and crop production stages (see Table 1): (1) land and soil management. This group encompasses CSAs like minimum soil disturbance (Arslan et al. 2015), no-tillage Brouziyne et al. (2018), and laser land leveling (Ghosh 2019); (2) seed use. This category involves CSAs such as improved crop varieties (Xiong et al. 2014), disease/pest resistant varieties, and drought tolerant varieties (Makate et al. 2019; Martey et al. 2020); (3) chemical input use. Encompassing CSAs include adjusting chemical fertilizer use intensity (Kimaro et al. 2016), farm yard manure use (Khanal et al. 2018a), and integrated pest management (Midingoyi et al. 2019); (4) water management. This group comprises CSAs such as water absorption trenches (Amadu et al. 2020), adjusting irrigation frequency and amount (Khan et al. 2022), and having settling ponds (Do and Ho 2022); (5) crop calendars and rotations. Encompassing CSAs involve legume intercropping (Fao 2015), crop diversification (Khatri-Chhetri et al. 2016), and changing planting dates (Wang et al. 2022). It is important to note that this typology does not prescribe specific CSAs, as the effectiveness of CSA adoption hinges on contextual factors. However, it does offer a versatile toolkit that farmers can draw from when confronting new challenges posed by climate change.

Table 1 CSA groups that increase crop yields and productivity
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In this category, few studies solely concentrate on one specific CSA. For example, Midingoyi et al. (2019) showed that fruit fly-integrated pest management increased mango production in Kenya. Wang et al. (2022) demonstrated that adjusting crop calendars enhances annual caloric yields in India and Bangladesh. Moreover, empirical literature underscores the amplified role of jointly adopting CSAs in elevating crop yields and productivity compared to singular CSA practice adoption. For example, Jamil et al. (2021) found that adopting irrigation and soil/crop management practices jointly impacts maize yield more in Pakistan than adopting only one.

Moreover, some studies have made efforts to identify the best combinations that help obtain the highest crop yields considering three or more CSAs (e.g., Arslan et al. 2015; Khanal et al. 2018b; Khatri-Chhetri et al. 2017; Muneer et al. 2023). For example, Arslan et al. (2015) found that adopting five CSAs, including minimum soil disturbance, crop rotation, legume intercropping, inorganic fertilizer, and improved seeds, contributes to the highest crop yields. Muneer et al. (2023) reported that jointly adopting the CSA practices, including encompassing modifications in cropping timing, shifting patterns, altering input use, soil and water conservation, income diversification, and infrastructure development, can generate the highest gains for farmers in Pakistan. The impact of climate change on agricultural production is multifaceted, with irregular precipitation patterns and shifting temperatures necessitating comprehensive attention to various aspects of crop cultivation (Zhou et al. 2023). Given this complexity, it is reasonable to emphasize joint CSA adoption, as its comprehensive approach is anticipated to substantially impact crop yields and productivity.

The literature within this category predominantly encompasses Asian (e.g., China, Vietnam, and Pakistan) and African countries (e.g., Uganda, Kenya, and Zimbabwe). A substantial portion of the population in these nations, particularly within rural areas, relies on agricultural production for income and sustenance. The imperative to adapt to climate change accentuates the priority of augmenting crop yields and productivity, propelling prior investigations into the effects of CSA adoption on these factors in these countries. In addition, the demand for grain-based sustenance significantly influences the crops under examination. Within this domain, 24 studies concentrated on the relationship between CSA adoption and the yields or productivity of grain crops such as rice, maize, and wheat, collectively accounting for 77.4% of the reviewed studies. Conversely, few papers explore the ramifications of CSA adoption on oil-bearing and cash crops like cotton (Jamil et al. 2021) and cereal and legume crops (Makate et al. 2019). Studies also analyze fruit crops like mango (Midingoyi et al. 2019) and fisheries such as shrimp (Do and Ho 2022).

3.2 Impacts on incomes

Another facet of the first CSA goal involves the sustainable enhancement of income. It is imperative to scrutinize the effects of CSA adoption on income-related indicators, such as income, net returns, and profit. While the augmentation of crop yields and productivity primarily bolsters food supply, aiding rural residents in averting hunger, the elevation in income possesses the potential to mitigate poverty. Moreover, it empowers rural residents to access a broader spectrum of food varieties beyond those they cultivate.

We have collected 27 papers exploring CSA adoption’s impact on income-related indicators. Some studies exclusively focused on one or two CSAs. For example, Fentie and Beyene (2019) found that row planting adoption increases teff income in Ethiopia. Similarly, Song et al. (2018) showed that adopting irrigation and drainage improved grain net profit in China. Conversely, most of the literature has examined the simultaneous adoption of multiple CSAs, which is anticipated to yield a greater income increase than a single adoption. For example, Khatri-Chhetri et al. (2016) found that adopting four identified CSAs, including improved crop varieties, crop diversification, laser land leveling, and zero tillage practice, increases rice and wheat production incomes in India. In another study, Belay et al. (2023) investigated the role of seven CSAs, such as soil and water conservation with biological measures, crop rotation, improved crop varieties, agroforestry systems, improved breeds, and residue incorporation in enhancing the income of farmers in Ethiopia. They confirmed the positive relationship between CSA practice adoption and income growth.

The examined indicators comprise (1) crop income or gross revenue (Khatri-Chhetri et al. 2016; Imran et al. 2018); (2) farm income (Scognamillo and Sitko 2021); (3) household income (Makate et al. 2019; Chiputwa et al. 2022); (4) net returns, net income, or profit (defined as the difference between gross revenue and production costs) (Jamil et al. 2021; Dey et al. 2023); (5) net household income (Brüssow et al. 2017; Kien et al. 2023); (6) other indicators like net present values (Mutenje et al. 2019) and farm assets (Danso-Abbeam and Baiyegunhi 2018). The details are presented in Table 2. Although crop income or household income provide insights, they do not encompass production costs or household expenditures (Zheng et al. 2021a). Therefore, incorporating net returns or net household income is valuable for a comprehensive assessment of the income-enhancing impact of CSA adoption.

Table 2 CSA groups that increase income-related indicators
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Findings in this category also underscore the importance of utilizing indicators like net returns or net household income (see Table 9 in the Appendix). When crop income, farm income, or household income are employed as outcome variables, prevailing studies consistently reveal that adopting various CSA combinations yields a positive and statistically significant impact on these variables (Abid et al. 2016; Imran et al. 2018; Makate et al. 2019; Ogada et al. 2020), suggesting the economic viability of CSA adoption. Nevertheless, the efficacy of CSA adoption is contingent upon considering production costs or household expenditures. For example, net returns or net farm income is the disparity between crop/farm gross revenue and production costs. Net household income is derived from the contrast between total household income and expenditure. Several studies revealed that CSA adoption contributes to an increase in net returns (Ghosh 2019), net farm income (Teklewold et al. 2017; Kakraliya et al. 2018), or household net income (Brüssow et al. 2017; Kien et al. 2023). However, Song et al. (2018) exhibited that engineering-type measures have negligible influence on crop net profit in China, while Quddoos et al. (2022) emphasized that effective climate change adaptation measures could still lead to a 4.4% profit reduction for farms in Austria.

Both grain crops (such as wheat and rice) and cash crops (like cotton and fruit) contribute to increased household income, with the latter often playing a more substantial role due to its commercialization. As such, the literature analyzing the relationship between CSA adoption and income-related indicators encompasses both grain and cash crops, differing slightly from the literature assessing the impact of CSA adoption on crop yields and productivity in the preceding subsection. For example, this subsection examines crops like wheat (Abid et al. 2016; Khatri-Chhetri et al. 2016), rice (Bairagi et al. 2020; Dey et al. 2023), teff (Fentie and Beyene 2019), and grain (Song et al. 2018). Simultaneously, existing studies concentrate on cash crops like cotton (Imran et al. 2018; Jamil et al. 2021), cocoa (Danso-Abbeam and Baiyegunhi 2018), mango (Midingoyi et al. 2019).

3.3 Impacts on technical and resource use efficiency

In addition to directly analyzing the impact of CSA adoption on farm productivity and income indicators, some studies have investigated the effective pathways through which CSA adoption enhances farm productivity and incomes. One example is enhancing technical and resource use efficiency, allowing rural households to achieve greater output with consistent production inputs. Technical efficiency refers to the ratio of farmers’ observed output to the maximum achievable output given the existing inputs, reflecting the utilization efficiency of various agricultural inputs (Zheng et al. 2021b). In this subsection, we focus on the literature examining the effects of CSA adoption on technical and resource use efficiency.

A total of 16 papers were collected to examine the impact of CSA adoption on efficiency-related indicators (see Table 3). Among them, seven studies focused on the relationship between CSA adoption and technical efficiency (e.g., Imran et al. 2019; Khanal et al. 2018b; Pangapanga-Phiri and Mungatana 2021), which reflects the efficiency of utilizing agricultural input combinations. They consistently found that CSA adoption increases technical efficiency in crop production in countries like Nepal (Khanal et al. 2018b), Pakistan (Imran et al. 2019), and Malawi (Pangapanga-Phiri and Mungatana 2021). In addition, seven papers analyzed the efficiency of water utilization. For example, Çetin and Kara (2019) studied the effect of adopting surface and subsurface drip irrigation on water productivity in Turkey, reporting an increase in water productivity. Wang et al. (2022) demonstrated that adjusting crop calendars reduces the blue water requirement in India and Bangladesh. In addition, adopting various CSA practices has also enhanced energy productivity in India (Kakraliya et al. 2018) and land economic productivity in Turkey (Çetin and Kara 2019). In conclusion, existing evidence supports the notion that adopting CSA practices is an effective strategy for increasing technical and resource use efficiency, thereby contributing to achieving the first CSA goal of sustainable farm productivity and income enhancement.

Table 3 Overview of literature analyzing the impact of CSA adoption on technical and resource use efficiency
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4 Impacts of CSA adoption on resilience

The second goal of CSA is to enhance the adaptability and resilience of both people and agrifood systems to the effects of climate change. Resilience can be understood from various perspectives, such as psychology, sociology, and biological disciplines (Herrman et al. 2011), resulting in a lack of consensus on its operational definition. Our review of existing literature indicates that many CSA-related studies primarily focus on enhancing physical resilience among individuals. This involves improving physical health by increasing food consumption, dietary diversity, and food security (e.g., Bazzana et al. 2022; Hasan et al. 2018; Teklewold et al. 2019). Thus, we examine the literature examining the impact of CSA adoption on food-related indicators. In addition, the resilience of agrifood systems pertains to their ability to address potential risks and mitigate vulnerabilities. Consequently, we then delve into the literature discussing the effects of CSA adoption on production risk and vulnerability.

4.1 Impacts on food consumption, dietary diversity, and food security

We have collected 22 papers that analyze the influence of CSA adoption on food consumption, dietary diversity, and food security. As summarized in Table 4, food consumption is assessed through metrics such as food consumption expenditure (Danso-Abbeam and Baiyegunhi 2018; Hasan et al. 2018) or weighted food consumption score (Brüssow et al. 2017; Egeru et al. 2022). Dietary diversity refers to the variety of food items (typically across 12 categories) consumed by a household within a specified period (usually three or seven days) (Ma et al. 2022). Food security is commonly gauged using subjective measurements (Danso-Abbeam and Baiyegunhi 2018), a weighted score (Agarwal et al. 2022; Dey et al. 2023), or specific metrics (Bazzana et al. 2022). Some studies employed a reverse perspective, considering food insecurity scores (Hasan et al. 2018; Issahaku and Abdulai 2020a) or the food insecurity experience scale (Ali et al. 2022). In addition, our analysis incorporates indicators like food availability (Lopez-Ridaura et al. 2018; Teklewold et al. 2019) and human health (Midingoyi et al. 2019).

Table 4 CSA groups that increase food consumption, dietary diversity, and food security
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Existing studies consistently demonstrate that adopting various CSA practices significantly increases food consumption and expenditure (see Table 10 in the Appendix). For example, Fentie and Beyene (2019) observed that row planting significantly elevated teff consumption per capita in Ethiopia. Egeru et al. (2022) evidenced that multiple CSA adoptions notably enhanced food consumption scores in Uganda. However, the impact of CSA adoption on dietary diversity is not uniform. Hasan et al. (2018) emphasized the lack of significant effects of multiple CSA adoption on household dietary diversity scores in Bangladesh. In contrast, studies in Ghana (Issahaku and Abdulai 2020a) and Ethiopia (Teklewold et al. 2019; Cholo et al. 2019; Ali et al. 2022) reported a positive relationship between CSA adoption and household dietary diversity.

Regarding the impact of CSA adoption on food security indicators, the existing literature consistently supports that CSA adoption increases food security (Brüssow et al. 2017; Cholo et al. 2019; Dadzie et al. 2020; Oyawole et al. 2020; Abegunde et al. 2022) or reduces food instability and insecurity (Issahaku and Abdulai 2020a; Bazzana et al. 2022). However, Hasan et al. (2018) found no significant influence of multiple CSA adoption on household insecurity access scores in Bangladesh. In addition, in Kenya, Midingoyi et al. (2019) analyzed the impact of integrated pest management on human health, a more comprehensive indicator of people’s physical resilience. They established a positive relationship between integrated pest management and human health.

4.2 Impacts on production risk and vulnerability

CSA adoption could enhance agrifood systems’ resilience by improving their ability to manage risks and reduce vulnerability. Around 11 of our reviewed studies have assessed CSA adoption’s impact on production risk and vulnerability (see Table 5). These risk-related indicators include the expected error term, estimated through a moment-based production function (Zheng and Ma 2023), and its variance, skewness, and kurtosis (Wang et al. 2018; Shahzad and Abdulai 2020; Sarr et al. 2021). Vulnerability, reflecting the capacity of agrifood systems to anticipate and recover from climate change impacts (Wouterse et al. 2022), lacks a consistent concept (Adonadaga et al. 2022). Arslan et al. (2018) employed the logarithm of income per capita and the probability of falling below the poverty line as vulnerability metrics. Adonadaga et al. (2022) defined drought vulnerability using four components: threshold capacity, coping capacity, recovery capacity, and adaptive capacity.

Table 5 Overview of literature analyzing the impact of CSA adoption on production risk and vulnerability
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The literature examining the impact of CSA adoption on production risk focuses on grain crops such as rice (Wang et al. 2018), maize (Issahaku and Abdulai 2020b), and wheat (Komarek et al. 2019). For example, Wang et al. (2018) demonstrated that irrigation practices significantly increase rice yield and reduce variance, decreasing risk exposure. This aligns with Issahaku and Abdulai (2020b), who observed that improved extension services increase crop revenue and risk exposure (skewness of crop yield) in Ghana. In Tanzania, Sarr et al. (2021) determined that the system of rice intensification significantly enhances expected yields and yield skewness while yield variance remains relatively unchanged. In addition, Shahzad and Abdulai (2020) considered kurtosis, the fourth moment, and revealed that adopting climate-smart farming contributes to decreased kurtosis, indicating reduced production risk. These findings in this literature strand extend the evidence summarized in Section 3.1, highlighting that CSA adoption increases crop yields and productivity, significantly mitigates production risk, and stabilizes crop yields and net returns.

We identified four papers that explore the relationship between CSA adoption and vulnerability. Arslan et al. (2018) discovered that diversification of crops, livestock, and income significantly increases per capita income and decreases the probability of falling below the poverty line in rural Zambia. This underscores the importance of diversification strategies in reducing vulnerability. In contrast, Adonadaga et al. (2022) emphasized the ongoing challenge of reducing vulnerability to drought in Ghana due to difficulties in implementing adaptation strategies. In Ethiopia, Teklu et al. (2022) demonstrated that adopting soil and water conservation, improved varieties, crop rotation, composting, row planting, and agroforestry decreases livelihood vulnerability. Similarly, Ali et al. (2023) reported that adopting multiple CSAs reduces vulnerability indices.

5 Impacts of CSA adoption on greenhouse gas emissions

The third CSA goal is to mitigate GHG emissions when possible. Agriculture, forestry, and land use collectively contributed 18.4% of global GHG emissions in 2020 (Ritchie and Roser 2020). Notably, agricultural production is a major emission source within the agrifood systems, with crop and livestock activities within the farm gate accounting for approximately 142Tg CH4 and 8.0Tg N2O annually in 2007–2016 (FAO 2020). Thus, promoting CSA adoption is crucial to mitigate GHG emissions from agricultural production. This section first reviewed literature exploring the direct relationship between CSA adoption and GHG emissions. In addition, it is vital to consider GHG emissions arising from land use and changes like deforestation and peatland degradation, which are linked to agriculture in various regions and account for 5–14% of total GHG emissions (FAO 2020). For this reason, we also discuss existing studies on the impact of CSA adoption on soil quality.

5.1 Impacts on GHG emissions

We reviewed 19 papers that analyze the impact of CSA adoption on GHG emissions (see Table 6). Most studies in this strand have quantified the impact of CSA adoption on reducing GHG emissions. Some specifically highlight the negative impact of adopting various CSA practices. For example, McNunn et al. (2020) found that adopting crop rotations, tillage practices, stover removal practices, cover crops, and nitrogen timing decreases GHG emissions in the United States. Teklu et al. (2022) showed that adopting soil and water conservation, improved varieties, crop rotation, composting, row planting, and agroforestry reduces GHG emissions in Ethiopia. In addition, several studies have estimated the extent of the reduction effect from CSA adoption. For example, Ariani et al. (2018) indicated that adopting practices like leaf color charts for applying N fertilizer, paddy soil test kits for determining basic fertilizer, organic matter amendment, and intermittent irrigation could reduce the global warming potential of GHGs by 7%–23%. Iqbal et al. (2023) demonstrated that applying biochar can reduce GHG emissions by 50 tons per hectare per year globally.

Table 6 Overview of literature analyzing the impact of CSA adoption on greenhouse gas emissions
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GHG emissions in agrifood systems encompass CO2 and non-CO2 gases, such as N2O and CH4. Several studies have delved into the impact of CSA adoption on these emissions, considering both CO2 and other components. For example, Chitakira and Ngcobo (2021) demonstrated that composting could reduce 1,026 million tons in CO2 emissions, while row seedling might decrease 887 million tons in CO2 emissions in South Africa. Jamil et al. (2023) indicated that planting late blight and cold-tolerant GM potatoes could reduce CO2 emissions by 740 million pounds, and zero tillage practices could reduce 94,000 tons in CO2 emissions. Some studies have found that CSA adoption contributes to carbon emission reduction by carbon sequestration (Kumar and Nath 2019; Sikka et al. 2018). For example, Sikka et al. (2018) found that adopting participatory integrated watershed management increases carbon sequestration in India. In addition, Iqbal et al. (2023) found that combining biochar, fertilizer, and soils of medium texture could reduce N2O emissions by 18% and CH4 emissions by 25%.

Some studies in this field focus on specific countries. For example, Taneja et al. (2014) explored the relationship between CSA adoption and GHG emissions in India. Kakraliya et al. (2021) also analyzed the impact of CSA adoption on GHG mitigation in India. They consistently found that CSA adoption reduces GHG emissions in India. Meanwhile, many studies have taken a broader perspective, examining transnational, regional, and global scales. For example, Ogle et al. (2014) revealed that adopting CSA practices contributes to reducing GHG emissions in both developing countries (Malawi, Costa Rica, Mexico, Kenya) and developed countries (the United States). Alemaw and Simalenga (2015) and Abegunde et al. (2019) concentrated on the role of CSA adoption in influencing GHG emissions in Africa. They consistently showed that CSA adoption reduces GHG emissions in Africa. Numerous pieces of literature have investigated the impact of CSA adoption on global GHG emissions (e.g., Acosta-Alba et al. 2019; Ariani et al. 2018; Jamil et al. 2023). This broad scope reflects that GHG emissions are not confined to regional boundaries and require global responses.

In summary, increasing CSA adoption does contribute to lowering GHG emissions. However, pinpointing a specific CSA group for GHG reduction is challenging. The influence and magnitude of CSA adoption are context-specific, influenced by factors such as study location, period, and types of GHGs.

5.2 Impacts on soil quality

Given the significant contribution of GHG emissions from cropland and soil to the overall emissions, it becomes crucial to focus on carbon sequestration in soils and biomass, reducing soil erosion and preventing soil fertility decline. Our review examined seven papers investigating how CSA adoption impacts soil conditions (see Table 7). These indicators encompass soil organic matter and soil fertility (Shrestha et al. 2014; Mujeyi and Mudhara 2021), soil moisture (Komarek et al. 2019), soil carbon stock (Tadesse et al. 2021), and soil nutrient (Recha et al. 2022).

Table 7 Overview of literature analyzing the impact of CSA adoption on soil quality
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The literature findings in this realm consistently affirm that CSA adoption enhances soil quality. This is achieved through augmenting organic matter content, enhancing porosity, and improving nutrient levels. For example, Hamidov et al. (2018) studied CSA adoption across 13 European countries and demonstrated that it positively influences soil functions and organic carbon storage. Komarek et al. (2019) observed that integrated soil fertility management adoption in Ethiopia enhances soil fertility, moisture, and conservation while reducing soil erosion. Recha et al. (2022), in their analysis of multiple CSA adoptions in Uganda, Kenya, and Tanzania, found that it leads to improvements in both soil macronutrient and micronutrient content.

6 Conclusions and policy implications

6.1 Conclusions

This study aims to comprehensively understand how adopting CSA affects farm productivity and incomes, resilience, and greenhouse gas emissions. Our thorough review includes examining 107 scholarly papers. We have categorized the existing literature into three categories corresponding to the three CSA goals. This categorization of the literature based on CSA objectives serves as an analytical framework, enabling the identification of effective strategies and approaches tailored to specific CSA goals.

The study’s results offer valuable insights into the impact of CSA adoption. Regarding the first CSA goal to sustainably increase agricultural productivity and incomes, our analysis reveals that CSA adoption enhances farm productivity and incomes through increased crop yields and productivity, income, and technical and resource use efficiency. Addressing the second CSA goal of fostering resilience in people and agrifood systems against climate change, our findings demonstrate that CSA adoption bolsters individuals’ resilience by boosting food consumption, dietary diversity, and food security. Moreover, at the system level, CSA adoption enhances agrifood system resilience by mitigating production risks and decreasing vulnerability. Concerning the third CSA goal of lowering GHG emissions, our review establishes that CSA adoption contributes to reducing emissions, including CO2, N2O, and CH4. In addition, CSA adoption promotes carbon sequestration in soils and biomass, thereby improving soil quality.

6.2 Policy implications

Drawing definitive policy implications about the overall effectiveness of CSA adoption requires careful consideration. Firstly, our review highlights that the positive impact of CSA adoption on these goals is context-dependent. Acknowledging this context specificity, policymakers are urged to adopt an approach that tailors CSA strategies to each region’s unique socio-economic, environmental, and geographic conditions. In addition, it is imperative to recognize that no one-size-fits-all CSA strategy guarantees universal success. Policymakers should prioritize flexibility in policy frameworks, allowing for adaptation to the distinct characteristics of various agricultural landscapes. This flexibility will enable the effective customization of CSA practices, ensuring their alignment with the specific challenges and opportunities faced by farmers in diverse regions.

Secondly, it is essential to note that the published literature does not always yield consistent findings regarding the positive effects of CSA adoption. In some instances, we observe cases where CSA adoption has not proven to be effective. In addition, the tendency to publish studies with positive results while neglecting those with negative or inconclusive outcomes can introduce a bias in the overall literature. This selective reporting can skew our understanding of a particular phenomenon and lead to an incomplete or distorted view of the research landscape. Policymakers must be aware of this potential bias. Encouraging researchers to disseminate comprehensive findings, regardless of the direction of outcomes, is essential for mitigating the risk of skewed perspectives in formulating evidence-based policies.