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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Sustain. Food Syst.</journal-id>
<journal-title>Frontiers in Sustainable Food Systems</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Sustain. Food Syst.</abbrev-journal-title>
<issn pub-type="epub">2571-581X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fsufs.2023.1136866</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Sustainable Food Systems</subject>
<subj-group>
<subject>Systematic Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>A systematic review of the ecological, social and economic sustainability effects of community-supported agriculture</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name><surname>Egli</surname> <given-names>Lukas</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x0002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1714845/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>R&#x000FC;schhoff</surname> <given-names>Judith</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/2210662/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Priess</surname> <given-names>J&#x000F6;rg</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/803794/overview"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Department of Computational Landscape Ecology, UFZ&#x02014;Helmholtz Centre for Environmental Research</institution>, <addr-line>Leipzig</addr-line>, <country>Germany</country></aff>
<aff id="aff2"><sup>2</sup><institution>Department of Soil System Science, UFZ&#x02014;Helmholtz Centre for Environmental Research</institution>, <addr-line>Halle</addr-line>, <country>Germany</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Marilyn Sitaker, Washington State University, United States</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Barbora Du&#x0017E;&#x000ED;, Institute of Geonics (ASCR), Czechia; Raivo Kalle, University of Gastronomic Sciences, Italy</p></fn>
<corresp id="c001">&#x0002A;Correspondence: Lukas Egli <email>lukas.egli&#x00040;ufz.de</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>16</day>
<month>05</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>7</volume>
<elocation-id>1136866</elocation-id>
<history>
<date date-type="received">
<day>03</day>
<month>01</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>25</day>
<month>04</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2023 Egli, R&#x000FC;schhoff and Priess.</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Egli, R&#x000FC;schhoff and Priess</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p></license> </permissions>
<abstract>
<sec>
<title>Introduction</title>
<p>Community-supported agriculture (CSA) offers a high potential to provide synergies between ecological, economic and social sustainability aspects. While CSA is still in a niche, it has experienced rapid growth and increasing interest during the last years. An overview of sustainability impacts of CSA based on quantitative empirical work is missing, which is needed for well-informed and targeted policies and funding, as well as to tackle research gaps.</p>
</sec>
<sec>
<title>Methods</title>
<p>Here we reviewed the literature to systematically assess empirical and quantitative findings regarding sustainability outcomes of CSA at different levels.</p>
</sec>
<sec>
<title>Results</title>
<p>We found that &#x0003C; 30% of the 39 studies included assessed ecological sustainability aspects. If CSA farms were compared to reference systems, they mostly performed better with regard to resource use efficiency and greenhouse gas emissions. The majority of studies evaluated social aspects. While many studies showed that CSA yet fails to reach low-income households, and therefore members do not represent the average population, CSA membership improves health and sustainability behavior. Economic variables were assessed in more than half of the considered studies, but knowledge on the relative performance remains scarce. Nevertheless, first studies indicate high economic viability.</p>
</sec>
<sec>
<title>Discussion</title>
<p>Our review suggests a largely positive performance of CSA with regard to sustainability. Accordingly, if CSA would reach a bigger share in the food system, it could contribute to a transformation toward sustainable food systems. To address important knowledge gaps, we recommend the consideration of more and particularly ecological sustainability aspects, comparisons across different farming and marketing systems and the integration of knowledge from different sources such as theses and practical knowledge documented in various languages in different parts of the world.</p>
</sec></abstract>
<kwd-group>
<kwd>alternative food systems</kwd>
<kwd>community-based farming</kwd>
<kwd>food system transformation</kwd>
<kwd>local food systems</kwd>
<kwd>resilience</kwd>
<kwd>solidarity</kwd>
</kwd-group>
<counts>
<fig-count count="3"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="85"/>
<page-count count="11"/>
<word-count count="7997"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Social Movements, Institutions and Governance</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1">
<title>1. Introduction</title>
<p>In the light of climate change, biodiversity loss, increasing demand for agricultural products, social inequalities, and economic pressures, a transformation toward sustainable, resilient and inclusive food systems is urgently needed (Pigford et al., <xref ref-type="bibr" rid="B59">2018</xref>). Alternative food systems, including farmers&#x00027; markets and shops, community-supported agriculture, food cooperatives and organic agriculture, are increasingly recognized as promising approaches to address these challenges (Renting et al., <xref ref-type="bibr" rid="B64">2003</xref>; Ilbery and Maye, <xref ref-type="bibr" rid="B34">2005</xref>; Forssell and Lankoski, <xref ref-type="bibr" rid="B24">2015</xref>).</p>
<p>In particular, community-supported agriculture (CSA) offers opportunities to provide synergies between ecological, economic and social aspects that could contribute to a transformation toward sustainable food systems (Nost, <xref ref-type="bibr" rid="B53">2014</xref>; Bloemmen et al., <xref ref-type="bibr" rid="B5">2015</xref>; Schmutz et al., <xref ref-type="bibr" rid="B70">2018</xref>; Haack et al., <xref ref-type="bibr" rid="B31">2020</xref>). Linking farmers and consumers (members) through long-term partnerships including upfront payments to cover production costs is a core principle of CSA (Lamb, <xref ref-type="bibr" rid="B39">1994</xref>; Cone and Myhre, <xref ref-type="bibr" rid="B13">2000</xref>; Volz et al., <xref ref-type="bibr" rid="B78">2016</xref>). Thus, both risks and the harvest are shared. CSA differs from other cooperative approaches, for example community gardens, where gardening is mainly carried by unpaid and nonprofessional volunteers, or food cooperatives, where risks are not shared by producers and consumers and products are not necessarily obtained from primary producers (Haack et al., <xref ref-type="bibr" rid="B31">2020</xref>). CSA farms are highly heterogenous for example regarding size, products, member involvement and legal forms (Volz et al., <xref ref-type="bibr" rid="B78">2016</xref>). In its simplest form, CSA is a contractual agreement between a farm and a group of members (Cone and Myhre, <xref ref-type="bibr" rid="B13">2000</xref>), but also models exist where both farmers and consumers are organized in one legal entity (Str&#x000FC;ber et al., <xref ref-type="bibr" rid="B72">2023</xref>). Likewise, underlying motives include securing livelihoods of farms, spiritual-communal practices (e.g., connection to nature, emphasis on community) or a political tool for sociopolitical change by opposing the capitalistic system through decommodification of food (Bl&#x000E4;ttel-Mink et al., <xref ref-type="bibr" rid="B4">2017</xref>; Paech et al., <xref ref-type="bibr" rid="B55">2020</xref>). Environmentally friendly farming practices however, are a main principle of most CSA farms (Volz et al., <xref ref-type="bibr" rid="B78">2016</xref>; Cristiano et al., <xref ref-type="bibr" rid="B15">2020</xref>; Netzwerk Solidarische Landwirtschaft e.V., <xref ref-type="bibr" rid="B50">2022b</xref>). Accordingly, reducing synthetic inputs, closing nutrient cycles, improving soil properties and biodiversity are inherent goals of many CSAs (Haack et al., <xref ref-type="bibr" rid="B31">2020</xref>; Cristiano, <xref ref-type="bibr" rid="B14">2021</xref>). Regarding social aspects, many CSA aim at fair wages, transparency, knowledge exchange and participation (Schmutz et al., <xref ref-type="bibr" rid="B70">2018</xref>; Diekmann et al., <xref ref-type="bibr" rid="B16">2020</xref>). Economic security is fostered through holding members and guaranteed sales (Matzembacher and Meira, <xref ref-type="bibr" rid="B44">2019</xref>; Paech et al., <xref ref-type="bibr" rid="B55">2020</xref>).</p>
<p>During the past years, CSA has gained increasing attention and the number of CSA farms has grown in many world regions. In the United States over 12.000 CSA farms existed in 2017 (Woods et al., <xref ref-type="bibr" rid="B82">2017</xref>; Samoggia et al., <xref ref-type="bibr" rid="B68">2019</xref>). The first CSA in Europe was founded in 1978 in Switzerland, yet currently most European CSAs are located in France (&#x0003E;2,000) (Volz et al., <xref ref-type="bibr" rid="B78">2016</xref>; Egartner et al., <xref ref-type="bibr" rid="B21">2020</xref>). In Germany, only five CSA were founded between 1988 and 2010, but more than 400 farms are registered today (Diekmann, <xref ref-type="bibr" rid="B17">2020</xref>; Netzwerk Solidarische Landwirtschaft e.V., <xref ref-type="bibr" rid="B49">2022a</xref>). In China, the first CSA farm has been only founded in 2009, yet already 254 existed in 2016 (Tang et al., <xref ref-type="bibr" rid="B73">2019</xref>). In Japan however, the interest in CSA has recently declined (Gugerell et al., <xref ref-type="bibr" rid="B30">2021</xref>). Compared to the total number of farms [e.g., more than two millions in the US in 2017; (USDA National Agricultural Statistics Service, <xref ref-type="bibr" rid="B75">2023</xref>)], CSA only provides a small proportion of total food production so far. Nevertheless, CSA is increasingly recognized in policy, civil society and academia, also during the COVID pandemic due to increased interest in regional food supply (Stephens et al., <xref ref-type="bibr" rid="B71">2020</xref>; Enthoven and van den Broeck, <xref ref-type="bibr" rid="B23">2021</xref>). In Germany, for example, it has been mentioned as a best-practice model with a catalytic impact in government documents and commissions (CDU et al., <xref ref-type="bibr" rid="B9">2018</xref>; Zukunftskommission Landwirtschaft, <xref ref-type="bibr" rid="B85">2021</xref>).</p>
<p>Despite the growing interest, to our knowledge, an overview of sustainability impacts of CSA is missing, which is essential, given the sustainability promises of CSA. In this study we provide a synthesis of ecological, social and economic sustainability outcomes based on quantitative empirical work in English and peer-reviewed literature. For this purpose, we (i) developed an analytical framework to assess sustainability outcomes of CSA at the farm level in a transdisciplinary process and (ii) reviewed the literature to systematically assess empirical and quantitative findings related to the different levels of the framework. On the one hand, this is an important baseline for well-informed and targeted policies and funding. On the other hand, this work will highlight relevant research gaps, given that research on CSA is still in an early stage (Cristiano, <xref ref-type="bibr" rid="B14">2021</xref>).</p>
</sec>
<sec id="s2">
<title>2. Materials and methods</title>
<p>Within a transdisciplinary research project, we developed an analytical framework for a comprehensive assessment of sustainability impacts of community-supported agriculture at the farm level. This framework consists of dimensions, categories, sub-categories and key performance indicators. We then conducted a literature review to systematically assess empirical and quantitative findings related to the different levels of the framework.</p>
<sec>
<title>2.1. Analytical framework</title>
<p>At the beginning of the transdisciplinary project &#x0201C;InnoLand-Sachsen&#x0201D;, we developed an analytical framework to assess sustainability outcomes of community-supported agriculture at the farm level. In a first step, we developed a hierarchical indicator topology following Carmen et al. (<xref ref-type="bibr" rid="B7">2020</xref>). Therefore, we adapted a German tool to assess different sustainability benefits of farms for the society and the environment (Regionalwert Leistungen GmbH). At the highest level we also included three dimensions (ecology, social and economy), but used economy instead of regional economy to be more generic (<xref ref-type="table" rid="T1">Table 1</xref>). Regarding the ecological dimension, we distinguished the categories soil, biodiversity, inputs and outputs. We referred to in- and outputs instead of &#x0201C;water and climate&#x0201D; to further emphasize the management perspective, as well as desired (e.g., harvest) and undesired outputs (e.g., greenhouse gas emissions). We neglected &#x0201C;animal welfare&#x0201D; as animal husbandry is less relevant in many CSA farms including the ones involved in the project. Regarding the social dimension, we combined the original aspects &#x0201C;expertise&#x0201D; and &#x0201C;employment and work&#x0201D; to the category <italic>team</italic> to cover all aspects related to the employees of a farm. We divided societal effects into farm level aspects and surroundings, as well as members, which are specific for CSA. Here, we also integrated aspects from an existing indicator set to describe social and economic stability of CSA (Str&#x000FC;ber et al., <xref ref-type="bibr" rid="B72">2023</xref>). Regarding economy, we specified economic sovereignty in five categories (farm, costs, revenues, financial resources, operating area) to assess economic performance in more detail, also including CSA-specific aspects (Str&#x000FC;ber et al., <xref ref-type="bibr" rid="B72">2023</xref>). Finally, we removed the original aspects &#x0201C;regional networks&#x0201D; and &#x0201C;regional economic flows,&#x0201D; as they were partly covered in the social category <italic>surroundings</italic> and because regionalization was not a specific focus of our project. For each category we selected sub categories based on existing catalogs and literature (INL, XXXX; Regionalwert Leistungen GmbH; Sanders and He&#x000DF;, <xref ref-type="bibr" rid="B69">2019</xref>; Haack et al., <xref ref-type="bibr" rid="B31">2020</xref>; Str&#x000FC;ber et al., <xref ref-type="bibr" rid="B72">2023</xref>). We further added the sub categories <italic>buffer capacity</italic> and <italic>rejection/recognition</italic>, as we experienced these aspects as important from our previous work with CSA farms (Voge et al.)<xref ref-type="fn" rid="fn0001"><sup>1</sup></xref>. For each sub category, we then proposed indicators to describe them. In a next step, we presented the initial framework to a group of seven CSA experts. The CSA experts consisted of five employees (four farmers and one coordinator) of three CSA farms in Saxony, Germany, a researcher from a project focusing on the transformative potential of CSA and an employee from a regional association strengthening direct marketing. During five workshops of around two hours each between October 2021 and March 2022, experts could first modify existing or propose additional indicators. Second the experts rated relevance and feasibility from 1 (not relevant/feasible) to 5 (highly relevant/feasible) (Carmen et al., <xref ref-type="bibr" rid="B7">2020</xref>). Based on this assessment we selected a final set of indicators that were subsequently measured in the three CSA farms involved (where both evaluation criteria reached a score of 3 or higher on average). The analytical framework and its underlying indicators are merely descriptive. To evaluate actual sustainability outcomes, the observed indicator values need to be linked to specific sustainability objectives (Latruffe et al., <xref ref-type="bibr" rid="B40">2016</xref>).</p>
<table-wrap position="float" id="T1">
<label>Table 1</label>
<caption><p>Analytical framework including the sustainability dimensions, categories and sub categories.</p></caption> 
<table frame="box" rules="all">
<thead>
<tr style="background-color:&#x00023;919498;color:&#x00023;ffffff">
<th valign="top" align="left"><bold>Dimension</bold></th>
<th valign="top" align="left"><bold>Category</bold></th>
<th valign="top" align="left"><bold>Sub category</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Ecology: focus on biotic environment, but also including abiotic factors and farming activities with environmental impacts (Lebacq et al., <xref ref-type="bibr" rid="B41">2013</xref>)</td>
<td valign="top" align="left">Soil</td>
<td valign="top" align="left">Fertility; erosion; density; climate</td>
</tr> <tr>
<td/>
<td valign="top" align="left">Inputs</td>
<td valign="top" align="left">Water; vehicles/machinery; electricity; pesticides; fertilizer; seeds; seedlings; material/technology; energy</td>
</tr> <tr>
<td/>
<td valign="top" align="left">Outputs</td>
<td valign="top" align="left">Climate; production; environmental impact; energy</td>
</tr> <tr>
<td/>
<td valign="top" align="left">Biodiversity</td>
<td valign="top" align="left">Crop diversity; plant diversity; livestock diversity; animal diversity; land use</td>
</tr> <tr>
<td valign="top" align="left">Social: farm community and society affected by farm activities (Lebacq et al., <xref ref-type="bibr" rid="B41">2013</xref>; Terrier et al., <xref ref-type="bibr" rid="B74">2013</xref>)</td>
<td valign="top" align="left">Team</td>
<td valign="top" align="left">Knowledge/learning; trust; diversity/inclusion; fluctuation; income satisfaction; full time/part time; buffer capacity</td>
</tr> <tr>
<td/>
<td valign="top" align="left">Members</td>
<td valign="top" align="left">Knowledge/learning; trust; diversity/inclusion; fluctuation; satisfaction; engagement; identification; distance; supply; behavior; well-being/health</td>
</tr> <tr>
<td/>
<td valign="top" align="left">Farm</td>
<td valign="top" align="left">Transparency; attractivity; goals/visions/strategies; bidding; community building</td>
</tr> <tr>
<td/>
<td valign="top" align="left">Surroundings</td>
<td valign="top" align="left">Cooperation; competition; rejection/recognition; knowledge</td>
</tr> <tr>
<td valign="top" align="left">Economy: economic viability of a farm (Latruffe et al., <xref ref-type="bibr" rid="B40">2016</xref>), as well as general economic characteristics of the farm</td>
<td valign="top" align="left">Farm</td>
<td valign="top" align="left">Products; management; age; distribution; marketing channels</td>
</tr> <tr>
<td/>
<td valign="top" align="left">Costs</td>
<td valign="top" align="left">Labor; running costs; investments</td>
</tr> <tr>
<td/>
<td valign="top" align="left">Revenues</td>
<td valign="top" align="left">Membership fees; donations; subsidies; projects</td>
</tr> <tr>
<td/>
<td valign="top" align="left">Financial resources</td>
<td valign="top" align="left">Liquidity; equity ratio; balance; diversification; contract duration</td>
</tr> <tr>
<td/>
<td valign="top" align="left">Operating area</td>
<td valign="top" align="left">Yard; operating area; farm size</td>
</tr> <tr>
<td/>
<td valign="top" align="left">Range</td>
<td valign="top" align="left">Shares; access; innovation; productivity</td>
</tr></tbody>
</table>
</table-wrap>
</sec>
<sec>
<title>2.2. Literature review</title>
<p>We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to guide the selection of literature (Moher et al., <xref ref-type="bibr" rid="B47">2009</xref>). We sourced literature from Web of Science using the following search term considering all fields: (&#x0201C;shared agriculture&#x0201D; OR &#x0201C;community supported agriculture&#x0201D; OR &#x0201C;community based agriculture&#x0201D;) AND (&#x0201C;sustainable&#x0201D; OR &#x0201C;sustainability&#x0201D;). We restricted our search to the years 1945 to 2021 and updated the search August 15 2022.</p>
<p>We only included articles that (i) assessed sustainability-related outcomes of community-supported agriculture at the farm level, (ii) related to our analytical framework, (iii) agriculture, (iv) included empirical, (v) quantitative findings, and (vi) were written in English. For example, we excluded qualitative findings on the motivation or drivers of farmers and members to establish or join a CSA or investigations of non-members. Due to the limited number of articles within our scope, we did not apply any criteria regarding underlying statistics (e.g., regarding significance or sample size).</p>
<p>Regarding the included articles, we extracted all quantitative results that could be associated to the sub categories of our analytical framework, i.e., that used indicators describing these sub categories. We remained on the sub category level to achieve a higher consistency between our framework and the literature included (e.g., when different indicators were used to describe the same sub category).</p>
<p>For each investigated variable, we extracted the country, number of CSA farms and members included, and the effect (positive, neutral, negative, unclear) if the outcome at the CSA was related to a reference system (conventional farm, average population, farm statistics etc.) or time period (e.g., time before joining a CSA) and could be clearly linked to a sustainability objective (Latruffe et al., <xref ref-type="bibr" rid="B40">2016</xref>). The number of underlying CSA farms was not documented in four studies. Here we estimated the number of investigated CSA farms by dividing the members included by the average number of members included per CSA investigated in all other studies.</p>
<p>Regarding effects, a positive effect would indicate that the CSA farms achieved higher sustainability values for a given variable, for example if the investigated CSA farms produced less greenhouse gas emissions. Regarding diversity of CSA members, we rated an effect as positive, if they represented the average population, e.g., with regard to ethnicity, income or education. If values were similar to a reference system, the differences were insignificant if applicable or if CSA performed better than one reference system but worse than another, we classified the effect as &#x0201C;neutral.&#x0201D; We classified an effect as &#x0201C;unclear,&#x0201D; if it was ambiguous whether an observed difference between the CSA and a reference is desirable from a sustainability perspective, e.g., regarding farm size and age, or if the results were not compared to a reference. Based on this assessment we aggregated the number or proportion of variables showing positive, neutral, negative and unclear effects per dimension or sub-category. We used the statistical software package R 4.1.3 (R Core Team, <xref ref-type="bibr" rid="B61">2022</xref>) run via RStudio (RStudio Team, <xref ref-type="bibr" rid="B66">2022</xref>) for data analysis.</p>
</sec>
</sec>
<sec id="s3">
<title>3. Results</title>
<sec>
<title>3.1. Literature overview</title>
<p>Our literature search yielded 150 records, of which 75 were excluded after we screened the abstract and 36 after we assessed the full article, hence we included 39 articles in the review (<xref ref-type="fig" rid="F1">Figure 1</xref>; <xref ref-type="supplementary-material" rid="SM1">Supplementary Tables 1, 2</xref>). The reviewed studies included more than 2,500 CSA farms (<xref ref-type="table" rid="T2">Table 2</xref>). The large majority of studies were implemented in the United States (26), where over 2,000 CSA farms were investigated. All other studies focused on European countries (nine), except for one study each in Brazil, China, and Japan. More than 85% of the studies were published after 2010, while the first study was published in 2000 (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 2</xref>). Major research areas included agriculture (14), environmental sciences and ecology (11), science and technology&#x02014;other topics (11), and sociology (six; <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 3</xref>).</p>
<fig id="F1" position="float">
<label>Figure 1</label>
<caption><p>PRISMA flow diagram showing the steps involved in the systematic review (adapted from Moher et al., <xref ref-type="bibr" rid="B47">2009</xref>; Begho et al., <xref ref-type="bibr" rid="B3">2022</xref>).</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fsufs-07-1136866-g0001.tif"/>
</fig>
<table-wrap position="float" id="T2">
<label>Table 2</label>
<caption><p>Number of investigated CSA farms and underlying studies per country (<italic>n</italic> = 39).</p></caption> 
<table frame="box" rules="all">
<thead>
<tr style="background-color:&#x00023;919498;color:&#x00023;ffffff">
<th valign="top" align="left"><bold>Country</bold></th>
<th valign="top" align="left"><bold>CSA farms</bold></th>
<th valign="top" align="left"><bold>Studies</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">US</td>
<td valign="top" align="left">2,368</td>
<td valign="top" align="left">26</td>
</tr> <tr>
<td valign="top" align="left">Spain</td>
<td valign="top" align="left">57</td>
<td valign="top" align="left">2</td>
</tr> <tr>
<td valign="top" align="left">Multiple</td>
<td valign="top" align="left">41</td>
<td valign="top" align="left">2</td>
</tr> <tr>
<td valign="top" align="left">Italy</td>
<td valign="top" align="left">20</td>
<td valign="top" align="left">2</td>
</tr> <tr>
<td valign="top" align="left">United Kingdom</td>
<td valign="top" align="left">8</td>
<td valign="top" align="left">2</td>
</tr> <tr>
<td valign="top" align="left">China</td>
<td valign="top" align="left">7</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Romania</td>
<td valign="top" align="left">3</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Turkey</td>
<td valign="top" align="left">3</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Brazil</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Sweden</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">1</td>
</tr></tbody>
</table>
<table-wrap-foot>
<p>One study investigated CSAs in two different countries (US, Hungary) and one in three different countries (Austria, Norway, Japan).</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec>
<title>3.2. Sustainability dimensions</title>
<p>In almost all CSA farms considered, social variables were investigated (<xref ref-type="fig" rid="F2">Figure 2</xref>). Economic and ecological variables were investigated in around 13 and 7% of the farms, respectively. In 169 farms, structural variables were examined including management practices (with or without organic certification), organizational and legal form, which is about 7% of the farms considered.</p>
<fig id="F2" position="float">
<label>Figure 2</label>
<caption><p>Number of CSA farms where ecological, social or economic variables were investigated. Number of underlying studies are indicated on the top of the bars.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fsufs-07-1136866-g0002.tif"/>
</fig>
</sec>
<sec>
<title>3.3. Sustainability effects</title>
<p>Effects were unclear in 46% of the investigated variables, mainly because CSA farms were not compared to any reference, for example to a different farming system or the average population. Regarding ecological variables, CSA farms performed better than the reference systems in 44% of the cases (<xref ref-type="fig" rid="F3">Figure 3</xref>). Negative effects were only identified in 6%. Regarding social variables, effects were more ambiguous. Positive effects were found in 25% of the comparisons, neutral and negative effects in 19 and 20%, respectively (<xref ref-type="fig" rid="F3">Figure 3</xref>). In economy, no comparisons were made for more than 60% of the variables investigated. Negative effects were found in 6%, compared to 17% with positive effects (<xref ref-type="fig" rid="F3">Figure 3</xref>).</p>
<fig id="F3" position="float">
<label>Figure 3</label>
<caption><p>Ratio of investigated variables with positive, neutral, negative or unclear effect in each sustainability dimension comparing CSA and reference systems.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fsufs-07-1136866-g0003.tif"/>
</fig>
<sec>
<title>3.3.1. Ecological sustainability</title>
<p>Ecological variables covered inputs, outputs and biodiversity, while soil variables were never considered (<xref ref-type="table" rid="T3">Table 3</xref>; <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 4</xref>). Regarding inputs, most studies found that CSA farms used less fertilizer, vehicles and machinery, pesticides and energy compared to reference systems. Organic substances were typically used in higher amounts. For example, one CSA farm in Spain used more organic pesticides compared to two conventional farms, yet their energy consumption was around 10 times lower compared to the energy consumption for pesticides used in the conventional farms (P&#x000E9;rez-Neira and Grollmus-Venegas, <xref ref-type="bibr" rid="B58">2018</xref>). In a comprehensive life-cycle assessment, P&#x000E9;rez-Neira and Grollmus-Venegas (<xref ref-type="bibr" rid="B58">2018</xref>) showed that the investigated CSA performed much better for most ecological variables compared to two conventional farms. In particular, non-renewable energy demand was substantially lower both per ha cultivated and per kg of produce. Regarding climate emissions, only positive, neutral or unclear effects were found. For example, the global warming potential of seven CSA farms investigated in China was on average 61 and 39% lower compared to eight conventional and organic farms, respectively (Zhen et al., <xref ref-type="bibr" rid="B83">2020</xref>). According to a study including four CSA farms in the UK, CSA could contribute to a 28% reduction of greenhouse gas emissions from dietary intake (Mills et al., <xref ref-type="bibr" rid="B45">2021</xref>). Agricultural production was reported in three studies, yet not compared to any reference system (<xref ref-type="table" rid="T3">Table 3</xref>). This also applied for crop and livestock diversity. On average, 64 CSA farms investigated in the United States cultivated more than 44 crops (Galt et al., <xref ref-type="bibr" rid="B27">2012</xref>; Paul, <xref ref-type="bibr" rid="B57">2019</xref>).</p>
<table-wrap position="float" id="T3">
<label>Table 3</label>
<caption><p>Number of variables with positive, neutral, negative or unclear effects in each sub category.</p></caption> 
<table frame="box" rules="all">
<thead>
<tr style="background-color:&#x00023;919498;color:&#x00023;ffffff">
<th valign="top" align="left"><bold>Dimension</bold></th>
<th valign="top" align="left"><bold>Category</bold></th>
<th valign="top" align="left"><bold>Sub category</bold></th>
<th valign="top" align="left"><bold>Positive</bold></th>
<th valign="top" align="left"><bold>Neutral</bold></th>
<th valign="top" align="left"><bold>Negative</bold></th>
<th valign="top" align="left"><bold>Unclear</bold></th>
<th valign="top" align="left"><bold>CSA farms</bold></th>
<th valign="top" align="left"><bold>Studies</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Ecology</td>
<td valign="top" align="left">Inputs</td>
<td valign="top" align="left">Water</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">8</td>
<td valign="top" align="left">2</td>
</tr> <tr>
<td valign="top" align="left">Ecology</td>
<td valign="top" align="left">Inputs</td>
<td valign="top" align="left">Vehicles/machinery</td>
<td valign="top" align="left">5</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">11</td>
<td valign="top" align="left">112</td>
<td valign="top" align="left">8</td>
</tr> <tr>
<td valign="top" align="left">Ecology</td>
<td valign="top" align="left">Inputs</td>
<td valign="top" align="left">Electricity</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">7</td>
<td valign="top" align="left">3</td>
</tr> <tr>
<td valign="top" align="left">Ecology</td>
<td valign="top" align="left">Inputs</td>
<td valign="top" align="left">Pesticides</td>
<td valign="top" align="left">5</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">9</td>
<td valign="top" align="left">3</td>
</tr> <tr>
<td valign="top" align="left">Ecology</td>
<td valign="top" align="left">Inputs</td>
<td valign="top" align="left">Fertilizer</td>
<td valign="top" align="left">14</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">3</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">57</td>
<td valign="top" align="left">4</td>
</tr> <tr>
<td valign="top" align="left">Ecology</td>
<td valign="top" align="left">Inputs</td>
<td valign="top" align="left">Energy</td>
<td valign="top" align="left">7</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">57</td>
<td valign="top" align="left">4</td>
</tr> <tr>
<td valign="top" align="left">Ecology</td>
<td valign="top" align="left">Outputs</td>
<td valign="top" align="left">Climate</td>
<td valign="top" align="left">4</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">9</td>
<td valign="top" align="left">17</td>
<td valign="top" align="left">4</td>
</tr> <tr>
<td valign="top" align="left">Ecology</td>
<td valign="top" align="left">Outputs</td>
<td valign="top" align="left">Production</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">3</td>
<td valign="top" align="left">25</td>
<td valign="top" align="left">3</td>
</tr> <tr>
<td valign="top" align="left">Ecology</td>
<td valign="top" align="left">Outputs</td>
<td valign="top" align="left">Environmental impact</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">7</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Ecology</td>
<td valign="top" align="left">Biodiversity</td>
<td valign="top" align="left">Crop diversity</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">64</td>
<td valign="top" align="left">2</td>
</tr> <tr>
<td valign="top" align="left">Ecology</td>
<td valign="top" align="left">Biodiversity</td>
<td valign="top" align="left">Livestock diversity</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">48</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Team</td>
<td valign="top" align="left">Knowledge/learning</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">68</td>
<td valign="top" align="left">5</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Team</td>
<td valign="top" align="left">Diversity/inclusion</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">8</td>
<td valign="top" align="left">83</td>
<td valign="top" align="left">2</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Team</td>
<td valign="top" align="left">Income</td>
<td valign="top" align="left">4</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">2110</td>
<td valign="top" align="left">5</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Team</td>
<td valign="top" align="left">Satisfaction</td>
<td valign="top" align="left">4</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">23</td>
<td valign="top" align="left">3</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Team</td>
<td valign="top" align="left">Full time/part time</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">4</td>
<td valign="top" align="left">59</td>
<td valign="top" align="left">4</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Members</td>
<td valign="top" align="left">Knowledge/learning</td>
<td valign="top" align="left">4</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">8</td>
<td valign="top" align="left">3</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Members</td>
<td valign="top" align="left">Diversity/inclusion</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">16</td>
<td valign="top" align="left">48</td>
<td valign="top" align="left">38</td>
<td valign="top" align="left">166</td>
<td valign="top" align="left">21</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Members</td>
<td valign="top" align="left">Fluctuation</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">10</td>
<td valign="top" align="left">187</td>
<td valign="top" align="left">8</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Members</td>
<td valign="top" align="left">Satisfaction</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">13</td>
<td valign="top" align="left">2</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Members</td>
<td valign="top" align="left">Engagement</td>
<td valign="top" align="left">3</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">6</td>
<td valign="top" align="left">30</td>
<td valign="top" align="left">7</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Members</td>
<td valign="top" align="left">Identification</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">16</td>
<td valign="top" align="left">3</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Members</td>
<td valign="top" align="left">Distance</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">5</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Members</td>
<td valign="top" align="left">Supply</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">3</td>
<td valign="top" align="left">13</td>
<td valign="top" align="left">4</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Members</td>
<td valign="top" align="left">Behavior</td>
<td valign="top" align="left">39</td>
<td valign="top" align="left">21</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">8</td>
<td valign="top" align="left">33</td>
<td valign="top" align="left">11</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Members</td>
<td valign="top" align="left">Well-being/health</td>
<td valign="top" align="left">7</td>
<td valign="top" align="left">6</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">6</td>
<td valign="top" align="left">2</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Farm</td>
<td valign="top" align="left">Transparency</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">19</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Farm</td>
<td valign="top" align="left">Goals/visions/strategies</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">19</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Farm</td>
<td valign="top" align="left">Community building</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">10</td>
<td valign="top" align="left">3</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Surroundings</td>
<td valign="top" align="left">Cooperation</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">56</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Social</td>
<td valign="top" align="left">Surroundings</td>
<td valign="top" align="left">Knowledge</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">4</td>
<td valign="top" align="left">56</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Farm</td>
<td valign="top" align="left">Products</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">43</td>
<td valign="top" align="left">2</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Farm</td>
<td valign="top" align="left">Management</td>
<td valign="top" align="left">3</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">20</td>
<td valign="top" align="left">2</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Farm</td>
<td valign="top" align="left">Age</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">9</td>
<td valign="top" align="left">174</td>
<td valign="top" align="left">9</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Farm</td>
<td valign="top" align="left">Distribution</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">3</td>
<td valign="top" align="left">48</td>
<td valign="top" align="left">3</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Farm</td>
<td valign="top" align="left">Marketing channels</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">46</td>
<td valign="top" align="left">3</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Costs</td>
<td valign="top" align="left">Running costs</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">9</td>
<td valign="top" align="left">3</td>
<td valign="top" align="left">19</td>
<td valign="top" align="left">33</td>
<td valign="top" align="left">5</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Costs</td>
<td valign="top" align="left">Investments</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">7</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Revenues</td>
<td valign="top" align="left">Membership fees</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">9</td>
<td valign="top" align="left">152</td>
<td valign="top" align="left">10</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Revenues</td>
<td valign="top" align="left">Donations</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">19</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Financial resources</td>
<td valign="top" align="left">Liquidity</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">37</td>
<td valign="top" align="left">2</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Financial resources</td>
<td valign="top" align="left">Balance</td>
<td valign="top" align="left">8</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">97</td>
<td valign="top" align="left">7</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Operating area</td>
<td valign="top" align="left">Operating area</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">11</td>
<td valign="top" align="left">166</td>
<td valign="top" align="left">10</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Range</td>
<td valign="top" align="left">Shares</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">14</td>
<td valign="top" align="left">191</td>
<td valign="top" align="left">12</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Range</td>
<td valign="top" align="left">Access</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">16</td>
<td valign="top" align="left">1</td>
</tr> <tr>
<td valign="top" align="left">Economy</td>
<td valign="top" align="left">Range</td>
<td valign="top" align="left">Productivity</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">0</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">26</td>
<td valign="top" align="left">4</td>
</tr></tbody>
</table>
<table-wrap-foot>
<p>Only variables with at least 5 underlying CSA farms are shown.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec>
<title>3.3.2. Social sustainability</title>
<p>Most social variables covered team (i.e., employees) and member aspects (<xref ref-type="table" rid="T3">Table 3</xref>; <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 4</xref>). Variables related to the entire farm or the surroundings were only addressed in a few studies. Regarding CSA farmers, positive effects were found for satisfaction and income. For example, Hunter et al. (<xref ref-type="bibr" rid="B33">2022</xref>) found that happiness and positive future beliefs were higher in CSA farms compared to other alternative food networks. Farmers in Romania stated that they are more satisfied and respected since being a CSA farmer (Moellers and B&#x000EE;rhal&#x00103;, <xref ref-type="bibr" rid="B46">2014</xref>). In the US, the gender pay gap in CSA farms was around one third lower compared to the average (Fremstad and Paul, <xref ref-type="bibr" rid="B25">2020</xref>), less partners needed to work off-farm compared to organic farming (Galt et al., <xref ref-type="bibr" rid="B27">2012</xref>) and earnings were more than 350% higher than on average, yet still not enough to secure living (Paul, <xref ref-type="bibr" rid="B57">2019</xref>). In a CSA in Spain, income was up to around 50 and 75% higher than income from investigated conventional farms (P&#x000E9;rez-Neira and Grollmus-Venegas, <xref ref-type="bibr" rid="B58">2018</xref>).</p>
<p>Investigated CSA members were generally not representing the average population. They were typically white, well-educated and with higher income than the average population (<xref ref-type="table" rid="T3">Table 3</xref>). Moreover, women were typically overrepresented. In contrast, effects on members&#x00027; behavior and well-being and health were largely positive or neutral (<xref ref-type="table" rid="T3">Table 3</xref>). For example, various studies found that CSA members more often prepared food at home, ate less processed food and more vegetables and fruits (MacMillan Uribe et al., <xref ref-type="bibr" rid="B43">2012</xref>; Wilkins et al., <xref ref-type="bibr" rid="B80">2015</xref>; Allen et al., <xref ref-type="bibr" rid="B1">2017</xref>; Rossi et al., <xref ref-type="bibr" rid="B65">2017</xref>; Vassalos et al., <xref ref-type="bibr" rid="B76">2017</xref>). CSA membership was further related to sustainability behaviors such as recycling (MacMillan Uribe et al., <xref ref-type="bibr" rid="B43">2012</xref>; Vassalos et al., <xref ref-type="bibr" rid="B76">2017</xref>). However, no significant positive effect was found regarding the reduction of food waste (Russell and Zepeda, <xref ref-type="bibr" rid="B67">2008</xref>). Among others, health benefits included lower expenditures at the pharmacy and higher self-evaluated health since joining CSA (Allen et al., <xref ref-type="bibr" rid="B1">2017</xref>; Rossi et al., <xref ref-type="bibr" rid="B65">2017</xref>). Mostly positive effects were achieved regarding knowledge transfer and learning, for example, related to cooking expertise and nutritional awareness (Rossi et al., <xref ref-type="bibr" rid="B65">2017</xref>). Regarding engagement, CSA membership was associated with higher volunteerism (Obach and Tobin, <xref ref-type="bibr" rid="B54">2014</xref>; Carolan, <xref ref-type="bibr" rid="B8">2017</xref>) and higher participation in political events (Carolan, <xref ref-type="bibr" rid="B8">2017</xref>).</p>
</sec>
<sec>
<title>3.3.3. Economic sustainability</title>
<p>Economic variables encompassed all categories (farm, costs, revenues, financial resources, operating areas, range), yet actual effects were largely unclear (<xref ref-type="table" rid="T3">Table 3</xref>; <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 4</xref>). Only regarding the financial balance, several studies found a positive effect. Zhen et al. (<xref ref-type="bibr" rid="B83">2020</xref>) showed that average profit per hectare was nearly three times higher in CSA compared to conventional farms. The gross benefit in a CSA in Spain was nearly 17 times higher than the costs (P&#x000E9;rez-Neira and Grollmus-Venegas, <xref ref-type="bibr" rid="B58">2018</xref>). One study in Sweden indicated that farm management is more efficient compared to other types of alternative food networks (Hunter et al., <xref ref-type="bibr" rid="B33">2022</xref>). In contrast, running costs were found to be higher regarding delivery and labor (Zhen et al., <xref ref-type="bibr" rid="B83">2020</xref>), as well as marketing (Hardesty and Leff, <xref ref-type="bibr" rid="B32">2010</xref>). Regarding economic productivity, the number of positive and negative effects was equal. Studies in Romania (Moellers and B&#x000EE;rhal&#x00103;, <xref ref-type="bibr" rid="B46">2014</xref>) and Spain (P&#x000E9;rez-Neira and Grollmus-Venegas, <xref ref-type="bibr" rid="B58">2018</xref>) found that more labor is needed compared to other farms. However, profit and sales per labor hour were substantially higher compared to other direct marketing approaches in 21 CSA farms in the United States (Jablonski et al., <xref ref-type="bibr" rid="B37">2019</xref>).</p>
</sec>
</sec>
</sec>
<sec id="s4">
<title>4. Discussion</title>
<p>We found that &#x0003C; 30% of the quantitative studies included investigated ecological aspects and in around 40% of these studies relative effects compared to other farming systems were either unclear or not investigated, thus a reliable evaluation of the ecologic sustainability of CSA is not yet possible (Christensen et al., <xref ref-type="bibr" rid="B12">2018</xref>; Wellner, <xref ref-type="bibr" rid="B79">2018</xref>). Nevertheless, existing studies show a clear positive trend. In particular, regarding resource use efficiency and greenhouse gas emissions, investigated CSAs mostly performed better than conventional systems. Research on crop yields, crop and livestock diversity, and soil health remains incomplete or is not yet performed. Environmental effects have been investigated widely and more often than social and economic aspects for agri-food systems generally, but also with regard to organic agriculture and local food systems (Mundler and Laughrea, <xref ref-type="bibr" rid="B48">2016</xref>; El Bilali et al., <xref ref-type="bibr" rid="B22">2021</xref>). To which extent these findings are transferrable to the CSA context needs to be evaluated. With regard to slowly changing processes in complex ecosystems such as soil, changes in soil functions as response to altered management practices might be only detectable after decades (Nortcliff, <xref ref-type="bibr" rid="B52">2002</xref>; Bai et al., <xref ref-type="bibr" rid="B2">2018</xref>; B&#x000FC;nemann et al., <xref ref-type="bibr" rid="B6">2018</xref>). In this case, the use of proxies and systemic modeling approaches combined with field data might be essential to evaluate altered management practices long-term sustainability (B&#x000FC;nemann et al., <xref ref-type="bibr" rid="B6">2018</xref>; Rabot et al., <xref ref-type="bibr" rid="B62">2018</xref>; Vogel et al., <xref ref-type="bibr" rid="B77">2018</xref>).</p>
<p>Nearly 90% of the quantitative studies included addressed social sustainability aspects. Given that CSA is a social innovation centered around a community of producers and consumers, their relationship, solidarity, cooperation, trust, engagement and participation, this is hardly surprising (Jarosz, <xref ref-type="bibr" rid="B38">2000</xref>). Moreover, in contrast to many ecological variables that require continuous and long-term effort for data collection, a wide range of social aspects can be captured with one-time (online) surveys or interviews. However, the majority of studies within the social dimension assessed socio-economic variables of CSA members including gender, age, income, ethnicity and education. Accordingly, CSA members do not represent the average population, for example with regard to low income households (Galt et al., <xref ref-type="bibr" rid="B26">2017</xref>). Besides various internal mechanisms to offset costs, e.g., membership fees related to income or anonymous bidding rounds, externally subsidized memberships could improve access to CSA and related health benefits (Izumi et al., <xref ref-type="bibr" rid="B36">2018</xref>). Apart from the limited diversity of CSA members, most studies found positive social effects, particularly with regard to health and sustainability behavior, for example, including dietary changes, which can substantially reduce environmental impacts of food systems (Willett et al., <xref ref-type="bibr" rid="B81">2019</xref>).</p>
<p>More than half of the studies included covered economic aspects. However, knowledge on actual economic performance compared to other systems is still very limited. Nevertheless, first studies indicate high economic viability of CSA farms. If this pattern is generalizable, CSA could provide a suitable alternative to farm growth or termination in the light of economic competition in the agricultural sector (Paech et al., <xref ref-type="bibr" rid="B56">2019</xref>). In this context, diffusion of CSA is another emerging topic in the CSA literature screened here. Amongst others, diffusion relies on institutional support, access to affordable land and sufficient demand (Doernberg et al., <xref ref-type="bibr" rid="B20">2016</xref>; Pisarn et al., <xref ref-type="bibr" rid="B60">2020</xref>; Zoll et al., <xref ref-type="bibr" rid="B84">2021</xref>). For example, Diekmann and Theuvsen (<xref ref-type="bibr" rid="B18">2019a</xref>) found that 27% of non-participants would be interested in CSA membership in Germany, i.e., much more than the proportion of the German population currently organized in a CSA, which is &#x0003C; 1% (own estimation based on Netzwerk Solidarische Landwirtschaft e.V., <xref ref-type="bibr" rid="B49">2022a</xref>). However, members need to be hold, e.g., by increasing crop diversity and cooperation among different CSA farms (Galt et al., <xref ref-type="bibr" rid="B28">2019</xref>). In this context, understanding and fostering the values and preferences of CSA members is crucial to establish long term relationships (Chen, <xref ref-type="bibr" rid="B10">2013a</xref>,<xref ref-type="bibr" rid="B11">b</xref>; Diekmann and Theuvsen, <xref ref-type="bibr" rid="B19">2019b</xref>). Reducing fluctuation is particularly relevant in the context of current inflation rates, which will also provide insights on the economic resilience of CSA.</p>
<p>Besides the observed bias in current CSA literature toward social variables, we also observed a clear geographical imbalance. While most studies analyzed in this paper focused on the US, the country with the largest number of CSA farms, no study investigated French CSA farms, where the vast majority of European CSA farms are located (Samoggia et al., <xref ref-type="bibr" rid="B68">2019</xref>; Egartner et al., <xref ref-type="bibr" rid="B21">2020</xref>), yet this might also be related to our search strategy (see below). Moreover, besides Brazil, China and Turkey no countries from the Global South or emerging economies were considered. In the light of contrasting socio-economic conditions, knowledge from different types of countries is crucial. To obtain an overview of the current status of CSA, the international CSA network Urgenci (<ext-link ext-link-type="uri" xlink:href="https://www.urgenci.net">urgenci.net</ext-link>) is launching a global census in 2023, which will provide an important baseline for future research. Many of the studies considered only cover a limited number of CSA farms, focus on few sustainability aspects and often remain descriptive.</p>
<p>While our study offers an important overview of sustainability-related effects of CSA, it faces two major limitations. First, we only included English articles indexed in Web of Science, which leads to a bias toward articles published in US journals and particularly neglects research from the Global South (Gibbs, <xref ref-type="bibr" rid="B29">1995</xref>; Lund, <xref ref-type="bibr" rid="B42">2022</xref>). Given that CSA research is often geographically limited and closely related to practice, many studies are likely to be published in other languages. This could also explain, why despite the large number of CSAs, no study from France was included. In Germany (and probably also elsewhere), the number of theses on CSA is rapidly increasing. While most of them are in German and not published in scientific journals, many of them offer valuable insights that should be considered, if certain quality criteria are fulfilled. While CSA is the most common term in international literature, including country-specific terms, for example AMAP (Association pour le Maintien d&#x00027;une Agriculture Paysanne) in France and teikei in Japan could increase the literature base and the geographic scope. Second, we only included quantitative findings related to our framework and without applying any criteria regarding the statistics of the selected paper. In particular regarding social aspects, qualitative studies offer additional valuable insights, for example related to underlying values, identity and social practices (Diekmann and Theuvsen, <xref ref-type="bibr" rid="B19">2019b</xref>; Neulinger et al., <xref ref-type="bibr" rid="B51">2020</xref>; Zoll et al., <xref ref-type="bibr" rid="B84">2021</xref>). Consequently, our literature review is only a first step and more literature need to be included to draw broader conclusions on existing findings of the sustainability of CSA.</p>
<p>Based on our review we suggest that more studies investigating actual sustainability effects of CSA farms following standardized protocols are needed, in particular including comparisons across different farming systems and with regard to their ecological effects. As empirical work in this context might require high efforts, proxies and findings related to organic farming could be considered. More research is essential for CSA stabilization, development and scaling, as well as the development of policies to support CSA. This also includes approaches to reduce the fluctuation of CSA members, to increase their diversity and to understand and utilize future consumer potentials. Moreover, existing knowledge should be better integrated and publicly accessible. The German CSA network for example, collects bibliographic information on existing theses. Ideally, the central findings of such research would be integrated into one structured and international database to simplify access and knowledge transfer. Finally, more funding is needed to support these efforts. In the light of the high sustainability promises of CSA shown so far and the urgent need to transform food systems toward sustainability, such funding would be well placed to support this goal. Therefore, obstacles for CSA to gain access to existing programs and funds (e.g. common agricultural policy in the EU) could be reduced and new programs could be established.</p>
</sec>
<sec sec-type="data-availability" id="s5">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s9">Supplementary material</xref>, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec sec-type="author-contributions" id="s6">
<title>Author contributions</title>
<p>JR identified the relevant studies for the review. LE performed the analyses and wrote the paper in collaboration with JR and JP. All authors designed the study and revised multiple versions of the manuscript.</p>
</sec>
</body>
<back>
<sec sec-type="funding-information" id="s7">
<title>Funding</title>
<p>This research is part of the project InnoLand-Sachsen (Innovative Modelle f&#x000FC;r eine nachhaltige und regionale Wertsch&#x000F6;pfung: Synergien und Potenziale der Solidarischen Landwirtschaft in Sachsen. This measure is co-financed with tax funds on the basis of the budget passed by the Saxon State Parliament (FKZ:100595134).</p>
</sec>
<ack><p>We thank Sabrina Gerdes and Marius Rommel, as well as the three CSA farms involved for their contribution during the development of the analytical framework.</p>
</ack>
<sec sec-type="COI-statement" id="conf1">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="s8">
<title>Publisher&#x00027;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec sec-type="supplementary-material" id="s9">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fsufs.2023.1136866/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fsufs.2023.1136866/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Data_Sheet_1.pdf" id="SM1" mimetype="application/pdf" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Data_Sheet_2.xlsx" id="SM2" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
<fn-group>
<fn id="fn0001"><p><sup>1</sup>Voge, J., Newiger-Dous, T., Ehrlich, E., Ermann, U., Ernst, D., Haase, D., et al. (in review). Food for the plate and not for the waste - assessing yields, food loss and waste in community-supported agriculture in the region of Leipzig, Germany. <italic>Int. J. Agric. Sustain</italic>.</p></fn>
</fn-group>
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