# Networking supports crop diversity decisions: insights from the Gaillac wine-growing region (France)

Antoine Doncieux, Antoine Rignault, Delphine Renard, Sophie Caillon

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## To cite this version:

Antoine Doncieux, Antoine Rignault, Delphine Renard, Sophie Caillon. Networking supports crop diversity decisions: insights from the Gaillac wine-growing region (France). Ecology and Society, 2025, 30 (3), pp.20. 10.5751/ES-16152-300320. http://05217754

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Research

# Networking supports crop diversity decisions: insights from the Gaillac wine-growing region (France)

Antoine Doncieux<fnref n="1" /> ID, Antoine Rignault <fnref n="1" />,² ID, Delphine Renard<fnref n="1" /> ID and Sophie Caillon<fnref n="1" /> ID

**ABSTRACT.** The diversity of crop species and varieties is a key lever for promoting sustainable and resilient farming systems. Adopting new species and varieties requires knowledge tailored to specific crops. Farmers rely on diverse sources of knowledge to make cropping decisions, which depend on both the characteristics of the crops and the farmers themselves. Understanding the various pathways of knowledge transmission provides critical insights into the dynamics that either facilitate or constrain the local diffusion of crop diversity. This study examines how farmers engage with different social networks when selecting the three key components of grapevine cultivation: variety, clone, and rootstock. We combined social network analysis with ethnographic data to compare the composition (i.e., the sources involved), structure (i.e., the interactions between sources), and content of knowledge regarding grapevine selection in the Gaillac wine-growing region (France). Our results show that knowledge is predominantly obtained through social interactions with nearby farmers rather than through independent consultation of written sources, such as books and websites. Across all three networks, the most frequently cited knowledge providers were local experts with extensive experience managing diverse grapevine varieties. We found that grapevine varieties hold greater biocultural value for farmers than clones and rootstocks, shaping knowledge circulation networks. While varieties are central to farmers' concerns, clones and rootstocks are perceived as adjustment variables used to optimize yield and adapt to environmental conditions. As a result, farmer-to-farmer knowledge exchange primarily revolves around grapevine varieties, whereas knowledge about clones and rootstocks is largely disseminated by vine nurseries. Our findings highlight the role of social relationships in sustaining agronomic knowledge about numerous rare and uncultivated varieties within the locality, which may bolster farmers' capacity to adapt to rapid social-ecological changes.

**Key Words:** agrobiodiversity; cépage; clone; crop choices; knowledge exchange; rootstock; social network analysis; viticulture

## INTRODUCTION

A key pathway for agricultural systems to adapt and transform in the face of social-ecological changes is through the modification and diversification of on-farm crop diversity (Lin 2011, Altieri and Nicholls 2017). The diversity of varieties and species has the potential to mitigate agricultural losses from climate change (Rising and Devineni 2020), while reducing water use, fertilizer, and pesticide inputs (Kremen and Miles 2012). Greater crop diversity also buffers temporal yield and income instability, especially during climatic shocks (Renard and Tilman 2019). Understanding farmers' abilities to shift and diversify their crops is instrumental in building the resilience of agricultural systems.

Substituting or embracing additional species and varieties requires knowledge that is tailored to the type of crops being grown (Périnelle et al. 2024). Each crop requires specific knowledge to address the diverse and interconnected motivations that farmers consider in their cropping decisions, including socio-cultural, ecological, economic, and agronomic factors (Demongeot et al. 2022). Without available sources of knowledge related to the different motivations ascribed to crop choices, farmers are likely to be "locked in" to their current crops (Oliver et al. 2018, Meynard et al. 2018). Moreover, previous studies have shown that knowledge acquired by farmers before and during the acquisition of crops is key to their long-term cultivation (Toffolini et al. 2017, Périnelle et al. 2024).

In the case of woody perennial species, the lifespan of some perennial crops can be up to 100 years. Farmers must make the "right" decision by considering the long-term evolution of

economic and environmental factors. They must develop complex strategies to obtain key information. Moreover, most of these perennials are clonally propagated (e.g., apple, plum, cherry, and grapevine). Farmers need knowledge not only about the fruit-bearing variety, but also about its intra-varietal variations (clone) and the genetically distinct root system onto which it is grafted (rootstock, Fig. 1).

An extensive body of literature shows that farmers draw on a diverse array of knowledge sources to guide their decision-making, including a wide range of stakeholders (e.g., other farmers, extension services, and private actors) as well as written sources, such as textbooks, websites, blogs, and specialized portals (Coomes et al. 2015, Sáenz et al. 2024). Previous studies have shown that different types of knowledge sources may disseminate different worldviews, beliefs, and forms of knowledge, including "tacit" knowledge derived from local practices and "codified" knowledge associated with formal education and academia (Súmane et al. 2018). Recent studies have demonstrated that knowledge circulation networks are not one-size-fits-all; farmers engage in different social networks to access different types of knowledge (Cofré-Bravo et al. 2019; Sutherland et al. 2017). In particular, Ayoub (2023) showed that farmers in France combined different knowledge sources (e.g., technical advisors, press and media, suppliers) when selecting different types of crops such as cereals, potatoes, or crops for industrial purposes (e.g., sunflowers, flax). Crop characteristics (e.g., biocultural value, timing of introduction, sexual or clonal reproduction) and farmer characteristics (e.g., gender, social status, crop richness) also influence the way seed and knowledge circulate (Pautasso et al. 2013, Porcuna-Ferrer et al. 2023, Mariel et al. 2024). For example,

<footnote n="1">¹CEFE, CNRS, Université de Montpellier, EPHE, IRD, Montpellier, France, ²Département d'anthropologie, Université de Montréal, Montréal, Québec, Canada</footnote>
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** A schematic representation of two vine stocks of the Syrah variety, each with a different clone (No. 470 and No. 1354) and rootstock (Sélection Oppenheim 4 and 3309 Couderc).</figcaption></figure>

Thomas and Caillon (2016) found in Vanuatu that seed circulation of the most bioculturally (i.e., based on biological, cultural, and use characteristics) valued plants (i.e., starch species compared to snack and side dish species) is governed by the social status of farmers (i.e., respect and migration history). Unraveling the various pathways of knowledge transmission provides critical insights into the dynamics that can either facilitate or constraint the local diffusion of crop diversity. Equally important is the diffusion of crops alongside accurate and context-specific knowledge, ensuring their long-term cultivation and optimal use while drawing on the expertise of those with prior experience in cultivating them.

Recent theoretical and empirical studies have shown that the composition (i.e., the sources involved) and the structure (i.e., the ways these sources interact) of social networks are one of the patterns behind the capacity of social-ecological systems to adapt and transform in the face of perturbations (Barnes et al. 2017, Labeyrie et al. 2021, Barrera and Ibarra 2024). For instance, heterogeneity in knowledge sources fosters adaptive capacity by integrating diverse expertise and know-how that allow responses in different ways to shocks and perturbations (Bodin et al. 2006, Bruce et al. 2021). Moreover, redundancy among the knowledge sources is equally critical, as it ensures functional continuity by allowing other actors to assume the roles of those lost, thereby buffering the system against disruptions and preserving its stability over time (Janssen et al. 2006, Sterk et al. 2017, Bruce et al. 2021). These relationships have yet to be explored within the specific context of knowledge circulation networks associated with crop choice.

Viticulture is an interesting case study for investigating knowledge circulation networks associated with crop choices. The diversity of varieties, clones, and rootstocks represents a promising lever for promoting sustainable viticulture, including reducing pesticide use (Guimier et al. 2019, Zachmann et al. 2024) and

mitigating the impacts of climate change (Morales-Castilla et al. 2020, van Leeuwen et al. 2024). Since the decimation of European vineyards due to the accidental introduction of the American aphid pest (Phylloxera) in the 19th century, European *Vitis vinifera* varieties have been grafted onto naturally resistant American Vitis species (Ollat et al. 2024). This combination helps maintain fruit quality while ensuring Phylloxera resistance. In addition, rootstocks also contribute to the control of other soil-borne pests, such as nematodes, and serve as an adaptation mechanism to various abiotic constraints, including drought, salinity, limestone, and mineral nutrition problems (Ollat et al. 2019). The rootstocks also impact overall plant development, including yield and phenology (van Leeuwen et al. 2019). Clonal selection began in France in the 1950s to provide genetically homogeneous and virus-free varieties (Lacombe 2012). Genetic inter-variability among clones exists in traits such as water use efficiency, disease resistance, and yield (Tortosa et al. 2019, Pagliarani et al. 2019).

In European viticulture, commercial legislation and regulation impose that farmers access to grapevine material exclusively to grapevine nurseries (Borsellino et al. 2012). Previous studies have suggested that seed and knowledge networks overlap (Calvet-Mir et al. 2012, Reyes-García et al. 2013, Coomes et al. 2015). According to this view, knowledge about grapevine varieties, clones, and rootstocks should mostly emerge from grapevine nurseries. However, farmers to farmers relationships persist in the face of commercialization and legislation (Coomes et al. 2015), and farmers often reach to peers when making decisions (Isaac et al. 2007, Wood et al. 2014, Šůmane et al. 2018).

This study aims to investigate the sources of knowledge used by farmers when selecting grapevine varieties, clones, and rootstocks in Gaillac, one of the most varietally diverse wine regions in France (Doncieux et al. 2022). Data were collected and analyzed using social network analysis (SNA) combined with an ethnographic approach. SNA provided a holistic approach for examining how individuals select knowledge sources, including people, books, the internet, and the like (Haselmair et al. 2014). Ethnographic data were used to design the sampling strategy, and gain a deeper understanding of the relationships and processes within knowledge circulation networks. We compared the composition, structure, and content of knowledge circulation networks regarding the choice of varieties, clones, and rootstocks.

## METHODS

### Study area

Fieldwork was conducted in the wine-growing region of Gaillac (43.9° N, 1.89° E), located the southwestern part of France. The area is a mix of plains and hillsides with a slight altitudinal gradient (110–320 m). The pedoclimatic context includes limestone plateaus, clay-limestone soils, silty-sandy soils, and gravelly soils (Delaunois and Revel 2016).

The area has been occupied by wine-growing activities at least since the 1st century AD (Balmelle et al. 2001) and 6540 ha were cultivated with vines in 2020 (Doncieux et al. 2022) The diversity of grapevine varieties in the locality is highly dynamic, with 93% of grapevine varieties having changed and varietal richness decreasing by of 71%, over the 1960–2020 period in response to anthropogenic (changes in market, policies, land use, agricultural
technologies, and demography) and environmental drivers (Doncieux et al. 2022). Despite these historical dynamics, the Gaillac region is one of the most diverse in France today, with at least 62 varieties grown in 2020. Farmers cultivate 7.9 ± 4.1 varieties on average.

In 2020, the vineyards were managed by 352 farmers, a number that has declined by 22-fold since 1960 (Doncieux et al. 2022). About half of the farms are run by wine makers who grow grapes and sell wines through their own marketing networks. The other half are grape growers who only produce grapes and deliver their harvest to one of the two cooperative cellars, of which they are members. In 2020, 83% of the wine-growing area was under conventional agriculture (i.e., involving the use of synthetic chemicals). However, organic and biodynamic farming have been booming in the vineyard, increasing from 30 hectares in 1995 to 1404 hectares in 2019 (Pouzenc and Vincq 2013, Chambre d'Agriculture 2020). Finally, since the 1990s, the Gaillac vineyard has also been home to a small number of neo-farmers (~18 individuals)—producers who have taken over a vineyard without inheriting it from their parents.

In the Gaillac region, both public and private agricultural organizations play a key role in the wine-growing system. First, a local section of the *Institut Français de la Vigne et du Vin* (IFV) was established in 2003, initiating multiple applied research programs on wine-growing (e.g., trials of varieties, clones, and rootstocks) and winemaking (e.g. understanding wine aromas) activities. Overall, 15 technicians and engineers manage micro-vinification cellars (producing 400 vintages per year), representing 15 ha of vines dedicated to experimentation, along with a genetic conservatory of over 425 varieties, several clones, and 22 rootstocks. Second, there is a local section of the *Chambre d'agriculture* (CA), a professional public institute that today constitutes one of the main pillars of agro-environmental and territorial development (Villemaine 2013). Among the 50 technicians and engineers devoted to agricultural activities in the region (e.g., cereal crops, livestock), two advisors focus on wine-growing activities and develop paid individual or collective training programs. One advisor oversees a “Sustainable Viticulture Group” called the DEPHY network, created by the French Ministry of Agriculture in 2010 as a new policy instrument to support farmers in redesigning their cropping systems to consume fewer chemical products. To date, it involves 12 growers and about 500 ha of vines, in partnership with the IFV and the two cooperative cellars. Lastly, two vine nurseries specialize in graft production, multiplication, and distribution. Established in the early 1900s, the first nursery offers 60 varieties and 15 rootstocks, while the second offers 36 varieties and 11 rootstocks.

For comparison, 334 grape varieties can be cultivated in France, yet just five account for slightly more than half (53%) of the total area (FranceAgrimer 2022). The concentration of wine-growing systems on a handful of grape varieties is primarily driven by a marketing strategy favoring single-varietal wines (Garcia-Parpet 2007), as well as national regulations and geographical indications that limit the flexibility of farmers in choosing which varietals to grow (Wolkovich et al. 2018). Many breeding programs have led to the creation of hundreds of different clones, including up to 48 clones for the single Pinot Noir variety (Boursiquot 2020). In France, 31 rootstocks are commercially available, and six (SO4,

110R, 3309 Couderc, Fercal, Gravesac, and 110 Richter) account for 75% of plantings (FranceAgrimer 2023). In 2024, the number of grapevine nurseries in France was estimated at 407 (FranceAgrimer 2024), with one of the largest able to provide up to 1200 clones of over 300 varieties grafted onto 16 distinct rootstocks (https://www.pepinieres-mercier.com).

## Data collection

We used an ethnographic approach to document farmers' knowledge circulation networks regarding varieties, clones, and rootstocks. Fieldwork was conducted over nine months, from January 2020 to August 2022, with interruptions due to COVID-19. This included participant observation and surveys with farmers and related professionals across the region. The first author spent nine months in the Gaillac region, the second spent three months, and the last has worked there for about five years. The long field stays involved observing social interactions and actively participating in tasks such as pruning and harvesting with farmers. Several back-and-forth movements between ethnographic accounts and network analysis were instrumental in forming hypotheses and contextualizing quantitative findings, especially by clarifying social exchange processes (Salpeteur et al. 2017). For instance, during our explanatory fieldwork, we observed that farmers often referred to their peers, researchers, technicians of the cooperative cellars, private oenologists, and consumers as having influenced their choice of grape variety, particularly through discussions about the advantages and disadvantages of the variety and wine quality.

Between November 2021 and January 2022, we conducted surveys to collect knowledge circulation data. We used convenience sampling to capture the diversity of knowledge sourcing from a range of farmers who varied in their agricultural practices (conventional and organic production), farming activities (wine makers and grape growers), and social backgrounds (whether they inherited their land or not). The original list of names included research participants from previous studies in the area to leverage established trust. Additionally, the two cooperative cellars were asked to provide lists of their members who might be interested in participating. Our sample includes 26 wine makers and 24 grape growers (13 from Vinovalie and 11 from La Bastide). Among the wine makers, a substantial proportion adhered to organic farming practices, with a significant majority of neo-farmers adopting this approach (Table 1). In contrast, the majority of grape growers employed conventional farming methods, with a smaller fraction of neo-farmers engaging in organic practices. Compared to the overall farmer population in the Gaillac region, our sample represents approximately 16% of wine makers, 12% of grape growers, 41% of farmers engaged in organic production, and 89% of neo-farmers. The interviewed farmers were predominantly men (92%) due to the male gender bias in the farmer population. On average (± SD), farmers were 54 ± 10.7 years old, and had spent 25.4 ± 12.1 years as farm heads. Before taking over the farm, most farmers (90%) had completed studies in viticulture or agriculture. The average farm area was 22.1 ± 17.2 ha.

The surveys consisted of both quantitative and qualitative questions, organized into two sections. The first section focused on the history of the family and farm, as well as social information (e.g., date and place of birth, seniority on the farm, professional background). In the second section, we asked farmers to list the
<table><caption>**Table 1.** Research design and sample size.</caption><thead><tr><th>Total number of farmers interviewed</th><th></th><th>Organic production (% of farmers)</th></tr></thead><tbody><tr><td>Wine makers</td><td>26</td><td>17 (65%)</td></tr><tr><td>Nb. of neo-farmers (%)</td><td>11 (42%)</td><td>8 (73%)</td></tr><tr><td>Grape growers</td><td>24</td><td>5 (21%)</td></tr><tr><td>Nb. of neo-farmers (%)</td><td>5 (21%)</td><td>2 (40%)</td></tr></tbody></table>

varieties, clones, and rootstocks they were growing in 2021. This section also aimed to gather a list of knowledge sources that the respondent typically used (i.e., egocentric networks) for each item: varieties, clones, and rootstocks. Separate questions were asked for each type of agrobiodiversity: "Can you provide the names of all the sources of knowledge you use when selecting a new variety?"; "Can you do the same for a new clone?"; and "And for a new rootstock?". Following previous studies (e.g., Thomas and Caillon 2016; Wencélius et al. 2016), we only asked about knowledge received, and not knowledge given, due to recall difficulties. For each knowledge circulation event, we also documented: i) the type of knowledge giver (e.g., farmers, agricultural advisors, books, websites), ii) the content of the knowledge event, and iii) the working location, which corresponded to the commune of the individual knowledge giver (i.e., the smallest administrative division in France). No limit was imposed on respondents regarding the number, date, geographical location, or type of sources listed. Qualitative data were collected to explore why they relied on the quoted sources.

Additionally, we conducted semi-structured interviews with four non-farming actors who emerged from the interviews as the most cited sources in the networks to gain a deeper understanding of knowledge sharing. They were asked qualitative questions about their professional background and their role in knowledge exchange. This sample includes one agronomic researcher from the IFV, one technician from each of the two cooperative cellars, and a vine nursery director.

Before each interview, we obtained free, prior, and informed consent by writing. All the interviews were audio recorded and transcribed. Our research project complies with the European General Data Protection Regulation (RGPD) on the protection of individual information under the reference 2-21088.

## Data analysis

We used a mixed quantitative and qualitative approach to analyze our data. Results from the knowledge circulation data are interpreted and discussed in light of qualitative data we gathered throughout our fieldwork in the region. Statistics were computed with the R software version 4.2.3 (R Core Team 2023).

### Classifying knowledge sources and knowledge contents

We used a classification approach to code sources into categories (social vs. written sources) and types of sources (Table 2). Based on previous research conducted in the Gaillac region on farmers' motivations for grape choices (Doncieux et al. 2025), we also classified the types of varieties and the contents of knowledge. The varieties listed during interviews were grouped into either dominant (9) or rare (26) varieties. Dominant varieties are those present in the fields of most farms (> 40%), while rare varieties

are grown by few farms (< 40%). For instance, Fer and Duras are grown by 81% of farmers, while Semillon is grown by only 2% of farmers. The contents of knowledge were grouped into four domains: agronomic knowledge (e.g., climatic requirements, yield), wine-related knowledge (e.g., organoleptic properties, winemaking practices), economic value, and patrimonial value. For each domain, we classified the knowledge content as "unspecified" when informants recalled the knowledge source but could not remember the specific details they inquired about.

### Social network analysis

We used social network analysis (SNA) to visualize and analyze the knowledge sources used by farmers when selecting varieties, clones, and rootstocks. SNA originated in the 1930s within anthropology and quantitative sociology as a method for studying social relationships in human societies (Borgatti et al. 2009). SNA has been used across a variety of research lines, including the management of natural resources (e.g., Bodin 2017), the circulation of crops (e.g., Labeyrie et al. 2016), and the transmission of local ecological knowledge (e.g., Salpeteur et al. 2016). In particular, SNA has yielded powerful insights for theorizing and empirically investigating how and why social interactions facilitate adaptive and transformative change in agricultural systems through collective action, social learning, exchanges of planting materials, and knowledge (Pautasso et al. 2013, Salpeteur et al. 2017, Labeyrie et al. 2024).

Network formalism conceptualizes a system as a set of nodes (also called vertices) and the relationships between them (i.e., ties or edges). In our study, each node can be either a knowledge receiver (ego in network vocabulary) or a provider (alter). The alters can be either social or written sources as described in Table 2. For network visualization, we considered three types of nodes: farmers, individuals working for agricultural organizations, and written sources. The ties correspond to an event of knowledge circulation from a provider (alter) who provides information to a receiver (ego). The alters may or may not have been interviewed. The ties between nodes were directed and unweighted, meaning that duplicate ties between a knowledge provider and a receiver were removed. The multiple ties were retained if the exchange partners shared different types of knowledge content (e.g., agronomic knowledge and winemaking knowledge) or different varieties, clones, and rootstocks. In this study, the citation of multiple individuals belonging to the same institution (e.g., several individuals from IFV) was not grouped in a single node because they may share varying points of view. We did not include ties between non-farming actors from additional semi-structured interviews in the SNA.

The knowledge circulation ties were represented in an aggregated network of knowledge encompassing knowledge inquired for varieties, clones, and rootstocks. Next, the ties were separated into three groups based on the type of agrobiodiversity involved in the aggregated knowledge circulation network (variety, clone, and rootstock), which allowed us to create three subnetworks. The networks were represented, and network statistics were calculated using the R package *igraph*, version 2.0.3 (Csárdi and Nepusz 2006).

For each network, we computed three network-level measures and three node-level centrality measures (Borgatti et al. 2018; Table 3). Because we used an egocentric network approach, common
<table><caption>**Table 2.** Description of the categories of actors found in the three sub-networks of varieties, clones, and rootstocks.</caption><thead><tr><th>Category of sources</th><th>Type of sources</th><th>Definition</th><th>Code</th></tr></thead><tbody><tr><td rowspan="10">Social sources</td><td rowspan="2">Farmers-based</td><td>Individual farmers</td><td>Represents knowledge circulation events between the interviewed farmer and other individuals (e.g., speaking by phone, face-to-face conversation). This implies a dialogue between two or several individuals.</td></tr><tr><td>Grape growers</td><td>A farmer is an individual who cultivates grapevines to sustain their livelihood. Grape growers typically refer to individuals who cultivate grapevines primarily for the purpose of supplying grapes to external entities, such as wineries or cooperative cellars.</td></tr><tr><td rowspan="2">Network of farmers</td><td>Wine makers</td><td>Wine makers (vigneron indépendants in French) are farmers who cultivate grapevine and produce wine under their own label.</td></tr><tr><td>Agricultural organizations</td><td>A formal viticulture group of farmers (i.e., the Dephy network). An individual engaged in the agricultural sector, supported by a private or public institution, who does not cultivate grapevines for his livelihood. It includes self-employed agronomist consultants, advisors, scientists, and commercials employed by companies.</td></tr><tr><td rowspan="2">Chambre d'Agriculture (CA)</td><td>A public institution tasked with supporting farmers in their establishment and agricultural activities, focusing on economic, administrative and agronomic aspects.</td></tr><tr><td>Private research and development organization focused on the wine industry, covering plant breeding, viticulture, winemaking, and marketing.</td></tr><tr><td>Cooperative cellars</td><td>Organizations where multiple grape growers combine their harvests to collectively produce wine. They employ viticultural advisors to oversee vineyard management and coordinate the harvest schedule.</td></tr><tr><td>Vine nurseries</td><td>Vine nurseries are specialized facilities that multiply and propagate clones and rootstocks for sale.</td></tr><tr><td>Agricultural suppliers</td><td>Organizations specialized in the sale of fertilizers, crop protection products, and agricultural equipment.</td></tr><tr><td>Consulting companies</td><td>Professional service firms that offer expertise for a fee in various aspects of wine production and grape growing activities (e.g., soil tests, varietal choices).</td></tr><tr><td rowspan="2">Written sources</td><td rowspan="2">Longstanding books</td><td>These sources include both longstanding books and digital (websites, online articles) written supports that contain knowledge associated with crops. These documents may originate from farmers, a public or private organization. Individuals can access written sources independently of social relationships.</td></tr><tr><td>It includes paper-based documents that are not available online and are published for over 20 years.</td></tr><tr><td>Digital contents</td><td>Digital contents</td><td>Electronic materials such as technical reports (e.g., IFV, CA, plantgrape), e-books and monthly viticultural specialized magazine (e.g., Vitisphère, Le Rouge et le Blanc, La Grappe d'Autant) accessed online.</td></tr></tbody></table>

statistics at the global level such as density, reciprocity and community's detection are not applicable. We used the degree centrality measures as a proxy of actor centrality because the implications of unrecorded ties cannot be assessed. Since we focused solely on knowledge received, in-degree was calculated only for the knowledge receivers (i.e., the egos), while out-degree was measured only for the knowledge providers (i.e., the alters).

For each network, we calculated the proportion of ties based on the category of sources, type of sources, knowledge circulation content, and the geographical locations of knowledge sources involving social relationships, excluding written sources. For geographical information, two classes were created based on the distances between the working locations of providers and recipients, calculated using the geosphere package version 2.0. We defined local exchanges (< 40 km) and long-distance exchanges (> 80 km) based on the distribution of distances, as no data points were observed in the 40–80 km range. The geographical networks of knowledge were mapped. We conducted independence tests

(Pearson's chi-square test, and when not possible, Fisher's exact test) between the type of knowledge and knowledge circulation characteristics (i.e., sourcing methods, categories of sources, content of knowledge, and geographical location). Analyses were carried out using the stats package, version 4.2.3. Lastly, we identified for each network the most frequently cited sources within each category of sources by selecting the ten sources with the highest out-degree scores. Based on our ethnographic fieldwork and out-degree scores, we selected and described three key actors who play a crucial role in the diffusion of variety, clone, and rootstock knowledge.

For each network of knowledge, we performed three negative binomial generalized models to identify variables influencing informants' degree centrality measures (degree, in-degree, and out-degree). This model family was chosen to avoid the overdispersion associated with Poisson GLMs. We ran separate models because centrality measures are not independent; thus, each model includes a different centrality measure with all explanatory variables. Variables used in each model included the
<table><caption>**Table 3.** Network-level and node-level measures calculated to describe the structural properties of knowledge circulation networks.</caption><thead><tr><th></th><th>Measure</th><th>Definition</th></tr></thead><tbody><tr><td rowspan="3">Network-level measures</td><td>Size</td><td>The total number of nodes in the network. High network size indicates a larger number of nodes, suggesting a more extensive network with potentially more diverse sources for knowledge diffusion, but possibly slower diffusion due to greater complexity.</td></tr><tr><td>Number of edges</td><td>The total number of edges in the network. A high number of edges indicates a greater level of interaction between actors, reflecting a more active network with frequent exchanges.</td></tr><tr><td>Diversity of source category</td><td>We used the Simpson concentration index D = 1/Σp<sup>i</sup> from the R package vegan (Oksanen et al. 2019), where p<sup>i</sup> is the proportion of ties from the category i. The higher the value of D, the greater is the diversity of source categories within the social network.</td></tr><tr><td rowspan="3">Node-level measures</td><td>Degree centrality</td><td>The number of ties, which is in our case represents the number of sources with whom a farmer is directly connected.</td></tr><tr><td>In-degree</td><td>The number of ingoing ties, which in our case represents the number of sources from which the farmers requested knowledge.</td></tr><tr><td>Out-degree</td><td>The number of outgoing ties, which in our case represents the number of farmers who sought knowledge from that source.</td></tr></tbody></table>

number of varieties (quantitative variable), type of farmers (wine makers and grape growers, categorical variables), social background (neo-farmers and successor farmers, categorical variables), and management methods (organic production and conventional production, categorical variables). The number of varieties was also used as a proxy for farm area as we observed a correlation between these two variables (rho = 0.72, p < 0.001). The models were fitted using the R package MASS (Venables and Ripley 2002).

## RESULTS

### Farmer's knowledge regarding varieties, clones and rootstocks

Participant observations and interviews revealed that the knowledge held by farmers differed among varieties, clones, and rootstocks. Farmers effortlessly listed all the grapevine varieties they cultivated (9.3 ± 3.6 on average, n = 50). They described in detail the agronomic characteristics of each variety, including phenology, yield, susceptibility to pests and diseases, and drought tolerance, tailored to specific fields. Farmers also explained the type of wine produced from each variety under various environmental conditions and its marketability in local and international wine markets. In contrast, farmers were not able to identify the specific clones of the grape varieties they grow by name. They only distinguished between high-yielding and low-yielding clones based on the production objectives of each plot. Farmers were not aware of clone-specific traits, such as phenology or susceptibility to pests and diseases. Most farmers (60%) listed the rootstocks they cultivated with some difficulty, and the dataset contains missing values for 15 farmers. On average, they reported 3.1 ± 1.8 rootstocks (n = 35). Upon reflection, they mostly identified the rootstocks in relation to soil types and the production objectives of the field. When uncertain, farmers referred to administrative records if available. Most farmers described only the drought and active limestone tolerance of each rootstock and its influence on yield. Informants noted that, although they had studied the various characteristics of rootstocks during their education, they mostly depend on nurserymen for this expertise:

> The rootstocks are too specialized for the farmers. Everyone has their own job; we choose the variety, and the grapevine nursery chooses the rootstocks with the help of soil analysis (WM 12, successor, conventional agriculture).

### Knowledge networks composition and structure

In total, 262 distinct knowledge circulation events between a provider and a recipient were documented. Knowledge circulation networks varied in size (Table 4). Of the total number of ties, just under half (44.3%, n = 116) concerned the choice of varieties, 30.5% (n = 80) were related to rootstocks, and 25.2% (n = 66) to clones. The richness and diversity of source categories varied across the three networks. The variety-related knowledge network was the largest (107 nodes), while the clone network was the smallest (62 nodes). The Simpson index values indicated that the rootstock network was the most diverse (5.03), while the variety (3.08) and clone (3.90) networks encompassed fewer categories of sources.

<table><caption>**Table 4.** Descriptive characteristics of knowledge circulation networks. Sample size: Variety (n = 40 farmers), clone (n = 40 farmers), rootstock (n = 43 farmers).</caption><thead><tr><th>Knowledge circulation network measures</th><th>Variety</th><th>Clone</th><th>Rootstock</th></tr></thead><tbody><tr><td>Number of nodes</td><td>107</td><td>62</td><td>78</td></tr><tr><td>Number of ties</td><td>116</td><td>66</td><td>80</td></tr><tr><td>Diversity of source categories (Simpson index)</td><td>3.08</td><td>3.90</td><td>5.03</td></tr></tbody></table>

No significant link was found between the three networks and the type of sourcing methods (i.e., social sources vs written sources) across the three networks (x-square = 2.03, df = 2, p = 0.362). We found that knowledge sourcing predominantly occurred through social relationships (i.e., dialogue between two or more individuals), representing 90% of knowledge circulation events for varieties, 83% for clones, and 87.5% for rootstocks, compared to written sources (i.e., longstanding books and digital content), which accounted for 10%, 17%, and 12.5%, respectively. As wine maker 16 (neo-farmer, conventional agriculture) explained:

> When planting grapevines, it is a significant investment and a commitment that spans several decades, we can't afford any mistakes [...] My documentation relies more on conversations with people than on websites or other sources because online information is often hit-or-miss and tends to remain very general. I believe that the experiences of others are what really matter and can provide answers to our questions. Often, it's about the
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Proportion of knowledge circulation events based on the knowledge providers. Code corresponds with Table 1: VN (grapevine nurseries), IFV (Institut Français de la Vigne et du Vin), Coop (cooperative cellars), CA (chambre d'agriculture), AS (agricultural suppliers), CC (consulting compagnies), DC (digital content), LB (longstanding books).</figcaption></figure>

mistakes others have learned to fix, whether through their
specific training or by asking the right question to the
right person.

We found a statistically significant difference in the proportion of
the different categories of source between the three networks (x-
square = 85.122, df = 16, *p* = 1.96e-11). Other farmers were the
main providers of variety-related knowledge (52%), whereas
grapevine nurseries (VN) served as the primary source of
knowledge for clones (40%) and rootstocks (35%) (Fig. 2). The
private research and development organization IFV provided
information more evenly: 10% for varieties, 21% for clones, and
13.7% for rootstocks.

Contents of knowledge circulation networks

In the variety network, 79.1% of knowledge circulation events mention a specific variety name (n = 182). A total of 35 varieties were identified, along with one broad category: “varieties ResDur.” This group of varieties, which accounted for 16.5% of the knowledge requests, refers to disease-resistant varieties developed through research to combat downy and powdery mildews (e.g., Artaban, Vidoc, Floreal, and Voltis). In addition to the “varieties ResDur,” which are currently being tested in the Gaillac region, 44.6% of knowledge circulation events involved rare or uncultivated varieties in the region (e.g., Cinsault, Bouysselet, Vermentino). According to interviews, these varieties may cope with new temperature regimes through well-adapted functional traits, such as a later ripening period or better sugar-acidity balance. Other variety-related knowledge circulation events (18%) referred to common and local varieties (e.g., Fer, Mauzac blanc). In the rootstock network, 28.7% of knowledge circulation events did not specify a rootstock name (n = 122). Of the twelve distinct rootstocks identified, the most frequently requested are Fercal (17%), SO4 (11.5%), and 110 Richter (9%).

Statistically significant differences were identified in the content
of knowledge across the three networks (Fisher's exact test, p =
1e-07). The main knowledge conveyed through the three networks
was related to agronomic properties: 56.3% for varieties, 52.8%

for clones, and 76.5% for rootstocks. We noted that a substantial
amount of knowledge circulation events remained unspecified by
farmers for clones (47.7%) compared with rootstocks (23.5%) and
varieties (12%; Fig. 3). Knowledge about rootstock primarily
concerned soil adaptation (43.9%) and graft interactions (22.4%).
The clone network mostly conveyed knowledge regarding yield
(30.5%). For the variety network (Appendix 1), we noted that
other farmers primarily shared agronomic (55%) and wine-related
knowledge (32.5%), whereas cooperative cellars conveyed
knowledge on economics (46.9%) and agronomy (46.7%).
Regarding the content on clones and rootstocks, the knowledge
appeared to be consistent across the different types of sources
(Appendix 1).

Geographical extents of the networks of knowledge

The geographical location of individual sources did not differ
significantly across the three networks (x-square = 2.22, df=2, *p*
= 0.329). Most knowledge circulation events involved individuals
located less than 40 km from the farm, representing 80.8% of the
variety network (n = 104 ties), 88.9% of the clone network (n =
54), and 86.9% of the rootstock network (n = 69). However, the
variety network exhibited a broader geographical reach,
connecting individuals from eight wine-growing regions (e.g.,
Alsace Est, Aquitaine), including Brittany as an emerging wine-
growing region, and spanning distances of up to 640 km (Fig. 4).
In contrast, the clone and rootstock networks were more
geographically limited, linking individuals from only two and
three wine-growing regions, respectively, with a maximum
distance of 250 km for each. Overall, just under a quarter (22.5%,
n = 80) of farmer-to-farmer knowledge circulation events
occurred over long distances. However, other farmers were the
primary providers of long-distance knowledge for the variety
network (85%, n = 20) and focused on uncultivated varieties in
the Gaillac region, such as Saint-Côme, Camaralet, Vermentino,
and Mourvèdre. IFV and the CA were mobilized to gather
information on "ResDur varieties." The small number of long-
distance events for clones and rootstocks was primarily conveyed
by vine nurseries, accounting for 83.7% and 77.8%, respectively.
<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Number of knowledge circulation events across the three networks depending on the contents of knowledge.</figcaption></figure>

According to the interviews, these vine nurseries offer an alternative grafting method to mechanical omega grafting, which is the most commonly used by nurseries. This alternative is Whip and Tongue grafting (greffe à l'anglaise in French), where the rootstock and scion are manually joined. They also provide hot water treatment for disease prevention and propagate varieties through mass selection.

For the aggregate network, the geographical location of individual sources did not differ between grape growers and wine makers (x-square = 1.496, df=1, *p* = 0.221), as well as between successors and neo-farmers (x-square = 3.167, df=1, *p* = 0.075). By contrast, organic farmers were engaged in more long-distance circulation events than conventional farmers (x-square = 18.918, df=1, *p* = 1.395e-05).

## The most frequent knowledge sources

Among the non-farmer sources of knowledge (e.g., agricultural organizations and material resources), the nodes IFV 1, Coop 1, Coop 2, VN 7, and VN 1 were the most frequently cited sources of knowledge (Fig. 5, Appendix 2). According to the interviews, all these actors have been established in Gaillac for several generations, are over 45 years old, male, and hold diplomas in viticulture and oenology. Due to their professions, they also possess significant experience in managing a diversity of varieties, clones, and rootstocks.

Node IFV 1 has been working at the IFV in Gaillac since 2003. His work includes field prospecting at both local and international levels to identify grapevine species, varieties, clones, and rootstocks. He also manages a network of in-situ conservatories of varieties in southwestern France, preserving 1300 accessions of 425 varieties and 22 rootstocks. As a result, he possesses extensive knowledge of a broad range of grape varieties, clones, and rootstocks while maintaining strong connections with field agents (e.g., vine nurseries, chamber of agriculture, PDO syndicate) and fundamental research institutes such as INRAE

(Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement) and CNRS (Centre National pour la Recherche Scientifique). He explained that, "I remain as neutral and objective as possible, neither promoting any particular type of plant material nor advising against planting a specific variety, simply stating its strengths and weaknesses." He responds to requests for advice whenever possible, even though it is not part of his official duties. This often occurs during his free time and sometimes encroaches on his working hours. He is also involved in drafting technical sheets on the agronomic characteristics of varieties, clones, and rootstocks available online.

Coop 1 and Coop 2 are advisors at the two cooperative cellars in Gaillac. Their work involves supervising and assisting grape growers with all viticultural practices, including grape selection, harvest timing, managing ground vegetation, and controlling vineyard diseases. Regarding grape choices, they act as intermediaries between the needs of the cooperative cellar and the objectives of the grape growers:

> The grape grower has the freedom to choose which grape varieties to plant, with no obligation. However, we aim to guide them towards specific varieties based on our policy of producing what we can sell. Grape growers are required to consult with me before planting grapevines. We agree on the variety to plant based on the production strategy, the field's location, and irrigation availability [...] We often visit the field together to discuss, assess the land, take soil samples for analysis, and create a roadmap for ordering from the vine nurseries. For clones, I direct them towards the most productive and oenologically beneficial ones, and similarly for rootstocks in relation to soil types [...] Increasingly, we also consider climate change issues, advising drought-resistant rootstocks when irrigation is not feasible and limiting early-ripening varieties, such as Gamay [...] When uncertain, we consult IFV 1 or research online, particularly DC 6. (Coop 2)
<figure><img src="image_6.png" /><figcaption>**Fig. 4.** Spatialized knowledge circulation networks among the social sources for A) variety, B) clone, and C) rootstock. Farmers are represented by circles, and individuals from agricultural organizations by squares. Color refers to the main wine-growing regions in France (Delpuech 2021). The knowledge circulation events within the Gaillac region are concealed to protect informants' anonymity.</figcaption></figure>

The source DC 6 is a website developed by researchers in 2009 and provides knowledge on varieties, clones, and rootstocks cultivated in France (https://www.plantgrape.fr/en).

VN 1 has worked as a commercial manager at the vine nursery directed by VN 7 for over 20 years. His responsibilities include advising farmers on grapevine selection, overseeing the grafting process, and managing relationships with other vine nurseries:

> For grape varieties, farmers generally already know what they want to plant before coming to see us [...] For clones and rootstocks, it's more technical, and they ask for our advice, except for those who already know what they want [...] We ask about the desired planting date, soil type, and production goals to refine the scope of possibilities [...] Our primary challenge is managing stock availability to align with the order and planting dates requested by farmers [...] In certain situations, we need to provide alternative plant material or arrange order exchanges with other farmers or vine nurseries [...] When faced with uncertainty regarding an alternative clone or rootstock, we seek guidance from IFV 1. As recently as yesterday, I sought advice from IFV 1 regarding a farmer who was insistent on obtaining SO4 (VN 1).

Farmer's varietal richness was positively and significantly associated with important knowledge providers (i.e., out-degree) for the aggregate and variety networks (Table 5). Compared to wine makers, grape growers sought information to a greater number of sources (i.e., in-degree), in general, and specifically for

varieties (i.e., aggregate and variety networks). Grape growers, in general, are more active in asking and giving knowledge than wine makers (i.e., total degree). Neo-farmers, compared to successor farmers, are also more active in knowledge circulation overall, and particularly for varieties. In contrast, agricultural practices (organic vs. conventional farming) did not significantly influence the number of knowledge sources for either giving or receiving information. For the clone and rootstock networks, the predictors showed only marginal or non-significant effects.

## DISCUSSION

This study combined network analysis with an ethnographic approach to explore the differences in farmers' knowledge sourcing across the three components of vine stocks: the variety, the clone, and the rootstock. By comparing the composition and structural features of the three knowledge circulation networks, we found that knowledge related to varieties, clones, and rootstocks is predominantly obtained through social interactions with nearby individuals, rather than from independent consultation of written sources such as books and websites. Previous studies have shown that tacit knowledge is primarily conveyed through social relationships and local networks (Wood et al. 2014, Śûmane et al. 2018, Polge and Pagès 2022). This knowledge is tacit, tailored to context-dependent environmental, social, and economic conditions. Shared by farmers and other rural professionals, it draws heavily on expertise derived locally through observation, experience, and trial and error. The most frequently cited knowledge sources across the three networks (i.e., degree centrality) were local experts with significant experience in managing a diverse range of grapevine
<figure><img src="image_7.png" /><figcaption>**Fig. 5.** Knowledge circulation networks for A) variety, B) clone, and C) rootstock. Farmers are represented by circles, individuals from agricultural organizations by squares, and written sources (i.e., digital contents and longstanding books) by triangles. Node size is proportional to the out-degree +1, related to the number of conveyed knowledges. Code corresponds with Table 1: GG (grape grower), WM (wine maker), VN (grapevine nurseries), IFV (Institut Français de la Vigne et du Vin), Coop (cooperative cellars), CA (chambre d'agriculture), AS (agricultural suppliers), CC (consulting compagnies), DC (digital content), and LB (longstanding books).</figcaption></figure>

varieties. In our case study, written sources were seldom used for direct knowledge sourcing; instead, they were mainly consulted to identify key experts and organizations to contact for specific issues. For example, farmers preferred direct interaction with IFV 1 over sourcing knowledge from online content produced by IFV 1 (e.g., DC 4). This finding supports those of Hoffman et al. (2015), who observed that farmers in Californian vineyards place higher trust in individuals (e.g., other farmers, winery staff) than in written sources (e.g., newspapers, internet resources, viticultural reference books) for gathering knowledge. Regardless

of their primary role in knowledge diffusion in our study, it is important to note that locally embedded social relationships are key drivers of social-ecological resilience and agricultural sustainability (Cinner and Barnes 2019, Barnes et al. 2020). These relationships foster trust, strengthen a sense of community, and facilitate mutual support among farmers, contributing to the preservation of local knowledge systems.

In contrast, we observed recurring differences between the three networks in terms of the identity of knowledge providers (e.g., farmers, IFV, vine nurseries), the structure, and the content of
<table><caption>**Table 5.** Estimations of negative binomial generalized linear models for knowledge circulation networks (n = 50 interviewed farmers) for: all type of knowledge (aggregate), variety, clone, and rootstocks knowledge. p-values: +, *, **, *** at the 0.1, 0.05, 0.01, and 0.001 levels.</caption><thead><tr><th rowspan="2">Knowledge circulation network</th><th rowspan="2"></th><th colspan="4">Predictor</th></tr><tr><th>Varietal richness</th><th>Grape growers<br>[vs wine makers]</th><th>Neo-farmers<br>[vs successors]</th><th>Organic production<br>[vs conventional production]</th></tr></thead><tbody><tr><td rowspan="3">Aggregate</td><td>Total degree</td><td>0.074</td><td>0.321 *</td><td>0.431 **</td><td>-0.049</td></tr><tr><td>In-degree</td><td>-0.085</td><td>0.432 **</td><td>0.458 **</td><td>-0.160</td></tr><tr><td>Out-degree</td><td>0.748 ***</td><td>-0.318</td><td>0.044</td><td>0.357</td></tr><tr><td rowspan="3">Variety</td><td>Total degree</td><td>0.171</td><td>0.348</td><td>0.714 **</td><td>0.200</td></tr><tr><td>In-degree</td><td>-0.118</td><td>0.600 *</td><td>0.839 **</td><td>0.012</td></tr><tr><td>Out-degree</td><td>0.797 ***</td><td>0.280</td><td>0.123</td><td>0.789</td></tr><tr><td rowspan="3">Clone</td><td>Total degree</td><td>-0.077</td><td>0.326</td><td>-0.215</td><td>-0.606 +</td></tr><tr><td>In-degree</td><td>-0.100</td><td>0.453</td><td>-0.173</td><td>-0.524</td></tr><tr><td>Out-degree</td><td>5.598</td><td>-24.139</td><td>-19.860</td><td>-33.242</td></tr><tr><td rowspan="3">Rootstock</td><td>Total degree</td><td>-0.034</td><td>0.355</td><td>0.459 +</td><td>-0.070</td></tr><tr><td>In-degree</td><td>-0.037</td><td>0.327</td><td>0.478 +</td><td>-0.054</td></tr><tr><td>Out-degree</td><td>-0.006</td><td>1.447</td><td>-0.168</td><td>-0.569</td></tr></tbody></table>

knowledge (e.g., agronomic, oenological, and economic) within social networks. Our findings align with previous research showing that farmers interact with their social networks in varying ways when selecting different crop species, as observed in France (Ayoub 2023), Senegal (Porcuna-Ferrer et al. 2023), Madagascar (Mariel et al. 2024), Vanuatu (Thomas and Caillon 2016), and Ghana (Cadger et al. 2016). Our results suggest that grapevine varieties have higher biocultural value for farmers than clones and rootstocks, which in turn shapes the structure of knowledge circulation networks as found in Vanuatu (Thomas and Caillon 2016) and Senegal (Porcuna-Ferrer et al. 2023). In our case study, farmers do not relate equally with varieties that they can observe, recognize and name, with clones that have been created by research institutes in the 1950s with impersonal numerical names (e.g., N°234, N° 1069), or with invisible buried rootstocks that were imposed after the Phylloxera traumatic episode. Farmers demonstrated extensive knowledge of their cultivated varieties, easily recalling both the varietal names and the content of knowledge they sought. As for humans, names could recall a geographical, ecological, or cultural origin (Rézeau 2014), and always prompt an imaginary sense. In contrast, knowledge about the names and characteristics of clones, and to some extent rootstocks, was less well described by farmers. According to the interviews, varieties matter most to farmers because they largely determine the taste and quality of the wine produced, as well as the associated marketing opportunities. Conversely, rootstocks and clones were seen as adjustment variables, used to optimize yield and adapt to the biotic and abiotic factors of the environment. Knowledge related to clones and rootstocks falls more into the realm of technical and specialized knowledge, which is outside the scope of expertise for most farmers interviewed. As a result, we found that while farmers are the primary sources of information on grape varieties, they play a smaller role in disseminating knowledge about clones and rootstocks, where vine nurseries take precedence. Garforth et al. (2003: p. 324) points out: “An almost universal finding from studies of farmers’ sources of information and influence is that “other farmers” are their most frequently reported source”. However, science-driven conventional agriculture has led to a loss of local knowledge by distancing farmers from the production process, thereby narrowing their skillset (Ingram 2008, van Der Ploeg 2021).

Our study, therefore, calls for further investigations of the non-linearity of agricultural information dissemination (e.g., farmer to farmer via vine nursery). Triadic transitivity (i.e., the tendency to give to indirect receivers; Robins et al. 2007) is a common structural pattern of advice seeking in social networks (Alexander et al. 2018). In this way, vine nurseries could act as brokers by providing feedback from farmers to other farmers on particular rootstocks under certain ecological conditions.

Previous studies have shown that social networks facilitate the generation, acquisition, and dissemination of essential knowledge for crop diversification at both the plot (Isaac 2012) and landscape levels (Isaac and Matous 2017). In the Gaillac region, we observed that social networks sustain knowledge related to a broad range of grapevine varieties. This enables farmers to respond to social-ecological changes in various ways. We recorded knowledge circulation events for rare and uncultivated varieties, disease-resistant varieties, and varieties that could be suited to warmer conditions. The knowledge sustained within social networks primarily focused on agronomic traits (e.g., soil adaptation, yield, phenology), which are crucial for adapting to climate change. This finding highlights the role of knowledge circulation networks in the adaptive capacity of farming systems. This flexibility and diversity of adaptation options in crop selection, as well as farmers' willingness to engage with alternative crops, may strengthen the resilience of wine-growing systems at a local scale in a future of dramatic environmental stresses.

For the three networks, we found that the most cited sources of knowledge (i.e., those with high out-degree) were individuals with significant expertise and experience in managing a diverse range of grapevine varieties. The most cited actors in knowledge diffusion included farmers, an IFV researcher, vine nurseries, and technicians from cooperative cellars. This result suggests that individuals who maintain crop diversity locally are also the key influencers in diffusing knowledge associated with crop diversity. This finding differs from those of other published studies that did not observe a positive association between out-degree score and crop diversity in social networks (Kawa et al. 2013, Thomas and Caillon 2016, Abizaid et al. 2016, Porcuna-Ferrer et al. 2023). Interestingly, we did not observe the opposite pattern. We found
no association between grapevine varietal diversity and being an important knowledge receiver (i.e., in-degree), as found by previous studies (Porcuna-Ferrer et al. 2023). One possible explanation for this is that seeking knowledge from individuals does not necessarily translate into a planting decision. Central actors can be both beneficial and damaging in social networks, either by spreading, influencing, or limiting knowledge diffusion within a community (Borgatti 2006). The central actors may influence farmers' cropping decisions by facilitating the adoption of certain crops while discouraging the adoption of others. Importantly, IFV 1 emerged as a key knowledge provider for farmers, vine nurseries, and technicians from cooperative cellars. This highlights the low redundancy in the observed knowledge circulation networks. For example, if an unexpected change impacted IFV 1, the network could become fragmented, and access to knowledge might be constrained. Following Sutherland et al. (2017) and Fieldsend et al. (2019), we argue that publicly funded individuals should be employed to enhance and support the longevity of knowledge circulation networks, ensuring the diffusion of agronomic and oenological knowledge.

We found that neo-farmers and grape growers sought knowledge from a greater number of sources (i.e., high in-degree), whereas organic farmers were involved in more long-distance ties. In addition to peer exchanges, grape growers benefit from the support and daily guidance of technicians from cooperative cellars (Chiffoleau and Touzard 2014). Agricultural cooperatives facilitate innovation diffusion and foster interactions among members by providing knowledge on various topics (Oreszczyn et al. 2010, Sáenz et al. 2024). Neo-farmers, who are individuals starting a second career in agriculture with little or no experience in agricultural production (Carolan 2018), are more likely to seek specific knowledge on crop choices, as found by Zollet and Maharjan (2021) in Japan. The organic transition in Gaillac is relatively recent, and organic farmers remain a minority in the region (Pouzenc and Vincq 2013). As a result, they may rely on national networks of like-minded farmers. Interviews revealed that long-distance knowledge transfer among organic farmers primarily occurred at trade shows. These events serve as temporary hubs where farmers from all over France come together to taste wines, exchange insights, and engage in discussions on winemaking and wine-growing practices (Prudham and MacDonald 2020). These findings align with Junquera et al. (2022) and are similar to what has been reported for no-till farmers in England (Skaalsveen et al. 2020).

## CONCLUSION

The results presented here provide valuable insights into the structure of knowledge circulation networks related to crop choices. Our case study is among the few that examine the circulation of knowledge regarding the three key components of a single crop. We show that knowledge about crop decisions is deeply embedded in social relationships within a specific geographical area. The most cited knowledge sources were those rooted in experience with managing grapevine diversity. These included technicians at cooperative cellars, researchers from private research organizations, and farmers. Additionally, we confirm that, as shown in previous studies, knowledge circulation networks are not universal. Instead, they are shaped by the biocultural value of crops and the characteristics of farmers.

Agroecological knowledge acquisition is increasingly recognized as a critical tool in sustainability sciences, addressing the complex challenge of building sustainable futures (Gliessman 2020, Tittonell 2020). Farmers' ability and willingness to engage with these knowledge pools play a crucial role in shaping the dynamics of crop diversity (Bassignana et al. 2025). However, knowledge sharing extends beyond the farmer level, with cooperative cellars, IFV, and vine nurseries also participating in frequent and intensive exchanges. These exchanges occur at both local and global scales. They are embedded within physical and digital communities that inform and support farmers in shaping their agricultural practice. This study focuses on a specific segment of the broader knowledge circulation network related to crop choices: farmer-level interactions. Further research is needed to explore how knowledge sharing among agricultural organizations influences the quality and content of advisory services offered to farmers. Given the complexity of these networks, a multilayered approach provides a valuable framework for assessing how the composition, the structure, and the content of social networks influence farmers' access to knowledge and, ultimately, the resilience of agricultural systems (Labeyrie et al. 2021).

## Author Contributions:

A. D.: Conceptualization, investigation, analysis, writing (drafting, reviewing). A. R.: Investigation, analysis, writing (reviewing). S.

C.: Conceptualization, writing (reviewing). D. R.: Conceptualization, project administration, writing (reviewing).

## Acknowledgments:

Research leading to this contribution was supported by the French National Research Agency (ANR) under the "Programme d'Investissements d'Avenir" (reference 17-MPGA-0004). We are grateful to the farmers in Gaillac for generously sharing their time to participate in our survey. We also thank Marney Isaac, Vanesse Labeyrie, and the members of the ReSoDiv Research Group (https://lresodiv.cnrs.fr/ample-gdr/) for their valuable input and constructive discussions. Finally, we thank the three anonymous reviewers for their insightful comments and suggestions, which helped enhance the quality of this manuscript.

## Data Availability:

Data and code that support the findings of this study are partially available from the GitHub repository: https://github.com/ AntoineDoncieux/crop_diversity_knowledge_networks. Data jeopardizing the anonymity of the research participants has been removed. Our research project complies with the European General Data Protection Regulation (RGPD) on the protection of individual information under the reference 2-21088.

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**Appendix 1.** Number of knowledge circulation events across the knowledge providers for A) the variety, B) the clone, and C) the rootstock networks. Code corresponds with Table 1: VN (grapevine nurseries), IFV (Institut Français de la Vigne et du Vin), Coop (cooperative cellars), CA (chambre d'agriculture), AS (agricultural suppliers), CC (consulting compagnies), DC (digital content), LB (longstanding books).

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Contents of knowledge circulation networks:

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<figure><img src="image_12.png" /><figcaption>**Appendix 2.** Out-degree distribution of the top ten knowledge-providing actors within four distinct knowledge circulation networks: A) the aggregated network integrating all elements involved in grapevine choice, namely variety, clone, and rootstock, B) the network specific to grapevine varieties, C) the clone-specific network, and D) the rootstock-specific network. Code corresponds with Table 1: WM (wine makers), VN (grapevine nurseries), IFV (Institut Français de la Vigne et du Vin), Coop (cooperative cellars), CA (chambre d'agriculture), AS (agricultural suppliers), CC (consulting compagnies), DC (digital content), LB (longstanding books).</figcaption></figure>

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Knowledge sources

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Knowledge sources