Social-ecological networks, such as seed exchange networks (SEN), allow examining resilience in farming systems. These networks are relational structures that foster agrobiodiversity within farming systems, thereby enabling farmer communities to cope with broader social-ecological changes. This study contributes to the understanding of SEN and their role in farming resilience by exploring local seed exchange dynamics in a territory recognized for its high agrobiodiversity in the southern Andes of Chile. Using a relational approach including qualitative and quantitative methods, we co-constructed a SEN from a sample of 80 homegardens tended by campesinos and lifestyle migrants who have recently arrived in this territory. We examined a set of network properties that have been implicated with farming resilience, including density, modularity, and centrality. Furthermore, we used egocentrically exponential random graph models (ego-ERGMs) to examine if (i) seeds were actors configuring the observed exchange interactions, and (ii) whether the origin of people engaged in small-scale farming, along with the diversity of exchanged crop varieties and their functional traits, may contribute to homophilous tendencies in subgroup formation within this network. We observed a decentralized and fragmented SEN connecting 559 campesinos and migrant homegarden tenders. We found that homegarden tenders and seeds are coupled actors shaping seed exchange interactions and subgroup formation in SEN. Despite this result, we did not find any homophilous tendency based on the crops’ functional traits. Our results provide evidence that diversity, across both social and ecological scales, is critical to foster seed exchange interactions and farming resilience.

In the semi-arid tropics of India, agrarian distress, farmer suicides, livelihood precarity, and entrenched caste-driven social stratification persist amidst underdeveloped or inaccessible formal financial systems. Limited non-farm livelihood options heighten dependence on agriculture, making social networks vital for resilience (Patnaik, 2010). Using household-level data from Kanzara village on social networks, input use, labor patterns, and agricultural output, we explore how these networks mitigate risks and enhance productivity in a climate-vulnerable, resource-constrained context. Social networks foster trust-based cooperation, enabling farmers to pool resources, share timely information on weather and inputs (Pratiwi & Suzuki), and access labor during critical periods, thereby reducing transaction costs and liquidity constraints (Barnett-Howell & Mobarak, 2021). However, caste-based hierarchies stratify network access, often excluding marginalized groups from high-yield knowledge or equipment-sharing arrangements, perpetuating inequities. This study examines how social networks—centered on credit access, agricultural information sharing, farm equipment exchange, and labor collaboration—influence input decisions, labor allocation, and productivity. It also investigates how caste-based hierarchies shape these networks and affect who benefits from resource sharing. This research highlights the role of social networks in mitigating farming risks where formal institutional support, such as credit markets or extension services, is limited. These findings offer valuable insights for policies aimed at strengthening agricultural resilience and sustainability in similar agrarian settings.

References

Barnett-Howell, Z., & Mobarak, A. M. (2021). Social networks analysis in agricultural economies. In Handbook of Agricultural Economics (Vol. 5, pp. 4613-4652). Elsevier.

Patnaik, I. (2010). Distress situation in dryland areas impacts on livelihood pattern and the coping strategies: A review. Research Unit for Livelihoods and Natural Resources.

Pratiwi, A., & Suzuki, A. (2017). Effects of farmers’ social networks on knowledge acquisition: Lessons from agricultural training in rural Indonesia. Journal of Economic Structures, 6, 1-23.

Smallholder farmers critically depend on seed access. It is especially true, in regions experiencing significant interannual precipitation variability, where access to a broad diversity of locally-adapted seed varieties is key for agricultural systems resilience.

However, a general assessment of the drivers of seed access is lacking. This study investigates the processes through which smallholder farmers source seeds in challenging environmental conditions, examining the socioeconomic, cultural, and geographical drivers of seed sourcing patterns. It examines how the structure and composition of seed circulation networks influence farmers' equitable access to seeds, and identifies the key drivers of inequality.

The research is based on a comparative analysis across three geographically and socioculturally distinct study sites in Senegal, Madagascar, and Morocco. These sites were selected due to their diverse agroecological conditions and institutional frameworks, while also sharing similarities in farming systems and crop diversity management. We analyzed data collected through surveys in 2,000 household surveys, documenting crop diversity at both species and varietal levels, agricultural management practices, socioeconomic indicators, and seed sourcing networks.

The study: (1) applies multivariate approaches and cluster analysis to identify households profiles based on their seed sourcing practices; and (2) uses social network analysis to identify key network actors, structural configurations, and relational dynamics that influence seed access opportunities for households.

This assessment across these three countries will allow to identify, if share patterns exist, which will be useful to deliver practical recommendations for improving equity in seed access.

Ecological networks model species-to-species interactions, and are intended to be predictive models for an ecosystem. When inferring ecological networks from observational data, we assume precision and recall, i.e., that (1) a network link reflects a true pairwise functional relationship between species, and (2) all true relationship are modelled as links. Unfortunately, for opaque ecosystems such as the soil, with numerous and microscopic species, functional information is rare. Instead, co-occurrence networks are inferred by sampling the soil. We ask the question: how accurate are these spatial networks of microorganisms, as inferred with current soil-sampling methods?

An agent-based model with biologically realistic behaviour and parametrisation simulates a plot of land, with true trophic links between species. We observe the spatial co-occurrence that these trophic links naturally produce in space. We also simulate the taking of individual samples from this spatial distribution of species. Finally, we evaluate the accuracy of the co-occurrence network inferred from samples, against the true co-occurrence of the plot.

We find that biological properties other than the interactions, such as the species diversity in the plot, can be estimated with relatively low error by sample pooling. On the other hand, the inference of the co-occurrence network is poor. We see high errors of the pairwise link weights, with large mean errors, and large standard deviations between experiments. The co-occurrence network inferred is thus both inaccurate and unstable (explaining the large differences seen among algorithms for co-occurrence inference), and this is intuitively explainable in spatial terms.

Germany is exploring collective approaches to agri-environmental and climate schemes (cAECS) to enhance ecological, economic, and social effectiveness. This study examines key actors, their roles and responsibilities, and their interconnections to inform institutional design, particularly concerning ‘collective elements’ (e.g. participatory design, collective planning, involvement of third-party intermediaries). To do so, we integrate Social Network Analysis (SNA) with the Institutional Analysis and Development (IAD) framework. Using the Net-Map method, we collect data from three early-implementation cAECS cases in Germany that vary in biophysical conditions (farming and ecosystem characteristics), social attributes (farm sizes and social structures), and rules-in-use (funding sources and contract types).

Our results show how these contextual differences influence the structure of collective networks as well as the presence of ‘collective elements’. Intermediaries serving as coordinating actors emerge as a central feature of these networks, bearing most of the administrative workload, while others assume supporting roles. Trust-building during the initiation phase is identified as a critical factor for fostering long-term collaboration and further integration of collective elements. Additionally, variations in contract types and farm sizes shape both the design and implementation requirements of collective approaches. Despite these differences, all cases demonstrate the potential for significant benefits from adopting a collective approach to agri-environmental and climate scheme governance. Examples of such benefits include the adoption of measures on a landscape scale, the reduction of transaction costs and the increase in social cohesion.