Tropical coastal systems are characterized by complex interactions between ecological processes and human activities. Effectively managing these systems requires holistic approaches that integrate scientific insights with local knowledge.

In this work, we developed a qualitative social-ecological network model to investigate the dynamics of the coastal resource use sector in Sechura Bay, Peru. By collaborating with local stakeholders from diverse backgrounds and experts from the social and natural sciences, we identified and mapped key system components and their interactions. This process integrated ecological expertise with social perspectives, resulting in a comprehensive model that captures the essential dynamics of the local social-ecological system.

We then applied dynamic network analysis and qualitative mathematical modelling to ask “What if …?” questions and explore the outcomes of potential future scenarios. This approach provides deeper insights into the direct and indirect effects of management strategies, societal dynamics and environmental changes on both coastal communities and ecosystems, allowing stakeholders to anticipate future challenges, evaluate the sustainability of interventions, and better adapt to changing conditions.

Our goal is to develop an accessible and versatile decision-support tool that can be easily applied in data-limited settings in tropical regions around the world. By combining participatory methods with network modelling tools, the presented approach fosters interdisciplinary collaboration and supports inclusive and informed decision-making for effective resource management in tropical coastal systems.

Studies have shown that motivation is key to productivity. As such motivating farmers is an essential tool to enhance their productivity. This study analyzed four motivation types among farmers, and proposed methods for enhancing motivation to improve performance and productivity. We asked 65 farmers about their relationships with their peers to gain insight into the types of relationships they engage in, which could help motivate them to enhance their performance. We used four-layered motivation types, which were analyzed via multiplex network analysis. The results showed that the edges of all layers were statistically significant indicating farmers willingness to engage in motivation ties hook ups. But reciprocity was not significant for all four layer which show competition in the network thereby helping farmers to look out for avenues to be more productive. We also found out that, all four layers had different number of communities indicating that the links formed in different layers are different; hence, each motivation type attracts a different link source. Thus, we discovered that each farmer prefers a different motivation type and are not influenced by their peers' choices. Also we found few farmers as authorities indicating the presents of hierarchy. Accordingly, their opinions regarding the importance of motivation differ, which is consistent with the expectation that individuals need different motivations to improve productivity and performance. Therefore, identifying the motivation types preferred by farmers is critical for increasing their productivity.

Social network (ARS) complex systems approach is each time covering new research social areas. One of these is related with the rural development area mainly because implied by itself the construction of complex social systems around a central resilient element to the current societes: the food production. And in times of climate changes, the societes going to be much more worry about such system , specially in their sustainability degree and the assesment of this latest. This will be a confluence break point between different evaluation tools to analyzed this sustainability degree particularly around a central research question: the organization patterns in the social system responsible to: a) give training to a wide horizont of social actors: from peasants, original groups, administratives and guvernamental employeers, college students, among others, and b) responsible to stablish: norms, rules, concepts, schools, books, manuscripts, etc.. We are referring to the social research systems involved in the next research areas: hydric resource, agriculture, swine production and botanic, agroecology, rural transfer technology, rural enterprises, etc. We found that each social research subsystem es very different but all of them confluence in particular characteristics some of them are so problematic in climate change time. so it will be necesary begin to implement deep changes in systems that are not maded it to get fast movements.

In Ethiopia, limited empirical studies exist on how seed supply access constraints condition adoption intensity (demand). Hence, this research employs the augmented Double hurdle model to incorporate the effect of seed access (local supply) constraints in conditioning demand. Moreover, nine factors were constructed of twenty-eight indicators using Principal Components Analysis to resolve which cognitive and structural indicators drive social capital at the farm household level. The Double hurdle result reveals that social capital indeed determines wheat varieties access; besides, different forms of social capital have dissimilar effects on varieties demand. In addition to social capital variables (such as getting well with other farmers, generalized trust, and trust in agricultural institutions), information on seed access, training on varieties selection, and education have significant positive effects on relaxing seed access constraints and demand. Hence, the result suggests that agricultural policy and extension efforts should consider not only human, and physical capital, but also social capital in relaxing seed access constraints and demand. Furthermore, the government of Ethiopia should develop strong regulatory mechanisms to reduce corruption in the seed supply system.

The sustainability of socio-ecological systems has been shown to depend highly on social structure; factors such as levels of trust and cooperation have an impact on environmental management decisions. In turn, social structure is influenced by factors that favour or hinder tie formation such as the perception of risk. The perception of social and ecological risks can limit or enable the formation of communication ties among people which ultimately will have an impact on resource access. This study examines how perceived social and ecological risk influences social structure among small-scale fishers in Jamaica, Kenya, and Papua New Guinea. Using Exponential Random Graph Models (ERGM), and data on information exchange and fishing practices (e.g., type of fishing gear used), we explore how the fishers' perception of social risk (e.g., non-compliance with regulations) and ecological risk (e.g., fish stock change) affects the social structure. We test node-level effects, hypothesizing that fishers who perceive higher social or ecological risk will tend to communicate with more people, regardless of their own risk perception. We also examine dyadic homophily, expecting that fishers who perceive higher social or ecological risk will prefer to communicate with others who share their perception of risk. Additionally, we model structural network effects, including triadic closure (the tendency for communication ties to form in closed triads), the effect of organizational membership, and external factors such as whether using the same fishing gear type increases the likelihood of communication.