# Institutional network relationships and environmental governance in the Colombian and Peruvian Amazon

Carlos Eduardo Gonzalez-Rodriguez, Oscar Buitrago-Bermúdez, Jean-François Le Coq, Carolina Gonzalez, Johana Marcela Castillo-Rivera

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Carlos Eduardo Gonzalez-Rodriguez, Oscar Buitrago-Bermúdez, Jean-François Le Coq, Carolina Gonzalez, Johana Marcela Castillo-Rivera. Institutional network relationships and environmental governance in the Colombian and Peruvian Amazon. AMBIO: A Journal of Environment and Society, In press, 10.1007/s13280-025-02269-8. hal-05329042

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# Institutional network relationships and environmental governance in the Colombian and Peruvian Amazon

Carlos Eduardo González-Rodríguez, Oscar Buitrago-Bermúdez, Jean-François Le Coq, Carolina Gonzalez, Johana Marcela Castillo-Rivera

Received: 9 November 2024 / Revised: 25 March 2025 / Accepted: 26 August 2025

© The Author(s) 2025

**Abstract** The Amazon—the most biodiverse biome in the world—faces huge conservation challenges. Multiple institutional and technological actors, organized in environmental networks, collaborate to support improved environmental governance. However, these efforts are understudied and underrecognized, particularly in the case of the Colombian and Peruvian Amazon. Employing a social network analysis, this study evaluates the actors, the institutional-technological relationships, and the network addressing socio-environmental challenges. We identified 392 development actors (nodes) with different levels of international, national, and regional participation. They use transnational technologies, but have limited integration of local actors where environmental challenges are most pressing. To combat the biome's rapid degradation, these countries could strengthen their environmental agendas, governance, and policy design—for greater environmental impact—by effectively integrating cooperation between international and local partners. Both countries should develop their local networks, create participatory collaborative spaces to enhance national capacities, and promote diverse and coordinated coalitions.

**Keywords** Amazonian biome · Cooperation · Conservation · Environmental · Networks · Technology

## INTRODUCTION

The Amazon is a vast ecosystem of rich bio-cultural diversity, flora, and fauna. The region is a focal point in both national and international discussions regarding economic and environmental sustainability. Relevant issues include the conservation of primary forests, biodiversity, ancestral knowledge, and Indigenous native languages, among others. Sustainable development issues encompass numerous stakeholders, economic activities, and change initiatives, highlighting the need for environmental science to address significant global challenges (Betts et al. 2008).

The challenges presented by the Amazon biome are extensive and involve complex issues that exceed the capacities of the countries and their local authorities. Some of the stressors on the biome include deforestation, illegal mining, and the expansion of agriculture (Adamek et al. 2021). These activities lead to vegetation cover loss, aggravated by exposure to extreme weather events, fires, and droughts (da Silva Júnior et al. 2019), increasing carbon emissions enhanced by forest drying and warming (Gatti et al. 2023).

Multiple organizations and environmental activists have mobilized individually and collaboratively to reverse the challenges of ecosystem deterioration within a framework of environmental governance (Ritvala and Salmi 2010). Their efforts can be detected by analyzing patterns in their relationships, such as the presence of actors mobilizing resources, technologies, and initiatives. Efforts to address the Amazon's challenges can be seen through institutional and individual actors (known in network science as "nodes") harnessing multidisciplinary science and cooperation in their interventions (Barlow et al. 2011).

In a social system, environmental collaboration networks are crucial for enhancing governments' adaptation and

<footnote>**Supplementary Information** The online version contains supplementary material available at https://doi.org/10.1007/s13280-025-02269-8.</footnote>
response capacity. For example, addressing increased drought in the Amazon requires a multi-institutional approach (Betts et al. 2008). To reduce deforestation, Lemos and Roberts (2008) emphasize the importance of a strong and extensive network of actors and institutions to improve the efficiency of government policies. Unfortunately, the Amazon landscape's rapid degradation means that the sheer extent of the environmental damage can easily overwhelm efforts to address the issue (Vergara et al. 2022). There is a clear need to mobilize efforts and social systems to respond to environmental challenges through networks, guidelines, and directives. From the environmental sciences perspective, this problem provides a scientific opportunity to understand how local, regional, and international organizations interact within the Amazonian environmental context. Understanding how actors and agencies work together can also help us identify potential sources of inefficiency in efforts to improve the biome's socio-ecological system.

Various types of actors work through environmental technology platforms and networks to address environmental issues in the Amazon. Despite their efforts to integrate ecological and social knowledge, there is a lack of information and data on how these actors function, their relationship patterns, their levels of engagement, their potential vulnerabilities, and the adaptive capacity that arises from the interaction between individuals, communities, and organizations managing their ecosystems, among other aspects (Martinez-Baron et al. 2018). Filling this knowledge gap calls for research on these networks to understand their environmental prioritization processes, their level of collaboration with local actors, how they learn, adapt, and are aligned with the region's environmental issues (Guerrero et al. 2015).

This paper describes a network analysis of the actors linked to environmental and technological interventions in the Amazon biome of Colombia and Peru. The analysis visualizes actor interactions and institutional dynamics related to the biome's conservation, analyzing the strength and fragility of these interactions. The key elements for mapping these networks are: (1) identifying influential actors cooperating on conservation efforts; (2) mapping relationships based on technology use and development; and (3) exploring participation, discussion, and collaboration among partners who have similar or complementary relationships.

# THEORETICAL FRAMEWORK

## Environmental governance and collaborative networks

Environmental governance (EG) involves the establishment, reaffirmation, or modification of institutions to

resolve conflicts over environmental resources in an integrated manner (Paavola 2007). EG is a complex dynamic that emerges from the collaboration among stakeholders, amplifying the actions of various environmental entities and groups (Barraclough et al. 2022). EG refers to the set of rules, laws, policies, institutions, structures, networks, and processes that shape the behavior of actors in using a natural resource (Bennett and Satterfield 2018). Under this approach, environmental governance is manifested by collaborative networks that involve diverse actors and structural relationships. Ideally, the network of actors can combine their capacities to tackle environmental challenges (Bäckstrand 2006) and manage resources effectively without formal legal mandates or official authority (Sehnsweeney Fischer 2022).

This study considers one aspect of EG, the one related to institutions, networks, and relational structure, leaving aside political influence, norms, and laws. The paper explores the organizational relationships connecting actors from different categories and levels, capturing information about diverse governance structures. Furthermore, it investigates the participation gap in global, national, and local governance by incorporating a diverse range of stakeholders and intergovernmental actors (Barros-Platiau et al. 2019).

## Social and environmental networks

Socio-environmental networks, as part of EG, reflect the relationship between people and their environment. The connections among network actors are mobilized around dilemmas and conflicts over natural resources. Network analysis fosters the exploration of tensions in environmental management in specific biomes and ecosystems, as well as analysis of organizational structures in institutional and social contexts. Network analysis provides tools and analytical methods for examining connections between actors and how they influence environmental policy outcomes (Iannacone 2024). How academics, scientists, policymakers, NGOs, and other relevant actors work together determines the outcomes and impact of their interactions (Feldman 2012).

From an analytical perspective, a network is a set of nodes linked by some type of relationship and defined by specific criteria, often understood through metrics and patterns of relationships between different types of actors (homophily or heterophily). However, these measurements must be complemented with context and information from the socio-environmental setting in which collaborations are configured (Mertens et al. 2011).

Similar studies have been conducted on the use of social network analysis to map institutional processes and decision-making in environmental contexts. According to
Therrien et al. (2019), the network analysis approach made it possible to identify governance strategies and offer a perspective for the implementation of urban resilience and adaptation policies. Similarly, in the Dry Corridor of Honduras, Gonzalez-Rodriguez et al. (2024) highlighted the importance of evaluating institutional interventions, identifying spatial misalignments in interactions linked to agriculture, climate change, and food security.

## Networks and environmental governance in the Colombian and Peruvian Amazon

Biome degradation drives the formation of transboundary environmental networks to influence local governance in Amazonian countries (Perz et al. 2022). These networks enable collaboration to address common challenges such as deforestation, expanding agricultural frontiers, illegal mining, wildlife trafficking, pollution, and the effects of climate change (Viteri-Salazar and Toledo 2020). Network actors participate in collaborative governance agreements to address the Amazon's environmental issues. Examples include: (a) SERVIR Amazonia (2020), which monitors and provides technological support for environmental decision-making; (b) the Amazon Cooperation Treaty Organization (OTCA 2020); and (c) the Science Panel for the Amazon, which provides sound scientific evidence and recommendations for informed decision-making (SPA 2021).

The complex landscape of social and environmental interactions is set within the broader problems of the Amazon's sustainability, transformation, and development (Brondizio et al. 2021). The academic literature lacks research on the lessons, institutions, and types of actors involved, among other aspects (Filho et al. 2019). This paper fills this gap by exploring environmental cooperation in the Colombian and Peruvian Amazon, where EG networks have not been properly documented or studied, to shed light on how scientific and technological cooperation efforts shape the Amazon as a relevant space for the design and dissemination of technological, environmental, and socio-environmental innovations (Olsson and Galaz 2012).

## MATERIALS AND METHODS

This study employs network analysis to evaluate how actors and agencies organize their efforts in the Colombian and Peruvian Amazon (Contractor et al. 2011). To map the actor network, the study builds on three premises (Fig. 1):

(a) Cooperative relationships are established between institutions (nodes) for purposes related to science, resource mobilization, and exchange of experiences and knowledge (Barnes et al. 2016).

(b) Multidimensional networks encompass various types of actors, including technological nodes promoted by organizations (digital, virtual, artificial intelligence, genetic entities, etc.), service platforms (e.g., visualization of deforestation maps, climate information, etc.), and other similar entities (Yan et al. 2021).

(c) Nodes and relationships focus on the governance and mobilization of organizations within networks, platform-like structures, associations, and similar entities. These node typologies help in understanding governance processes and coalitions for managing environmental phenomena at multiple scales (Bodin 2017).

## Data collection flow

The data collection was conducted in two rounds. In the first round, between 2021 and 2022, we interviewed 131 experts from 60 organizations and institutions operating in the Colombian and Peruvian Amazon region. Based on their responses, data were then collected from the official and project websites of secondary sources (928 websites). The second round, conducted between 2022 and 2023, expanded and improved the information collected in the first round. Methodologically, the process can be explained as follows:

### Primary source interviews

To document attributes of the connections between actors, we utilized two methods: semi-structured interviews and digital surveys (Appendix S1, Supplementary Information). The interview process began by mapping organizations with experience and connections in the Amazon territory, conducted through video calls and field visits to Tarapoto (Peru) and Mocoa and Leticia (Colombia). To identify the interviewees, we created a database of organizations with the support of projects such as SERVIR Amazonia (SERVIR Amazonia 2020) and Climate Services Resilient Development Partnership-CSRD(CIAT 2020). This database, which has been continuously updated by these two projects since 2005, contains all the institutions and officials linked to projects, areas, and organizations with interventions in the Amazon. The records corresponding to Colombia and Peru were extracted from it. People interviewed had to be active in the field of EG or environmental conservation in each country. We balanced the number of people interviewed by considering a basic typology of social actors (state, civil society, and community). The above process also employed convenience sampling. Therefore, those interviewed were selected for their easy access and availability, not for statistical criteria or representativeness of the population (Gentles et al. 2015).
<figure><img src="image_2.png" /><figcaption>**Fig. 1** Schematic diagram of the methodological workflow employed in this review</figcaption></figure>

## Secondary sources

Based on the identification of the associated actors declared in the interviews and the technologies and innovations found, the next step was to list the organizations that cooperate or interact with others on Amazonian issues. We used available digital information, such as institutional websites, digital platforms, and blogs to compile a list of cooperating organizations and partners. Likewise, to identify the technologies, these same digital sources were explored to extract partners, technology developers, and other associated actors. This exercise was conducted at different times, between 2021 and 2023, during which the previously reported links, technologies, and data were updated.

## Methods of treatment and analysis

### Social network analysis

The methodological process begins with mapping the interactions between organizations in the Colombian and Peruvian Amazon using network analysis and a set of indicators (Noldus and Van Mieghem 2015). In this analysis, each organization is represented as a node, and the connections between them are represented as links. This analysis is conducted in the context of conservation and technology development in the Amazon biome. Socio-environmental networks are composed of three basic elements: (a) the nodes representing entities, technologies, and other network platforms; (b) links or edges, which are the connections; and (c) structures that integrate the nodes and links (Fig. S1, Supplementary Information). For both

nodes and edges, additional information or attributes can be added to enhance the visualization and understanding of the network.

The next step involves quantifying the various attributes and characteristics for which social network science offers numerous metrics, such as betweenness, closeness centrality, and density (Table S1, Supplementary Information). This study has chosen specific tools to facilitate the measurement of the network and the performance of the nodes at both the global and local levels, creating a comprehensive portfolio of global and local network analysis metrics.

### Connectivity and potential vulnerability analysis

The network's connectivity and its ability to communicate and disseminate information are tested through simulation techniques. These aim to place the structure under stress by removing one or more nodes. In this context, the participation, position, and influence of an actor in the network are crucial. We use a simulation model, based on the susceptible, infectious, and recovered (SIR) compartmental model, to examine communication within the Colombian and Peruvian Amazon networks and its potential impact (Nian et al. 2021).

The SIR method is applied to the mapped network to obtain: (a) the levels of dissemination or communication recorded by a specific node or disseminator and (b) that node's contribution to the network structure. The analysis also considers what would be lost if a node were removed from the network. How would a node's absence disrupt relationships and transfers within the system? Although network simulation models were originally designed for epidemiological studies
on disease contagion, they have also been applied to information flows, communication analysis, and for identifying influential nodes in social networks at the individual, agent, and organizational levels (Saito et al. 2012).

In large-scale and complex networks, adapting these models allows for evaluating the network's fragility in terms of its ability to transmit and mobilize information between actors. Since these simulations preserve the structures and relationships within the system, they represent a key tool for analyzing resilience and the information propagation dynamics in interconnected environments (Pei and Makse 2013).

The authors developed simple computational algorithms using R programming language and integrated them with two network analysis packages, igraph and SNA (Engelhardt 2009). The algorithm effectively simulates flows and interactions between nodes; however, they do not include per-actor or per-link attributes, nor do they model the network's resilience after being affected.

The model is composed of two main components: exposed nodes and receiving/adopting nodes. It configures the cumulative adoption process over time using a sigmoid or logistic curve, symbolizing the dissemination process (Figure S2a, Supplementary Information). The contribution in transmissibility per network node is calculated as the share of propagation steps in the sub-network compared to the cumulative of the total network (Figure S2b, Supplementary Information).

The method calculates each node's level of contribution and reaches within the overall network related to assessing the potential impacts of changes in the participation of some key nodes (central disseminators). Based on the simulations (n = 100), the method divides the total number of links achieved by the disseminator node by the total number of links completed by the total base network. The rate comparison, indicating the contribution of each node in the transmission and dynamic processes in the network, was calculated using the rate of contribution of the interaction, given by Eq. (1):

$$Rate_{contributionBy Difusser} = \frac{\#links Neighborhood_{Difusser_{Propagation}}}{\#links Overall Network_{Propagation}} \quad (1)$$

# RESULTS

## Institutional actor network of the Colombian and Peruvian Amazon

Our research identified a total of 392 nodes in the Colombian and Peruvian Amazon during the data collection period from 2021 to 2023 (Table S2, Supplementary Information). Of

these, 22.4% are national government organizations and 12.7% are international NGOs (Fig. 2). These nodes included organizations from various countries, other networks in the Colombian and Peruvian Amazon, and technological nodes (Table S2, Supplementary Information).

Figure 3 provides a summary of the composition of organizations and technologies operating in the region of interest, which can be broken down into: 51 technological nodes, 87 international actors from countries other than Colombia and Peru, 66 Colombian actors, and 100 Peruvian actors. Likewise, 13 institutions represent network forms of organization—platforms, networks, coalitions—related to the Amazon's conservation and protection. Of the international actors identified, 22 are US actors, 24 are from Brazil, and 16 are European. This comprehensive deployment demonstrates the international interest in the protection of the Amazon biome and highlights the significant interaction in the transfer of knowledge, resources, and technical support. Furthermore, the categories correspond to the origin of each actor, i.e., their nationality, as well as their local or regional operational scenarios. The technological nodes represent collaborative operational developments involving multiple organizations. Moreover, they reflect the characteristics of the actors, as they foster relationships, provide support, cooperate with other technologies, and mobilize resources, among other functions.

With the complex web of interactions, the nodes were categorized into groups to facilitate their interpretation. These include national agencies and other institutions from Colombia and Peru (marked with the suffixes “_Col” and “_Per”). Another category includes a group of international organizations (_Inter), such as research centers, private entities, and NGOs. Another group consists of the technologies (_Tech) that are part of collaborative projects, tools, information technology, innovations, and associated programs in the region. Furthermore, the US entities (EEUU), Brazil (_Br), Canada (_Canada), and platforms or networks (_net) have been recognized. The labels in Fig. 4 summarize the names of the organizations. Full details of the nodes are provided in the dashboard and Table S2, Supplementary Information.

Identified interactions—793 links or edges—include the declaration of joint activities such as funding relationships, technical cooperation, technological development, knowledge transfer, institutional collaboration, and others. This structure enables cooperation among other nodes in both countries, facilitated by technological nodes and international actors, resulting in a consolidated core with a certain level of centrality (Fig. 4, black square outline). The entire institutional system and its interactions in the Amazon biome in the countries of Colombia and Peru demonstrate a centralized core network and other local relational structures (Fig. 4).
<figure><img src="image_3.png" /><figcaption>**Fig. 2** Percentage of organizations in the Colombian and Peruvian Amazon by category. Categorization of the nodes in the graph is based on the standardized and structured list of types of institutions in the CGIAR Level Agricultural Results Interoperable System Architecture CLARISA Platform (Alliance of Bioversity International and CIAT et al. 2024)</figcaption></figure>

The central actors in the network play a role as coordinators, facilitators of collaborative projects, and providers of essential resources (for instance, the orange ovals in Fig. 4) (Kujala et al. 2020). Their centrality not only facilitates the transfer of technology and knowledge but also gives them a key decision-making role, ensuring the continuity and effectiveness of initiatives in the Amazon region. The relationship analysis reveals a predominance of technical cooperation and knowledge exchange links, highlighting the multidisciplinary and collaborative approach necessary to address the regions’ socio-environmental challenges. However, there is also a dependence on international actors (represented by dotted red squares in Fig. 4), representing both a challenge regarding regional autonomy and an opportunity to strengthen cooperation between local and transnational actors. While the participation of international entities brings resources and technical knowledge, it may also generate asymmetries in defining strategic priorities within the Amazon, sidelining local needs.

## Global network patterns

The network displays small, disconnected components. However, among the reported metrics and numbers, we only consider the major subgraph or component, which consists of 382 nodes and 793 edges.

a. The network has a low density, representing a low relational dynamic among the actors, with a value of only 1% of 100% of the potential observed relationships. A high density value for a network indicates a greater potential for collective actions, greater effectiveness in interventions between groups, and greater support for the governance of natural resources (Bodin and Crona 2009).

b. The presence of highly connected nodes, identified by connections in the environmental network, reflects the preferences for association and collaboration with these organizations.
<figure><img src="image_4.png" /><figcaption>**Fig. 3** Total stakeholders (nodes) related to the Colombian and Peruvian Amazon network by category</figcaption></figure>

c. There is a low concentration of interactions in a broker or mediator mode, hinting at the existence of internal roles of prominence, influence, power, and prestige within some organizations (**betweenness** centrality of 16%).

d. Groups of organizations have close relationships, indicated by the grouping by modules between nodes. These blocks bring together technological and institutional actors with shorter distances between them than other groups for the Amazon network (modularity = 0.51)

e. Less connected nodes seek out more connected actors (assortativeness = -0.17). The network reflects a disassortative structure, where nodes of different connectivity degrees tend to link with each other, rather than connecting with nodes of similar connectivity ties.

## Individual patterns

Table 1 shows the mapping of nodes within the network and their level of importance or influence; the table shows the most connected actors based on the number of interactions and other centrality metrics. The top three nodes

are SERVIR Amazonia-International Node (SERVIR-Inter), the Alliance of Bioversity International and CIAT node (Bio_CIAT_Inter), and Amazon Science Panel-Network node (PCA_net). The high rank of the first two nodes is expected due to access to their institutional relations database. These nodes stand out as the most prominent in the network due to their high connectivity, intermediation, and closeness. All three entities share a common focus on the conservation and sustainable development of the Amazon, as well as promoting the role of scientific knowledge, collaboration among diverse actors, and the promotion of biodiversity.

The network is a complex web of interactions between organizations at various levels. This study has classified each node according to the origin of the institution by region (Colombia, Peru, Brazil, USA, EU, UK, etc.) or by function (_Tech or _net). By elevating the analysis on these categories, interactions can be better quantified (Table 2). The results highlight the key role of technological and international nodes in connecting, propagating, transferring, and motivating the interactions of the network, given
<figure><img src="image_5.png" /><figcaption>**Fig. 4** Total network graph of the Colombian and Peruvian Amazon conservation and technology network. The visualization uses the Fruchterman-Reingold algorithm. The color corresponds to the node type</figcaption></figure>

<table><caption>**Table 1** Node within the network and level of importance or influence. These are the top 10 nodes with the highest centrality in the network. The suffixes Inter, Net, Col, and Per correspond to the International, Network, Colombia, and Peru categories, respectively</caption><thead><tr><th>Top</th><th>Name</th><th>Node</th><th>Edge Freq</th><th>Betweenness centrality</th><th>Closeness centrality</th></tr></thead><tbody><tr><td>1</td><td>SERVIR Amazonia</td><td>SERVIR_Inter</td><td>38</td><td>0.112</td><td>0.351</td></tr><tr><td>2</td><td>Alliance of Bioversity International and CIAT</td><td>Bio_CIAT_Inter</td><td>29</td><td>0.165</td><td>0.379</td></tr><tr><td>3</td><td>Amazon Scientific Panel</td><td>PCA_net</td><td>29</td><td>0.105</td><td>0.318</td></tr><tr><td>4</td><td>Forest and Watershed Monitoring System</td><td>smbyc_Tech</td><td>28</td><td>0.095</td><td>0.348</td></tr><tr><td>5</td><td>Institute of Hydrology, Meteorology and Environmental Studies</td><td>IDEAM_Col</td><td>27</td><td>0.117</td><td>0.343</td></tr><tr><td>6</td><td>Amazon Andes Fund</td><td>Andes_Amazon_FUND_Inter</td><td>24</td><td>0.060</td><td>0.323</td></tr><tr><td>7</td><td>Geobosques</td><td>geobosques_Tech</td><td>22</td><td>0.070</td><td>0.331</td></tr><tr><td>8</td><td>Amazon Conservation ACCA</td><td>ACCA_Per</td><td>22</td><td>0.055</td><td>0.331</td></tr><tr><td>9</td><td>Amazon Cooperation Treaty Organization</td><td>OTCA_Inter</td><td>22</td><td>0.060</td><td>0.322</td></tr><tr><td>10</td><td>MAPBIOMAS</td><td>Mapbiomas_Tech</td><td>19</td><td>0.038</td><td>0.280</td></tr></tbody></table>

the weight in the identified links (Rohrschneider and Dalton 2002) (Table 3). In numerical terms, technological nodes are involved in 44% of the network's interactions (bidirectional links). Colombian and Peruvian institutions participate in 23% and 33% of the network interactions, respectively. Likewise, international institutions participate in 37% of the interactions.

## Country analysis

Extracting only the Colombian and Peruvian ties and nodes as a subgraph, no clear pattern of direct cooperation between the two countries was found, despite their shared common biome, border, and language. Transnational relations regarding Amazonian issues between the nodes of
<table><caption>**Table 2** Network participation in interactivity is simulated by categories (a) and isolated nodes (b)</caption><thead><tr><th>(a)<br>Categories</th><th>Network participation (%)</th></tr></thead><tbody><tr><td>Technological</td><td>23.7</td></tr><tr><td>International</td><td>21.1</td></tr><tr><td><strong>Peru</strong></td><td><strong>20.7</strong></td></tr><tr><td><strong>Colombia</strong></td><td><strong>14.1</strong></td></tr><tr><td>Net</td><td>9.6</td></tr><tr><td>USA</td><td>4.0</td></tr><tr><td>Brazil</td><td>2.2</td></tr><tr><td>Germany</td><td>0.9</td></tr><tr><td>Others</td><td>0.7</td></tr><tr><td>Ecuador</td><td>0.6</td></tr><tr><td>Norway</td><td>0.4</td></tr><tr><td>Venezuela</td><td>0.2</td></tr><tr><td>Switzerland</td><td>0.2</td></tr><tr><td>Canada</td><td>0.2</td></tr><tr><td>France</td><td>0.1</td></tr><tr><td>Bolivia</td><td>0.1</td></tr><tr><td>UK</td><td>0.1</td></tr><tr><td>Australia</td><td>0.05</td></tr><tr><td>Chile</td><td>0.05</td></tr><tr><td>Netherlands</td><td>0.05</td></tr><tr><td>Trinidad and Tobago</td><td>0.05</td></tr></tbody></table><table><thead><tr><th>(b)<br>Categories</th><th>Number of nodes isolated</th></tr></thead><tbody><tr><td>Technological</td><td>73</td></tr><tr><td>Net</td><td>25</td></tr><tr><td>International</td><td>25</td></tr><tr><td>Peru</td><td>20</td></tr><tr><td>Colombia</td><td>16</td></tr><tr><td>USA</td><td>4</td></tr></tbody></table>

these countries were not identified as a visible theme in the review of the sources, data, and public reports consulted.

The sub-network in Fig. 5 shows the cooperation and collaboration relationships at the institutional level of each country separately. In Peru, organizations such as SENAMHI (National Service of Meteorology and Hydrology), IIAP (Institute of Amazonian Research), and INIA (National Institute of Agrarian Innovation) stand out. Additionally, there is notable participation from multiple nodes, including regional governments, ministries, government agencies, and academic institutions, reflecting a greater internal interaction within the country on Amazonian issues. It is important to highlight that the Amazonian region of Peru encompasses a total of 220 districts (similar to municipalities). In Colombia, the most dynamic

organizations are CorpoAmazonia (Corporation for the Sustainable Development of the Southern Amazon), IDEAM, and Amazonian Institute of Scientific Research-SINCHI. Colombia's Amazonian region is comprised of only 69 political-administrative units (municipalities), indicating a less dense collaboration network compared to Peru.

## Role of technology nodes in the Colombian and Peruvian Amazon

The Colombian and Peruvian Amazon sub-network includes 51 technologies and platforms (Table S3, Supplementary Information). These technologies and platforms are categorized into two main groups: *Tools and applications* and *Data and information platforms*.

The *Tools and applications* group encompasses a wide range of tools, such as remote sensing (MAPBIOMAS 2024), drones for deforestation monitoring and territorial defense (ecoamazonia 2020), applications for monitoring illicit crops (Biesimci 2023), fire prediction models (SERVIR Amazonia 2023), and satellite images for detecting illegal mines (Universidad del Rosario 2022).

The *Data and information platforms* group includes satellite information for climate monitoring (NASA 2023), platforms for accessing climate and land-use data (SERFOR 2023), applications for monitoring native forest (OSINFOR 2023), water and meteorological sensors (SIAP + MICROS 2023), platforms for monitoring forest cover and change (SIAC 2024), portals with spatial data infrastructure on forest and wildlife data (SERFOR 2023), the environmental information system for the Amazon (SINCHI 2023), platforms for concessions and permits related to forest exploitation (OSINFOR 2023), and platforms for integrating georeferenced data (SENAMHI 2017).

These technologies and platforms consist of a total of 228 nodes and 318 connections, accounting for 40% of interactions in the total network (Fig. 6). These linkages are diverse and include technical cooperation, knowledge transfer, financing, and logistical assistance, among others. Two important nodes focus on forest monitoring: (1) *sm-byc_Tech*, the forest and watershed monitoring system in Colombia (IDEAM 2024), and (2) *geobosques_Tech*, the monitoring platform for tracking changes in forest cover in Peru (MINAM 2024). Another prominent node is *Map-biomas_Tech*, the annual mapping project of Amazonian land cover change, a project created in association with specialists from several Amazonian countries (MAPBIOMAS 2024). These networks involve diverse and multiple connections with Colombian, Peruvian, and international organizations. The technological nodes (*_Tech*), even when they are tools jointly developed with other
<table><caption>**Table 3** Combinations and frequency of linkages between groups of node categories</caption><thead><tr><th>Top</th><th>Node cat. partner1</th><th>Node cat. partner2</th><th>Ties Freq</th><th>% contribution total network ties</th></tr></thead><tbody><tr><td>1</td><td>Technological</td><td>International</td><td>68</td><td>8.64</td></tr><tr><td>2</td><td>Peru</td><td>Peru</td><td>66</td><td>8.39</td></tr><tr><td>3</td><td>Technological</td><td>Colombia</td><td>53</td><td>6.73</td></tr><tr><td>4</td><td>Technological</td><td>Peru</td><td>52</td><td>6.61</td></tr><tr><td>5</td><td>International</td><td>International</td><td>34</td><td>4.32</td></tr><tr><td>6</td><td>Peru</td><td>International</td><td>33</td><td>4.19</td></tr><tr><td>7</td><td>International</td><td>Technological</td><td>32</td><td>4.07</td></tr><tr><td>8</td><td>Colombia</td><td>Colombia</td><td>30</td><td>3.81</td></tr><tr><td>9</td><td>Peru</td><td>Technological</td><td>30</td><td>3.81</td></tr><tr><td>10</td><td>Technological</td><td>EEUU</td><td>30</td><td>3.81</td></tr><tr><td>11</td><td>Colombia</td><td>Technological</td><td>26</td><td>3.30</td></tr><tr><td>12</td><td>Colombia</td><td>International</td><td>24</td><td>3.05</td></tr><tr><td>13</td><td>International</td><td>Peru</td><td>23</td><td>2.92</td></tr><tr><td>14</td><td>Net</td><td>International</td><td>21</td><td>2.67</td></tr><tr><td>15</td><td>Net</td><td>Colombia</td><td>18</td><td>2.29</td></tr><tr><td>16</td><td>Peru</td><td>Net</td><td>17</td><td>2.16</td></tr><tr><td>17</td><td>International</td><td>Colombia</td><td>15</td><td>1.91</td></tr><tr><td>18</td><td>Colombia</td><td>Net</td><td>14</td><td>1.78</td></tr><tr><td>19</td><td>Net</td><td>Peru</td><td>14</td><td>1.78</td></tr><tr><td>20</td><td>Technological</td><td>Technological</td><td>13</td><td>1.65</td></tr></tbody></table>

<figure><img src="image_6.png" /><figcaption>**Fig. 5** Cooperative and collaborative efforts among institutions in both Colombia and Peru. Colombian sub-networks are on the left side of the figure, in blue; the Peruvian sub-networks are on the right side, in purple</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>**Fig. 6** Technology networks identified in the Colombian and Peruvian Amazon. The graph illustrates a bipartite network structure, comprising two distinct node types: technological and institutional (Zhou et al. 2007). The relationships between these nodes are bidirectional</figcaption></figure>

institutions, are playing transfer and bridging roles, and interacting with diverse partners.

## Communicability and fragility in network interactions

The results show that the 30 most centralized nodes have the highest propagation values across different diffusion rates (ranging from 0.2 to 0.9). Further information on the propagation of the communication is shown in Fig. S3, Supplementary Information. Consequently, a node with high centralization could disseminate and communicate ideas, projects, and technologies, leading to faster and denser propagation than the average node.

Conversely, the absence of a key actor could detrimentally impact the network, potentially resulting in structural friction or fragmentation, as well as a reduction in the collective capacity to disseminate technologies, information, and ideas within the network. Simulating the

absence of a key node highlights the crucial role of these nodes in the rapid spread of ideas, knowledge, or technology within the conservation and technology network of the Colombian and Peruvian Amazon.

The highest transfer contribution rate detected per node was 2.5%, attributable to the Amazon Scientific Panel (PCA_net). If this actor were to be removed, there could be a reduction in the transmission of information, ideas, and knowledge within the network by this amount. The data indicate the interaction capacity of the network could decrease by up to 38% in an extreme scenario where most central actors are excluded. This scenario could occur if there are political changes, changes in field operations by donor institutions, internal conflicts and crises, or lack of resources. This extreme scenario would affect 8% of the network, equivalent to 30 nodes, which play a significant role in dissemination and communication within the network (Fig. S4, Supplementary Information).
In a simulated scenario where key nodes such as tech-
nologies, different networks, and foreign countries are elimi-
nated, and only Colombian and Peruvian actors are considered,
the system's capacity for interaction could be reduced by 65%.
This happens because by eliminating the central nodes, the
actors are isolated, limiting collaboration and communication
among them (Table 2a). Likewise, it was possible to detect the
isolation of institutions where the institution connecting them
to their network is eliminated (Table 2b). The technological
nodes and other networks have the greatest potential to create
islands of isolated institutions when removed.

DISCUSSION

While this research shows a massive and complex rela-
tionship of more than 392 nodes (actors and technologies),
it also provides a high-resolution snapshot of a complex
system that is responding to the Amazon's accelerated
degradation. However, the research falls short of mapping
the totality of organizations and linkages that are operating
directly in the biome. Indeed, the effort is constrained by
difficulties in reaching respondents, and lack of funding,
field mobility, and security in the territory. Still, with the
integration of information to improve the interaction
between policy, community, and science, the study results
provided sufficient data to identify key global and local
patterns in this network. These include patterns related to
network dynamics, policy scenarios, and governance
implications, as described below.

Network dynamics

Usually, international technologies and organizations have
had an active participation as donors or technical support
providers. However, this study indicates that their role goes
beyond their geographic or organizational scope, acting as
a bridge that connects with local organizations.

According to our network map of technologies and
capacities transferred between actors, stakeholders are
configuring spaces for cooperative exchange between
(i) multiple technological nodes and (ii) technological and
institutional nodes. Technologies have the potential to
transcend their technical function, motivating collective
actions, information exchange, and social learning. Tech-
nological nodes play a key role in transmitting knowledge,
methods, and technology throughout the network. They
contribute 23% of the capacity and dynamics of interaction
between nodes. However, technological nodes also show
evidence of strong fragmentation within the network, with
73 isolated institutions (zero interactions) in an extreme
scenario of removal or total inaction. These nodes function
as bridges within the network links. When they are

removed or their operation is interrupted, other dependent
nodes will be disconnected.

The network reveals a pattern of scientific and techno-
logical cooperation between international organizations
and national agencies located in central cities outside the
biome. However, these interactions fail to reach local
communities (MinCiencias 2022). Similar studies on large-
scale technology developments and their transfer to local
territories in the Amazon have reported factors that rein-
force these cooperation systems (Lahsen and Nobre 2007).
They include the lack of accountability in research, failure
to report results and evidence, and the prioritization of
global and scientific interests over urgent local needs—all
factors leading to weak environmental outcomes. In this
regard, there is an opportunity to rethink current environ-
mental governance. Stakeholders can take advantage of this
research to more effectively channel the participation of
actors, resources, and knowledge toward cooperation
models with greater impact (Johnson et al. 2022).

Policy scenario

From a policy perspective, policymakers, local communi-
ties, and stakeholders should create a favorable environ-
ment for developing environmental technologies that are
easy to integrate into fieldwork, respond to challenges and
local needs (Krainovic et al. 2023), and improve the
applicability of public policies. The efforts should build
simple and understandable narratives, facilitating decision-
making and promoting inclusive exchanges at all geo-
graphic and institutional scales (Vincenzi et al. 2023).
Likewise, policies should develop initiatives to integrate
the local actors’ perspectives in the search for solutions to
curb environmental degradation. For example, local tech-
nical agroclimatic committees (MTAs, for their acronym in
Spanish) can seek common perspectives on problems and
solutions, fostering local networking (Castellanos et al.
2023).

Given the complexity and variety of challenges in the
biome, policymakers should generate adequate inputs for
prioritizing interventions in the Amazon. In other words,
policymakers must provide clear signals to the network of
institutions and technologies on where and how to inter-
vene. These signals or guidelines are key to improving the
impact of technologies and other actions on the ground.
They enhance the sustainability of these initiatives.
Stakeholders should facilitate and simultaneously monitor
temporary projects or organizations that undertake high-
impact actions. They should seek mechanisms for local
partners to sustain these actions over time, ensuring the
sustainability of development, experiences, and resources.

The international nodes transmit experiences and
knowledge about the protection of the Amazon relating to
these two countries (Valente 2012). In the Colombian and Peruvian Amazon, transnational and international nodes play a crucial role, contributing 24% to knowledge and technology transmission, and accounting for 37% of all documented links in the network. These networks indicate strong clustering of organizations rather than broad network participation (high modularity), low internal interaction among nodes (density), and a moderate number of nodes that serve as bridges between actors in the network (Biggs et al. 2015).

There is a notable disparity between national and international mobilization efforts to prevent Amazon degradation. At the national level, the concentration of responsibilities within a few nodes risks reinforcing ineffective strategies and groupthink (Matous and Bodin 2021). Empirical data suggest that national efforts often lack integration with international initiatives, leading to fragmented conservation strategies. Stronger collaboration between local and international organizations is essential. Enhanced communication can ensure cohesive strategies and improve the credibility and effectiveness of conservation initiatives.

## Governance implications

At local levels, there are critical implications for environmental policy and governance associated with the central and influential nodes: (a) the speed of action and the length of commitment of the central nodes (Ritvala and Salmi 2010)—given that they are key players, even if they are temporary organizations or special programs with a fixed duration—calls for regional research programs (RRP) or projects (Lahsen et al. 2013), and (b) the central nodes need to be well-resourced to maintain the level of energy demanded by the partnerships they have accumulated (Prell et al. 2009).

Environmental governance in the Amazon operates as a complex network involving interactions and actors working across different levels to protect the region. The network goes beyond traditional regional agreements and formalities, demonstrating effective transnational connections and knowledge sharing with international partners. Our research findings provide new insights for enhancing the environmental governance of the Amazon. Colombian and Peruvian stakeholders can improve their efforts by increasing connections with other countries, adopting environmental technologies, and strengthening relationships with local actors.

To strengthen environmental governance, three groups of actors should collaborate. First, funders could adjust their calls and priorities, encouraging research proposals focused on collaboration between communities and local organizations. They could prioritize innovations and

environmental technologies with the support of multi-actor and transboundary networks. Second, governments could mobilize transboundary cooperation agreements with their counterparts. They could develop joint projects and plans, creating strategies and incentives to increase the involvement of the national public sector in both countries. Third, all actors should maintain a map and inventory of platforms and technologies in the biome.

## CONCLUSIONS

The Colombian and Peruvian Amazon has a configuration of institutional and technological relationships that form a complex cooperation network that has received little research attention. This study's research maps the network of functional and relational links of institutional actors in the biome, identifying 392 nodes with interests in conservation, protection, and technology development. The analysis identified 793 interactions and relationships between institutions, configured as a dense relational structure in the institutional map. However, the results reveal a limited connection among local institutions and actors in both countries. Consequently, this fragile biome is protected by a network with a certain level of vulnerability at the interaction level. Eliminating 8% of the central network (30 nodes) can potentially reduce the capacity to transmit knowledge, methods, and technology by up to 38%.

Technological and international nodes play a fundamental role in connecting and energizing interactions to advance environmental conservation in the Amazon. These roles are manifested through building collaboration among actors and overcoming geographical and organizational limitations. The technological and international nodes represent 44% of all interactions, surpassing the share of interactions for Colombian (23%) and Peruvian (33%) nodes. International institutions are involved in 37% of the links, emphasizing the importance of foreign collaboration and the central role of technology in facilitating effective interactions in the network. Public and private institutions can improve their networks to better coordinate, strengthen, and promote effective actions for sustainable development. Treaties should be established not only between country governments, but between organizations and donors, making networking and cooperation more operational, effective, and collaborative in the biome. A notable case is the operational integration of the environmental technology Geobosques as a platform for monitoring land cover changes in the Peruvian Amazon. This platform is disseminated through various interoperability systems to the public, supported by a national forest conservation program for climate change mitigation (PNCBMCC). This operation receives international support
from the World Wildlife Fund (WWF), the United States Agency for International Development (USAID), and organizations such as Global Forest Watch, as well as collaboration from forestry and wildlife authorities like SERFOR, regional governments, and information systems like National Forestry and Wildlife Information System (SNIFFS) and National Environmental Information System in Peru (SINIA). In this sense, local organizations could increase their political and strategic influence by engaging with the key actors identified in this study. This would allow them to improve access to information, resources, technologies, and political spaces, for an impactful management of the Amazon biome's conservation.

**Acknowledgements** We thank the following researchers and groups for their advice and support to this research: the SERVIR-Amazonia program; our colleagues of the Catalyzing and Learning through Private Sector Engagement for Biodiversity Conservation (AL-PSE) project in Brazil, Sylvia Mitraud and Vivian Zeidemann; the Amazon Environmental Research Institute (IPAM) researchers; the Performance, Innovation and Strategic Analysis for Impact (PISA4) Program of the Alliance of Biodiversity International and CIAT; and Glenn Hyman, consultant editor to the Alliance of Biodiversity International and CIAT Science Writing Service.

**Author contributions** Carlos Eduardo González Rodríguez: Investigation, Writing—Original Draft and Review, Data Curation, Formal Analysis, Conceptualization. Oscar Buitrago-Bermúdez: Writing—Original Draft, Conceptualization. Jean Francois Le Coq: Conceptualization, Writing—Original Draft. Carolina González: Conceptualization, Writing—Draft and Review. Johana Marcela Castillo Rivera: Corresponding Author, Writing—Original Draft, writing editor.

**Data availability** We declare that the data used to construct the figures, tables, and results can be found in the supplementary material, freely accessible to readers. The processes performed in R Studio can also be provided upon reader request.

## Declarations

**Conflict of interest** The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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## AUTHOR BIOGRAPHIES

Carlos Eduardo González-Rodríguez is doctoral candidate in environmental science and Senior Research associate in international Center for Tropical Agriculture-CIAT. His research interests include social network analysis and climate change.

Address: International Center for Tropical Agriculture-CIAT, Cali, Colombia.

Address: Universidad del Valle Colombia, Cali, Colombia.

e-mail: c.e.gonzalez@cgiar.org

Oscar Buitrago-Bermúdez is PhD in Geography and professor in University of Valle. His research interests include territory, geography and environmental science research.

Address: Universidad del Valle Colombia, Cali, Colombia.

e-mail: oscar.buitrago@correounivalle.edu.co

Jean-Francois Le Coq is PhD in Agro-economist and research in agronomy department of the Center for International Cooperation in Agronomic Research for Development (CIRAD). His research interests include.

Address: Center for International Cooperation in Agronomic Research for Development-CIRAD, Paris, France.

Address: Universidad Federal Rural Rio de Janeiro, Rio de Janeiro, Brazil.

e-mail: jean-francois.le_coq@cirad.fr

Carolina Gonzalez is PhD in Agricultural Economics and Research and thematic leader in international Center for Tropical Agriculture-CIAT. Her research interests include evaluation projects with different international, ONGs and governmental institutions as the World Bank, GEF, NARs, Agriculture and Environmental Ministries, among others.

Address: International Center for Tropical Agriculture-CIAT, Cali, Colombia.

e-mail: c.gonzalez@cgiar.org

Johana Marcela Castillo-Rivera (✉) is specialist in government and public policy and research associate in international Center for Tropical Agriculture-CIAT. Her research interests include food system and climate change.

Address: International Center for Tropical Agriculture-CIAT, Cali, Colombia.

e-mail: j.castillo@cgiar.org