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Network and spatial analysis for forest governance

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Presented by Dr. Matt Hamilton, The Ohio State University, USA and Dr. Caleb Gallemore, Lafayette College, USA, on 10 November 2020 at "International workshop: Enhancing wetland management and sustainable development"

Published in: Environment
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Network and spatial analysis for forest governance

  1. 1. Network and spatial analysis for forest governance
  2. 2. Network analysis: A set of approaches for understanding interactions
  3. 3. Network analysis: A set of approaches for understanding interactions ??? What is the structure of those interactions?
  4. 4. Network analysis: A set of approaches for understanding interactions ??? What explains the structure of those interactions? ??? What is the structure of those interactions?
  5. 5. Network analysis: A set of approaches for understanding interactions ??? ??? What are the implications of those interactions? What explains the structure of those interactions? ??? What is the structure of those interactions?
  6. 6. Components of a network: nodes and links Representation LinksNodes people, organizations, institutions, concepts/factors, places, habitat patches… collaboration, exchange of information, co-occurrence, biophysical connectivity... capacity, economic sector, preferences, location, size, type… direction (or lack thereof), frequency, magnitude, sign, type… Measurement
  7. 7. Different levels of network analysis / Examples of research questions Node-level: Do local conservation groups have more influence (e.g., more incoming links) than local authorities? Substructure-level: Which types of organizations broker the exchange of information about PES between communes and provincial-level organizations? Network-level: How well connected are forest governance networks?
  8. 8. • People connect with visualizations of networks – opportunities for engagement with stakeholders and decision-makers. • Highly appropriate methodology for studying collaborative resource management, coupled human-natural systems, and other environmental social science fields that emphasize relationships. • Increasingly accessible and powerful tools for data collection, analysis, and visualization. • Network perspectives are increasingly common (and expected) in many environmental social science fields. Strengths & Opportunities This is my reality!
  9. 9. • Respondent fatigue • Network analysis is more sensitive to missing data (because observations are interdependent). Weaknesses & Challenges • Can be difficult to identify the boundary of a network. • Conceptualizing a complex system as a network requires simplification and abstraction.
  10. 10. How networks help us understand forest governance Collaboration between two organizations Organization Organization Organizations collaborate for many different reasons. What predicts collaboration among organizations involved in PFES/REDD+?
  11. 11. How networks help us understand forest governance Collaboration between two organizations after participating in the same PFES or REDD+ workshop Organization Organization If organizations participate in the same workshops, are they more likely to collaborate in the future? If so, workshops may be playing an important role in sparking cooperationWorkshop
  12. 12. How networks help us understand forest governance Collaboration between two organizations that work in the same place Organization Organization If organizations work in the same place, are they more likely to collaborate? If so, those partnerships can help organizations avoid inefficiencies Place
  13. 13. Exploring these questions by bringing together multiple network datasets Organization Organization Longitudinal collaboration network from REDD+ Policy Network Study Longitudinal network of organizations participating in REDD+ and PFES workshops Network of where organizations work WorkshopOrganization Organization Place
  14. 14. Preliminary results from network model (stochastic actor oriented model) Model 1 Rate parameter period 1 7.39 (0.49)*** Rate parameter period 2 5.58 (0.45)*** Outdegree (density) -1.61 (0.18)*** Reciprocity -0.00 (0.20) Organizations co-attended workshops in prior time period 0.53 (0.22)* Organizations work in the same place -0.31 (0.15)* Governmental organization 0.51 (0.33) Collaboration between governmental organizations 0.56 (0.20)** Iterations 2669 ***p < 0.001, **p < 0.01, *p < 0.05
  15. 15. Yes, organizations that attended the same workshops are more likely to collaborate in the future! Model 1 Rate parameter period 1 7.39 (0.49)*** Rate parameter period 2 5.58 (0.45)*** Outdegree (density) -1.61 (0.18)*** Reciprocity -0.00 (0.20) Organizations co-attended workshops in prior time period 0.53 (0.22)* Organizations work in the same place -0.31 (0.15)* Governmental organization 0.51 (0.33) Collaboration between governmental organizations 0.56 (0.20)** Iterations 2669 ***p < 0.001, **p < 0.01, *p < 0.05
  16. 16. But organizations that work in the same places are more less likely to collaborate! Model 1 Rate parameter period 1 7.39 (0.49)*** Rate parameter period 2 5.58 (0.45)*** Outdegree (density) -1.61 (0.18)*** Reciprocity -0.00 (0.20) Organizations co-attended workshops in prior time period 0.53 (0.22)* Organizations work in the same place -0.31 (0.15)* Governmental organization 0.51 (0.33) Collaboration between governmental organizations 0.56 (0.20)** Iterations 2669 ***p < 0.001, **p < 0.01, *p < 0.05
  17. 17. Taking stock of (preliminary!) results In addition to disseminating information and training participants, workshops may also catalyze collaboration, which can contribute to more cohesive forest governance Organizations seem to avoid one another when working in the same areas. This may present challenges for coordination of forest management activities
  18. 18. Combining Network Analysis and Geographic Information Science (GIS)
  19. 19. Imagine a forest patch . . .
  20. 20. It doesn’t exist on its own.
  21. 21. It is part of an infinite number of networks.
  22. 22. Ecological networks, like wildlife corridors . .
  23. 23. Or watersheds . . .
  24. 24. Economic networks, like global supply chains.
  25. 25. Governance networks, like PFES Regions.
  26. 26. Information networks, like for REDD+.
  27. 27. Our patch exists because of the networks.
  28. 28. And it is important because of networks.
  29. 29. So let’s think about some of these networks together. Corridors Watersheds Governance Supply Chains Information
  30. 30. New Partnerships for Sustainability (NEPSUS) Project, Tanzania • Coordinated by Stefano Ponte at Copenhagen Business School and Christine Noe at University of Dar es Salaam • Studies three different natural resource sectors:
  31. 31. Forest Case, with Lasse Folke Henricksen & Kelvin Kamnde
  32. 32. Examining how network patterns affect performance of village livelihood forest reserves with Forest Stewardship Council certification
  33. 33. A complex governance network
  34. 34. Key independent variables: longitudinal network data ● Number of civil society ● Number of private sector ● Percentage of completed triangles
  35. 35. Network structure and membership predict forest loss!
  36. 36. (Very!) Preliminary results for payments for ecosystem services (PFES) in Vietnam
  37. 37. Assessing PFES in Vietnam • Random nation-wide sample of 250,000 pixels that were forested as of 2000 from Global Forest Watch data, combined with random sample of 250,000 pixels that were forested in 2000 but deforested by 2018 • Data on provincial activities carried out by organizations recorded as active in REDD+ and/or PFES by CIFOR’s GCS-REDD studies carried out since 2010 • Control variables - elevation, terrain ruggedness, surrounding cropland, distance from road • Random effects by region (will move to province with a larger sample)
  38. 38. Deforestation declines substantially when PFES becomes active.
  39. 39. Deforestation declines moderately when additional organizations are active in the province.
  40. 40. Summary • Conservation efforts take place in a complex network of processes • Emerging evidence both institutional (policy) and relational (network) variables affect success in stemming forest loss • Network building for conservation isn’t just about building bigger networks, but also about building networks with the most effective structures
  41. 41. Questions/Discussion? • Matthew Hamilton, The Ohio State University, hamilton.1323@osu.edu • Caleb Gallemore, Lafayette College, gallemoc@lafayette.edu

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