Community-based Monitoring Design and Implementation in Mangrove Restoration: Guidelines for Restoration Monitoring
0 likes106 views
The document provides comprehensive guidelines for community-based monitoring and implementation of mangrove restoration, including steps for designing monitoring plans, defining objectives, and selecting indicators. It emphasizes the importance of community participation in the monitoring process and introduces tools for data management, including a mobile app and dashboard for tracking restoration progress. Additionally, the document highlights adaptive management practices to address disturbances and ensure effective restoration outcomes.
Community-based Monitoring Design and Implementation in Mangrove Restoration: Guidelines for Restoration Monitoring
- 1. Organized by: In partnership with: Community-based Monitoring Design and Implementation in Mangrove Restoration Beni Okarda Guidelines for Restoration Monitoring
- 2. Design Monitoring Plan Organized by: In partnership with:
- 3. Design Monitoring Steps Organized by: In partnership with: RECORDING AND REPORTING SHORT TERM MONITORING DEFINE MONITORING OBJECTIVES SELECT MONITORING INDICATORS ESTABLISHED MONITORING PLOT ADAPTIVE MANAGEMENT AS RESPONSE TO SHORT TERM MONITORING CONTINUE RECORDING AND MONITORING FOR LONG TERM MONITORING
- 4. DEFINE MONITORING OBJECTIVES AND INDICATORS
- 5. Monitoring Objectives Organized by: In partnership with: EVALUATE RESTORATION PROGRESS IDENTIFY DISTURBANCES MEASURE BENEFI T TO ECOSYSTEM ADAPT MANAGEMENT STRATEGY
- 6. Organized by: In partnership with: Select Monitoring Indicators Survival Rate Carbon Sequestration Disturbances Seediling Growth Rate Inundation Precipitation
- 8. Restoration area divided into smaller observation areas using grids. Divide the monitoring unit into smaller areas will ease the field observation process when counting and recording the number of survived seedlings. The monitoring grid also useful as an address to locate the monitoring subject if needed. We also suggest that the grid can be set before planting, as the grid can be used as guidance in planting process as well. Established the Monitoring Grid
- 9. Organized by: In partnership with: Monitoring Grid Setup Digital gr id m ap gener ated fr om r em ote sensing im ages Def ine G r id Size ( 20x20 met er or 10x40 met er r ect angle gr id) Mar k gr id boundar ies with poles and labels. Acquir ing GPS coor dinates of the gr id r ectangles
- 10. Organized by: In partnership with: Labelling
- 11. Collaborative Planning and Training • In context of community-based mangroves restoration, community participation is the main actor on monitoring process. • To ensure all the measurement processes are followed the standard procedure, training and mentoring are required at the beginning of the monitoring phase
- 12. Organized by: In partnership with: Monitoring team
- 14. Organized by: In partnership with: Survival Rate Method Communities doing census for mangrove survival monitoring using hand counters Hand Counter
- 15. Organized by: In partnership with: Survival Rate Example Equation Average Species Survi val Rate Chart for Phase 1 Average Species Survi val Rate Chart for Phase 2 Average Species Survi val Rate Chart for Replanti ng Phase Frequency Where, ti is time at monitoring and t0 is time at planting.
- 16. Organized by: In partnership with: Disturbance Method Observation through site walkthrough Type of Disturbance in Mangrove Seedling Pest
- 17. Organized by: In partnership with: Disturbance Marine liters Ferns Draught
- 18. Organized by: In partnership with: Growth Rate Method The locations of the sampled trees in monitoring plots should be documented. Height Measurement DRC measurement using vernier caliper
- 19. Organized by: In partnership with: Frequency Growth Rate Example Height Growth Model Equation Where Y is the yield (DBH, height, volume, etc) and t is the time of measurement. R² = 0.9949 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 0 10 20 30 40 50 60 Average Height (M) Month BG Monitoring Projection Expon. (Monitoring) R² = 0.9469 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 0 10 20 30 40 50 60 Average Height (M) Month KC Monitoring Projection Expon. (Monitoring) R² = 0.9413 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 0 10 20 30 40 50 60 Average Height (M) Month RM Monitoring Projection Expon. (Monitoring) R² = 0.9747 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 0 10 20 30 40 50 60 Average Height (M) Month RA Monitoring Projection Expon. (Monitoring)
- 20. Organized by: In partnership with: Frequency Growth Rate Example Average Height Equation Average Species Height Chart for Phase 1 Average Species Height Chart for Phase 2 Average Species Height Chart for Replanti ng Phase Where Y is the yield (DBH, height, volume, etc) and t is the time of measurement. AM; 33.0 BG; 66.0 KC; 137.0 RA; 105.9 RM; 107.2 RS; 78.0 SA; 124.4 SC; 141.0 0 20 40 60 80 100 120 140 160 07-2023 10-2023 01-2024 04-2024 07-2024 10-2024 Average Height (cm) Monitoring Month Average Height Species Phase 1 BG; 66.3 KC; 101.4 RA; 52.1 RM; 91.5 0 20 40 60 80 100 120 07-2023 10-2023 01-2024 04-2024 07-2024 10-2024 Average Height (cm) Monitoring Month Average Height Species Phase 2 RM; 61.9 48 50 52 54 56 58 60 62 64 07-2023 10-2023 01-2024 04-2024 07-2024 10-2024 Average Height (cm) Monitoring Month Average Height Species Replanting Phase
- 21. Organized by: In partnership with: Carbon Benefit Method Allometric Equation Development
- 22. Organized by: In partnership with: Carbon Benefit Example | Allometric R² = 0.9181 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 0.0 0.5 1.0 1.5 2.0 2.5 Total biomass (Kg) Height (M) BG R² = 0.8263 0.0 0.5 1.0 1.5 2.0 2.5 0 0.5 1 1.5 2 Total Biomass (Kg) Height (M) KC R² = 0.8818 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Total Biomass (Kg) Height (M) RM R² = 0.9012 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 0.0 0.5 1.0 1.5 2.0 2.5 Total Biomass (Kg) Height (M) RA
- 23. Organized by: In partnership with: Carbon Benefit Example | Allometric
- 24. Organized by: In partnership with: Carbon Benefit G r o w t h p r o j e c t i o n f o r t h e s p e c i e s R M , R A , B G , a n d K C H e i g h t G r o w t h a n d S e q u e s t r a t i o n P r o j e c t i o n S e q u e s t r a t i o n p r o j e c t i o n f o r t h e s p e c i e s R M , R A , B G , a n d K C BG; 3.14 KC; 5.61 RA; 5.38 RM; 5.15 0.0 1.0 2.0 3.0 4.0 5.0 6.0 1 2 3 4 5 Average Height (M) Year BG KC RA RM BG; 50.1 KC; 75.8 RA; 91.8 RM; 65.6 0 10 20 30 40 50 60 70 80 90 100 1 2 3 4 5 TCO2e /Ha Year BG KC RA RM
- 25. Organized by: In partnership with: Carbon Benefit Example Output *) Projection
- 26. Organized by: In partnership with: Environment Condition Method 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Tides (m) Date & Time Tides Vs Date Time (December 2024) Sample of Tides Vs Time Data from SMART project Sample of precipitation and inundation period from SMART project
- 28. Data collection is important to inform decisions or as input for adaptive management, however if the data are not properly managed or are not discoverable, they are of limited use (Raynie et al., 2020). In SMART project, we demonstrated the use of Community Based Restoration Monitoring System (CBRMS), a CIFOR-ICRAF Flagship Product (FP). The system consists of two main tools: an android based mobile app to input data from restoration areas and an interactive dashboard providing information of restoration progress Data Management and Reporting
- 29. Organized by: In partnership with: CBRMS • Mobile app for data collection • Data analytic • Dashboard for visualization • Cloud database https://data.cifor-icraf.org/cbrms/
- 30. Organized by: In partnership with: CBRMS
- 31. Organized by: In partnership with: CBRMS App - Sample Form
- 32. Organized by: In partnership with: CBRMS App - Dashboard
- 33. Organized by: In partnership with: CBRMS App - Dashboard Site Page
- 35. Adaptive Management • Adaptive management in ecological restoration is a form of structured and iterative process of “learning-by-doing” and decision-making in respond to continuous change • In our case, most of decisions came out of monitoring results were to address disturbances. Routine monitoring has informed us the importance of doing maintenance such as weeding, collecting trash, etc.
- 36. Organized by: In partnership with: Adaptive Management Implemented in Our Site Weeding Pulling out bamboo tubes from older sapling Blocking canals to prolonged inundation period and trap the sediment Applying systematic insecticide to fight woodborer pests
- 37. Reference Kershner, J.L. (1997) ‘Monitoring and adaptive management’, in J.E. Williams, C.A. Wood, and M.P. Dombeck (eds) Watershed Restoration: Principles and Practices. Bethesda, Maryland: American Fisheries Community, pp. 116–131. Herrick, J.E., Schuman, G.E. and Rango, A. (2006) ‘Monitoring ecological processes for restoration projects’, Journal for Nature Conservation, 14(3–4), pp. 161–171. Available at: https://doi.org/10.1016/j.jnc.2006.05.001. Sprenkle-Hyppolite, S. (2022) Tree Restoration Monitoring Framework: Field Test Edition. Biswas, S.R. et al. (2018) ‘Plant invasion in mangrove forests worldwide’, Forest Ecology and Management, 429, pp. 480–492. Available at: https://doi.org/10.1016/j.foreco.2018.07.046. Martínez-Garza, C., Bongers, F. and Poorter, L. (2013) ‘Are functional traits good predictors of species performance in restoration plantings in tropical abandoned pastures?’, Forest Ecology and Management, 303, pp. 35–45. Available at: https://doi.org/10.1016/j.foreco.2013.03.046. Raynie, R. et al. (2020) ‘Coastal monitoring and data management for restoration in Louisiana’, Shore & Beach, pp. 92–101. Available at: https://doi.org/10.34237/10088111.
- 38. Thank you! Organized by: In partnership with: