Community-based forest monitoring in North Rupununi, Guyana

Map of participatory monitoring location
Northern Rupununi, Guyana
Participatory forest monitoring in Guyana
Training in North Rupununi
Key Lessons 
  • Communities in North Rupununi are able to collect, and train other communities to collect, information on forest change, wellbeing and resource use that is useful for both local and national stakeholders.
  • Communities were able to carry out data analysis, which is usually carried out by external experts. However, some ongoing technical support is still needed in data reporting.
  • While using smartphone technology and the internet brought benefits (e.g. accuracy and speed), it also introduced challenges in training and data analysis, and represented significant costs. The trade-offs in using technology for community based monitoring should be further explored prior to pursuing similar initiatives.
  • Building local data management capacity and developing a data sharing protocol were important for establishing clear principles on data ownership and security.

Since 2011, the project has been working with sixteen Amerindian communities of the North Rupununi, Guyana. It aims to build local capacity to develop and run a community based monitoring system to inform decision-making on territorial management, and to develop sub-national measurement, verification and reporting (MRV) within the national REDD+ programme in Guyana.

Guyana has a high level of forest cover of approximately 85%, and low deforestation rates. However, the country faces an increasing risk of deforestation. The North Rupununi region is increasingly threatened by the development of Guyana’s interior, which is being driven by mining and timber extraction. In the North Rupununi region, participating communities identified farming as the main local driver of deforestation and forest degradation, but also logging and the development of community infrastructure.

The data generated through the project provides local communities and government institutions with baseline information on drivers of forest loss, changing land use practices and socio-economic issues. This information can help improve management strategies and strengthen local institutions, and to inform external intervention programmes in the region.  In addition, the results and experiences of this project are being integrated into wider initiatives for reducing carbon emissions from deforestation and forest degradation (REDD+) currently being developed in Guyana.

The community-based monitoring project in North Rupununi is coordinated by the Global Canopy Programme in collaboration with sixteen villages represented by the North Rupununi District Development Board (NRDDB), and supported by the Iwokrama International Centre for Rainforest Conservation and Development (IIC). It is funded by the Norwegian Agency for Development Cooperation (NORAD).

International Forest Agenda/s 
Monitoring Theme/s 
Carbon biomass
  • Tree species 
  • Vegetation cover density (primary, secondary, fallow)
  • Diameter at breast height (DBH)
  • Soil type
  • Slope of terrain
  • Height of forest
  • Plot GPS location
Natural resources


  • Number households extracting timber 
  • Frequency and seasonality of extraction
  • Quantity extracted (m3/month/species)
  • Extraction methods and operation size
  • Species preference 
  • Perceived timber scarcity over 5 years
  • Extraction location
  • Occurrence of illegal extraction
  • Quantity commercialisation
  • Demand/price per species of timber



  • Number households extracting NTFP
  • Seasonality of extraction
  • Quantity extracted (KG/month/household)
  • Extraction methods
  • Species preference and demand demand (price/species)
  • Perceived scarcity over 5 years
  • Extraction location



  • Number households extracting fish 
  • Seasonality and frequency of extraction
  • Quantity extracted (KG/monthly)
  • Extraction methods (techniques and tools)
  • Species preference 
  • Extraction effort and time
  • Quantity commercialised and price by species
  • Perceived fish size changes over 5 years
  • Perceived fish scarcity over past 5 years/availability and location
  • Extraction location, distance
  • Occurence of illegal extraction
  • Perceptions on sport fishing
  • Effectiveness of Management plans (rules and enforcement)



  • Number HH extracting game
  • Seasonality of extraction
  • Quantity extracted (units/monthly)
  • Hunting methods
  • Species preference and demand (price per species)
  • Quantity commercialised
  • Extraction location 
  • Occurrence of illegal hunting
  • Perceived scarcity, availability and location of game



  • Water extraction points and sources
  • Quantity (litres) extracted monthly
  • Extraction methods
  • Proximity of contaminants to water sources
  • Water treatment frequency
  • Perceived threats and changes to water quality and quantity
  • Vegetation cover near water sources
Wellbeing & social issues

Employment & enterprise

  • Frequency of out-migration (past 6 months)
  • Perceived community development
  • Number of HH that access to financial loans
  • Number and type of community businesses
  • Cost of basic items


Social relations &  governance

  • Frequency of food exchanges
  • Number of households participating in village activities
  • Households married or in long-term partnership
  • Incidence of resource conflict
  • Number of households with extended family support
  • Existence of communication infrastructure
  • Attendance of village meetings
  • Perceived level of cooperation
  • Perceived quality of village leadership


Culture & believes

  • Frequency and number of church attendance
  • Number of households speaking native language
  • Purchase of food and water
  • Existence of traditional activities
  • Building material preference



  • Occurrence of theft
  • Frequency of alcohol-related incidents (past 6 months)
  • Frequency of illegal activities (past 6 months).
  • Frequency and perceived length of flooding and droughts
  • Vehicle volumes per day



Education & skills

  • Number of people with official education
  • Number education facilities in the community
  • Perceived quality of  education services
  • Time and costs in accessing educational services



  • Self-reported health and emotional wellbeing
  • Perceived frequency of diseases
  • Health facilities in the community
  • Number of households with potable water,
  • Distance from contaminants
  • Perceived quality of health services
  • Number of leisure and sport facilities
  • Water treatment and waste disposal
  • Number of road accidents
  • Time and costs in accessing health services


Deforestation drivers
Land use change
  • Location and area (ha) under commercial and traditional farming
  • Estimated production quantity (kg/hectare)
  • Types of crops grown
  • Farm inputs and machinery used
  • Distance from road infrastructure
  • Frequency and quantity of crop and timber commercialised

Policy context

Guyana is actively pursuing a REDD+ agenda through its Low Carbon Development Strategy, a national plan to reorient Guyana’s economy and move towards more sustainable extractive industries and forest management. A bilateral agreement between the governments of Guyana and Norway establishes a framework for performance-related finance for the implementation of the Low Carbon Development Strategy.

By gathering data on wellbeing and social structure, indigenous land tenure regimes, natural resource use, community forest carbon stocks and land use change, this project is informing the development of a national forest monitoring and safeguard information system as part of the Low Carbon Development Strategy. It is hoped that the results of this initiative will generate information to improve local resource management, and move scientific and policy discussions on REDD+ and indigenous participation forward at the national and international levels.

Community participation 

With the increasing development of Guyana’s interior, there has been growing awareness amongst Amerindian communities of the importance of sustainable forest, and interest in how monitoring could support these efforts. 

To ensure the project was aligned with the needs of the local communities, discussions were held during the design of the project with the NRDDB, the community-based institution which represents the sixteen villages in the region. The final project proposal was approved and endorsed by the communities. The monitoring themes were identified based on interests expressed by the toshaos (the democratically elected village leaders of their communities), village councillors and wider community members. These were then prioritised according to their relevance for management decisions at the village and district level (community goals) and for REDD+ (government goals).

Five local project management team members and 32 community monitors were recruited from the 16 villages to run the monitoring programme. The monitors were paid a salary equivalent to that of the average local teacher.

Data analysis and management initially relied upon external support, but after training and the adoption of more user-friendly software the project staff gradually took over this process, although external analytical, IT and GIS support was still required.

Working with a local team and community leaders was essential for strengthening community ownership, building local capacity, building trust, and running a fully participatory project.

The use of mobile phone technology also encouraged collaboration between elders with knowledge about natural resources and young people who were quick to pick up the mobile handsets.

Monitoring methodology

Questionnaires were created to collect data on the following broad key themes: forest change, natural resources, wellbeing, and project impacts.

Monitoring forest change

A series of workshops were held with community members to identify the main forest disturbance activities. It was agreed that monitoring the impacts of community farming practices on forest change should be prioritised.

Community monitors then carried out a survey of active and fallow farms, recording the location, area, crop types and surrounding vegetation of each farm plot they visited. More detailed information on traditional farming practices was collected through structured interviews with land owners. Mobile phones were used to record the boundaries of the farmland, and the results were presented visually using Google Maps Engine.

The monitors also carried out on-the-ground verification (ground-truthing) of government maps of forest change based on LANDSAT images, For this, they used a systematic sampling approach over a 250m grid. They also estimated above-ground biomass within woodland and agricultural land, using radial nested plots.

Monitoring natural resource use and availability

Qualitative and quantitative information on water use, timber and non-timber harvests, and fishing and hunting practices was gathered by the monitors through facilitated group discussions with top extractors and semi-structured household interviews.

Community resources were mapped, taking in burial sites, tourism zones, community infrastructure (e.g. roads, schools, health posts), hunting grounds, fishing areas, farms, forest conservation areas, and titled lands.

Monitoring wellbeing

The monitors carried out interviews with members of households and village councils, to assess wellbeing and understand wider inter-communal issues. These interviews explored issues such as community relationships, safety, income and assets, health and emotional wellbeing, and education.

Monitoring project impacts

An interim project impact assessment was carried out so that any lessons learned could inform and improve the project. Feedback questionnaires, group interviews and participatory workshops were used to gather a broad range of perspectives on the positive and negative impacts of the project.

The assessment highlighted a need to enhance channels of communication between the project team, partners and the wider community. This was successfully addressed through improved communication and outreach.

Digital technology

The questionnaires on forest change, natural resources, wellbeing, and project impacts were created and mounted onto Android (Samsung) smartphones using Google’s Open Data Kit (ODK) software suite.

Community monitors then used the smartphones to collect and manage data offline, using the ODK software. Once collected, the data were transferred to a central computer to be uploaded to an online data storage system and analysed.

Analysis was carried out using a range of tools including Microsoft Excel, Arc GIS, and ODK Aggregate, and later SMAP software, QGIS, and Google Maps Engine.

Achievements and challenges

The project was successful in training participants from the communities to use the technology and methodology, and deliver workshops. Local staff were also able to process and analyse the data collected - a role which is often carried out by external experts. The success of the training was clearly demonstrated when community members from North Rupununi led a training programme on forest monitoring, sharing their skills with people from Wai-Wai communities in south Guyana.

Developing the communities’ capacity to manage and analyse the data themselves was also an important aspect of respecting and facilitating their ownership and control of the data. A data sharing protocol was established to address concerns raised by the communities about ownership and security.

In addition, all project participants learned about climate change, ecosystem services, Monitoring, Reporting, and Verification (MRV), Guyana’s Low Carbon Development Strategy and the principles of Free, Prior and Informed Consent (FPIC).

The use of digital technology enabled real time and straightforward collection of data, and removed the need to transcribe data from the field. Increasing the efficiency of data collection and transfer is fundamental to scaling up community based monitoring.

However, the new technologies that were tested and adopted also introduced significant challenges. For example, once data had been collected and uploaded, considerable effort was needed to analyse data because of the design and format of ODK forms used in data collection. More importantly, poor internet connectivity in North Rupununi meant that the project’s reliance on the internet was problematic. This affected data uploading and access, and proved to be the biggest bottle-neck for data analysis and reporting back to communities. (See the links on this page for guidance on the use of ODK.)

While community based monitoring may lower the cost of data collection over time, this project also showed that the high initial and ongoing costs of the technology, and of developing local capacity building programmes, are a key challenge for scaling this model. However, the success of the community-to-community training course led by the North Rupununi participants demonstrated that monitoring skills can subsequently spread in a cost-effective way.

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