Tailoring forest inventories and biodiversity monitoring for Tanzanian Communities with the United States Forest Service
MCDI and The United States Department of Agriculture (USDA) Forest Service (FS) entered into a partnership in 2015. Through this partnership, the USDA-FS is leveraging its resources and expertise enable to help us and our partner, Kilwa District Council, to advance our mission and vision for certified community-based forest management in South-Eastern Tanzania.
Technical experts from USDA-FS have visited us on five occasions to provide their hands-on support. Previous technical missions have focused on building our in-house skills and capacity in geographic information systems (GIS), biodiversity monitoring and forest inventory, as well as providing GPS units, wildlife cameras and other tools and equipment (e.g. ESRI ArcMap software). (Read more about USDA-FS's support to us on GPS units here and wildlife cameras here.)
This week, we’re lucky enough to have five experts from the USDA-FS with us for their 6th technical support mission. For eight days, we will be working together in both the office and in the field to set up and test systems and protocols to improve our forest inventory and biodiversity monitoring in communities.
Based on observations and recommendations developed during their last technical mission in 2018, the three key areas of our participatory forest inventory method that we are focusing on improving are:
- Broadening the scope of our inventory approach to include not only trees that villages plan to harvest, but also other trees as well. This will help to give us an communities a more rounded, holistic understanding of the composition and plant biodiversity in their forests. In turn, this can provide useful insights into how to improve their management.
- Including measures of forest regeneration in forests through regular fixed plots along transects. Previously, our inventory has focused on measuring trees in three size classes: extra large trees, harvestable trees and trees that are too small to be harvested (i.e. the cohort that we expect to replace trees harvested in the forest in the next 5 to 10 years). Expanding this further to include measures of new growth of seedlings and saplings will also enable us to assess and monitor the ability of forests to replenish themselves 20 to 50 years down the line.
- Slowing down and running some tests to assess the accuracy of data being collected in the field. For example, through conducting repeatability tests whereby two teams walk the same transect, one after the other, and then come together to compare results. Differences in the data collected by the two teams will provide us with an indication of how consistent we are at measuring trees in the forests, and where we need to improve our procedures to increase the accuracy of forest inventory results.
The three key aspects of our biodiversity monitoring that we are working to improve are:
- Identifying good indicator bird species for Miombo woodlands – Previously, our biodiversity monitoring has focused on three species of bird which are good indicators of Coastal Forest health. We prioritised this habitat due to its high conservation value and because it is a biodiversity hot spot of global concern. However, one of the key questions we want to answer through our biodiversity monitoring is whether sustainable timber harvesting is having an impact on forest health. Since most of selecting logging by communities takes place in Miombo woodlands, it is important that we find a selection of species that we can use as indicators of the health of this habitat as well. The trick is that they also need to be easily identifiable by communities and, in the case of birds, to make themselves known to our monitoring teams through their calls.
- Harmonising our biodiversity monitoring and forest inventories, so that these take place along the same transects. This will enable us to identify patterns and to make more robust observations about the links between changes in local wildlife and forest stand composition over time.
- Improving our monitoring of more obscure wildlife through camera traps, by comparing detection between habitat types (Miombo, Coastal Forests and Riparian zones) and using different lures to attract animals to the cameras (feathers, fatty acid tablets and CDs). Read more about our work with camera traps here.