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Cycle 5 (2015 Deadline)

Using multi data for biodiversity conservation at Dak Nong Province in the Central Highlands of Vietnam

PI: Nguyen Thi Thanh Huong (, Tay Nguyen University
U.S. Partner: Volker Radeloff, University of Wisconsin–Madison
Project Dates: December 2016 - November 2019

Project Overview:

5-253 Forest Data Collection
The team conducts data collection in the study area (photo courtesy of Dr. Nguyen)
Development of sustainable forest management and conservation strategies requires an understanding of how the composition and structure of tropical forests change in response to different disturbance regimes and how this affects both species distributions and people living in and near these forests. Most forests in Vietnam are affected by land cover change (LCC) resulting from human activities. To map and quantify the patterns of LCC, Dr. Nguyen and her team will analyze Landsat satellite images, GIS data, and field inventory data to classify forests by type and disturbance status. They will use these maps to stratify their field sampling and assess plant biodiversity among forest types and their changes following different levels of human disturbances (i.e., minor, moderate, and heavy impact). Furthermore, they will compare tree composition and structure along different ecological gradients, such as topography. By combining remote sensing, field data, and statistical processing, they expect to advance current methods to measure disturbance and biodiversity in the Central Highlands, which are largely based on field inventories. However, remotely sensed data is likely insufficient to map rare and endangered species, and hence areas of high conservation value. Therefore, the researchers will integrate spatial data with the experience of forestry workers and the indigenous knowledge of local people in the second phase of the project. Dr. Nguyen and her colleagues will collaborate closely with Dr. Radeloff, who will provide expert advice on forest sampling, analysis of vegetation diversity, and the use of remote sensing in ecology and biodiversity.

The project will involve all relevant stakeholders, including local authorities, forestry officers from various levels, and local people who depend on the forest. The project is designed so as to enhance conservation awareness among local people and improve skills and knowledge among forestry workers and officials responsible for conservation. The results will be transferred to relevant departments and reported to the Provincial People’s Committee (PPC) of Dak Nong Province in the form of recommendations for forestry strategies. This will be of crucial importance for the PPC in order to implement proper forestry policies, conservation strategies, and forest management for the province in the context of climate change. Furthermore results from the project will contribute in several ways to the development of techniques, methodology, and training in forest biodiversity inventory and monitoring, which is still very limited in the Central Highlands, including Dak Nong Province. Combining remote sensing, terrestrial data, and social surveys will also provide insights into how forest dynamics in the Central Highlands have changed in recent decades. These inferences will contribute to development of a strategy for forest management that can incorporate payments for ecosystem services, REDD, and biodiversity conservation in the Central Highlands.

Summary of Recent Activities

Data analysis was the primary activity for Dr. Huong and her team during the second quarter of 2019. The identified field data for trees in 181 sample plots by Latin name, calculated biodiversity indices and forest variables, and continued analyzing remote sensing data. They also undertook a field inventory to land owned by the forestry company Dak N’Tao to collect data on high conservation value (HCV) tree species. Two team members also attended a software training course in Singapore organized by Trimble Inc., a developer of electronic devices and associated software tools, and they will apply what they learned to ongoing image processing work on the project. Based on their project results so far, they had papers accepted for publication by the journal of Tay Nguyen University and by the journal of the Vietnamese Academy Institute of Forestry, which are expected to appear in print later in 2019. The researchers have also prepared and updated a set of guidelines for the application of remote sensing and GIS for forest management, and they hope to publish it early in 2020.

5-253 Forestry Discussions5-253 Forestry GIS Training
The research team discusses rare tree species with forestry staff.The team training the head of the forest station on how to use GIS for monitoring forests with his mobile phone.
All photos courtesy of Dr. Nguyen
Collaboration is an important aspect of this project, and as in previous reporting periods, the PI and her team worked closely with foresters from Dak N'Tao on inventorying HCV trees. Local people were also engaged to discuss problems and solutions related to conserving rare and endangered tree species at the site. Distribution of these species was also preliminarily defined on a map before field inventorying began. The forestry staff and local people then participated in measuring characteristics of rare and endangered tree species during the field inventory. Their contributions were important for biodiversity conservation at this location, and through their activities, forestry staff members and local residents gained knowledge and insights into the importance and current status of rare and endangered species. Many of them are interested in taking a more advanced follow-up course to the previous basic course on remote sensing and GIS in forest management that was organized by the PEER team in 2018 for more than 30 attendees.

The PI also reports that the remote sensing techniques and training materials she and her group developed for using in mapping land use and land cover (LULC) in their PEER project have also attracted the attention of other organizations such as the World Wildlife Fund, which works in Yok Don National Park. The WWF group invited the PEER team to provide training for their staff, and a national project based at the Vietnamese Academy Institute of Technology and Science invited the team to collaborate on updating their LULC data and maps.

During the second half of 2019, the PEER researchers will conduct field work to supplement their biodiversity data and HCV inventory database, mainly for woody species. They will also continue to hone their LULC and LULC change analyses to ensure maximum accuracy. This will require some field visits to various districts in Daknong Province to collect more GPS sample points to interpret forest cover, as well as to obtain information from the locally-based forest agency staff. Dr. Huong and her colleagues will present their results at the 40th Asian Conference on Remote Sensing, to be held October 14-18, 2019, in Daejeon, Korea. A planned working visit by Dr. Huong to the lab of U.S. partner Dr. Volker Radeloff at the University of Wisconsin – Madison may need to be postponed until early 2020 due to other schedule commitments by both parties. A no-cost extension beyond the current end date of November 30, 2019, may be necessary and will be considered later this fall.

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