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The Chiang Mai Research Agenda for Advancing Automated Forest Restoration

Language:
The Chiang Mai Research Agenda for Advancing Automated Forest Restoration
Date:
2020
Author(s):
Multiple
Publisher:
FORRU-CMU
Editor(s):
Elliott, S.
Serial Number:
201
Suggested Citation:

Elliott, S. (Editor), 2020. The Chiang Mai Research Agenda for Advancing Automated Forest Restoration. Chapter 15, pp 229-246 in Elliott S., G, Gale & M. Robertson (Eds), Automated Forest Restoration: Could Robots Revive Rain Forests? Proceedings of a brain-storming workshop, Chiang Mai University, Thailand. 254 pp.

Two of the most important objectives of the workshop: “Automated Forest Restoration (AFR): Could Robots Revive Rainforests?” were:

  1. to design research programs to improve technologies for AFR, leading to development of prototype auto-restoration systems for testing and
  2. to facilitate collaboration among technologists and restoration ecologists and the formation of interdisciplinary research teams

Therefore, the main output was an agenda to guide research on AFR of tropical forest ecosystems. The workshop comprised 5 brainstorming sessions: 1) auto-seed-collection, 2) auto-seed-delivery, 3) auto-weed-control, 4) auto-monitoring (plants and animals) and 5) legal and regulatory issues. Expert speakers presented keynote topic reviews, followed by discussion sessions, which generated hundreds of research ideas. Screening, during plenary sessions, established support for 95 of them. Finally, participants voted on those research ideas, which they considered most likely to advance the AFR concept – “developing technologies that perform forest ecosystem restoration tasks on remote sites at low cost, ultimately leading to integrated, autonomous systems that minimize labour inputs to achieve restoration goals”. Thirty-nine participants each had 5 votes. The results, in declining order of support, were 1) seed bombs and pellets for automated tree establishment (41 votes[1]), 2) allelopathic herbicides for auto-weed-control (18), 3) improve drone tech (16), 4) AI for auto-tree-species recognition (13), 5) databases for species selection & restoration management (12), 6) technologies for auto-wildlife monitoring (9) and 7) data capture & indices for auto-monitoring restoration (7). These priorities were mostly re-confirmed in 2021, during an online reunion discussion with workshop participants and other AFR researchers. Only “3) improve drone tech” was lowered in priority (to 7th), since participants felt that since 2015, drone tech applicable to AFR needs, had advanced considerably. Participants in the 2021 discussion group also emphasized the need for more data-sharing among AFR researchers, funding mechanisms to support AFR research and a life-cycle approach for dealing with any e-waste that AFR might generate. For graduate students looking for thesis-project ideas, please consider the topics listed in this chapter, since their priority is supported by a broad spectrum of experts in the field.

Some participants voted for more than one subtropic under this heading

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