Toward a healthy planet through fungal biotechnology and Indigenous futures thinking: an opinion paper
Bibliographic record
Abstract
New fungal biotechnologies are advancing applied and conservation mycology to support global regenerative outcomes for natural and human systems. Fungi can support planetary health, “the health of human civilization and the state of the natural systems it depends on,” through the Kunming-Montreal Global Biodiversity Framework (KM-GBF). The KM-GBF is humanity's best effort at reconciling the sustainable development of all societies and biodiversity loss while respecting Indigenous Peoplesʻ (IP) rights. Target 17 of the KM-GBF calls for sharing biotechnology benefits and sustainable use of biotechnology for biodiversity conservation. It complements Article 19 of the Convention on Biological Diversity (CBD), which calls for biotechnology access and benefit sharing (ABS). Fungal biotechnologies are uniquely positioned to address Article 19 and the KM-GBF Targets. Fungi can help grow our material world sustainably, and conserving them is best done by preserving the ecosystems they inhabit, so-called “conservation of abundance.” Through capacity building and Indigenous Data Sovereignty (IDSov), all 23 KM-GBF Targets can be addressed. In this opinion paper, we apply indigenous futures thinking to explore how advancements in fungal biotechnology and digital technologies enable the Kara & Kichwa Nation, people indigenous to Ecuador and the Andes Mountains, to practice and govern applied and conservation mycology. We propose a framework that extends efforts by the mycology community, further decentralizing applied and conservation mycology. Our framework centers fungal biotechnological innovation by Indigenous Peoples, and their participation in the global bioeconomy in service of planetary health and all 23 KM-GBF Targets. Specifically, we advocate for Global North governments and organizations to commit to the Targets and for Kara and Kichwa Nations to advance their fungal biotechnologies. We offer a starting point for envisioning future fungal technologies made possible by the design, development, and implementation of applied fungal biotechnologies by Indigenous Peoples.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".