The End Of Knowledge - Vault 4/58 - AI For Good - 2021 - Big Data for Biodiversity: New Technologies in Accounting for Nature

graph LR classDef main fill:#f9f9f9, font-weight:bold, font-size:14px classDef edna fill:#ffcc99, font-weight:bold, font-size:14px classDef biodiversity fill:#ccff99, font-weight:bold, font-size:14px classDef collaboration fill:#99ccff, font-weight:bold, font-size:14px classDef data fill:#ff99cc, font-weight:bold, font-size:14px classDef aiGood fill:#ccccff, font-weight:bold, font-size:14px A[Big Data for
Biodiversity: New Technologies
in Accounting for
Nature] A --> B[eDNA
unlocks biodiversity data
for AI. 1] B --> C[Founded by Bruce,
introduced to eDNA. 2] B --> D[Insects are indicators
eDNA rapid. 3] B --> E[eDNA applied beyond academia
for management. 4] B --> F[eDNA maps 650 species
in Amazon. 5] A --> G[Biodiversity monitoring
misses major patterns. 6] G --> H[Small organisms drive ecosystems,
need assessing. 7] G --> I[eDNA + AI profiles
ecosystem changes. 8] G --> J[Tracks health, links
to complex ecology. 9] G --> K[eDNA + AI build
global biodiversity maps. 10] A --> L[Nature-positive economy needs
detailed biodiversity data. 11] L --> M[Biodiversity data as
city planners map. 12] L --> N[Routine business practice
with detailed maps. 13] L --> O[eDNA avoids human contamination
in monitoring. 14] L --> P[Food waste affects
eDNA results. 15] A --> Q[Citizen science enables
continuous monitoring. 16] Q --> R[eDNA detects rare species,
aids tourism. 17] Q --> S[No pristine ecosystems,
use best habitats. 18] Q --> T[Ancient DNA could recreate
pre-human ecosystems. 19] Q --> U[Nature Metrics collaborates
with IUCN. 20] A --> V[eBioAtlas integrates biodiversity
in global finance. 21] V --> W[Climate change prioritized,
biodiversity aids restoration. 22] V --> X[Habitats need all levels
for carbon storage. 23] V --> Y[Visualizing eDNA data crucial
for decisions. 24] V --> Z[Updated biodiversity sat nav
guides management. 25] A --> AA[Independently verified eDNA
data builds trust. 26] AA --> AB[Biodiversity data routine
in business practice. 27] AA --> AC[Upcoming AI for sustainable
fashion discussion. 28] AA --> AD[Climate AI features
notable figures. 29] AA --> AE[AI for Good has
year-round programming. 30] class A,B,C,D,E,F edna class G,H,I,J,K biodiversity class L,M,N,O,P collaboration class Q,R,S,T,U data class V,W,X,Y,Z aiGood class AA,AB,AC,AD,AE aiGood

Resume:

1.- Nature Metrics uses environmental DNA (eDNA) to unlock the world's biodiversity data layer and enable AI/ML to understand environmental impacts.

2.- Kat Bruce founded Nature Metrics after her PhD supervisor Doug Yu introduced eDNA sequencing as a faster way to assess biodiversity.

3.- Insects are good environmental indicators but identifying them is slow. eDNA allows sequencing thousands together to rapidly assess diversity.

4.- Kat wanted to apply eDNA beyond academia to real-world challenges. Nature Metrics makes it accessible for environmental management.

5.- eDNA provides biodiversity data at unprecedented scales, e.g. mapping 650 Amazon species from one river sampling trip.

6.- Biodiversity is complex with interconnected species responding to many variables. Monitoring a few species misses patterns until major declines occur.

7.- Most biodiversity is small organisms like insects, soil organisms and microbes that drive ecosystems. Assessing biodiversity must account for them.

8.- eDNA combined with AI could profile how communities change along a gradient from pristine to degraded ecosystems.

9.- This allows placing a sample on the gradient to track ecosystem health simply, linking it to the complex ecology underneath.

10.- Doug focuses on using eDNA and AI to build constantly updated global biodiversity maps to direct activities to lower impact areas.

11.- Shifting the world's $90 trillion annual economic activity to be nature-positive requires detailed biodiversity data accessible to all.

12.- Current biodiversity data is limited - we need a "city planner's map" interpolated from eDNA and remote sensing using neural networks.

13.- Detailed, AI-generated biodiversity maps could make accounting for biodiversity a routine business practice rather than a rare, heroic effort.

14.- eDNA avoids human-generated noise that hampers some environmental monitoring. Algorithms can identify and exclude human DNA contamination.

15.- Salmon DNA from human food waste can end up in rivers and be mistaken for wild salmon - an issue for eDNA analysis.

16.- eDNA collection is simple enough for citizen science. This enables cost-effective, continuous monitoring to track seasonal patterns and human impacts.

17.- Lack of observing wildlife doesn't mean absence. eDNA detects rare species, exciting for tourism and conservation.

18.- No ecosystems are pristine due to human impact over time. eDNA must be benchmarked against the best available habitats.

19.- Ancient DNA preserved in marine sediments could recreate pre-human ecosystems as a baseline. Research is exploring this possibility.

20.- Nature Metrics collaborates widely, including a program with the IUCN to map global biodiversity with 30,000 eDNA samples over 3 years.

21.- The eBioAtlas will provide data to integrate biodiversity into global finance and support the post-2020 UN biodiversity framework.

22.- Climate change is the top priority. Biodiversity can help via restoration increasing carbon sequestration, if done accounting for whole ecosystems.

23.- Restored habitats need all trophic levels, not just vegetation, to survive long-term and deliver carbon storage. eDNA guides this.

24.- Visualizing multi-dimensional eDNA data and its uncertainty is challenging but crucial to inform decision-making. Nature Metrics is hiring visualization experts.

25.- The goal is an always-updated biodiversity "sat nav" to guide management, enable clear targets, and hold stakeholders accountable.

26.- eDNA data can be independently verified, building trust to get efficient solutions, overcoming suspicion from proprietary datasets.

27.- Nature Metrics aims to make biodiversity data accessible and trusted so accounting for nature becomes a routine business practice.

28.- AI for Good has upcoming discussions on AI for sustainable fashion, celebrating AI startups, and accelerating climate science.

29.- The AI for Good Discovery series on Climate AI will feature Ban Ki-moon, Turing Award winners, IPCC representatives and Oxford academics.

30.- AI for Good has year-round online programming beyond the annual summit. Updates are on their website AIforGood.itu.int and social media.

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