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Artificial intelligence approaches for mapping the nexus of biodiversity, climate change and human society

Ahmed, Rafsan LU orcid ; Aasa, Carl ; Berntsson, Petter ; Skafte, Alexander ; Kazemi Rashed, Salma LU ; Klang, Marcus LU orcid ; Barvesten, Adam ; Olde, Ola ; Lindholm, William and Lamarca Arrizabalaga, Antton , et al. (2025) Swedish Biodiversity Symposium
Abstract
We face closely intertwined crises related to biodiversity, climate change, global health and
inequality. Unfortunately, the knowledge that could help overcome these existential crises is
scattered across millions of scientific articles, reports, policy documents, databases, and
individual datasets, far exceeding human processing capabilities. This hinders evidence-based
research, innovation and policymaking that would enable a sustainable transformation.
Artificial intelligence (AI) can help overcome this problem by rapidly identifying and
synthesizing information on a large scale. We have developed an easy-to-use customizable AI
tool that extracts information about key entities such as species, habitats,... (More)
We face closely intertwined crises related to biodiversity, climate change, global health and
inequality. Unfortunately, the knowledge that could help overcome these existential crises is
scattered across millions of scientific articles, reports, policy documents, databases, and
individual datasets, far exceeding human processing capabilities. This hinders evidence-based
research, innovation and policymaking that would enable a sustainable transformation.
Artificial intelligence (AI) can help overcome this problem by rapidly identifying and
synthesizing information on a large scale. We have developed an easy-to-use customizable AI
tool that extracts information about key entities such as species, habitats, chemicals,
environmental processes, genes/proteins and diseases from any large text collections. We use
this to extract information from large scientific literature databases, which is then visualized
in intuitive interaction graphs (“nexus knowledge graphs”) and further enriched with
information from databases and datasets. This helps reveal the intricate interplay between
ecosystems and human society from molecular pathways to complex systems leading to
actionable insights. For example, we can reveal links and feedback loops connecting individual pollutants and environmental processes with various species and habitats or
identify research biases and knowledge gaps. Thereby, our tools can support decision-making
related to biodiversity, climate change, medicine, human society in various contexts and
enable meaningful transformative change. (Less)
Please use this url to cite or link to this publication:
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organization
publishing date
type
Contribution to conference
publication status
published
subject
conference name
Swedish Biodiversity Symposium
conference location
Gothenburg, Sweden
conference dates
2025-10-21 - 2025-10-23
language
English
LU publication?
yes
id
58595dff-47bc-4a7d-9df0-0e2b8b05deff
alternative location
https://swedishbiodiversitysymposium.se/sites/default/files/2025-10/Book%20of%20Abstracts_Swedish%20Biodiversity%20Symposium%202025.pdf
date added to LUP
2026-01-15 08:59:08
date last changed
2026-01-15 10:48:33
@misc{58595dff-47bc-4a7d-9df0-0e2b8b05deff,
  abstract     = {{We face closely intertwined crises related to biodiversity, climate change, global health and<br/>inequality. Unfortunately, the knowledge that could help overcome these existential crises is<br/>scattered across millions of scientific articles, reports, policy documents, databases, and<br/>individual datasets, far exceeding human processing capabilities. This hinders evidence-based<br/>research, innovation and policymaking that would enable a sustainable transformation.<br/>Artificial intelligence (AI) can help overcome this problem by rapidly identifying and<br/>synthesizing information on a large scale. We have developed an easy-to-use customizable AI<br/>tool that extracts information about key entities such as species, habitats, chemicals,<br/>environmental processes, genes/proteins and diseases from any large text collections. We use<br/>this to extract information from large scientific literature databases, which is then visualized<br/>in intuitive interaction graphs (“nexus knowledge graphs”) and further enriched with<br/>information from databases and datasets. This helps reveal the intricate interplay between<br/>ecosystems and human society from molecular pathways to complex systems leading to<br/>actionable insights. For example, we can reveal links and feedback loops connecting individual pollutants and environmental processes with various species and habitats or<br/>identify research biases and knowledge gaps. Thereby, our tools can support decision-making<br/>related to biodiversity, climate change, medicine, human society in various contexts and<br/>enable meaningful transformative change.}},
  author       = {{Ahmed, Rafsan and Aasa, Carl and Berntsson, Petter and Skafte, Alexander and Kazemi Rashed, Salma and Klang, Marcus and Barvesten, Adam and Olde, Ola and Lindholm, William and Lamarca Arrizabalaga, Antton and Nugues, Pierre and Aits, Sonja}},
  language     = {{eng}},
  month        = {{10}},
  title        = {{Artificial intelligence approaches for mapping the nexus of biodiversity, climate change and human society}},
  url          = {{https://swedishbiodiversitysymposium.se/sites/default/files/2025-10/Book%20of%20Abstracts_Swedish%20Biodiversity%20Symposium%202025.pdf}},
  year         = {{2025}},
}