Project Details
Description
Tropical forests are among the most important ecosystems on Earth. They host an extraordinary share of
biodiversity and play a crucial role in mitigating climate change by absorbing large amounts of carbon
dioxide. However, rising temperatures, changing rainfall patterns, deforestation, and other human
pressures are increasingly threatening these forests. If these pressures become too strong, tropical forests
could reach critical tipping points beyond which they may lose key functions or even collapse. At present,
scientists cannot reliably predict when or where this might happen, because the combined effects of
climate, biodiversity, and human activities are too complex for existing tools.
The Afrotropical-FORECAST project aims to better understand the risk of large-scale tropical forest decline,
with a focus on the Congo rainforests. To do this, the project will develop a new generation of computer
models that combine established ecological knowledge with artificial intelligence. These models will
integrate satellite observations, field measurements, and ecological theory to realistically simulate how
forests respond to environmental stress.
By linking these forest models with climate models, the project will create a digital twin of Afrotropical
forests. These virtual forests will allow researchers to explore future scenarios efficiently and identify the
conditions under which tropical forests can survive—or fail—under combined climate and land-use change
biodiversity and play a crucial role in mitigating climate change by absorbing large amounts of carbon
dioxide. However, rising temperatures, changing rainfall patterns, deforestation, and other human
pressures are increasingly threatening these forests. If these pressures become too strong, tropical forests
could reach critical tipping points beyond which they may lose key functions or even collapse. At present,
scientists cannot reliably predict when or where this might happen, because the combined effects of
climate, biodiversity, and human activities are too complex for existing tools.
The Afrotropical-FORECAST project aims to better understand the risk of large-scale tropical forest decline,
with a focus on the Congo rainforests. To do this, the project will develop a new generation of computer
models that combine established ecological knowledge with artificial intelligence. These models will
integrate satellite observations, field measurements, and ecological theory to realistically simulate how
forests respond to environmental stress.
By linking these forest models with climate models, the project will create a digital twin of Afrotropical
forests. These virtual forests will allow researchers to explore future scenarios efficiently and identify the
conditions under which tropical forests can survive—or fail—under combined climate and land-use change
| Acronym | FWOAL1220 |
|---|---|
| Status | Active |
| Effective start/end date | 1/03/26 → 28/02/30 |
Keywords
- Tipping points
- Hybrid and Causal Artificial Intelligence
- Tropical forests
Flemish discipline codes in use since 2023
- Climate change
- Terrestrial ecology
- Remote sensing
- Computational biomodelling and machine learning
- Biogeochemical cycli
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