In a new study, published today in Nature Climate Change, we explore how carbon dioxide removal (CDR) – approaches that take CO2 out of the atmosphere – may affect biodiversity. 
Many scenarios outlining how long-term global warming could still be limited to #1.5°C rely heavily on cdr, particularly via planting forests and bioenergy with carbon capture and storage. 
To work at scale, these CDR approaches would require millions of square kilometres of land, thereby potentially interfering with critical biodiversity areas. 
In our #study, we present a multi-model scenario assessment of CDR‘s spatial overlap with areas of high biodiversity importance. 
We find that scenarios allocate substantial parts of critical biodiversity areas for CDR. Many of these overlaps fall in places where CDR is considered unsuitable from an #ecosystem perspective. 
What is particularly striking is that biodiversity areas are disproportionately allocated in non-high income countries – countries that have historically contributed little to causing climate change. 
Nonetheless, we also show how, if implemented carefully, CDR may substantially benefit biodiversity by reducing warming-related habitat loss. 
To realize such potential, we need to:
- cut fossil emissions rapidly and deeply to limit our dependence on CDR as much as possible. This can give us wiggle room to use CDR in a way that maximises benefits and minimizes risks.
- refine model-based land allocation patterns for CDR deployment to take biodiversity and other sustainability constraints better into account.
- further explore how positive and negative implications of CDR deployment compare to each other and how they are distributed across space and time.
With our study, we provide entry points for more biodiversity-sensitive and equitable siting of CDR in climate action planning and scenario development. 
This project, which began more than three years ago, was made possible by a large, cross-institutional, multidisciplinary team of scientists who brought together diverse expertise and rich datasets. 
Interesting for scientists working with scenarios: As part of our study, we made the gridded land allocation data for the original SSP-RCP scenarios from the participating model frameworks publicly available. 
Link to the open access study: https://doi.org/10.1038/s41558-026-02557-5
Joeri Rogelj, Gaurav Ganti, Jeff Price, Rachel Warren, Nicole Forstenhäusler, Yazhen Wu, Andrey Lessa Derci Augustynczik, Michael Wögerer, Tamás Krisztin, Petr Havlík, Florian Kraxner, Stefan Frank, Tomoko Hasegawa, Jonathan Doelman, Vassilis Daioglou, Florian Humpenöder, Alexander Popp and Sabine Fuss
Humboldt-Universität zu Berlin
Potsdam Institute for Climate Impact Research
Grantham Institute - Climate Change and the Environment
International Institute for Applied Systems Analysis
Imperial College London
Tyndall Centre for Climate Change Research
University of East Anglia
University of Natural Resources and Life Sciences, Vienna (BOKU)
Ritsumeikan University
PBL Planbureau voor de Leefomgeving
Copernicus Institute of Sustainable Development
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