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National climate change impact assessments underestimate the potential of autonomous adaptation

Abstract:
Central Europe is projected to lose up to 25% of its crop productivity by 2050 because of climate change, posing significant challenges to agricultural systems and food security. Effective adaptation strategies must consider not only domestic impacts but also global climate effects, including international trade dynamics. We performed a multilevel analysis of climate change impacts on agriculture, using the Czech Republic, a landlocked, crop production-based economy with an open market, as a case study. We integrated the global biosphere management model (GLOBIOM) with the gridded global crop model EPIC-IIASA. Climate impacts were projected with five global circulation models under three climate scenarios, with and without CO2 fertilization, and applied in national, EU-regional, and global productivity change scenarios. The results show that national-only assessments underestimate both risks and opportunities: production is projected to decline by up to 9% when global interactions are excluded but to increase by up to 8% when trade and market effects are included. Autonomous adaptation mechanisms, such as cropland reallocation, shifts in management intensity, and trade adjustments, buffer biophysical yield losses and improve economic outcomes. Neglecting global interactions in national climate change assessments increases the risk of maladaptation and policy inefficiencies. The incorporation of international market linkages enhances the ability to design robust adaptation strategies, enabling countries such as the Czech Republic to maximize resilience while minimizing environmental and socioeconomic trade-offs.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s10113-026-02521-1

Authors

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Role:
Author
ORCID:
0000-0001-8440-1933


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Funder identifier:
https://ror.org/058aeep47


Publisher:
Springer
Journal:
Regional Environmental Change More from this journal
Volume:
26
Issue:
1
Article number:
35
Publication date:
2026-02-03
Acceptance date:
2025-12-18
DOI:
EISSN:
1436-378X
ISSN:
1436-3798


Language:
English
Keywords:
Pubs id:
2412310
Local pid:
pubs:2412310
Source identifiers:
3722695
Deposit date:
2026-02-03
ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.

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