Back

Towards Climate-Smart Rewilding: An Integrated Framework For Biodiversity, Climate Change, And Society

Stark, G.; Weissgerber, M.; Fernandez, N.; Quintero-Uribe, L.; Giergiczny, M.; Poulsen, N. R.; Villar, N.; Mols, B.; Bakker, E.; Smith, A. M.; Winkel, G.; Alagador, D.; Rey-Benayas, J.; Espelta, J. M.; Selwyn, M.; Brotons, L.; Kluvankova, T.; Brnkalakova, S.; Kloibhofer, J.; Prestele, R.; Smith, H.; Lazaro-Gonzalez, A.; Buitenwerf, R.; Pearce, E.; Svenning, J.-C.; Santana, J.; Beja, P.; Moreira, F.; Wunder, S.; Svoboda, M.; Vancura, V.; Arneth, A.; Hampe, A.; Pereira, H.

2025-03-25 ecology
10.1101/2025.03.21.644513 bioRxiv
Show abstract

The UN Decade on Ecosystem Restoration and the Kunming-Montreal Global Biodiversity Framework aim to restore 30% of degraded ecosystems. Both the IPCC and IPBES highlight the crucial role of ecosystem restoration in addressing the interconnected crises of climate change and biodiversity loss. One key restoration strategy is rewilding, which enhances ecosystem complexity with minimal human intervention. While traditional rewilding strategies often focus on benefits for biodiversity, we propose a climate-smart rewilding framework as a new approach designed to deliver climate benefits alongside biodiversity restoration. This framework seeks to integrate biodiversity, climate change adaptation and mitigation, as well as socio-economic benefits and trade-offs. We illustrate how this framework can be utilized to identify areas across Europe where rewilding could increase carbon sequestration, enhance species abilities to adapt to the velocity of climate change, and maximize wildlife-watching benefits while minimizing the costs associated with livestock-wildlife conflict. Finally, we acknowledge some limitations of climate-smart rewilding, but we argue that its adaptability and low cost render it a promising solution to the challenges facing Europe and beyond.

Published in One Earth · not in our set (fewer than 10 published preprints to learn from) · training set

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Biological Conservation
○ 46 papers in training set
Top 0.1%
11.3%
Similar papers in this journal
2
Conservation Biology
○ 17 papers in training set
Top 0.1%
9.3%
Similar papers in this journal
3
Global Change Biology
○ 78 papers in training set
Top 0.2%
7.5%
Similar papers in this journal
4
Conservation Letters
○ 14 papers in training set
Top 0.1%
7.5%
Similar papers in this journal
5
Conservation Science and Practice
○ 15 papers in training set
Top 0.1%
6.4%
Similar papers in this journal
6
Science of The Total Environment
○ 186 papers in training set
Top 0.8%
5.2%
7
Journal of Applied Ecology
○ 39 papers in training set
Top 0.2%
5.2%
50% of probability mass above
8
Biodiversity and Conservation
○ 12 papers in training set
Top 0.1%
4.6%
9
Environmental Research Letters
○ 14 papers in training set
Top 0.1%
4.6%
10
Ecological Indicators
○ 21 papers in training set
Top 0.1%
4.1%
11
Global Ecology and Biogeography
○ 47 papers in training set
Top 0.4%
3.1%
12
Global Ecology and Conservation
○ 25 papers in training set
Top 0.3%
3.0%
13
Methods in Ecology and Evolution
○ 176 papers in training set
Top 0.9%
2.3%
14
Ecography
○ 54 papers in training set
Top 0.7%
2.0%
15
Landscape Ecology
○ 13 papers in training set
Top 0.1%
1.8%
16
Diversity and Distributions
○ 28 papers in training set
Top 0.3%
1.8%
17
Ecological Informatics
○ 33 papers in training set
Top 0.5%
1.4%
18
eLife
● 5828 papers in training set
Top 57%
1.3%
19
Ecology and Evolution
○ 267 papers in training set
Top 4%
1.3%
20
Ecological Applications
○ 34 papers in training set
Top 0.7%
1.1%
21
Nature Communications
○ 5641 papers in training set
Top 52%
1.1%
22
Animal Conservation
○ 13 papers in training set
Top 0.3%
0.9%
23
Peer Community Journal
● 281 papers in training set
Top 5%
0.9%
24
Oikos
○ 84 papers in training set
Top 2%
0.8%
25
Journal of Environmental Management
○ 13 papers in training set
Top 0.6%
0.8%
26
PLANTS, PEOPLE, PLANET
○ 27 papers in training set
Top 0.7%
0.8%
27
Journal of Biogeography
○ 46 papers in training set
Top 0.8%
0.8%
28
Ecological Modelling
○ 28 papers in training set
Top 0.6%
0.6%
29
PeerJ
◐ 308 papers in training set
Top 13%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.