Transboundary cooperation in Arctic climate change governance under geopolitical tensions.

Political conflicts or geopolitical tensions can create uncertainty in addressing climate change and environmental management in the Arctic. Dissecting how actors interact with each other and form networks is important for understanding ecological and environmental management challenges during geopo...

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Published in:Journal of Environmental Management
Main Authors: Guo, Yu, Bai, Rui, Hong, Tao
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier Science 2024
Subjects:
Online Access:https://doi.org/10.1016/j.jenvman.2024.120855
https://pubmed.ncbi.nlm.nih.gov/38614007
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spelling ftpubmed:38614007 2024-05-12T07:59:05+00:00 Transboundary cooperation in Arctic climate change governance under geopolitical tensions. Guo, Yu Bai, Rui Hong, Tao 2024 Apr 12 https://doi.org/10.1016/j.jenvman.2024.120855 https://pubmed.ncbi.nlm.nih.gov/38614007 eng eng Elsevier Science https://doi.org/10.1016/j.jenvman.2024.120855 https://pubmed.ncbi.nlm.nih.gov/38614007 Copyright © 2024 Elsevier Ltd. All rights reserved. J Environ Manage ISSN:1095-8630 Volume:358 Arctic climate change governance Geopolitical tensions Temporal exponential random graph model Transboundary cooperation networks Journal Article 2024 ftpubmed https://doi.org/10.1016/j.jenvman.2024.120855 2024-04-14T16:01:00Z Political conflicts or geopolitical tensions can create uncertainty in addressing climate change and environmental management in the Arctic. Dissecting how actors interact with each other and form networks is important for understanding ecological and environmental management challenges during geopolitical tensions, as well as promoting better governance. We construct transboundary networks for Arctic climate change governance (ACCG) from 2013 to 2021 based on the Global Database of Events, Language, and Tone (GDELT). Further, we used network descriptive statistical analysis and Temporal Exponential Random Graph Models (TERGM) to explore the structure of ACCG networks and the key factors influencing cooperation formation. The findings suggest that the overall cooperation density of the ACCG is low, and the dominant position of core actors is continuously strengthening. Non-state actors are less likely to be seen as partners and their participation depends largely on cooperation with states. The results also show that actors with similar stances and problem exposure are more likely to cooperate, but those exposed to high latitudes often choose not to cooperate; first-comers are more likely to perceive as cooperating yet they are inclined to establish internal cooperation. Additionally, two geographically proximate actors are more likely to cooperate. This indicates that under geopolitical tensions, the ACCG faces challenges not only due to the limited capacity of non-state actors to perform transboundary functions but also because the cooperation mechanisms are influenced by regional political logic. Accordingly, we further suggest policy recommendations from developing binding international frameworks to guide transboundary cooperation, enhancing cooperation among non-state actors, and ensuring the representativeness and fairness of non-Arctic actors' participation. This research provides insights into transboundary environmental management under political tensions, while also offering new pathways for analysing large-scale environmental governance structures. Article in Journal/Newspaper Arctic Climate change PubMed Central (PMC) Arctic Journal of Environmental Management 358 120855
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Arctic climate change governance
Geopolitical tensions
Temporal exponential random graph model
Transboundary cooperation networks
spellingShingle Arctic climate change governance
Geopolitical tensions
Temporal exponential random graph model
Transboundary cooperation networks
Guo, Yu
Bai, Rui
Hong, Tao
Transboundary cooperation in Arctic climate change governance under geopolitical tensions.
topic_facet Arctic climate change governance
Geopolitical tensions
Temporal exponential random graph model
Transboundary cooperation networks
description Political conflicts or geopolitical tensions can create uncertainty in addressing climate change and environmental management in the Arctic. Dissecting how actors interact with each other and form networks is important for understanding ecological and environmental management challenges during geopolitical tensions, as well as promoting better governance. We construct transboundary networks for Arctic climate change governance (ACCG) from 2013 to 2021 based on the Global Database of Events, Language, and Tone (GDELT). Further, we used network descriptive statistical analysis and Temporal Exponential Random Graph Models (TERGM) to explore the structure of ACCG networks and the key factors influencing cooperation formation. The findings suggest that the overall cooperation density of the ACCG is low, and the dominant position of core actors is continuously strengthening. Non-state actors are less likely to be seen as partners and their participation depends largely on cooperation with states. The results also show that actors with similar stances and problem exposure are more likely to cooperate, but those exposed to high latitudes often choose not to cooperate; first-comers are more likely to perceive as cooperating yet they are inclined to establish internal cooperation. Additionally, two geographically proximate actors are more likely to cooperate. This indicates that under geopolitical tensions, the ACCG faces challenges not only due to the limited capacity of non-state actors to perform transboundary functions but also because the cooperation mechanisms are influenced by regional political logic. Accordingly, we further suggest policy recommendations from developing binding international frameworks to guide transboundary cooperation, enhancing cooperation among non-state actors, and ensuring the representativeness and fairness of non-Arctic actors' participation. This research provides insights into transboundary environmental management under political tensions, while also offering new pathways for analysing large-scale environmental governance structures.
format Article in Journal/Newspaper
author Guo, Yu
Bai, Rui
Hong, Tao
author_facet Guo, Yu
Bai, Rui
Hong, Tao
author_sort Guo, Yu
title Transboundary cooperation in Arctic climate change governance under geopolitical tensions.
title_short Transboundary cooperation in Arctic climate change governance under geopolitical tensions.
title_full Transboundary cooperation in Arctic climate change governance under geopolitical tensions.
title_fullStr Transboundary cooperation in Arctic climate change governance under geopolitical tensions.
title_full_unstemmed Transboundary cooperation in Arctic climate change governance under geopolitical tensions.
title_sort transboundary cooperation in arctic climate change governance under geopolitical tensions.
publisher Elsevier Science
publishDate 2024
url https://doi.org/10.1016/j.jenvman.2024.120855
https://pubmed.ncbi.nlm.nih.gov/38614007
geographic Arctic
geographic_facet Arctic
genre Arctic
Climate change
genre_facet Arctic
Climate change
op_source J Environ Manage
ISSN:1095-8630
Volume:358
op_relation https://doi.org/10.1016/j.jenvman.2024.120855
https://pubmed.ncbi.nlm.nih.gov/38614007
op_rights Copyright © 2024 Elsevier Ltd. All rights reserved.
op_doi https://doi.org/10.1016/j.jenvman.2024.120855
container_title Journal of Environmental Management
container_volume 358
container_start_page 120855
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