A network intervention for natural resource management in the context of climate change
As climate change impacts the Great Lakes region, the increased frequency and intensity of precipitation events are dramatically increasing the erosive effects of stormwater in the ravine ecosystem. Because formal governance structures may not be effective in providing coordination during turbulent...
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| Vydané v: | Social networks Ročník 75; s. 55 - 64 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier B.V
01.10.2023
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| ISSN: | 0378-8733 |
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| Abstract | As climate change impacts the Great Lakes region, the increased frequency and intensity of precipitation events are dramatically increasing the erosive effects of stormwater in the ravine ecosystem. Because formal governance structures may not be effective in providing coordination during turbulent and dynamic events, those seeking to manage natural resources during climate change may turn to resources located in their social networks. In this study network analysis was used to visualize collegial ties and self-reported consideration of climate change among those managing ravines along southwestern Lake Michigan. Professional development then leveraged the visualizations to modify the network, potentially increasing knowledge flows and coordination. Those who were targeted by the intervention increased their engagement in the network and contributed to bridging between subgroups to fill structural holes. This provides insight into the potential for interventions that leverage baseline network analysis for the management of natural resources in the context of climate change.
•Network intervention created new ties related to potential knowledge flows and coordination about climate change.•Network intervention filled structural holes in the system.•Network visualization directly informed network intervention through participant-researcher partnership. |
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| AbstractList | As climate change impacts the Great Lakes region, the increased frequency and intensity of precipitation events are dramatically increasing the erosive effects of stormwater in the ravine ecosystem. Because formal governance structures may not be effective in providing coordination during turbulent and dynamic events, those seeking to manage natural resources during climate change may turn to resources located in their social networks. In this study network analysis was used to visualize collegial ties and self-reported consideration of climate change among those managing ravines along southwestern Lake Michigan. Professional development then leveraged the visualizations to modify the network, potentially increasing knowledge flows and coordination. Those who were targeted by the intervention increased their engagement in the network and contributed to bridging between subgroups to fill structural holes. This provides insight into the potential for interventions that leverage baseline network analysis for the management of natural resources in the context of climate change.
•Network intervention created new ties related to potential knowledge flows and coordination about climate change.•Network intervention filled structural holes in the system.•Network visualization directly informed network intervention through participant-researcher partnership. |
| Author | Larsen, Angela Brown, Ethan Chen, Tingqiao Baule, William 'B.J.' Frank, Kenneth A. |
| Author_xml | – sequence: 1 givenname: Kenneth A. surname: Frank fullname: Frank, Kenneth A. email: kenfrank@msu.edu organization: Michigan State University – sequence: 2 givenname: Tingqiao surname: Chen fullname: Chen, Tingqiao organization: Google – sequence: 3 givenname: Ethan surname: Brown fullname: Brown, Ethan organization: Willamette Partnership – sequence: 4 givenname: Angela surname: Larsen fullname: Larsen, Angela organization: Allican for the Great Lakes – sequence: 5 givenname: William 'B.J.' surname: Baule fullname: Baule, William 'B.J.' organization: Michigan State University |
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| Keywords | Climate change Ravine management Knowledge flow Network intervention |
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