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Abstract Social connections among individuals are essential components of social‐ecological systems (SESs), enabling people to take actions to more effectively adapt or transform in response to widespread social‐ecological change. Although scholars have associated social connections and cognitions with adaptive capacity, measuring actors' social networks may further clarify pathways for bolstering resilience‐enhancing actions.We asked how social networks and socio‐cognitions, as components of adaptive capacity, and SES regime shift severity affect individual landscape management behaviours using a quantitative analysis of ego network survey data from livestock producers and landcover data on regime shift severity (i.e. juniper encroachment) in the North American Great Plains.Producers who experienced severe regime shifts or perceived high risks from such shifts were not more likely to engage in transformative behaviour like prescribed burning. Instead, we found that social network characteristics explained significant variance in transformative behaviours.Policy implications: Our results indicate that social networks enable behaviours that have the potential to transform SESs, suggesting possible leverage points for enabling capacity and coordination toward sustainability. Particularly where private lands dominate and cultural practices condition regime shifts, clarifying how social connections promote resilience may provide much needed insight to bolster adaptive capacities in the face of global change. Read the freePlain Language Summaryfor this article on the Journal blog.
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NAPS : Integrating pose estimation and tag‐based tracking
Abstract Significant advances in computational ethology have allowed the quantification of behaviour in unprecedented detail. Tracking animals in social groups, however, remains challenging as most existing methods can either capture pose or robustly retain individual identity over time but not both.To capture finely resolved behaviours while maintaining individual identity, we built NAPS (NAPS is ArUco Plus SLEAP), a hybrid tracking framework that combines state‐of‐the‐art, deep learning‐based methods for pose estimation (SLEAP) with unique markers for identity persistence (ArUco). We show that this framework allows the exploration of the social dynamics of the common eastern bumblebee (Bombus impatiens).We provide a stand‐alone Python package for implementing this framework along with detailed documentation to allow for easy utilization and expansion. We show that NAPS can scale to long timescale experiments at a high frame rate and that it enables the investigation of detailed behavioural variation within individuals in a group.Expanding the toolkit for capturing the constituent behaviours of social groups is essential for understanding the structure and dynamics of social networks. NAPS provides a key tool for capturing these behaviours and can provide critical data for understanding how individual variation influences collective dynamics.
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- Award ID(s):
- 1734030
- PAR ID:
- 10573512
- Publisher / Repository:
- Methods in Ecology and Evolution
- Date Published:
- Journal Name:
- Methods in Ecology and Evolution
- Volume:
- 14
- Issue:
- 10
- ISSN:
- 2041-210X
- Page Range / eLocation ID:
- 2541 to 2548
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1111/2041-210X.14201
