Abstract During the 21st century, human–environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex, coupled systems. Human–environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi‐resolution information for analysis. Climate change, land‐use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high‐density, and high‐resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) for Socio‐Environmental Systems (SES) research. In addition to providing an overview of NEON AOP datasets and outlining specific applications for addressing SES questions, we highlight current challenges and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 yr, offer exciting opportunities for cross‐site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio‐environmental challenges. We urge the SES research community to further explore questions and theories in social and economic disciplines that might leverage NEON AOP data.
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Extreme events and coupled socio-ecological systems
Rare, but potentially impactful, extreme events in socio-ecological systems (SES) can trigger significant consequences. The scarcity of theoretical frameworks for such events in SES is due to data limitations and difficulty in parameterizing coupled SES models. We explore the effect of extreme events on coupled socio- ecological systems using two stylized case studies: harvesting of old-growth forests and coral reef fisheries. We found that extreme events alter the long-term and transient dynamics of the systems. We identify counter- intuitive situations where the degradation of forests or coral habitat can prevent extinction through social dynamics feedback. Management outcomes show maximum variability at intermediate disturbance frequencies, complicating predictions of ecological recovery. We also found that initial conditions significantly influence system responses to shocks. Our work lays a foundation for future studies on extreme events in socio-ecological dynamics. Future work could explore more detailed models rooted in the literature, especially related to the modeling of the social dynamics.
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- Award ID(s):
- 1923707
- PAR ID:
- 10537472
- Publisher / Repository:
- Ecological Modelling
- Date Published:
- Journal Name:
- Ecological Modelling
- Volume:
- 495
- Issue:
- C
- ISSN:
- 0304-3800
- Page Range / eLocation ID:
- 110786
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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