Version 1st Edition

Sustainable Uplands: Learning to Manage Future Change, 2006-2009

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Hubacek, K.

Description

<p>This is a mixed method data collection. The study is part of the Rural Economy and Land Use (RELU) programme.<br> <br>The aim of this project was to combine knowledge from local stakeholders, policy-makers and social and natural scientists to anticipate, monitor and sustainably manage rural change in UK uplands. The project combined experience and new ideas from local people with cutting-edge natural and social science. The result will be a choice of solutions to future challenges that could never have been developed by either group alone.<br> <br>The research team started by identifying the current needs and aspirations of those who work, live and play in each site and were exploring the challenges and opportunities they face in future. Factors driving future change were modelled with computers to build up a detailed picture of possible future social, economic and environmental conditions. The research team sought innovative ideas from local people, policy makers and researchers about how people could adapt to these conditions. Suggestions were fed back into the models to evaluate how they might affect future society, economy and environment, and enabled participants to revise their ideas to avoid unintended consequences.<br> <br>This research will help in identifying appropriate ways for people to adapt in each upland area, and identify ways policy-makers can support adaptation. The research team fostered communication and understanding between different stakeholders and researchers through a series of joint site visits and workshops.<br> <br>Further information for this study may be found through the <a href="https://www.researchcatalogue.esrc.ac.uk/grants/RES-227-25-0001/read" target="_blank">ESRC Research Catalogue webpage: Managing Uncertainty in Dynamic Socio-Environmental Systems: An Application to UK Uplands.</a><a href="http://relu.data-archive.ac.uk/explore-data/search-browse/project/?ID=RES-227-25-0001"></a></p>

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.8

FAIR Score

31%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

UK Data Service

Assigned Domain

Subfield

Urban Studies

Field

Social Sciences

Domain

Social Sciences

Confidence Score

42%

Source

Scholar Data Model

Normalization Factors

FT

13.46

CTw

1.00

MTw

1.00