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Lea Berrang-Ford

Researcher at University of Leeds

Publications -  36
Citations -  604

Lea Berrang-Ford is an academic researcher from University of Leeds. The author has contributed to research in topics: Climate change & Indigenous. The author has an hindex of 7, co-authored 36 publications receiving 177 citations. Previous affiliations of Lea Berrang-Ford include Ford Motor Company & University of Alberta.

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A systematic global stocktake of evidence on human adaptation to climate change

Lea Berrang-Ford, +150 more
TL;DR: In this article, the authors present a systematic and comprehensive global stocktake of implemented human adaptation to climate change and identify eight priorities for global adaptation research: assess the effectiveness of adaptation responses, enhance the understanding of limits to adaptation, enable individuals and civil society to adapt, include missing places, scholars and scholarship, understand private sector responses, improve methods for synthesizing different forms of evidence, assess the adaptation at different temperature thresholds, and improve the inclusion of timescale and the dynamics of responses.
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Systematic mapping of global research on climate and health: a machine learning review

TL;DR: In this paper, the authors used machine learning methods to systematically synthesise an evidence base on climate change and human health and found that there are 15,963 studies in the field of climate and health published between 2013 and 2019.
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Changing access to ice, land and water in Arctic communities

TL;DR: In this article, the authors identify general thresholds for weather and sea ice variables that define boundaries that determine trail access, and apply these thresholds to instrumental data on weather conditions to model daily trail accessibility from 1985 to 2016 for 16 communities in northern Canada.
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Policy implementation styles and local governments: the case of climate change adaptation

TL;DR: In this paper, the authors analyze eight hypothesized drivers of local adaptation policy instrument choice using fractional regression analysis and multilevel modelling, and find that local governments are pursuing diverse adaptation policy implementation styles that are associated with different levels of internal capacity, local political economies and problem perception.