How and where should we expand UK woodlands to benefit people and biodiversity?
Lead Research Organisation:
University of Kent
Department Name: Sch of Anthropology & Conservation
Abstract
Background
We live in a time of profound environmental change due to climate collapse, land-use change, biotic homogenisation and species declines. The UK government has pledged to increase woodland cover from ~13% to ~19% to help achieve net zero carbon emissions by 2050. This could also have important implications for conservation, as 10% of UK woodland species are threatened with extinction and 53% are declining. How and where we expand tree cover therefore represents an unprecedented opportunity to transform our nation into a better place for people and biodiversity. This PhD will work across disciplines (conservation, ecology, human geography, environmental psychology, environmental economics) to explore how to maximise social and ecological benefits.
Research objectives and methodology
(1) Use mixed methods (e.g. focus groups, citizen juries, contingent ranking, Q methodology) to assess private landowner willingness to protect, restore or create woodland, through various initiatives (e.g. woodland creation grants).
(2) Use mixed methods to understand and quantify the people's preferences for different woodland types (e.g. native/introduced species, ancient woodlands, plantations), species (e.g. rare species, species they can encounter), accessibility (e.g. distance from home, woodland size), and use/non-use ecosystem service values (e.g. recreation, carbon sequestration and storage).
(3) Use existing biodiversity data, and the findings from (1) and (2), within spatial conservation prioritisation software to determine where best to protect, restore and create woodland to maximise biodiversity and social benefits.
Training
Depending on the candidate's background, training could include use of systematic conservation planning software (e.g. Marxan, Zonation), ArcGIS/QGIS, social science data collection and analysis (e.g. participatory methods, questionnaire design, NVivo, R), academic skills (e.g. writing journal papers), and transferable skills (e.g. multi-media communication, time management). The individual will also collaborate with the research, evidence and policy teams at Woodland Trust.
We live in a time of profound environmental change due to climate collapse, land-use change, biotic homogenisation and species declines. The UK government has pledged to increase woodland cover from ~13% to ~19% to help achieve net zero carbon emissions by 2050. This could also have important implications for conservation, as 10% of UK woodland species are threatened with extinction and 53% are declining. How and where we expand tree cover therefore represents an unprecedented opportunity to transform our nation into a better place for people and biodiversity. This PhD will work across disciplines (conservation, ecology, human geography, environmental psychology, environmental economics) to explore how to maximise social and ecological benefits.
Research objectives and methodology
(1) Use mixed methods (e.g. focus groups, citizen juries, contingent ranking, Q methodology) to assess private landowner willingness to protect, restore or create woodland, through various initiatives (e.g. woodland creation grants).
(2) Use mixed methods to understand and quantify the people's preferences for different woodland types (e.g. native/introduced species, ancient woodlands, plantations), species (e.g. rare species, species they can encounter), accessibility (e.g. distance from home, woodland size), and use/non-use ecosystem service values (e.g. recreation, carbon sequestration and storage).
(3) Use existing biodiversity data, and the findings from (1) and (2), within spatial conservation prioritisation software to determine where best to protect, restore and create woodland to maximise biodiversity and social benefits.
Training
Depending on the candidate's background, training could include use of systematic conservation planning software (e.g. Marxan, Zonation), ArcGIS/QGIS, social science data collection and analysis (e.g. participatory methods, questionnaire design, NVivo, R), academic skills (e.g. writing journal papers), and transferable skills (e.g. multi-media communication, time management). The individual will also collaborate with the research, evidence and policy teams at Woodland Trust.
Organisations
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| NE/S007334/1 | 01/10/2019 | 30/09/2027 | |||
| 2616909 | Studentship | NE/S007334/1 | 01/10/2021 | 31/08/2025 | Sam Aizlewood |