Key Considerations for integrating Quantitative Social Science within Landscape Decisions
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About this item
| Description: |
Comber, A
Wednesday 9th September 2020 - 13:30 to 14:00 |
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| Created: | 2020-09-10 19:55 |
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| Collection: | Mathematical and statistical challenges in landscape decision making |
| Publisher: | Isaac Newton Institute |
| Copyright: | Comber, A |
| Language: | eng (English) |
| Distribution: |
World
(downloadable)
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| Explicit content: | No |
| Aspect Ratio: | 16:9 |
| Screencast: | No |
| Bumper: | UCS Default |
| Trailer: | UCS Default |
| Abstract: | The land resource is used to satisfy many different land -related objectives: food production and security, biodiversity, housing and other developments, leisure and recreation, as well as flood protection, biomass, energy production and waste. Landscape Decisions are fundamentally concerned determining what to put where and have to balance competing demands for these different Ecosystem Services. This allocation problem is further complicated by a number of specifically social factors: - Different actors in landscape decision making (from policy to landowners to citizen ‘consumers’) have different objectives and priorities and value landscape elements in different ways - These values vary between and within groups, as well as with socio-economic context - Individual and institutional objectives also operate over different time frames and spatial scales Thus some form of socio-economic analysis or social modelling is integral to landscape decisions to - incorporate stakeholder preferences (e.g. the relative value of any given ESs) - model land management behaviours (e.g. risk seekers, consolidators, market reactors, etc) - evaluate the socio-economic impacts of landscape decisions (e.g. to quantify the trade-offs between food production and flood risk mitigation) This talk will outline and illustrate the impacts of a number of key but frequently overlooked issues associated with incorporating *any spatial data* (including data describing social processes) into landscape decision models, related to scale, scales of decision making and model evaluation.
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