4.7 Article

The impact of land use/land cover scale on modelling urban ecosystem services

期刊

LANDSCAPE ECOLOGY
卷 31, 期 7, 页码 1509-1522

出版社

SPRINGER
DOI: 10.1007/s10980-015-0337-7

关键词

Ecosystem services; Urban; Model; Natural capital; Scale; InVEST; Pollination; Erosion; Carbon; England

资金

  1. Fragments, Functions and Flows in Urban Ecosystem Services (F3UES) Project as part of the larger Biodiversity and Ecosystem Service Sustainability (BESS) [NE/ J015067/1]
  2. UK Natural Environment Research Council (NERC)
  3. Biotechnology and Biological Sciences Research Council (BBSRC) as part of the UK's Living with Environmental Change (LWEC) programme
  4. NERC
  5. BESS
  6. Natural Environment Research Council [NE/J015369/1, NE/J015067/1] Funding Source: researchfish
  7. NERC [NE/J015067/1, NE/J015369/1] Funding Source: UKRI

向作者/读者索取更多资源

Context Urbanisation places increasing stress on ecosystem services; however existing methods and data for testing relationships between service delivery and urban landscapes remain imprecise and uncertain. Unknown impacts of scale are among several factors that complicate research. This study models ecosystem services in the urban area comprising the towns of Milton Keynes, Bedford and Luton which together represent a wide range of the urban forms present in the UK. Objectives The objectives of this study were to test (1) the sensitivity of ecosystem service model outputs to the spatial resolution of input data, and (2) whether any resultant scale dependency is constant across different ecosystem services and model approaches (e.g. stock-versus flow-based). Methods Carbon storage, sediment erosion, and pollination were modelled with the InVEST framework using input data representative of common coarse (25 m) and fine (5 m) spatial resolutions. Results Fine scale analysis generated higher estimates of total carbon storage (9.32 vs. 7.17 kg m(-2)) and much lower potential sediment erosion estimates (6.4 vs. 18.1 Mg km(-2) year(-1)) than analyses conducted at coarser resolutions; however coarse-scale analysis estimated more abundant pollination service provision. Conclusions Scale sensitivities depend on the type of service being modelled; stock estimates (e.g. carbon storage) are most sensitive to aggregation across scales, dynamic flow models (e.g. sediment erosion) are most sensitive to spatial resolution, and ecological process models involving both stocks and dynamics (e.g. pollination) are sensitive to both. Care must be taken to select model data appropriate to the scale of inquiry.

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