Journal
SCIENCE OF THE TOTAL ENVIRONMENT
Volume 584, Issue -, Pages 118-130Publisher
ELSEVIER
DOI: 10.1016/j.scitotenv.2016.12.160
Keywords
ARIES; InVEST; LUCI; Water supply; Carbon; Nutrient retention
Categories
Funding
- NERC [NE/K015508/1, NE/J011991/1]
- CEH Project [NEC05059, NEC04596]
- Biodiversity and Ecosystem Service Sustainability (BESS) programme
- UK Natural Environment Research Council (NERC)
- Biotechnology and Biological Sciences Research Council (BBSRC), UK's Living with Environmental Change (LWEC) programme
- Glastir Monitoring and Evaluation Programme (GMEP) [C147/2010/11]
- NERC/Centre for Ecology & Hydrology (CEH Project) [NEC04780]
- NERC [NE/K015508/1, NE/J014818/1, ceh020008, NE/J011991/1, ceh020005] Funding Source: UKRI
- Natural Environment Research Council [ceh020008, ceh020005, NE/J011991/1, NE/K015508/1, NE/J014818/1] Funding Source: researchfish
Ask authors/readers for more resources
Ecosystem services modelling tools can help land managers and policy makers evaluate the impacts of alternative management options or changes in land use on the delivery of ecosystem services. As the variety and complexity of these tools increases, there is a need for comparative studies across a range of settings, allowing users to make an informed choice. Using examples of provisioning and regulating services (water supply, carbon storage and nutrient retention), we compare three spatially explicit tools - LUCI (Land Utilisation and Capability Indicator), ARIES (Artificial Intelligence for Ecosystem Services) and InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs). Models were parameterised for the UK and applied to a temperate catchment with widely varying land use in North Wales. Although each tool provides quantitative mapped output, can be applied in different contexts, and can work at local or national scale, they differ in the approaches taken and underlying assumptions made. In this study, we focus on the wide range of outputs produced for each service and discuss the differences between each modelling tool. Model outputs were validated using empirical data for river flow, carbon and nutrient levels within the catchment. The sensitivity of the models to land-use change was tested using four scenarios of varying severity, evaluating the conversion of grassland habitat to woodland (0-30% of the landscape). We show that, while the modelling tools provide broadly comparable quantitative outputs, each has its own unique features and strengths. Therefore the choice of tool depends on the study question. (C) 2017 The Authors. Published by Elsevier B.V.
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