Scientific challenge


Farmed land (photo by Rothamsted Research)

Humans are dependent on goods and services provided by the natural environment, including assets such as soils, trees, water, air and insect pollinators. We use the term 'natural capital' to recognise the importance of nature’s assets and the benefits that flow from them. In order to provide better information on natural capital to support policy and research needs, data, models and scientific knowledge need to be brought together.

The Natural Capital Metrics (NCMet) project is integrating UKCEH and external data, models and science on natural capital assets, ecosystem services and human well-being.  We envisage that this science will underpin policy implementation, such as natural flood management, ecosystem accounts and the Defra 25-year plan for natural capital restoration.

Project overview


Upland stream (photo by Andy Sier, CEH)

UKCEH has unrivalled expertise and experience in the science of the natural environment that underpins natural capital. We collect and collate data through programmes such as the Countryside Survey, Glastir Monitoring and Evaluation Project, the Environmental Change Network (ECN), the Biological Records Centre and the National River Flow Archive. Such environmental datasets can be used to define measures of natural capital that relate to human benefit.  However, this often requires datasets to be translated or combined in complex ways because of multifaceted interactions and the multiple benefits that arise. For example, the existence of woodland, its location in a catchment, the interaction of the trees with soil all combine to determine carbon storage, flood management, recreation and biodiversity. 

UKCEH has developed in-house statistical models, such as Ecomaps, and uses external models, such as InVEST, LUCI and ARIES, to explore such interactions and understand how decisions on management or restoration of environmental assets will deliver different levels of natural capital.

In the Natural Capital Metrics project we are developing evidence chains linking natural capital to ecosystem services and benefits. We are also developing a Natural Capital Portal to present these evidence chains and their associated data, models, national scale maps and evidence sources.




Woodland (photo by Denise Pallett, CEH)

The NCMet project is:

  • Defining a conceptual framework for linking natural capital asset datasets to human well-being, identifying and providing an evidence base for any intervening steps in the chain, such as intermediate or final ecosystem services
  • Producing inventories of available asset datasets that contribute to knowledge of natural capital
  • Identifying and making available best knowledge of the processes and functions that define the interactions among natural capital assets, and how such interactions underpin the delivery of ecosystem services (e.g. through reviews)
  • Developing and applying tools and models that use this best available knowledge and recent data processing capabilities (such as cloud computing) to combine natural capital datasets and produce outputs that are, or can be transformed (e.g. by economists) into, measures of ecosystem services and human well-being
  • Developing knowledge exchange and communication tools, including a Natural Capital Portal, to provide access to datasets and project outputs, and to enable exploration of the chain of evidence linking natural capital to ecosystem services and human well-being.

Work packages


Rural landscape (photo by Andy Sier, CEH)

The NCMet workplan integrates conceptual and methodological innovation with empirical analysis from a range of case studies covering natural capital assets in land, water and air systems (Figure 1). It is based on three organising principles:

  • WP1 Coordination and conceptual framework: provides the overall coordination and management for the project, and develops the conceptual framework for integration of project components.
  • WPs 2 to 4 Datasets, evidence chain and models/tools: identifies CEH and external datasets that provide information on natural capital assets, and evaluates the chain of evidence concerning how these assets can be translated into different ecosystem services and benefits, including the development or advancement of any models, tools, methods and/or algorithms that are needed for this translation.  Research focuses on selected case studies from land, water and air systems, including:
    • Land: (i) Pollination linked to food provision; (ii) Vegetation/soil linked to carbon stocks/climate regulation
    • Air: (i) Air quality regulation linked to clean air;
    • Water: (i) Lake water quality regulation linked to clean water; (ii) Flood mitigation through tree planting; (iii) Flood and drought mitigation through riverine vegetation; (iv) Conflicts between seabird conservation and renewable energy; (v) Fish linked to recreation.
  • WP5 Natural capital portal and knowledge exchange: supports the dissemination of the project outcomes through the development of a natural capital portal and other knowledge exchange activities.

Diagram showing connections between work packages

Project members

Paula Harrison (Project Lead); Mike Acreman; Thomas August; Nuria Bachiller-Jareno; Bill Bealey; Rachel Beck; Maria Bogdanova; Mike Brown; James Bullock; Eleanor Blyth; Ed Carnell; Dave Carss; Laurence Carvalho; Claire Carvell; Jon Cooper; Jack Cosby; Robert Dunford-Brown; Matthew Fry; Tim Goodall; Hyun Gweon; Jane Hall; Colin Harrower; Peter Henrys; Nick Isaac; Laurence Jones; Karolis Kazlauskis; Filip Kral; Cedric Laize; Toby Matthews; Dario Masante; Lindsay Maskell; Linda May; Gina Mills; Dan Morton; Eiko Nemitz; Lisa Norton; Matthew O'Hare; Gareth Old; Anna Oliver; Luke Preston; Daniel Read; John Redhead; Stefan Reis; Sue Rennie; Glenn Rhodes; Elin Roberts; David Robinson; David Roy; Paul Scholefield; Rod Scott; Katrina Sharps; Andrew Sier; Simon Smart; Katie Smith; Charlie Stratford; Philip Taylor; Philip Trembath; Marcel van Oijen; Massimo Vieno; John Watkins; Mike Wilson; Ian Winfield; Helen Woods; Dan Wright

Principal Investigator

Prof. Paula Harrison is a Co-director of the Centre of Excellence in Environmental Data Science, a joint venture between UKCEH and Lancaster University. In this role she facilitates cross-disciplinary research addressing global environmental challenges through methodological advances in data science.