Links to papers from the Landscape Decisions network and from our constituent project teams will be added here throughout the programme so be sure to check back regularly or follow us on Twitter to keep up with additions and check out the projects pages for further information on individual projects
Using remote sensors to predict soil properties: Radiometry and peat depth in Dartmoor, UK produced by the Issues of Uncertainty and Scale in Derived Products project team and published in Geoderma Volume 403, 1 December 2021, 115232
This research was funded by the NERC project NE/T004169/1 as part of the Landscapes Decisions Programme and by EPSRC as part of the Senior Fellowship in the Role of Digital Technology in Understanding, Mitigating and Adapting to Environmental Change grant no: EP/P002285/1. This paper is published with the permission of the Executive Director, BGS. The author is grateful to David Beamish (BGS), Christoph Kratz (Natural England) and Dylan Young (Leeds University) for informative discussions.
Uncertainty of modelled bioenergy with carbon capture and storage due to variability of input data produced by the ADVANCES project team in collaboration with teams outside of the Landscape Decisions Programme cohort. Authored by Anita Shepherd, Mike Martin & Astley Hastings. First published 08 January 2021 https://doi.org/10.1111/gcbb.12803
Climate and soil effects were tested on BECCS, as part of the UKERC (UK Energy Research Centre) Phase 4 research programme, funded by UK Research and Innovation (EP/S029575/1). Model development was also made possible by ADVENT (ADdressing Valuation of Energy and Nature Together).
Ensembles of ecosystem service models can improve accuracy and indicate uncertaint produced by the EnsemblES project team and published in Science of The Total Environment Volume 747, 10 December 2020, 141006
This work took place under the ‘WISER: Which Ecosystem Service Models Best Capture the Needs of the Rural Poor?’ project (NE/L001322/1), funded by the UK Ecosystem Services for Poverty Alleviation program (ESPA; www.espa.ac.uk) and ‘EnsemblES – Using ensemble techniques to capture the accuracy and sensitivity of ecosystem service models’ (NE/T00391X/1). JML acknowledges the support of the Spanish Government through María de Maeztu excellence accreditation 2018-2021 (Ref. MDM-2017-0714). We thank three anonymous reviewers for their insightful comments that improved this manuscript.