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Modelling historical landscape changes

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Abstract

Context

Historical maps of land use/land cover (LULC) enable detection of landscape changes, and help to assess drivers and potential future trajectories. However, historical maps are often limited in their spatial and temporal coverage. There is a need to develop and test methods to improve re-construction of historical landscape change.

Objectives

To implement a modelling method to accurately identify key land use changes over a rural landscape at multiple time points.

Methods

We used existing LULC maps at two time points for 1930 and 2015, along with a habitat time-series dataset, to construct two new, modelled LULC maps for Dorset in 1950 and 1980 to produce a four-step time-series. We used the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Scenario Generator tool to model new LULC maps.

Results

The modelled 1950 and 1980 LULC maps were cross-validated against habitat survey data and demonstrated a high level of accuracy (87% and 84%, respectively) and low levels of model uncertainty. The LULC time-series revealed the timing of LULC changes in detail, with the greatest losses in neutral and calcareous grassland having occurred by 1950, the period when arable land expanded the most, whilst the expansion in agriculturally-improved grassland was greatest over the period 1950–1980.

Conclusions

We show that the modelling approach is a viable methodology for re-constructing historical landscapes. The time-series output can be useful for assessing patterns and changes in the landscape, such as fragmentation and ecosystem service delivery, which is important for informing future land management and conservation strategies.

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Acknowledgements

Thanks to Maliko Tanguy and Emma Robinson, UKCEH Wallingford for their assistance with the UKCEH GEAR and CHESS datasets, respectively. Thank you to Josué Rodríguez, CEH Wallingford for his help installing python modules. Thank you also to James Douglass at the InVEST Natural Capital Project for his assistance with the Scenario Generator Rule-Based tool. This work was funded by the Natural Environment Research Council (NERC), Grant Reference Number: NE/P007716/1 as part of the project Mechanisms and Consequences of Tipping Points in Lowland Agricultural Landscapes (TPAL), which forms part of the Valuing Nature Programme. The Valuing Nature Programme (www.valuing-nature.net.) is funded by the Natural Environment Research Council (NERC), the Economic and Social Research Council, the Biotechnology and Biological Sciences Research Council, the Arts and Humanities Research Council and the Department for Environment, Food and Rural Affairs. The recast LCM1990 was supported by the NERC award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.

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Author notes

  1. Stephen C. L. Watson

    Present address: School of Biological Sciences, University of Portsmouth, Portsmouth, Hampshire, PO1 2UP, UK

Authors and Affiliations

  1. UK Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxfordshire, OX10 8BB, UK

    Lucy E. Ridding, John W. Redhead & James M. Bullock

  2. Faculty of Science and Technology, Centre for Ecology, Environment and Sustainability, Bournemouth University, Talbot Campus, Poole, Dorset, BH12 5BB, UK

    Adrian C. Newton & Stephen C. L. Watson

  3. UK Centre for Ecology & Hydrology, Library Avenue, Lancaster, LA1 4AP, UK

    Clare S. Rowland

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  1. Lucy E. Ridding
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Correspondence to Lucy E. Ridding.

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Ridding, L.E., Newton, A.C., Redhead, J.W. et al. Modelling historical landscape changes. Landscape Ecol 35, 2695–2712 (2020). https://doi.org/10.1007/s10980-020-01059-9

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