J.U. Smith 1*, S.J. Chapman 2, J.S. Bell 2, J. Bellarby 1, P. Gottschalk 1, G. Hudson 2, A. Lilly 2, P. Smith 1, W. Towers 2
ISBN 978 0 7559 7724 6 (Web only publication)
This document is also available in pdf format (1.7mb)
Contents
1. Executive Summary
1.1 Background
1.2 Exploring approaches to improve data used to derive changes in soil carbon stocks
1.2.1. Geostatistical analysis of sampling required to estimate total soil C stocks in Scottish peats
1.2.2. Timescales, logistics and deliverables for targeted resampling to measure total depth and bulk density
1.2.3. Evaluate retrospective use of archived dry bulk density to determine C stocks for peat bogs
1.2.4. Explore the costs and benefits of Ground Penetrating Radar ( GPR) and Light Detection and Ranging ( LIDAR)
to measure peat depth and monitor changes in soil C stocks in the peatlands of Scotland
1.3. Using ECOSSE to improve estimates of changes in soil carbon stock
1.3.1. Use data derived from NSIS_2 to improve accuracy of ECOSSE and its ability to predict the response of Scotland's organic soils to external change
1.3.2. Use of ECOSSE to address policy questions
2. Background
3. Exploring approaches to improve data used to derive changes in soil carbon stocks
3.1. Geostatistical analysis of the minimum sample numbers required to produce a statistically significant value for total soil
C stocks in Scottish peats
3.1.1. Introduction
3.1.2. Site descriptions of five typical peat bog areas
3.1.3. Data description
3.1.4. Data analysis methods
3.1.5. Exploratory plots
3.1.6. Descriptive statistics of peat depths
3.1.7. Statistical tests
3.1.8. Geostatistical study
3.1.9. Sensitivity analysis on current carbon stock estimates
3.1.10. Re-evaluation of peat depth data
3.1.11. Power analysis
3.1.12. Conclusions
3.2. Peat depth simulations
3.2.1. Introduction
3.2.2. Summary of the polygon and peat bog data
3.2.3. Geostatistical study of peat depths in bogs and polygons
3.2.4. Bayesian geostatistical simulations
3.2.5. Conclusions
3.3. Report on targeted peat resampling
3.3.1. Introduction
3.3.2. Methodology
3.3.3. Logistics
3.3.4. Logistical Issues
3.3.5. Timescales
3.3.6. Deliverables
3.3.7. Costs
3.3.8. Conclusions
3.4. Evaluation of use of archived dry bulk density values for peat bogs to determine C stocks values retrospectively
3.4.1. Introduction
3.4.2. Methodology
3.4.3. Results
3.4.4. Conclusions
3.5. Costs and benefits of GPR and Lidar to measure peat depth and the potential for using these methods to monitor changes in soil carbon stocks in the peatlands of Scotland
3.5.1. Introduction
3.5.2. Ground Penetrating Radar ( GPR)
3.5.3. Light Detection and Ranging technology ( LIDAR)
3.5.4. Other methods
3.5.5. Discussion and recommendations
4. Using ECOSSE to improve estimates of changes in soil carbon stock
4.1. Use NSIS data to improve the accuracy of ECOSSE and its ability to predict the response of Scotland's organic soils
to external change
4.1.1 Introduction
4.1.2. Input data
4.1.3. Data preparation
4.1.4. Results
4.1.5 Conclusions
4.2. Use national scale simulations of ECOSSE to address policy questions
4.2.1. Introduction
4.2.2. Adaptation of ECOSSE to use new data
4.2.3. Historical Simulations
4.2.4. Future Simulations
4.2.5. Mitigation options to reduce losses of soil C
4.2.6 Conclusions
5. Future Work
5.1. Geostatistical analysis of sampling required to estimate total soil C stocks in Scottish peats
5.2. Targeted resampling of map polygons containing peat to measure total depth, bulk density and %carbon
5.3. Explore the costs and benefits of Ground Penetrating Radar ( GPR) and Light Detection and Ranging ( LIDAR)
to measure peat depth and monitor changes in soil C stocks in the peatlands of Scotland
5.4. Use data derived from NSIS_2 to improve accuracy of ECOSSE and its ability to predict the response of Scotland's organic soils to external change
5.5. Use of ECOSSE to address policy questions
6. Conclusions
7. Acknowledgements
8. References
9. Appendices
9.1. Appendix 1. Summary data on peat depth (m) for 77 peat bogs, collated from the Scottish peat survey notes
1Institute of Biological and Environmental Sciences, School of Biological Science, University of Aberdeen, Cruickshank Building, St Machar Drive, Aberdeen, AB41 3UU, 2 Macaulay Institute, Craigiebuckler, Aberdeen AB15 8QH, * Project Manager
Project funded by the Rural and Environment Research and Analysis Directorate of the Scottish Government, Science Policy and Co-ordination Division.
The views expressed in this report are those of the researchers and do not necessarily represent those of the Scottish Government or Scottish Ministers