Spatio-Temporal Trends and Processes in Desertification in Africa and Europe

Project Outline

 

Desertification – the degradation of drylands caused by human activities catalysed by climatic variation – is a major global problem. Some 5,169 ha.106 in the arid, semi-arid and dry sub-humid zones – 40% of world land surface area – are susceptible to it, and the UN Convention to Combat Desertification (UNCCD) coordinates efforts to tackle it. Yet there is no reliable estimate of its actual global extent and rate of change. Four subjective estimates of the area of at least moderately desertified land prepared for the United Nations Environment Programme (UNEP) vary enormously, from 4,002 ha.106 to 3,272 ha.106 and 2,001 ha.106 in the 1970s, to 608 ha.106 in the 1980s in UNEP’s World Atlas of Desertification1. A 2008 estimate of 771 ha.106 uses a proxy variable of declining biomass growth, based on the Normalized Difference Vegetation Index derived from low (8 km) resolution satellite images, but biomass growth drops for other reasons, e.g. lack of rainfall, and soil erosion varies over areas as small as 0.1 ha2. The Third Edition of the World Atlas of Desertification, published in 2018 by a leading remote sensing group, the European Commission Joint Research Centre, did not use this method, or include any map of desertification at all3.

 

Shortages of empirical data constrain the work of the UNCCD generally, and its implementation of the Land Degradation Neutrality (LDN) target in the Sustainable Development Goals4. They also constrain scientific study of spatio-temporal desertification processes, which may include complex coupled and cross-scalar relationships between changes in land use and land cover. Alan Grainger helped to pioneer this field in the 1990s5 and further advances were made in an influential Science paper by Reynolds et al. in 20076.

 

Planetary measurement is still new – the first Landsat map of world forest area was not published until 2012, 40 years after the first Landsat was launched7. Desertification is far more complex than deforestation, involving changes in vegetation density and four types of soil degradation (wind erosion, water erosion, compaction and salinization), all affected by climatic variation.

 

Fortunately, mapping desertification is now more practical, since images from Very High (≤ 1 m) Resolution (VHR) satellite sensors, e.g. Ikonos and Quickbird, are freely available on Google Earth, and can be processed at global scale using open source software, e.g. Collect Earth, in the cloud. VHR images were first used for planetary measurement to map tree cover in the world’s drylands. Alan Grainger was a leading author of the resulting Science paper in 20178. This project will use the same methods to map soil and vegetation degradation.

 

Project Aims

 

  1. Produce the first empirical map of desertification and desertification trends in Africa and Europe by analysing VHR images.

 

  1. Advance knowledge of the geography of desertification processes.

 

Potential for High Impact Publications

 

This project offers an exciting opportunity for the successful candidate to make important advances in the planetary measurement of desertification and the modelling of its spatial-temporal processes, advances that are likely to lead to papers publishable in leading journals such as Nature and Science. These scientific advances will have important practical applications in helping governments to map how the dynamics of desertification and restoration trends in the same area can contribute to realizing the LDN SDG target.

 

Training and Supervision

 

The student will work under the supervision of Alan Grainger and Jon Lovett in the School of Geography, University of Leeds. They will be based within the School’s Ecology and Global Change cluster, and help to continue the cluster’s proud record of world-leading discoveries.

 

The student will have access to thousands of VHR images of Mediterranean Europe and Africa and be trained in how to use Collect Earth software to classify them using the characterization of plots selected selected by stratified systematic sampling to determine the degree of desertification for different land uses and soil degradation types. They will also be trained in the modelling of spatio-temporal desertification processes.

 

Applications

Students applying for this studentship should have, or expect to receive, a minimum 2.1 BSc and/or MSc degree in an appropriate discipline, and have interests and experience in global environmental change, land use and land cover change, biogeography and related areas.

To apply for the position, please visit https://panorama-dtp.ac.uk/how-to-apply/

 

Funding Notes

 

A fully-funded NERC studentship award covering the full cost of University fees plus maintenance of £15,609 (2021/22 rate) per year for 3.5 years is available, together with a generous research training and support grant. Applications are open to both home and international applicants.

 

References

 

  1. Middleton N.J. and Thomas D.S.G. (eds), 1992. World Atlas of Desertification. Arnold, London.
  2. Grainger A., 2009. Development of a Baseline Survey. UNCCD, Bonn.
  3. Cherlet M., Hutchinson C., Reynolds J., Hill J., Sommer S., and von Maltitz G. (eds), 2018. World Atlas of Desertification (3rd Edn). Publication Office of the European Union, Luxembourg.
  4. Grainger A., 2015. Is land degradation neutrality feasible in dry areas? Journal of Arid Environments 112:14-24.
  5. Grainger A., 1992. Characterization and assessment of desertification processes. In Chapman G.P. (ed.). Proceedings of Conference on Grasses of Arid and Semi-Arid Regions, Linnean Society, London, February 1991: 17-33. John Wiley, Chichester.
  6. Reynolds J.F., Stafford Smith D.M., Lambin E.F., Turner B.L. II et al., 2007. Building a science for dryland development. Science 316: 847-851.
  7. Townshend J.R., Masek J.G., Huang C., Vermote E.F., et al., 2012. Global characterization and monitoring of forest cover using Landsat data: opportunities and challenges. International Journal of Digital Earth 5: 373-397.
  8. Bastin J.-F., Berrahmouni N., Grainger A., Maniatis D. et al., 2017. The extent of forest in dryland biomes. Science 356: 635-638.