Understanding Turning Points in Dryland Ecosystem Functioning (U-TURN)

Start-End 01/12/2016 -  30/06/2018
Programme STEREO 3
Contract SR/00/339
Objective Drylands ecosystems are subjected to on-going global change, devastating climate extremes and unsustainable use of natural resources. Indications that some ecosystems have switched to a new state of functioning as a result of these climate and anthropogenic disturbances were found. Yet the understanding and quantification of such abrupt changes (so-called turning points) remains challenging, hampering the development of monitoring, modelling and early warning systems for ecosystem management and prevention of economic or ecological losses. The U-TURN project aims at quantifying and understanding turning points in the functioning of dryland ecosystems. Major focus will be put on disentangling climatic and anthropogenic drivers and the assessment of proxies for early warning of turning points in ecosystem functioning (EF). This will be achieved by combining advanced Earth Observation (EO) techniques with Dynamic Vegetation Models (DVMs).
Method The work in this project is divided into three main parts, consisting of five main research work packages. WP1 focuses on (i) the quantification and characterization of turning points in ecosystem functioning (EF) within the global drylands and (ii) the identification of focus areas for the next research steps. The occurrence, magnitude and timing of abrupt temporal changes in the ecosystem response to hydroclimatic conditions will be identified using improved time series segmentation technique. Activities related to WP1 will be completed during Phase 1. The second part of the project [WP 2 and WP3] will ensure high quality research and insight on the issue of turning point in dryland EF by (1) producing time series (approximately 5-year epochs) of HR LULC products for the focus areas (WP2) and (2) by optimizing the parameterization of two state-of-the-art DVMs (ED2 and LPJ-GUESS) for drylands (WP3). WPs2-3 will be running during both Phase 1 and 2. Finally the third part of the project [WP 4 and WP 5] aims at gaining insight in EF turning points [WP4] and explore the potential of early warning systems for ecosystems turning points [WP5]. Activities related to WP4 and WP5 will be completed during Phase 2.
Result Expected Scientific Results for Phase 1
  • Improved BFAST algorithm targeting turning point in ecosystem functioning
  • Global scale assessment of turning points in dryland ecosystems functioning
  • Design and tests of the prototype classification algorithm
  • Production of time series of HR LC maps over 2 focus areas
  • Initial parameterization of the ED2 and LPJ-GUESS model for African drylands

Expected Products and Services for Phase 1
  • New code for the improved BFAST algorithm in R-Forge
  • Map of ecosystem change types for global drylands
  • Collection of land cover maps for two focus areas since the early 1980’s
  • Initial version of ED2 and LPJ-Guess for African drylands
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Project Leader: SOMERS Ben KULeuven (Katholieke Universiteit Leuven)
Team Member: VERBEECK Hans Ugent (Universiteit Gent)
Team Member: VAN DE KERCKHOVE Ruben VITO (Vlaamse Instelling voor Technologisch Onderzoek)
Team Member: HORION Stéphanie University of Copenhagen
Team Member: VERBESSELT Jan University of Wageningen
Team Member: LHERMITTE Stefaan TU Delft (Technische Universiteit Delft)
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