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GM-GDE

Global mapping of threatened groundwater-dependent ecosystems by means of remote sensing

Groundwater resources are biodiversity hotspots and provide important ecosystem services. Groundwater-dependent ecosystems (GDEs) are exposed to anthropogenic threats such as climate change. In order to respond to these threats, the identification of GDEs needs to be advanced on a global scale. The project will develop a novel vegetation and hydrological approach for mapping, analysing and assessing GDEs on a global scale using multi-scale and multi-instrument methods.

 

Sub-project leader:
Team:
Project partners:
  • German Centre for Integrative Biodiversity Research
Background and objectives:
  • Entwicklung eines biom-spezifischen Workflows zur Kartierung von grundwasserabhängigen Ökosystemen
  • Validierung der Ergebnisse
  • Bewertung Gefährdungspotentials für GDEs
Methodological approach:
  • Definition of the global GDE mapping framework (remote sensing, spatial data integration)
  • Implementation of the global GDE mapping framework at the biome level
  • Proof of concept, validation and optimisation with existing GDE maps and data from field work (vegetation surveys, vegetation ecology measurements (SPAD, LAI, fluorescence, soil parameters)
  • Analysis of the sensitivity of GDEs to climate change and anthropogenic influences (remote sensing, geo-data integration)
Expected results:

A global map of groundwater-dependent ecosystems (especially groundwater-dependent terrestrial vegetation) in different biomes, validated with different (in-situ) geodata, is expected. On the basis of this map, the GDEs are to be assessed against the background of the Red List for ecosystems with regard to their endangerment by anthropogenic influence.

Publications:
1
Schulz, D.E., El-Hokayem, L. and Conrad, C. (2024, September 13) A New Approach towards Mapping-Dependent vegetation in the Temperate Biome Using and Sentinel-2 Data: A Case Study in Saxony-Anhalt. Poster, Freising.
1
El-Hokayem, L. (2024, September 13) From Phreatophyte Species to Habitat Probability for Groundwater-Dependent Vegetation - A Multiscale Approach. Talk, Freising.
1
El-Hokayem, L., De Vita, P., Lindau, A.-K. and Conrad, C. (2024) How Can Satellites Help Us Find Plants That Use Groundwater? Frontiers for Young Minds, 12, 1394341. https://doi.org/10.3389/frym.2024.1394341.
1
El-Hokayem, L., Damasceno, G., Bruehlheide, H., Sabatini, F.M. and Conrad, C. (2024, June 13) Using Global Vegetation Data and Remote Sensing to Identify Groundwater-Dependent Vegetation. Poster, Marburg.
1
El-Hokayem, L., De Vita, P., Usman, M., Link, A. and Conrad, C. (2023, August 30) Potential Groundwater Dependent Vegetation in the Mediterranean [Dataset]. PANGAEA. https://doi.pangaea.de/10.1594/PANGAEA.961765.
1
El-Hokayem, L., De Vita, P., Usman, M., Link, A. and Conrad, C. (2023) Mapping Potentially Groundwater-Dependent Vegetation in the Mediterranean Biome Using Global Geodata Targeting Site Conditions and Vegetation Characteristics. Science of The Total Environment, 898, 166397. https://doi.org/10.1016/j.scitotenv.2023.166397.
1
Link, Andreas, El-Hokayem, L., Usman, M., Conrad, C., Reinecke, R., Berger, M., Wada, Y., Coroama, V. and Finkbeiner, M. (2023, August 3) Groundwater-Dependent Ecosystems at Risk [Dataset]. Mendeley. https://doi.org/10.17632/P39Y3MDH6N.3.
1
Link, A., El-Hokayem, L., Usman, M., Conrad, C., Reinecke, R., Berger, M., Wada, Y., Coroama, V. and Finkbeiner, M. (2023) Groundwater-Dependent Ecosystems at Risk – Global Hotspot Analysis and Implications. Environmental Research Letters. https://doi.org/10.1088/1748-9326/acea97.
1
El-Hokayem, L., De Vita, P. and Conrad, C. (2023) Mapping of Potential Groundwater Dependent Vegetation Zones in the Mediterranean Using a Simple Index Based on Global-Available Geodata and High-Resolution Remote Sensing. EGU, Naples. https://doi.org/https://doi.org/10.5194/egusphere-gc8-hydro-61.
1
El-Hokayem, L., De Vita, P. and Conrad, C. (2023) Local Identification of Groundwater Dependent Vegetation Using High-Resolution Sentinel-2 Data – A Mediterranean Case Study. Ecological Indicators, 146, 109784. https://doi.org/10.1016/j.ecolind.2022.109784.
Theses:

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GM-GDE
  • Website

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  • Research area
Saxony-Anhalt, Germany; Campania, Italy; Kenya
  • Project duration
2022-2024
  • Funding body
MLUBioDivFund
  • Project orientation
Research
  • Contact

Léonard El-Hokayem