A global map of groundwater-dependent vegetation in the Mediterranean biome
(2026) In Ecological Indicators 183.- Abstract
Groundwater-dependent vegetation (GDV) plays a vital role in maintaining biodiversity and ecosystem services in the Mediterranean biome but is increasingly threatened by climate and land use change. Large-scale GDV mapping in arid regions is critical for effective conservation and water resource management but remains challenging due to limited ground-truth data and the lack of high-resolution remote sensing-based spatial models. In this study, we mapped GDV across the world's five Mediterranean climate regions using a multi-level approach combining species-occurrence, vegetation-plot, and remote-sensing data. At the species level, we compiled a global list of phreatophyte and groundwater-associated species, which we used to extract... (More)
Groundwater-dependent vegetation (GDV) plays a vital role in maintaining biodiversity and ecosystem services in the Mediterranean biome but is increasingly threatened by climate and land use change. Large-scale GDV mapping in arid regions is critical for effective conservation and water resource management but remains challenging due to limited ground-truth data and the lack of high-resolution remote sensing-based spatial models. In this study, we mapped GDV across the world's five Mediterranean climate regions using a multi-level approach combining species-occurrence, vegetation-plot, and remote-sensing data. At the species level, we compiled a global list of phreatophyte and groundwater-associated species, which we used to extract occurrence records from GBIF. At the community level, we classified vegetation-plot data from the sPlot database based on phreatophyte presence and coverage, resulting in a unique ground-truth species-community dataset. At the biome level, we trained Random Forest models with eleven predictor variables in order to map GDV distribution at 30 m resolution for the period 2018–2023. We identified 482,000 km2 of GDV, covering 28% of the study area and predicted GDV hotspots for the Western Iberian Peninsula, Southern France, California, Chile, and the West Coast of Australia. The largest absolute area of GDV was found in the Mediterranean Basin (306,000 km2), while the highest relative coverage was found in California (42%) and Chile (40%). Notably, only about a quarter of Mediterranean GDV lies within protected areas. Key environmental predictors include soil sand content, dry season vegetation vitality, and elevation. By integrating species, community, and remote-sensing data, our high-resolution GDV map provides a crucial basis for monitoring ecosystem response to global change, conservation planning, sustainable groundwater management, and risk assessment in the drought-stressed Mediterranean biome.
(Less)
- author
- organization
- publishing date
- 2026-02
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Biodiversity, Groundwater-dependent vegetation, Machine learning, Mediterranean, Phreatophytes, Remote sensing, Terrestrial ecosystem
- in
- Ecological Indicators
- volume
- 183
- article number
- 114669
- publisher
- Elsevier
- external identifiers
-
- scopus:105029226847
- ISSN
- 1470-160X
- DOI
- 10.1016/j.ecolind.2026.114669
- language
- English
- LU publication?
- yes
- id
- 113e5d53-e85e-4e5f-b6be-7ac29cba19c3
- date added to LUP
- 2026-02-18 14:59:24
- date last changed
- 2026-03-18 21:52:44
@article{113e5d53-e85e-4e5f-b6be-7ac29cba19c3,
abstract = {{<p>Groundwater-dependent vegetation (GDV) plays a vital role in maintaining biodiversity and ecosystem services in the Mediterranean biome but is increasingly threatened by climate and land use change. Large-scale GDV mapping in arid regions is critical for effective conservation and water resource management but remains challenging due to limited ground-truth data and the lack of high-resolution remote sensing-based spatial models. In this study, we mapped GDV across the world's five Mediterranean climate regions using a multi-level approach combining species-occurrence, vegetation-plot, and remote-sensing data. At the species level, we compiled a global list of phreatophyte and groundwater-associated species, which we used to extract occurrence records from GBIF. At the community level, we classified vegetation-plot data from the sPlot database based on phreatophyte presence and coverage, resulting in a unique ground-truth species-community dataset. At the biome level, we trained Random Forest models with eleven predictor variables in order to map GDV distribution at 30 m resolution for the period 2018–2023. We identified 482,000 km<sup>2</sup> of GDV, covering 28% of the study area and predicted GDV hotspots for the Western Iberian Peninsula, Southern France, California, Chile, and the West Coast of Australia. The largest absolute area of GDV was found in the Mediterranean Basin (306,000 km<sup>2</sup>), while the highest relative coverage was found in California (42%) and Chile (40%). Notably, only about a quarter of Mediterranean GDV lies within protected areas. Key environmental predictors include soil sand content, dry season vegetation vitality, and elevation. By integrating species, community, and remote-sensing data, our high-resolution GDV map provides a crucial basis for monitoring ecosystem response to global change, conservation planning, sustainable groundwater management, and risk assessment in the drought-stressed Mediterranean biome.</p>}},
author = {{El-Hokayem, Léonard and Damasceno, Gabriella and Sabatini, Francesco M. and Bruelheide, Helge and Bonari, Gianmaria and Dwyer, Ciara and Gonçalves, Fernando and Jiménez-Alfaro, Borja and Millett, Jonathan and Peñuelas, Josep and Svenning, Jens Christian and Altman, Jan and Chen, Han Y.H. and Dziuba, Tetiana and El-Sheikh, Mohamed A. and Güler, Behlül and Hending, Daniel and Hérault, Bruno and Hatim, Mohamed Z. and Jansen, Florian and Meyer, Carsten and Mukul, Sharif A. and Pielech, Remigiusz and Rodrigues, Flávio and Wang, Hua Feng and Conrad, Christopher}},
issn = {{1470-160X}},
keywords = {{Biodiversity; Groundwater-dependent vegetation; Machine learning; Mediterranean; Phreatophytes; Remote sensing; Terrestrial ecosystem}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Ecological Indicators}},
title = {{A global map of groundwater-dependent vegetation in the Mediterranean biome}},
url = {{http://dx.doi.org/10.1016/j.ecolind.2026.114669}},
doi = {{10.1016/j.ecolind.2026.114669}},
volume = {{183}},
year = {{2026}},
}