2018
DOI: 10.1111/gcb.14403
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Groundwater drawdown drives ecophysiological adjustments of woody vegetation in a semi‐arid coastal ecosystem

Abstract: Predicted droughts and anthropogenic water use will increase groundwater lowering rates and intensify groundwater limitation, particularly for Mediterranean semi-arid ecosystems. These hydrological changes may be expected to elicit differential functional responses of vegetation either belowground or aboveground. Yet, our ability to predict the impacts of groundwater changes on these ecosystems is still poor. Thus, we sought to better understand the impact of falling water table on the physiology of woody vege… Show more

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Cited by 32 publications
(30 citation statements)
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References 94 publications
(143 reference statements)
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“…Thus, those plants should show almost zero anomaly. In contrast, GDV plants coping well with usual summer drought can be expected to suffer an unusual stress under an extremely dry year, even having access to groundwater , 2014, with a negative impact of groundwater drawdown (Antunes et al, 2018). Therefore, GDV plants should show negative NDWI anomalies.…”
Section: Map Evaluationmentioning
confidence: 99%
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“…Thus, those plants should show almost zero anomaly. In contrast, GDV plants coping well with usual summer drought can be expected to suffer an unusual stress under an extremely dry year, even having access to groundwater , 2014, with a negative impact of groundwater drawdown (Antunes et al, 2018). Therefore, GDV plants should show negative NDWI anomalies.…”
Section: Map Evaluationmentioning
confidence: 99%
“…Mapping GDEs constitutes a first and fundamental step to their active management. Several approaches have been proposed, from local field surveys measuring plant transpiration of stable isotopes (Antunes et al, 2018) up to larger spatial scales involving remote-sensing techniques (e.g., normalized difference vegetation index -NDVI; Barron et al, 2014;Eamus et al, 2015;Howard and Merrifield, 2010), remote-sensing combined with ground-based observations (Lv et al, 2013), a geographic information system (GIS; Pérez Hoyos et al" 2016a) combining field surveys (Condesso de Melo et al, 2015) or even statistical approaches (Pérez Hoyos et al, 2016b).…”
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confidence: 99%
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