Global distribution of groundwater‐vegetation spatial covariation

Abstract

Groundwater is an integral component of the water cycle, and it also influences the carbon cycle by supplying moisture to ecosystems. However, the extent and determinants of groundwater‐vegetation interactions are poorly understood at the global scale. Using several high‐resolution data products, we show that the spatial patterns of ecosystem gross primary productivity and groundwater table depth are correlated during at least one season in more than two thirds of the global vegetated area. Positive relationships, i.e., larger productivity under shallower groundwater table, predominate in moisture‐limited dry to mesic conditions with herbaceous and shrub vegetation. Negative relationships, i.e., larger productivity under deeper groundwater, predominate in humid climates with forests, possibly indicating a drawdown of groundwater table due to substantial ecosystem water use. Interestingly, these opposite groundwater‐vegetation interactions are primarily associated with differences in vegetation than with climate and surface characteristics. These findings put forth the first evidence, and a need for better representation, of extensive and non‐negligible groundwater‐vegetation interactions at the global scale.

The partitioning of gross primary production for young Eucalyptus tereticornis trees under experimental warming and altered water availability

“…Furthermore, Koirala et al . () demonstrated correlations between GPP and groundwater table depth that were present over c . 70% of the vegetated surface of the Earth, suggesting that vegetation–groundwater interactions are common and globally relevant.…”

“…Previous studies have shown that groundwater use enables vegetation to mitigate production declines under conditions of surface moisture limitation (Baldocchi et al, 2010;Barbeta et al, 2015), and several eucalypt species are well-known users of groundwater (Mensforth et al, 1994;Pfautsch et al, 2011Pfautsch et al, , 2015Eamus et al, 2015;Zolfaghar et al, 2017). Furthermore, Koirala et al (2017) demonstrated correlations between GPP and groundwater table depth that were present over c. 70% of the vegetated surface of the Earth, suggesting that vegetation-groundwater interactions are common and globally relevant. Our study demonstrates that some trees may utilize access to soil water at depth to maintain moderate rates of photosynthetic C uptake and growth during extended droughts that lead to dry surface soils.…”

Reconstructed Solar‐Induced Fluorescence: A Machine Learning Vegetation Product Based on MODIS Surface Reflectance to Reproduce GOME‐2 Solar‐Induced Fluorescence

“…A correctly fitted and nonoverfitting NN is able to generalize instead of just learning a functional relationship on existing data (Wan et al, 2013). There have been multiple successful applications of NN in the geosciences in recent years ranging from soil moisture retrievals (Jimenez et al, 2013; Kolassa et al, 2013, 2016; Kolassa, Gentine, et al, 2017; Kolassa, Reichle, & Draper, 2017) and surface temperature and emissivity retrievals (Aires et al, 2001) to surface flux retrievals (Alemohammad et al, 2017; Beer et al, 2010; Jimenez et al, 2009; Jung et al, 2009; Koirala et al, 2017). …”

Satellite Observations of the Contrasting Response of Trees and Grasses to Variations in Water Availability

“…Figure 3 presents the partial correlations in time of deviations in SIF and EVI with respect to either temperature, incoming radiation or soil moisture, whilst controlling for the remaining two. The increase in photosynthesis also raises transpiration (Koirala et al, 2017), which would result in a reduction of soil water content that is less likely to be replenished by precipitation due to lower cloud cover. This confirms that variations in soil water content affect nonforested ecosystems mainly by causing plant structural and pigment changes (i.e., chlorophyll content and leaf area; , which translate into the observed variability in greenness, photosynthesis and APAR.…”