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The influence of vegetation on soil water repellency-markers and soil hydrophobicity
Mao, J.; Nierop, K.G.J.; Rietkerk, M.; Sinninghe Damsté, J.S.; Dekker, S.C. (2016). The influence of vegetation on soil water repellency-markers and soil hydrophobicity. Sci. Total Environ. 566-567: 608-620. dx.doi.org/10.1016/j.scitotenv.2016.05.077
In: Science of the Total Environment. Elsevier: Amsterdam. ISSN 0048-9697, more
Peer reviewed article  

Available in Authors 

Author keywords
    Soil water repellency; Vegetation cover; Grass roots; Oak roots; Soil water repellency markers

Authors  Top 
  • Mao, J.
  • Nierop, K.G.J.
  • Rietkerk, M.
  • Sinninghe Damsté, J.S., more
  • Dekker, S.C.

Abstract
    Soil water repellency (SWR) markers are defined as hydrophobic compounds in soil causing SWR and are mainly derived from plants. Previous studies have shown the types and abundance of SWR-markers in soils. However, how these SWR-markers are exactly related to SWR and their origin is poorly understood. This study aims to understand the relationship between SWR-markers, vegetation type and cover and SWR for a simple sandy soil ecosystem, consisting of oaks with sedge and six grass species. All the soil (at different depth) and vegetation samples were collected in the field along a 6 m transect, starting from an oak tree. Further along the transect grasses and sedges became more abundant. Free and ester-bound lipids from soils and plant leaves/roots were obtained using a sequential extraction method and identified by gas chromatography–mass spectrometry. Significant linear correlations were found between the main soil characteristics, such as total organic carbon content, and SWR. Single long-chain (> C20) SWR-markers derived from both plant leaf waxes and roots positively related to SWR. Both ester-bound ?-hydroxy fatty acids and C22 and C24 a,?-dicarboxylic acids were predominantly present in the grass roots, but to a lesser extent in the roots of oak and sedge. These suberin-derived ?-hydroxy fatty acids and a,?-dicarboxylic acids characteristic of roots could well predict the SWR. Additionally, the SWR predictors abundantly present in the soils matched well with high concentrations of the corresponding biomarkers in the dominant vegetation species that covered the soils. Our analyses demonstrated that grass roots influenced SWR more due to their more substantial contribution of organic matter to the topsoils than oak roots. This led to a stronger SWR of the soils covered with grass than those covered with oak vegetation.

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