Hydraulic redistribution (HR) on the field scale: Novel approaches for monitoring and assessing the implications of HR for the resilience of forest ecosystems

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In the face of global change, ecosystems world-wide are experiencing severe challenges. In Europe, the recent drought has caused devastating forest dieback due to direct and indirect effects of drought. Hydraulic redistribution (HR) - the passive movement of water between different soil parts via plant root systems - is a process that can potentially have an impact on the capacity of ecosystems to adapt to droughts. Hydraulic lift (HL) is the most common form of HR, where due to water potential gradients between wetter deep soil and dry surface soil water passively moves to the dry soil region during the night, potentially providing an important water source to be used by plants. More than two decades of research on HR have demonstrated that it is a process with a global importance for ecosystems. Despite this proven global importance, consistent datasets on HR on spatial scales larger than the tree-scale and evidence-backed modeling approaches are extremely scarce. As a consequence, we are currently not able to predict accurately if HR will be an important component for the resilience of forests and other ecosystems under predicted climatic changes. In this project, we will – for the first time – collect a spatially distributed (field-scale, up to 1 ha) and temporally (sub-daily to weekly) high resolution dataset on HR. With this dataset we aim at investigating the relevance of HR on the field scale, assess the heterogeneity of HR and identify who are the beneficiaries of HR. In order to achieve this, we will establish a monitoring scheme specifically designed to identify, monitor and quantify HR. This setup combines methods based on the in situ measurement of water stable isotopes with specific ecohydrological monitoring techniques and isotopic labeling experiments in a mixed broad-leaf forest. The dataset will subsequently be used to parametrize and calibrate the isotope-enabled soil-vegetation-atmosphere transfer (SVAT) model MuSICA and determine the contribution of HR to transpiration on the field scale using end-member mixing analysis (EMMA). The calibrated model will then be used in order to predict the importance of HR for the resilience of the investigated mixed broad-leaf forest ecosystem under climatic changes. The results of this project will help to understand the role of HR for forest ecosystems now and under predicted future climatic conditions. It will contribute to assess the potential buffering effect of HR during droughts and extreme conditions, which can help to inform forest management in terms of developing resilient forest ecosystems of the future. Furthermore, the proposed methodological framework could potentially become a standard procedure for assessing HR on larger spatial scales.