Congratulations!
Posted by Dr. Wenyan Zhang, head of the department Sediment Transport and Morphodynamics
On June 20, Peter Arlinghaus successfully defended his PhD thesis entitled “Benthos as a key driver of morphological evolution in coastal regions – exploration and explanation with numerical modeling”.
Peter did his research project at the Department of Sediment Transport and Morphodynamics in the Institute of Coastal Systems – Analysis and Modeling, supervised by Prof. Corinna Schrum and Dr. Wenyan Zhang.
It is well known that the morphological evolution of coastal zones is jointly controlled by physical, biological and anthropogenic processes. These exists extensive studies on the impacts of physical and anthropogenic drivers on coastal morphological development, from both observation and numerical modeling. The role of biota, especially plants such as seagrass, dune grass, mangroves and salt marshes, in guiding evolution of coastal landscapes has also received considerable interest in the past few decades.
However, most studies consider either one-way effect (e.g. hydro- and morphodynamics altered by presence of biota) and/or short-term (from tides, extreme events up to annual scale) changes. Few studies have focused on the two-way/mutual feedback between biota and hydro-morphodynamics, and long-term effect (from decadal up to millennial scale). Moreover, the majority of studies focus on coastal plants, and only a few have investigated the role of animals (e.g. benthic fauna) in hydro-morphodynamics of coastal zones. The thesis of Peter contributes to a deepened understanding of hydro-eco-morphodyhamics by focusing on the often-overlooked small animals (benthic fauna) that live in coastal zones. It presents an important step in filling the knowledge gap of hydro-eco-morphodynamics and provides a deepened understanding of a quantitative role of animals in coastal zone dynamics.
Bildergalerie
After his PhD defense, Peter will continue to work in the department of Sediment Transport and Morphodynamics as a postdoc to further his investigation on hydro-eco-morphodynamics, as well as utilization of advanced machine learning approaches for automatic classification of coastline types and quantification of changing rates.
