Long-Term Model Simulation of Environmental Conditions to Identify Externally Forced Signals in Biological Time Series


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Ute.Alexander [ at ] awi.de

Abstract

A case study is presented to demonstrate the added value which can be gained from combining long-term biological observations with model-based hind casts of physical environmental conditions. The study utilizes numerically simulated high-resolution fields of currents and water levels in the North Sea to investigate the relevance of hydrodynamic conditions for the occurrence of phytoplankton blooms, as observed at Helgoland Roads in the inner German Bight. Inter-annual variations as well as a possible regime shift are discussed with regard to the spring mean diatom day. The long-term high-resolution simulations of the North Sea circulation are taken from the data base 'coastDat'. © 2010 Springer Science+Business Media B.V.



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Inbook
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Published
Eprint ID
17664
DOI https://www.doi.org/10.1007/978-90-481-8782-9_11

Cite as
Stockmann, K. , Callies, U. , Manly, B. F. and Wiltshire, K. H. (2010): Long-Term Model Simulation of Environmental Conditions to Identify Externally Forced Signals in Biological Time Series , In: Müller, F., Baessler, C., Schubert, H., Klotz, S. (eds.), Long-term ecological research - between theory and application, Springer-Verlag, pp, Springer Netherlands, ISBN: 9789048187812 . doi: https://www.doi.org/10.1007/978-90-481-8782-9_11


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