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180606s2012 xx |||||o 00| ||eng c |
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|a (DE-627)JST114442150
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|a (JST)24876037
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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|a Alexandridis, Nikolaos
|e verfasserin
|4 aut
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|a Modeling the effects of abiotic and biotic factors on the depth distribution ofFucus vesiculosusin the Baltic Sea
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|c 2012
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|a Text
|b txt
|2 rdacontent
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|a Computermedien
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|2 rdamedia
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|a Online-Ressource
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|a ABSTRACT: The conspicuous retreat of the key speciesFucus vesiculosusfrom the deeper parts of its former distribution area in the Baltic Sea has triggered extensive research on the factors that control its growth. Based on recently obtained knowledge on a large number of potential drivers, we developed a numerical model incorporating effects of abiotic factors on the physiological functions of photosynthesis, respiration, and reproduction and the ecological processes of competition, grazing, and epibiosis. For all input combinations, the model delivers the monthly net growth rate near the bladder wrack’s depth limit and the maximum depth of its vertical distribution. The use of data corresponding to conditions presently observed in the western Baltic Sea sets the year’s maximum algal net growth rate in late spring and 2 minima in early spring and autumn. The depth limit of the wrack’s distribution is set at ~9 m. Light and its absorption by phytoplankton represent by far the most important factors controlling the modeled net growth rate and depth penetration, with the role of epibiosis requiring further investigation. Lacking findings on population dynamics and biotic interactions restrict the generated model to an exploratory rather than a predictive tool.
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|a © Inter-Research 2012
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|a Depth limit
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|a Benthic ecology
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|a Eutrophication
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|a Ecological modeling
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| 650 |
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|a Bladder wrack
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|a Biotic interactions
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|a Fucus physiology
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| 650 |
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|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Statistical models
|x Parametric models
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| 650 |
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|a Physical sciences
|x Earth sciences
|x Geography
|x Geomorphology
|x Bodies of water
|x Seas
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| 650 |
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|a Applied sciences
|x Research methods
|x Modeling
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| 650 |
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4 |
|a Biological sciences
|x Biology
|x Botany
|x Plants
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| 650 |
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4 |
|a Biological sciences
|x Ecology
|x Ecological modeling
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| 650 |
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4 |
|a Biological sciences
|x Biology
|x Physiology
|x System physiology
|x Respiratory physiology
|x Respiratory processes
|x Respiration
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| 650 |
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4 |
|a Biological sciences
|x Biology
|x Botany
|x Plant physiology
|x Plant growth
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| 650 |
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4 |
|a Mathematics
|x Mathematical values
|x Mathematical variables
|x Mathematical independent variables
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| 650 |
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|a Biological sciences
|x Biology
|x Botany
|x Marine botany
|x Phycology
|x Algae
|x Macroalgae
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| 650 |
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|a Physical sciences
|x Metrology
|x Radiometry
|x Irradiance
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|a research-article
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1 |
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|a Oschlies, Andreas
|e verfasserin
|4 aut
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1 |
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|a Wahl, Martin
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Marine Ecology Progress Series
|d Inter-Research, 1979
|g 463(2012) vom: Aug., Seite 59-72
|w (DE-627)320617998
|w (DE-600)2022265-8
|x 16161599
|7 nnns
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| 773 |
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|g volume:463
|g year:2012
|g month:08
|g pages:59-72
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|u https://www.jstor.org/stable/24876037
|3 Volltext
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|d 463
|j 2012
|c 08
|h 59-72
|