Scale-Specific Patterns of the Production of the Charophyte Chara aspera in the Brackish Baltic Sea: Linking Individual and Community Production and Biomass Growth

An understanding of the nature of scale-dependence in macroalgal production and to quantify how primary production is incorporated into autotrophic biomass requires an assessment of primary production at multiple scales. In this study we experimentally estimated seasonal variability in individual ph...

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Bibliographic Details
Published in:Frontiers in Marine Science
Main Authors: Jonne Kotta, Kaire Torn, Tiina Paalme, Merli Rätsep, Kaire Kaljurand, Martin Teeveer, Ilmar Kotta
Format: Article in Journal/Newspaper
Language:English
Published: Frontiers Media S.A. 2021
Subjects:
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Online Access:https://doi.org/10.3389/fmars.2021.674014
https://doaj.org/article/80d89347d734409ebb30e800cb4b698f
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Summary:An understanding of the nature of scale-dependence in macroalgal production and to quantify how primary production is incorporated into autotrophic biomass requires an assessment of primary production at multiple scales. In this study we experimentally estimated seasonal variability in individual photosynthesis, community production and growth in biomass of the charophyte Chara aspera in the Baltic Sea together with the key environmental variables known to regulate the production of macroalgae. The experiments suggested that the production and growth of C. aspera was defined largely by light and temperature at all studied scales. However, the algal production at the same light levels was systematically lower at the community than an individual level, suggesting the importance of shelf-shading and below-ground processes in natural plant assemblages. Moreover, the observation scale also defined response types between the environment, plant production and growth. This implies that the patterns of variability of the production and growth of macrophytes should always be interpreted in the context of scale and any multiscale model development should involve experimental validation at all important scales.