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Effects of temperature and particles on nitrification in a eutrophic coastal bay in southern China
Author(s) -
Zheng ZhenZhen,
Wan Xianhui,
Xu Min Nina,
Hsiao Silver SungYun,
Zhang Yao,
Zheng LiWei,
Wu Yanhua,
Zou Wenbin,
Kao ShuhJi
Publication year - 2017
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1002/2017jg003871
Subject(s) - nitrification , bay , eutrophication , biogeochemical cycle , particle (ecology) , environmental science , oceanography , seasonality , nitrogen , environmental chemistry , chemistry , ecology , biology , geology , nutrient , organic chemistry
Abstract Despite being the only link between reduced and oxidized nitrogen, the impact of environmental factors on nitrification, temperature and particles, in particular, remains unclear for coastal zones. By using the 15 NH 4 + ‐labeling technique, we determined nitrification rates in bulk (NTR B ) and free‐living (NTR F , after removing particles >3 μm) for water samples with varying particle concentrations (as sampled at different tidal stages) during autumn, winter, and summer in a eutrophic coastal bay in southern China. The highest NTR B occurred in autumn, when particle concentrations were highest. In general, particle‐associated nitrification rates (NTR P , >3 μm) were higher than NTR F and increased with particle abundance. Regardless of seasonally distinctive temperature and particle concentrations, nitrification exhibited consistent temperature dependence in all cases (including bulk, particle‐associated, and free‐living) with a Q 10 value of ~2.2. Meanwhile, the optimum temperature for NTR P was ~29°C, 5°C higher than that for NTR F although the causes for such a difference remained unclear. Strong temperature dependence and particle association suggest that nitrification is sensitive to temperature change (seasonality and global warming) and to ocean dynamics (wave and tide). Our results can potentially be applied to biogeochemical models of the nitrogen cycle for future predictions.