2019
DOI: 10.3354/ame01906
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Phytoplankton strategies to exploit nutrients in coastal lagoons with different eutrophication status during re-oligotrophication

Abstract: We studied a mesotrophic and a hypertrophic Mediterranean coastal lagoon, both of which had been simultaneously subjected to a nutrient input reduction for 9 yr. We compared these 2 lagoons to an oligotrophic coastal lagoon. Using bioassays comprising 24 h incubations with added phosphorus and/or ammonium, we investigated the response of the phytoplankton communities to nutrient enrichment during summer in terms of biomass, size class structure, abundance and growth. For nitrogen and phosphorus, we identified … Show more

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Cited by 11 publications
(12 citation statements)
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“…Increasing evidence has shown that disturbance could select species exhibiting speci c biological traits and markedly alter the composition of SCP community (Li et al, 2020;Stegen et al, 2012). A high relative abundance of Thalassiosira, Pseudo-nitzschia and Skeletonema, were observed and widely spread in the heavy eutrophication Maowei Sea, whereas Thalassiosira, Minutocellus, Navicula, and Chaetoceros were signi cantly over-dominated in the Qinzhou Bay and Beibu Gulf open sea as eutrophic states decreased, which is consistent with previous studies (Leruste et al, 2019;Tian et al, 2017). Bacillariophyta exhibited high adaptability for oligotrophic conditions as to be dominant in nutrient-de cient areas (Zhou et al, 2017).…”
Section: Characteristics Of the Scp Communities With Increasing Eutrophicationsupporting
confidence: 89%
“…Increasing evidence has shown that disturbance could select species exhibiting speci c biological traits and markedly alter the composition of SCP community (Li et al, 2020;Stegen et al, 2012). A high relative abundance of Thalassiosira, Pseudo-nitzschia and Skeletonema, were observed and widely spread in the heavy eutrophication Maowei Sea, whereas Thalassiosira, Minutocellus, Navicula, and Chaetoceros were signi cantly over-dominated in the Qinzhou Bay and Beibu Gulf open sea as eutrophic states decreased, which is consistent with previous studies (Leruste et al, 2019;Tian et al, 2017). Bacillariophyta exhibited high adaptability for oligotrophic conditions as to be dominant in nutrient-de cient areas (Zhou et al, 2017).…”
Section: Characteristics Of the Scp Communities With Increasing Eutrophicationsupporting
confidence: 89%
“…Increasing evidence has shown that disturbance could select species exhibiting speci c biological traits and markedly alter the composition of picophytoplankton community [31,32]. A high relative abundance of Rhodophyta was observed and widely spread in the heavy eutrophication Maowei Sea, whereas Bacillariophyta was signi cantly over-dominated in the Qinzhou Bay and Beibu Gulf open sea as eutrophic states decreased, which is consistent with previous studies [33,34]. Bacillariophyta exhibited high adaptability for oligotrophic conditions as to be dominant in nutrient-de cient areas [35].…”
Section: Assembly Processes Of Picophytoplankton Communities Along Eusupporting
confidence: 88%
“…This led to the accumulation of nutrients (from runoff and reduced exchanges with seawater). Parallel to the desalinization, observed until 2010, an increase in nitrates concentration was reported, linked to agricultural activities, and still ongoing, despite management measures taken in the past few years for nitrogen reduction through improved sanitation (Pasqualini et al, 2017;Leruste et al, 2019). This inertial pollution was found to be also due to the accumulation of nitrate in the groundwater (Erostate et al, 2018;Erostate et al, 2019;Jaunat et al, 2019).…”
Section: Global Ecological Evolution Contextmentioning
confidence: 99%
“…Finally, monthly phytoplankton cellular abundances (cell L −1 ) and community composition data were collected to analyze relative composition at the class level and identify dominant phytoplankton species and bloom events, defined as cellular proliferation over 100,000 cell L −1 threshold (Cecchi et al, 2016;Belin and Neaud-Masson, 2017). Data were issued from literature (Cecchi et al, 2016;Garrido et al, 2016;Leruste et al, 2019) and field sampling in 2020. All analyzed data came from optical microscopy identification (inverted microscope CKX31, OLYMPUS) and quantification through the Utermöhl method, applied on samples fixed with formaldehyde solution at 2.5% final concentration (Utermöhl, 1958;AFNOR, 2006).…”
Section: Long-term Data Collectionmentioning
confidence: 99%