Influence of nitrogen to phosphorus supply ratios and physicochemical conditions on cyanobacteria and phytoplankton species composition in the Experimental Lakes Area, Canada

1999 ◽  
Vol 56 (3) ◽  
pp. 451-466 ◽  
Author(s):  
S N Levine ◽  
D W Schindler

To test the hypothesis that N:P supply ratios influence phytoplankton species composition, and particularly that cyanobacteria are favored by a low ratio, mesocosms at one pelagic and two littoral sites within the Experimental Lakes Area, Ontario, were fertilized for 10-12 weeks with similar amounts of P but different amounts of N. Total N:P supply (LN:LP) ratios (fertilizer plus natural inputs) ranged from 8:1 to 50:1. Nitrogen deficiency was detected in all mesocosms with LN:LP ratios <17:1, but N2-fixing Anabaena gained dominance only in the low-N:P pelagic mesocosms, and only in late summer. Cryptophytes and (or) chlorophytes dominated littoral mesocosms at all N:P ratios, while Pseudoanabaena catenata, a nonheterocystous cyanobacterium, was the late-summer dominant in pelagic mesocosms with LN:LP ratios >17:1. Canonical correlation analysis related cyanobacterial dominance to high P and low CO2 availability. Low light intensities and low N:P ratios also favored heterocystous (but not nonheterocystous) cyanobacteria. Total phytoplankton biomass and productivity increased with LN:LP ratio, while periphyton growth was maximal at low N:P ratios. Nitrogen limitation of phytoplankton may encourage blooms of N2 fixers or drive productivity down to the sediment surface where N is more available.


Ophelia ◽  
1995 ◽  
Vol 42 (1) ◽  
pp. 179-191 ◽  
Author(s):  
P. Kauppila ◽  
G. Hällfors ◽  
P. Kangas ◽  
P. Kokkonen ◽  
S. Basova


2021 ◽  
Vol 8 ◽  
Author(s):  
Yuanyuan Feng ◽  
Fei Chai ◽  
Mark L. Wells ◽  
Yan Liao ◽  
Pengfei Li ◽  
...  

In addition to ocean acidification, a significant recent warming trend in Chinese coastal waters has received much attention. However, studies of the combined effects of warming and acidification on natural coastal phytoplankton assemblages here are scarce. We conducted a continuous incubation experiment with a natural spring phytoplankton assemblage collected from the Bohai Sea near Tianjin. Experimental treatments used a full factorial combination of temperature (7 and 11°C) and pCO2 (400 and 800 ppm) treatments. Results suggest that changes in pCO2 and temperature had both individual and interactive effects on phytoplankton species composition and elemental stoichiometry. Warming mainly favored the accumulation of picoplankton and dinoflagellate biomass. Increased pCO2 significantly increased particulate organic carbon to particulate organic phosphorus (C:P) and particulate organic carbon to biogenic silica (C:BSi) ratios, and decreased total diatom abundance; in the meanwhile, higher pCO2 significantly increased the ratio of centric to pennate diatom abundance. Warming and increased pCO2 both greatly decreased the proportion of diatoms to dinoflagellates. The highest chlorophyll a biomass was observed in the high pCO2, high temperature phytoplankton assemblage, which also had the slowest sinking rate of all treatments. Overall, there were significant interactive effects of increased pCO2 and warming on dinoflagellate abundance, pennate diatom abundance, diatom vs. dinoflagellates ratio and the centric vs. pennate ratio. These findings suggest that future ocean acidification and warming trends may individually and cumulatively affect coastal biogeochemistry and carbon fluxes through shifts in phytoplankton species composition and sinking rates.



1971 ◽  
Vol 28 (2) ◽  
pp. 189-201 ◽  
Author(s):  
D. W. Schindler ◽  
S. K. Holmgren

A modified 14C method is described for measuring phytoplankton production in low-carbonate waters. The procedure includes the use of the Arthur and Rigler (Limnol. Oceanogr. 12: 121–124, 1967) technique for determining filtration error, liquid scintillation counting for determining the radioactivity of membrane filters and stock 14C solutions, and gas chromatography for measuring total CO2.Primary production, chlorophyll a, and total CO2 were measured for two dates in midsummer from each of several lakes in the Experimental Lakes Area (ELA), ranging from 1 to 1000 ha in area and from 2 to 117 m in maximum depth. Phytoplankton species abundance and biomass were determined for the same dates. Production ranged from 0.02 to 2.12 gC/m3∙day and from 0.179 to 1.103 g C/m2∙day. Chlorophyll ranged from 0.4 to 44 mg/m3 and from 5 to 98 mg/m2 in the euphotic zone. The corresponding ranges for live phytoplankton biomass were 120–5400 mg/m3 and 2100–13,400 mg/m2. Chrysophyceae dominated the phytoplankton of most of the lakes.A system for classifying the lakes in terms of phytoplankton species composition and production–depth curves is developed.



2019 ◽  
Vol 11 (17) ◽  
pp. 2001 ◽  
Author(s):  
Qing Zhu ◽  
Fang Shen ◽  
Pei Shang ◽  
Yanqun Pan ◽  
Mengyu Li

Phytoplankton species composition research is key to understanding phytoplankton ecological and biogeochemical functions. Hyperspectral optical sensor technology allows us to obtain detailed information about phytoplankton species composition. In the present study, a transfer learning method to inverse phytoplankton species composition using in situ hyperspectral remote sensing reflectance and hyperspectral satellite imagery was presented. By transferring the general knowledge learned from the first few layers of a deep neural network (DNN) trained by a general simulation dataset, and updating the last few layers with an in situ dataset, the requirement for large numbers of in situ samples for training the DNN to predict phytoplankton species composition in natural waters was lowered. This method was established from in situ datasets and validated with datasets collected in different ocean regions in China with considerable accuracy (R2 = 0.88, mean absolute percentage error (MAPE) = 26.08%). Application of the method to Hyperspectral Imager for the Coastal Ocean (HICO) imagery showed that spatial distributions of dominant phytoplankton species and associated compositions could be derived. These results indicated the feasibility of species composition inversion from hyperspectral remote sensing, highlighting the advantages of transfer learning algorithms, which can bring broader application prospects for phytoplankton species composition and phytoplankton functional type research.





1999 ◽  
Vol 25 (1) ◽  
pp. 61-77 ◽  
Author(s):  
Suzanne N. Levine ◽  
Mark A. Borchardt ◽  
Moshe Braner ◽  
Angela d. Shambaugh


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