A nutrient limitation mosaic in the eastern tropical Indian Ocean

Twining, Benjamin S.; Rauschenberg, Sara; Baer, Steven E.; Lomas, Michael W.; Martiny, Adam C.; Antipova, Olga

doi:10.1016/j.dsr2.2019.05.001

Cited by 46 publications

(54 citation statements)

References 79 publications

(123 reference statements)

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“…Thus, severe Fe stress may be transient or seasonal in this region (Wiggert et al ; Behrenfeld et al ). Our sequence‐based findings are supported by nutrient addition incubation results from the same transect, which found evidence for Fe and N colimitation of planktonic communities but not classical iron limitation (Twining et al ). Overall, the distribution of ecotypes did not support the three‐biome hypothesis for the Eastern Indian Ocean.…”

Section: Resultssupporting

confidence: 81%

Subtle biogeochemical regimes in the Indian Ocean revealed by spatial and diel frequency of Prochlorococcus haplotypes

Larkin

Garcia

Ingoglia

et al. 2019

Limnology & Oceanography

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While the majority of studies use the environment to describe microbial populations, the high diversity of microbes can conversely be used as a resource to understand subtle environmental variability. Here, we used a high‐resolution spatial and temporal analysis of Prochlorococcus sp. in the Eastern Indian Ocean to determine whether ecotypes and microdiverse taxa can be used to identify fine‐scale biogeochemical regimes in this under‐studied region. A total of 246 DNA samples were collected every 4–6 h in April 2016 on GO‐SHIP cruise I09N, which transected gyre, equatorial, and monsoonal ecosystems between Western Australia and the Bay of Bengal. Using amplicon sequencing of the highly variable rpoC1 marker, we found that the region was largely dominated by the Prochlorococcus HL‐II clade. Conserved single nucleotide polymorphisms (SNPs) were used to identify four microdiverse haplotypes, or SNP‐delineated taxa, within the HL‐II clade of Prochlorococcus. The haplotypes showed regional patterns of relative gene count abundance that were significantly correlated with environmental conditions. Additionally, we used nonlinear least squares models to fit the sine wave function to our data and demonstrate that the haplotypes show distinct patterns in relative diel frequency, providing evidence that these microdiverse populations are ecologically and evolutionarily distinct. Overall, we show how the integration of a genomics data set into a biogeochemical framework can reveal a more nuanced understanding of a complex ocean basin.

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Section: Resultssupporting

confidence: 81%

Subtle biogeochemical regimes in the Indian Ocean revealed by spatial and diel frequency of Prochlorococcus haplotypes

Larkin

Garcia

Ingoglia

et al. 2019

Limnology & Oceanography

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“…In the surveyed areas, the surface N and the P levels were <1.0 and 0.10 µM (data not shown), with the N:P ratio being lower than 16, indicating a nitrogen limitation (Li et al, 2012a), especially in the southern Indian Ocean (Wilcoxon test, p < 0.05), where Chla biomass and picocells abundance were lower. Such a biomass variation could also be attributed by the spatial changes of trace mental iron (Chinni et al, 2019;Twining et al, 2019) that is often believed to regulate phytoplankton growth and has been observed to covary with Chla (Chinni et al, 2019;Sherman et al, 2020). On the other hand, the spatial variation in Chla was less in the DCM layer; it could be explained by the high nutrients that may be enough to support the growth of phytoplankton.…”

Section: Discussionmentioning

confidence: 98%

Acutely Rising Temperature Reduces Photosynthetic Capacity of Phytoplankton Assemblages in Tropical Oceans: A Large-Scale Investigation

et al. 2021

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Climate changes interacting with human activities are raising the temperature in global oceans. To explore physiological responses of in situ phytoplankton assemblages to increasing temperatures, we conducted a shipboard experiment in tropical regions of the eastern Indian Ocean, Java Sea, and southern South China Sea. Throughout the surveyed areas, phytoplankton biomass (Chla) ranged from 0.09 to 0.86 μg L−1 (median, 0.22 μg L−1) in the surface and from 0.30 to 0.99 μg L−1 (median, 0.50 μg L−1) in maximal chlorophyll layer (DCM), respectively. Picophytoplankton that occupied 27–89% (79%) and 83–92% (88%) of total Chla in the surface and DCM layers, ranged from 0.32 × 104 to 23.10 × 104 cells mL−1 (3.69 × 104 cells mL−1) and from 7.44 × 104 to 25.70 × 104 cells mL−1 (12.60 × 104 cells mL−1), respectively. Synechococcus took up 30–97% (78%) of pico-cells compositions in the surface layer, while, in the DCM layer, Prochlorococcus took up 42–98% (91%). Moreover, the maximal photochemical quantum yield (FV/FM) of photosystem II (PS II) and the rapid light curve (RLC)-derived light utilization efficiency (α) were lower in the surface layer than that in the DCM layer, but the saturation irradiance (EK) was higher. In particular, we found that acutely rising temperature decreased the FV/FM and α in both the surface and the DCM layers but increased the absorption cross-section (σPSII) of PSII photochemistry. Our results clearly indicate that the presently rising temperature adversely affects the photophysiology of natural phytoplankton assemblages in tropical oceans.

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“…The organic speciation of Cu may control its bioavailability to phytoplankton. Because of its important physiological role (e.g., for iron, oxygen, and nitrogen cycling; Granger & Ward, 2003;La Fontaine et al, 2002;Maldonado et al, 2006;Merchant & Helmann, 2012), Cu is required in phytoplankton cells in proportions varying on average between 0.4 and 2 mmol:mol relative to P and up to 3 mmolCu:molP (Twining & Baines, 2013;Twining et al, 2019). The most bioavailable form of copper for phytoplankton is Cu', but the very low concentrations in surface seawater may indicate that insufficient Cu' is available to meet phytoplankton requirements.…”

Section: Introductionmentioning

confidence: 99%

Insights Into the Major Processes Driving the Global Distribution of Copper in the Ocean From a Global Model

Richon

Tagliabue

2019

Global Biogeochemical Cycles

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Copper (Cu) is an unusual micronutrient as it can limit primary production but can also become toxic for growth and cellular functioning under high concentrations. Cu also displays an atypical linear profile, which will modulate its availability to marine microbes across the ocean. Multiple chemical forms of Cu coexist in seawater as dissolved species and understanding the main processes shaping the Cu biogeochemical cycling is hampered by key knowledge gaps. For instance, the drivers of its specific linear profile in seawater are unknown, and the bioavailable form of Cu for marine phytoplankton is debated. Here we developed a global 3‐D biogeochemical model of oceanic Cu within the NEMO/PISCES global model, which represents the global distribution of dissolved copper well. Using our model, we find that reversible scavenging of Cu by organic particles drives the dissolved Cu vertical profile and its distribution in the deep ocean. The low modeled inorganic copper (Cu') in the surface ocean means that Cu' cannot maintain phytoplankton cellular copper requirements within observed ranges. The global budget of oceanic Cu from our model suggests that its residence time may be shorter than previously estimated and provides a global perspective on Cu cycling and the main drivers of Cu biogeochemistry in different regions. Cu scavenging within particle microenvironments and uptake by denitrifying bacteria could be a significant component of Cu cycling in oxygen minimum zones.

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A nutrient limitation mosaic in the eastern tropical Indian Ocean

Cited by 46 publications

References 79 publications

Subtle biogeochemical regimes in the Indian Ocean revealed by spatial and diel frequency of Prochlorococcus haplotypes

Subtle biogeochemical regimes in the Indian Ocean revealed by spatial and diel frequency of Prochlorococcus haplotypes

Acutely Rising Temperature Reduces Photosynthetic Capacity of Phytoplankton Assemblages in Tropical Oceans: A Large-Scale Investigation

Insights Into the Major Processes Driving the Global Distribution of Copper in the Ocean From a Global Model

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