Copepod grazing and their impact on phytoplankton standing stock and production in a tropical coastal water during the different seasons

Jagadeesan, L.; Jyothibabu, R.; Arunpandi, N.; Parthasarathi, S.

doi:10.1007/s10661-017-5804-y

Cited by 31 publications

(7 citation statements)

References 58 publications

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“…The grazing of copepods can potentially decrease the abundance of specific phytoplankton species, which will create opportunities for other species to thrive and ultimately result in increased phytoplankton diversity. This ecological phenomenon is commonly referred to as “grazing control” and has been observed in various marine ecosystems [ 61 , 62 ]. By contrast, phytoplankton alpha diversities in the S and FS treatments were significantly lower than in the C and F treatments, and their assemblage compositions were similar but significantly different from those of the C and F treatments ( Figure 3 a–c).…”

Section: Discussionmentioning

confidence: 99%

The Effects of Intraguild Predation on Phytoplankton Assemblage Composition and Diversity: A Mesocosm Experiment

Cheng

et al. 2023

Biology

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Intraguild predation (IGP) can have a significant impact on phytoplankton biomass, but its effects on their diversity and assemblage composition are not well understood. In this study, we constructed an IGP model based on the common three-trophic food chain of “fish (or shrimp)–large branchiopods (Daphnia)–phytoplankton”, and investigated the effects of IGP on phytoplankton assemblage composition and diversity in outdoor mesocosms using environmental DNA high-throughput sequencing. Our results indicated that the alpha diversities (number of amplicon sequence variants and Faith’s phylogenetic diversity) of phytoplankton and the relative abundance of Chlorophyceae increased with the addition of Pelteobagrus fulvidraco, while similar trends were found in alpha diversities but with a decrease in the relative abundance of Chlorophyceae in the Exopalaemon modestus treatment. When both predators were added to the community, the strength of collective cascading effects on phytoplankton alpha diversities and assemblage composition were weaker than the sum of the individual predator effects. Network analysis further showed that this IGP effect also decreased the strength of collective cascading effects in reducing the complexity and stability of the phytoplankton assemblages. These findings contribute to a better understanding of the mechanisms underlying the impacts of IGP on lake biodiversity, and provide further knowledge relevant to lake management and conservation.

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Section: Discussionmentioning

confidence: 99%

The Effects of Intraguild Predation on Phytoplankton Assemblage Composition and Diversity: A Mesocosm Experiment

Cheng

et al. 2023

Biology

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“…Given the size difference between most diatoms and dinoflagellates (diatoms dominate the 12 μm samples, dinoflagellates dominate the 0.4 μm samples), these groups face different pressures when it comes to grazing. Diatoms, for example, are the primary food source for copepods (Jagadeesan et al, 2017; Liu et al, 2016), while dinoflagellates face grazing pressure from smaller plankton like ciliates (Pierce & Turner, 1992).…”

Section: Discussionmentioning

confidence: 99%

“…The increased relative abundance in diatoms could also help explain why copepod relative abundance also appears connected to rubble percent and mean NPP in the CAP ordinations (Figure 4). Both diatoms and ciliates are important components of copepod diets (Calbet & Saiz, 2005; Jagadeesan et al, 2017), and the increased relative abundance of both of these groups, combined with a decrease in abundance of higher trophic level predators at sites with high rubble percent, could allow for copepods to be more successful there.…”

Section: Discussionmentioning

confidence: 99%

Rubble fields shape planktonic protist communities in Indonesia at a local scale

Borbee

Ayu

Carvalho

et al. 2022

J Eukaryotic Microbiology

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The Coral Triangle encompasses nearly 30% of the world's coral reefs and is widely considered the epicenter of marine biodiversity. Destructive fishing practices and natural disturbances common to this region damage reefs leaving behind fields of coral rubble. While the impacts of disturbances in these ecosystems are well documented on metazoans, we have a poor understanding of their impact on microbial communities at the base of the food web. We use metabarcoding to characterize protist community composition in sites of varying fisheries management schemes and benthic profiles across the island of Lombok, Indonesia. Our study shows that rubble coverage and net primary productivity are the strongest explainers of variation in protist communities across Lombok. More specifically, rubble fields are characterized by increases in small heterotrophic protists, including ciliates and cercozoans. In addition to shifts in heterotrophic protist communities, we also observed increases in diatom relative abundance in rubble fields, which corresponded to sites with higher net primary productivity. These results are the first to characterize protist communities in tropical marine rubble fields and provide insight on environmental factors potentially driving these shifts on a local scale.

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“…4a). However, this predation or intake relationship for cyclopoids ingesting nanophytoplankton has been proved by a recent research work (50), and it means that the causality from nanophytoplankton to cyclopoids is true by the CVP algorithm for the plankton food chain (Fig. 4b).…”

Section: Detecting Causal Network In Multiple Contextsmentioning

confidence: 92%

Causal network inference based on cross-validation predictability

Zhang

Chang

et al. 2022

Preprint

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Identifying causal relations or causal networks among molecules/genes, rather than just their correlations, is of great importance but challenging in biology and medical field, which is essential for unravelling molecular mechanisms of disease progression and developing effective therapies for disease treatment. However, there is still a lack of high-quality causal inference algorithms for any observed data in contrast to time series data. In this study, we developed a new causal concept for any observed data and its causal inference algorithm built on cross-validated predictability (CVP) can quantify the causal effects of interventions in the whole system. The causality was extensively validated by combining a large variety of statistical simulation experiments and available benchmark data (simulated data and various real data). Combining the predicted causal network and the real benchmark network, the CVP algorithm demonstrates high accuracy and strong robustness in comparison with the mainstream algorithms. In particular, the CVP algorithm is robust in identifying reliable driver genes and network biomarkers from the perspective of network biology, with the prediction results outperforming the mainstream conventional methods for predicting driver genes. CRISPR-Cas9 knockdown experiments in the liver cancer have validated that the functional driver genes identified by the CVP algorithm effectively inhibit the growth and colony formation of liver cancer cells. Combining knockdown and control experiments, we demonstrated the accuracy and biological significance of the causality predicted by CVP and identified the novel regulatory targets of functional driver genes SNRNP200 and RALGAPB in the liver cancer. These inferred causal networks explain regulatory patterns in different biological contexts in a clear sense and provide biological insights into molecular mechanisms of disease progression from a causality perspective.

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Copepod grazing and their impact on phytoplankton standing stock and production in a tropical coastal water during the different seasons

Cited by 31 publications

References 58 publications

The Effects of Intraguild Predation on Phytoplankton Assemblage Composition and Diversity: A Mesocosm Experiment

The Effects of Intraguild Predation on Phytoplankton Assemblage Composition and Diversity: A Mesocosm Experiment

Rubble fields shape planktonic protist communities in Indonesia at a local scale

Causal network inference based on cross-validation predictability

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