Bacterial and plankton communities in mariculture water sources: a case study in Nampu and Sembukan seawaters, Wonogiri, Indonesia

Seawaters in Indonesia, part of the tropical marine ecosystem, have great microbial and plankton diversity. Seawater is used as a water source for marine aquacultures, such as shrimp, milkfish, lobster, and mud crab. Sustainability of environmental resources for supporting aquaculture activities can be assessed by analyzing the actual conditions of the water source environment, including bacterial and plankton communities. However, the characteristics of bacteria and plankton communities in Indonesian seawaters have not been well documented. In this study, we investigated the bacterial and plankton communities in surface seawater from two coastal areas, i.e. Nampu and Sembukan, Wonogiri regency, Central Java, Indonesia. Bacterial diversity was analyzed using the Illumina-based high throughput sequencing with a primer set targeting the V3-V4 region of the bacterial 16S rRNA gene. Meanwhile, the plankton community (phytoplankton and zooplankton) was calculated and identified using a counting chamber method. Sequencing analysis revealed that the five dominant bacterial phyla in the two seawater samples were similar, consisting of Proteobacteria, Firmicutes, Actinobacteria, Bacteriodetes, and Cyanobacteria. Although the two sites are separated by several kilometres, the distribution of dominant bacterial phyla in both seawater samples is similar. Phytoplankton in Nampu and Sembukan were similarly dominated by Trichodesmium sp., Navicula sp., and Rhabdonema sp. Dominant zooplankton in the two sites were Euterpina, Nauplius, Oithona sp., Oncaea sp., Tigriopus sp., and Gastropoda larvae. The seawater in Nampu and Sembukan is suitable as a water source for aquaculture.

A biodiversity survey on the planktonic protistan grazers of the Gulf of Naples (Italy)

Plankton communities include both unicellular and multicellular organisms. An important unicellular component is represented by those protists (i.e., unicellular eukaryotes) that are non-strictly autotrophic organisms and consume bacteria and other protists. These organisms are an important link between primary producers and metazoans and are usually known as microzooplankton, protozooplankton, or mixoplankton, as many of them couple phagotrophic and photoautotrophic behaviours. Herein we report on the diversity of these organisms sampled at two sampling sites (coastal and offshore stations), at two depths (0 and 10 m), in the Gulf of Naples during the early autumn of 2020. Despite efforts to list plankton biodiversity of primary producers and metazoan grazers made in this area so far, protistan grazers are still poorly investigated and previous information date back to decades ago. Our survey identified dinoflagellates and oligotrich ciliates as the most abundant groups, while tintinnids were less quantitatively relevant. The taxonomic composition in samples investigated herein remarked that reported by previous studies, with the sole exception of the tintinnid Ascampbeliella armilla, which was never reported before. A coastal-offshore gradient in the taxonomical composition of protistan grazers was also observed, with some species more abundant within coastal waters and other better thriving in offshore ones. Surface and sub-surface communities also differed in terms of species composition, with the deeper communities in the two sites being more similar reciprocally than with communities at the surface. These differences were associated with distinct environmental conditions, such as light availability, as well with the standing feeding environment, arising potential implications in the functioning of the planktonic food web at the local scale.

Response of Marine Plankton Communities in Ponds to the Presence of Vertical Structures

The effects of bottom vertical structures like AquaMats® in enhancing plankton productivity was evaluated. One experimental earthen pond of 500 m2 was provided with AquaMats® increasing the surface substrate area 12 times and water quality, phytoplankton and zooplankton populations developed during almost 100 days was compared with a pond without AquaMats®. Their presence favored the development of Dinoflagellates (Miozoa, Dinophyceae), mostly Gymnodiniales, which may be of some concern since some species of this group have been associated with toxic algal blooms while in the ponds without AquaMats® Diatoms (Bacillariophyta) predominate. In both ponds plankton production was very much sculptured by external nutrients added to the systems. The balance between different nutrients is extremely important to regulate the phytoplankton populations with Diatoms blooming at silicate concentrations higher than 2 μM and below this level and at low nitrate and high ammonium being more appropriate for Dinoflagellates. The linkage between phytoplankton and zooplankton population in ponds is strong with zooplankton exerting control over the phytoplankton population and vice-versa. The use of vertical substrates enhances plankton productivity by increasing the substrate area for periphyton fixation. The main zooplankton taxonomic groups associated with the presence of AquaMats® were Calanoid and Harpacticoid copepodites and nauplii, veligers of gastropods and trochophore of polychaets, larval stages of organisms that except for calanoid copepods are benthic and correspond to the meroplanktonic phase in the life cycle of those organisms.

Deep Learning Classification of Lake Zooplankton

Plankton are effective indicators of environmental change and ecosystem health in freshwater habitats, but collection of plankton data using manual microscopic methods is extremely labor-intensive and expensive. Automated plankton imaging offers a promising way forward to monitor plankton communities with high frequency and accuracy in real-time. Yet, manual annotation of millions of images proposes a serious challenge to taxonomists. Deep learning classifiers have been successfully applied in various fields and provided encouraging results when used to categorize marine plankton images. Here, we present a set of deep learning models developed for the identification of lake plankton, and study several strategies to obtain optimal performances, which lead to operational prescriptions for users. To this aim, we annotated into 35 classes over 17900 images of zooplankton and large phytoplankton colonies, detected in Lake Greifensee (Switzerland) with the Dual Scripps Plankton Camera. Our best models were based on transfer learning and ensembling, which classified plankton images with 98% accuracy and 93% F1 score. When tested on freely available plankton datasets produced by other automated imaging tools (ZooScan, Imaging FlowCytobot, and ISIIS), our models performed better than previously used models. Our annotated data, code and classification models are freely available online.

Food or physics: plankton communities structured across Gulf of Alaska eddies

Oceanic features, such as mesoscale eddies that entrap and transport water masses, create heterogeneous seascapes to which biological communities may respond. To date, however, our understanding of how internal eddy dynamics influence plankton community structuring is limited by sparse sampling of eddies and their associated biotic communities. In this paper, we used 10 years of archived Continuous Plankton Recorder (CPR) data (2002-2013) associated with 9 mesoscale eddies in the Northeast Pacific/Gulf of Alaska to test the hypothesis that eddy origin and rotational direction determines the structure and dynamics of entrained plankton communities. Using generalized additive models and accounting for confounding factors (e.g., timing of sampling), we found peak diatom abundance within both cyclonic and anticyclonic eddies near the eddy edge. Zooplankton abundances, however, varied with distance to the eddy center/edge by rotational type and eddy life stage, and differed by taxonomic group. For example, the greatest abundance of small copepods was found near the center of anticyclonic eddies during eddy maturation and decay, but near the edge of cyclonic eddies during eddy formation and intensification. Distributions of copepod abundances across eddy surfaces were not mediated by phytoplankton distribution. Our results therefore suggest that physical mechanisms such as internal eddy dynamics exert a direct impact on the structure of zooplankton communities rather than indirect mechanisms involving potential food resources.