scholarly journals The planktonic protist interactome: where do we stand after a century of research?

2019 ◽  
Vol 14 (2) ◽  
pp. 544-559 ◽  
Author(s):  
Marit F. Markussen Bjorbækmo ◽  
Andreas Evenstad ◽  
Line Lieblein Røsæg ◽  
Anders K. Krabberød ◽  
Ramiro Logares
Keyword(s):  
Large Scale ◽  
Microbial Interactions ◽  
Global Ocean ◽  
Ecological Interactions ◽  
Evolutionary Trends ◽  
Bipartite Networks ◽  
Host Interactions ◽  
Interaction Database ◽  
Marine Realm ◽  
Earth Ecosystem

Abstract Microbial interactions are crucial for Earth ecosystem function, but our knowledge about them is limited and has so far mainly existed as scattered records. Here, we have surveyed the literature involving planktonic protist interactions and gathered the information in a manually curated Protist Interaction DAtabase (PIDA). In total, we have registered ~2500 ecological interactions from ~500 publications, spanning the last 150 years. All major protistan lineages were involved in interactions as hosts, symbionts (mutualists and commensalists), parasites, predators, and/or prey. Predation was the most common interaction (39% of all records), followed by symbiosis (29%), parasitism (18%), and ‘unresolved interactions’ (14%, where it is uncertain whether the interaction is beneficial or antagonistic). Using bipartite networks, we found that protist predators seem to be ‘multivorous’ while parasite–host and symbiont–host interactions appear to have moderate degrees of specialization. The SAR supergroup (i.e., Stramenopiles, Alveolata, and Rhizaria) heavily dominated PIDA, and comparisons against a global-ocean molecular survey (TARA Oceans) indicated that several SAR lineages, which are abundant and diverse in the marine realm, were underrepresented among the recorded interactions. Despite historical biases, our work not only unveils large-scale eco-evolutionary trends in the protist interactome, but it also constitutes an expandable resource to investigate protist interactions and to test hypotheses deriving from omics tools.

scholarly journals The planktonic protist interactome: where do we stand after a century of research?

2019 ◽  
Author(s):  
Marit F. Markussen Bjorbækmo ◽  
Andreas Evenstad ◽  
Line Lieblein Røsæg ◽  
Anders K. Krabberød ◽  
Ramiro Logares
Keyword(s):  
Large Scale ◽  
Microbial Interactions ◽  
Global Ocean ◽  
Ecological Interactions ◽  
Evolutionary Trends ◽  
Bipartite Networks ◽  
Host Interactions ◽  
Interaction Database ◽  
Marine Realm ◽  
Earth Ecosystem

AbstractMicrobial interactions are crucial for Earth ecosystem function, yet our knowledge about them is limited and has so far mainly existed as scattered records. Here, we have surveyed the literature involving planktonic protist interactions and gathered the information in a manually curated Protist Interaction DAtabase (PIDA). In total, we have registered ~2,500 ecological interactions from ~500 publications, spanning the last 150 years. All major protistan lineages were involved in interactions as hosts, symbionts, parasites, predators and/or prey. Symbiosis was the most common interaction (43% of all records), followed by predation (39%) and parasitism (18%). Using bipartite networks, we found that protistan predators seem to be “multivorous”, while parasite-host and symbiont-host interactions appear to have moderate degrees of specialization. The SAR supergroup (i.e. Stramenopiles, Alveolata and Rhizaria) heavily dominated PIDA, and comparisons against a global-ocean molecular survey (TARA Oceans) indicated that several SAR lineages, which are abundant and diverse in the marine realm, were underrepresented among the compiled interactions. All in all, despite historical biases, our work not only unveils large-scale eco-evolutionary trends in the protist interactome, but it also constitutes an expandable resource to investigate protist interactions and to test hypotheses deriving from omics tools.

DESIGN AND IMPLEMENTATION OF THE OCEANOGRAPHIC MODELING AND OBSERVATION NETWORK (REMO) FOR PHYSICAL OCEANOGRAPHY STUDIES AND OCEAN FORECASTING

2014 ◽  
Vol 31 (2) ◽  
Author(s):  
Jose Antonio Moreira Lima
Keyword(s):  
Atlantic Ocean ◽  
Large Scale ◽  
North Pacific Ocean ◽  
Integrated Approach ◽  
Sea Surface ◽  
Global Ocean ◽  
Height Anomaly ◽  
The North ◽  
Observation Network ◽  
Ocean Forecasting

This paper is concerned with the planning, implementation and some results of the Oceanographic Modeling and Observation Network, named REMO, for Brazilian regional waters. Ocean forecasting has been an important scientific issue over the last decade due to studies related to climate change as well as applications related to short-range oceanic forecasts. The South Atlantic Ocean has a deficit of oceanographic measurements when compared to other ocean basins such as the North Atlantic Ocean and the North Pacific Ocean. It is a challenge to design an ocean forecasting system for a region with poor observational coverage of in-situ data. Fortunately, most ocean forecasting systems heavily rely on the assimilation of surface fields such as sea surface height anomaly (SSHA) or sea surface temperature (SST), acquired by environmental satellites, that can accurately provide information that constrain major surface current systems and their mesoscale activity. An integrated approach is proposed here in which the large scale circulation in the Atlantic Ocean is modeled in a first step, and gradually nested into higher resolution regional models that are able to resolve important processes such as the Brazil Current and associated mesoscale variability, continental shelf waves, local and remote wind forcing, and others. This article presents the overall strategy to develop the models using a network of Brazilian institutions and their related expertise along with international collaboration. This work has some similarity with goals of the international project Global Ocean Data Assimilation Experiment OceanView (GODAE OceanView).

scholarly journals Air-Sea Interactions over Eddies in the Brazil-Malvinas Confluence

2021 ◽  
Vol 13 (7) ◽  
pp. 1335
Author(s):  
Ronald Souza ◽  
Luciano Pezzi ◽  
Sebastiaan Swart ◽  
Fabrício Oliveira ◽  
Marcelo Santini
Keyword(s):  
Latent Heat ◽  
Large Scale ◽  
Surface Wind ◽  
Heat Fluxes ◽  
Lower Atmosphere ◽  
Meteorological Variables ◽  
Global Ocean ◽  
Study Region ◽  
Cold Core

The Brazil–Malvinas Confluence (BMC) is one of the most dynamical regions of the global ocean. Its variability is dominated by the mesoscale, mainly expressed by the presence of meanders and eddies, which are understood to be local regulators of air-sea interaction processes. The objective of this work is to study the local modulation of air-sea interaction variables by the presence of either a warm (ED1) and a cold core (ED2) eddy, present in the BMC, during September to November 2013. The translation and lifespans of both eddies were determined using satellite-derived sea level anomaly (SLA) data. Time series of satellite-derived surface wind data, as well as these and other meteorological variables, retrieved from ERA5 reanalysis at the eddies’ successive positions in time, allowed us to investigate the temporal modulation of the lower atmosphere by the eddies’ presence along their translation and lifespan. The reanalysis data indicate a mean increase of 78% in sensible and 55% in latent heat fluxes along the warm eddy trajectory in comparison to the surrounding ocean of the study region. Over the cold core eddy, on the other hand, we noticed a mean reduction of 49% and 25% in sensible and latent heat fluxes, respectively, compared to the adjacent ocean. Additionally, a field campaign observed both eddies and the lower atmosphere from ship-borne observations before, during and after crossing both eddies in the study region during October 2013. The presence of the eddies was imprinted on several surface meteorological variables depending on the sea surface temperature (SST) in the eddy cores. In situ oceanographic and meteorological data, together with high frequency micrometeorological data, were also used here to demonstrate that the local, rather than the large scale forcing of the eddies on the atmosphere above, is, as expected, the principal driver of air-sea interaction when transient atmospheric systems are stable (not actively varying) in the study region. We also make use of the in situ data to show the differences (biases) between bulk heat flux estimates (used on atmospheric reanalysis products) and eddy covariance measurements (taken as “sea truth”) of both sensible and latent heat fluxes. The findings demonstrate the importance of short-term changes (minutes to hours) in both the atmosphere and the ocean in contributing to these biases. We conclude by emphasizing the importance of the mesoscale oceanographic structures in the BMC on impacting local air-sea heat fluxes and the marine atmospheric boundary layer stability, especially under large scale, high-pressure atmospheric conditions.

scholarly journals Disentangling environmental effects in microbial association networks

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Ina Maria Deutschmann ◽  
Gipsi Lima-Mendez ◽  
Anders K. Krabberød ◽  
Jeroen Raes ◽  
Sergio M. Vallina ◽  
...  
Keyword(s):  
Data Processing ◽  
Simulated Data ◽  
Potential Interaction ◽  
Microbial Interactions ◽  
Ecological Interactions ◽  
Sign Pattern ◽  
Interaction Information ◽  
Microbial Association ◽  
Environmental Selection ◽  
Data Processing Inequality

Abstract Background Ecological interactions among microorganisms are fundamental for ecosystem function, yet they are mostly unknown or poorly understood. High-throughput-omics can indicate microbial interactions through associations across time and space, which can be represented as association networks. Associations could result from either ecological interactions between microorganisms, or from environmental selection, where the association is environmentally driven. Therefore, before downstream analysis and interpretation, we need to distinguish the nature of the association, particularly if it is due to environmental selection or not. Results We present EnDED (environmentally driven edge detection), an implementation of four approaches as well as their combination to predict which links between microorganisms in an association network are environmentally driven. The four approaches are sign pattern, overlap, interaction information, and data processing inequality. We tested EnDED on networks from simulated data of 50 microorganisms. The networks contained on average 50 nodes and 1087 edges, of which 60 were true interactions but 1026 false associations (i.e., environmentally driven or due to chance). Applying each method individually, we detected a moderate to high number of environmentally driven edges—87% sign pattern and overlap, 67% interaction information, and 44% data processing inequality. Combining these methods in an intersection approach resulted in retaining more interactions, both true and false (32% of environmentally driven associations). After validation with the simulated datasets, we applied EnDED on a marine microbial network inferred from 10 years of monthly observations of microbial-plankton abundance. The intersection combination predicted that 8.3% of the associations were environmentally driven, while individual methods predicted 24.8% (data processing inequality), 25.7% (interaction information), and up to 84.6% (sign pattern as well as overlap). The fraction of environmentally driven edges among negative microbial associations in the real network increased rapidly with the number of environmental factors. Conclusions To reach accurate hypotheses about ecological interactions, it is important to determine, quantify, and remove environmentally driven associations in marine microbial association networks. For that, EnDED offers up to four individual methods as well as their combination. However, especially for the intersection combination, we suggest using EnDED with other strategies to reduce the number of false associations and consequently the number of potential interaction hypotheses.

scholarly journals Watermasses as a unifying framework for understanding the Southern Ocean carbon cycle

2010 ◽  
Vol 7 (3) ◽  
pp. 3393-3451 ◽  
Author(s):  
D. Iudicone ◽  
I. Stendardo ◽  
O. Aumont ◽  
K. B. Rodgers ◽  
G. Madec ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Large Scale ◽  
Thermohaline Circulation ◽  
Model Simulation ◽  
Polar Front ◽  
Global Ocean ◽  
Inversion Method ◽  
Co2 Fluxes ◽  
Meridional Transport ◽  
Regional Patterns

Abstract. A watermass-based framework is presented for a quantitative understanding of the processes controlling the cycling of carbon in the Southern Ocean. The approach is developed using a model simulation of the global carbon transports within the ocean and with the atmosphere. It is shown how the watermass framework sheds light on the interplay between biology, air-sea gas exchange, and internal ocean transport including diapycnal processes, and the way in which this interplay controls the large-scale ocean-atmosphere carbon exchange. The simulated pre-industrial regional patterns of DIC distribution and the global distribution of the pre-industrial air-sea CO2 fluxes compare well with other model results and with results from an ocean inversion method. The main differences are found in the Southern Ocean where the model presents a stronger CO2 outgassing south of the polar front, a result of the upwelling of DIC-rich deep waters into the surface layer. North of the subantarctic front the typical temperature-driven solubility effect produces a net ingassing of CO2. The biological controls on surface CO2 fluxes through primary production is generally smaller than the temperature effect on solubility. Novel to this study is also a Lagrangian trajectory analysis of the meridional transport of DIC. The analysis allows to evaluate the contribution of separate branches of the global thermohaline circulation (identified by watermasses) to the vertical distribution of DIC throughout the Southern Ocean and towards the global ocean. The most important new result is that the overturning associated with Subantarctic Mode Waters sustains a northward net transport of DIC (15.7×107 mol/s across 30° S). This new finding, which has also relevant implications on the prediction of anthropogenic carbon redistribution, results from the specific mechanism of SAMW formation and its source waters whose consequences on tracer transports are analyzed for the first time in this study.

scholarly journals Abyssal Circulation Driven by Near-Boundary Mixing: Water Mass Transformations and Interior Stratification

2020 ◽  
Vol 50 (8) ◽  
pp. 2203-2226
Author(s):  
Henri F. Drake ◽  
Raffaele Ferrari ◽  
Jörn Callies
Keyword(s):  
Boundary Layer ◽  
Large Scale ◽  
Water Mass ◽  
Circulation Model ◽  
Global Ocean ◽  
Boundary Mixing ◽  
Downslope Flows ◽  
Abyssal Circulation ◽  
Midocean Ridge ◽  
Water Mass Transformations

AbstractThe emerging view of the abyssal circulation is that it is associated with bottom-enhanced mixing, which results in downwelling in the stratified ocean interior and upwelling in a bottom boundary layer along the insulating and sloping seafloor. In the limit of slowly varying vertical stratification and topography, however, boundary layer theory predicts that these upslope and downslope flows largely compensate, such that net water mass transformations along the slope are vanishingly small. Using a planetary geostrophic circulation model that resolves both the boundary layer dynamics and the large-scale overturning in an idealized basin with bottom-enhanced mixing along a midocean ridge, we show that vertical variations in stratification become sufficiently large at equilibrium to reduce the degree of compensation along the midocean ridge flanks. The resulting large net transformations are similar to estimates for the abyssal ocean and span the vertical extent of the ridge. These results suggest that boundary flows generated by mixing play a crucial role in setting the global ocean stratification and overturning circulation, requiring a revision of abyssal ocean theories.

scholarly journals Vertex priority based butterfly counting for large-scale bipartite networks

2019 ◽  
Vol 12 (10) ◽  
pp. 1139-1152 ◽  
Author(s):  
Kai Wang ◽  
Xuemin Lin ◽  
Lu Qin ◽  
Wenjie Zhang ◽  
Ying Zhang
Keyword(s):  
Large Scale ◽  
Bipartite Networks

scholarly journals Revealing biases in the sampling of ecological interaction networks

2018 ◽  
Author(s):  
Marcus A. M. de Aguiar ◽  
Erica A. Newman ◽  
Mathias M. Pires ◽  
Justin D. Yeakel ◽  
David H. Hembry ◽  
...  
Keyword(s):  
Network Topology ◽  
Large Scale ◽  
Sampling Design ◽  
Sampling Error ◽  
Interaction Networks ◽  
Ecological Interactions ◽  
Modular Networks ◽  
Underlying Network ◽  
Full Knowledge ◽  
Sampling Biases

AbstractThe structure of ecological interactions is commonly understood through analyses of interaction networks. However, these analyses may be sensitive to sampling biases in both the interactors (the nodes of the network) and interactions (the links between nodes), because the detectability of species and their interactions is highly heterogeneous. These issues may affect the accuracy of empirically constructed ecological networks. Yet statistical biases introduced by sampling error are difficult to quantify in the absence of full knowledge of the underlying ecological network’s structure. To explore properties of large-scale modular networks, we developed EcoNetGen, which constructs and samples networks with predetermined topologies. These networks may represent a wide variety of communities that vary in size and types of ecological interactions. We sampled these networks with different sampling designs that may be employed in field observations. The observed networks generated by each sampling process were then analyzed with respect to the number of components, size of components and other network metrics. We show that the sampling effort needed to estimate underlying network properties accurately depends both on the sampling design and on the underlying network topology. In particular, networks with random or scale-free modules require more complete sampling to reveal their structure, compared to networks whose modules are nested or bipartite. Overall, the modules with nested structure were the easiest to detect, regardless of sampling design. Sampling according to species degree (number of interactions) was consistently found to be the most accurate strategy to estimate network structure. Conversely, sampling according to module (representing different interaction types or taxa) results in a rather complete view of certain modules, but fails to provide a complete picture of the underlying network. We recommend that these findings be incorporated into field sampling design of projects aiming to characterize large species interactions networks to reduce sampling biases.Author SummaryEcological interactions are commonly modeled as interaction networks. Analyses of such networks may be sensitive to sampling biases and detection issues in both the interactors and interactions (nodes and links). Yet, statistical biases introduced by sampling error are difficult to quantify in the absence of full knowledge of the underlying network’s structure. For insight into ecological networks, we developed software EcoNetGen (available in R and Python). These allow the generation and sampling of several types of large-scale modular networks with predetermined topologies, representing a wide variety of communities and types of ecological interactions. Networks can be sampled according to designs employed in field observations. We demonstrate, through first uses of this software, that underlying network topology interacts strongly with empirical sampling design, and that constructing empirical networks by starting with highly connected species may be the give the best representation of the underlying network.

Causes for Large-Scale Hydrographic Changes at the Hawaii Ocean Time Series Station

2008 ◽  
Vol 38 (9) ◽  
pp. 1931-1948 ◽  
Author(s):  
D. Stammer ◽  
S. Park ◽  
A. Köhl ◽  
R. Lukas ◽  
F. Santiago-Mandujano
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Global Ocean ◽  
Modeling Framework ◽  
Decadal Time Scale ◽  
Quasi Biennial Oscillation ◽  
Salinity Field ◽  
Additional Information ◽  
Independent Observations ◽  
Station Aloha

Abstract Results from Estimating the Circulation and Climate of the Ocean (ECCO)–Scripps Institution of Oceanography (SIO) global ocean state estimate, available over the 11-yr period 1992 through 2002, are compared with independent observations available at the Hawaii Ocean time series station ALOHA. The comparison shows that at this position, the estimated temporal variability has some skill in simulating observed ocean variability and that the quality of future syntheses could benefit from additional information available from the Argo network and from the time series observations themselves. On a decadal time scale, the influence radius of the station ALOHA T–S time series covers large parts of the tropical and subtropical Pacific Ocean and reaches even into the Indian Ocean through the Indonesian Throughflow. Estimated changes in sea surface height (SSH) result largely from thermosteric changes; however, nonsteric (barotropic) variations on the order of 1–2 cm also contribute to SSH changes at station ALOHA. Moreover, changes of similar magnitude can be caused by changes in the salinity field because of a quasi-biennial oscillation in the horizontal flow structure and heaving of the mean salinity structure on seasonal and interannual time scales. The adjoint modeling framework confirms westward-propagating Rossby waves (due to wind forcing) and subduction of water-mass anomalies (due to surface buoyancy forcing) as the primary mechanisms leading to observed changes of T–S structures at station ALOHA. Specifically, the analysis identifies surface freshwater fluxes along the wintertime outcrop of intermediate waters as a primary cause for salinity changes at station ALOHA and wind stress forcing east of the station position as another forcing mechanism of salinity variations around the Hawaiian Archipelago.

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