A multi-level analysis of team climate and interpersonal exchange relationships at work

This paper seeks to advance research on interpersonal exchange relationships between supervisors, subordinates, and coworkers at work by integrating social exchange, workplace friendship, and climate research to develop a multi-level model. We tested the model using hierarchical linear modeling (HLM) with data obtained from a sample of 215 manager–employee dyads working in 36 teams. At the individual level, leader–member exchange (LMX) was found to be related to workplace friendship. Further, workplace friendship was positively related to team–member exchange (TMX) and mediated the LMX–TMX relationship. At the team level, HLM results indicated that the relationship between LMX and workplace friendship was moderated by affective climate. These findings suggest that high-quality LMX relationships are associated with enhanced workplace friendship between employees, especially when the affective climate is strong

The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): Illuminating the Functional Diversity of Eukaryotic Life in the Oceans through Transcriptome Sequencing

Microbial ecology is plagued by problems of an abstract nature. Cell sizes are so small and population sizes so large that both are virtually incomprehensible. Niches are so far from our everyday experience as to make their very definition elusive. Organisms that may be abundant and critical to our survival are little understood, seldom described and/or cultured, and sometimes yet to be even seen. One way to confront these problems is to use data of an even more abstract nature: molecular sequence data. Massive environmental nucleic acid sequencing, such as metagenomics or metatranscriptomics, promises functional analysis of microbial communities as a whole, without prior knowledge of which organisms are in the environment or exactly how they are interacting. But sequence-based ecological studies nearly always use a comparative approach, and that requires relevant reference sequences, which are an extremely limited resource when it comes to microbial eukaryotes

An operational overview of the EXport processes in the ocean from RemoTe sensing (EXPORTS) northeast pacific field deployment

The goal of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) field campaign is to develop a predictive understanding of the export, fate, and carbon cycle impacts of global ocean net primary production. To accomplish this goal, observations of export flux pathways, plankton community composition, food web processes, and optical, physical, and biogeochemical (BGC) properties are needed over a range of ecosystem states. Here we introduce the first EXPORTS field deployment to Ocean Station Papa in the Northeast Pacific Ocean during summer of 2018, providing context for other papers in this special collection. The experiment was conducted with two ships: a Process Ship, focused on ecological rates, BGC fluxes, temporal changes in food web, and BGC and optical properties, that followed an instrumented Lagrangian float; and a Survey Ship that sampled BGC and optical properties in spatial patterns around the Process Ship. An array of autonomous underwater assets provided measurements over a range of spatial and temporal scales, and partnering programs and remote sensing observations provided additional observational context. The oceanographic setting was typical of late-summer conditions at Ocean Station Papa: a shallow mixed layer, strong vertical and weak horizontal gradients in hydrographic properties, sluggish sub-inertial currents, elevated macronutrient concentrations and low phytoplankton abundances. Although nutrient concentrations were consistent with previous observations, mixed layer chlorophyll was lower than typically observed, resulting in a deeper euphotic zone. Analyses of surface layer temperature and salinity found three distinct surface water types, allowing for diagnosis of whether observed changes were spatial or temporal. The 2018 EXPORTS field deployment is among the most comprehensive biological pump studies ever conducted. A second deployment to the North Atlantic Ocean occurred in spring 2021, which will be followed by focused work on data synthesis and modeling using the entire EXPORTS data set

Flow cytometric identification and enumeration of photosynthetic sulfur bacteria and potential for ecophysiological studies at the single-cell level

17 páginas, 9 figuras, 2 tablas.We show the potential of flow cytometry as a fast tool for population identification and enumeration of photosynthetic sulfur bacteria. Purple (PSB) and green sulfur bacteria (GSB) oxidize hydrogen sulfide to elemental sulfur that can act as storage compound to be further oxidized to sulfate generating the reducing power required for growth. Both groups have different elemental sulfur allocation strategies: whereas PSB store elemental sulfur as intracellular inclusions, GSB allocate sulfur globules externally. We used well-characterized laboratory strains and complex natural photosynthetic populations developing in a sharply stratified meromictic lake to show that PSB and GSB could be detected, differentiated and enumerated in unstained samples using a blue laser-based flow cytometer. Variations in cell-specific pigment content and the dynamics of sulfur accumulation, both intra- and extracellularly, were also detected in flow cytometric plots as sulfur accumulation changed the light scatter characteristics of the cells. These data were used to show the potential for studies on the metabolic status and the rate of activity at the single-cell level. Flow cytometric identification and enumeration resulted in faster and more precise analyses than previous approaches, and may open the door to more complex ecophysiological experiments with photosynthetic sulfur bacteria in mixed cultures and natural environments.This work was financed by the coordinated project VIARC Grant No. REN2003-08333 to E.O.C. and C.M.B. and MicroDiff and Modivus Grants REN2001-2120/MAR and CTM2005-04795/MAR to J.M.G. from the Spanish Ministerio de Educación y Ciencia (MEC). We thank J. Mas for support and lab facilities at the Department of Genetics and Microbiology, Autonomous University of Barcelona. E.O.C. benefits from the Program Ramon y Cajal of the Spanish MEC and FEDER.Peer reviewe

A compilation of global bio-optical in situ data for ocean-colour satellite applications - Version two

© Authors. A global compilation of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (including, inter alia, MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT and GePCO) and span the period from 1997 to 2018. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties, spectral diffuse attenuation coefficients and total suspended matter. The data were from multi-project archives acquired via open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenization, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) was propagated throughout the work and made available in the final table. By making the metadata available, provenance is better documented, and it is also possible to analyse each set of data separately. This paper also describes the changes that were made to the compilation in relation to the previous version (Valente et al., 2016). The compiled data are available at https://doi.org/10.1594/PANGAEA.898188 (Valente et al., 2019)