10 research outputs found

    Case Study: An Approach to Assess the Impact of the Student Success Program that Target Students in Poverty at a New England School

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    Defining success is difficult due to the abstract nature of the term and the multiple, competing ideas of what success looks like. Therefore, assessing the impact of a program designed to increase student success in an independent, rural high school is murky. The purpose of this dissertation in practice is to understand what students determine as their own factors in their success. This positive deviance approach gives voices to students in the definition of success and allows the resulting suggestions to be implemented at the local level. This scholar-practitioner dissertation in practice uses a positive deviant lens to examine why some students from poverty perform well at a New England high school, with the goal of generalizing the successful findings to better serve future students living in poverty. Participant selection also used a positive deviant approach. Data analysis and interpretation was conducted from interviews, document review, and a teacher survey. The findings of this study indicate five traits of success in the participant: organization, perseverance, resiliency, empathy, and connections. Additionally, the findings indicate further research could be done in the areas of the role of special educators in the lives of students, the concept of Goals, Habits, Growth as a framework of success, and the relationship between helping others and personal success.Doctor of Education (Ed.D.)Doctor of Education in Educational LeadershipSchool of Educatio

    Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates - Collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

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    The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present collection presents the original data sets used to compile Global distributions of diazotrophs abundance, biomass and nitrogen fixation rate

    Global distributions of diazotrophs nitrogen fixation rates - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

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    The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs nitrogen fixation rates, computed from a collection of source data sets

    Global distributions of diazotrophs abundance and biomass - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

    No full text
    The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs abundance and biomass, computed from a collection of source data sets

    Global distributions of diazotrophs Gamma-A nifH genes abundance - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

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    The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs Gamma-A nifH genes abundance, computed from a collection of source data sets

    Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates - Gridded data product (NetCDF) - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

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    The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. This is a gridded data product about diazotrophic organisms . There are 6 variables. Each variable is gridded on a dimension of 360 (longitude) * 180 (latitude) * 33 (depth) * 12 (month). The first group of 3 variables are: (1) number of biomass observations, (2) biomass, and (3) special nifH-gene-based biomass. The second group of 3 variables is same as the first group except that it only grids non-zero data. We have constructed a database on diazotrophic organisms in the global pelagic upper ocean by compiling more than 11,000 direct field measurements including 3 sub-databases: (1) nitrogen fixation rates, (2) cyanobacterial diazotroph abundances from cell counts and (3) cyanobacterial diazotroph abundances from qPCR assays targeting nifH genes. Biomass conversion factors are estimated based on cell sizes to convert abundance data to diazotrophic biomass. Data are assigned to 3 groups including Trichodesmium, unicellular diazotrophic cyanobacteria (group A, B and C when applicable) and heterocystous cyanobacteria (Richelia and Calothrix). Total nitrogen fixation rates and diazotrophic biomass are calculated by summing the values from all the groups. Some of nitrogen fixation rates are whole seawater measurements and are used as total nitrogen fixation rates. Both volumetric and depth-integrated values were reported. Depth-integrated values are also calculated for those vertical profiles with values at 3 or more depths

    Nitrogen fixation and nitrogenase (nifH) expression in tropical waters of the eastern North Atlantic

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    Expression of nifH in 28 surface water samples collected during fall 2007 from six stations in the vicinity of the Cape Verde Islands (north-east Atlantic) was examined using reverse transcription-polymerase chain reaction (RT-PCR)-based clone libraries and quantitative RT-PCR (RT-qPCR) analysis of seven diazotrophic phylotypes. Biological nitrogen fixation (BNF) rates and nutrient concentrations were determined for these stations, which were selected based on a range in surface chlorophyll concentrations to target a gradient of primary productivity. BNF rates greater than 6‚ÄČnmolN‚ÄČl‚ąí1‚ÄČh‚ąí1 were measured at two of the near-shore stations where high concentrations of Fe and PO43‚ąí were also measured. Six hundred and five nifH transcripts were amplified by RT-PCR, of which 76% are described by six operational taxonomic units, including Trichodesmium and the uncultivated UCYN-A, and four non-cyanobacterial diazotrophs that clustered with uncultivated Proteobacteria. Although all five cyanobacterial phylotypes quantified in RT-qPCR assays were detected at different stations in this study, UCYN-A contributed most significantly to the pool of nifH transcripts in both coastal and oligotrophic waters. A comparison of results from RT-PCR clone libraries and RT-qPCR indicated that a ő≥-proteobacterial phylotype was preferentially amplified in clone libraries, which underscores the need to use caution interpreting clone-library-based nifH studies, especially when considering the importance of uncultivated proteobacterial diazotrophs

    Base de données mondiale des diazotrophes océaniques version 2 et estimation élevée de la fixation de N 2 dans l'océan mondial

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    International audienceAbstract. Marine diazotrophs convert dinitrogen (N2) gas into bioavailable nitrogen (N), supporting life in the global ocean. In 2012, the first version of the global oceanic diazotroph database (version¬†1) was published. Here, we present an updated version of the database (version¬†2), significantly increasing the number of in situ diazotrophic measurements from 13‚ÄČ565 to 55‚ÄČ286. Data points for N2 fixation rates, diazotrophic cell abundance, and nifH gene copy abundance have increased by 184‚ÄČ%, 86‚ÄČ%, and 809‚ÄČ%, respectively. Version¬†2 includes two new data sheets for the nifH gene copy abundance of non-cyanobacterial diazotrophs and cell-specific N2 fixation rates. The measurements of N2 fixation rates approximately follow a log-normal distribution in both version¬†1 and version¬†2. However, version¬†2 considerably extends both the left and right tails of the distribution. Consequently, when estimating global oceanic N2 fixation rates using the geometric means of different ocean basins, version¬†1 and version¬†2 yield similar rates (43‚Äď57 versus 45‚Äď63‚ÄČTg‚ÄČN‚ÄČyr‚ąí1; ranges based on one geometric standard error). In contrast, when using arithmetic means, version¬†2 suggests a significantly higher rate of 223¬Ī30‚ÄČTg‚ÄČN‚ÄČyr‚ąí1 (mean‚ÄȬĪ‚ÄČstandard error; same hereafter) compared to version¬†1 (74¬Ī7‚ÄČTg‚ÄČN‚ÄČyr‚ąí1). Specifically, substantial rate increases are estimated for the South Pacific Ocean (88¬Ī23 versus 20¬Ī2‚ÄČTg‚ÄČN‚ÄČyr‚ąí1), primarily driven by measurements in the southwestern subtropics, and for the North Atlantic Ocean (40¬Ī9 versus 10¬Ī2‚ÄČTg‚ÄČN‚ÄČyr‚ąí1). Moreover, version¬†2 estimates the N2 fixation rate in the Indian Ocean to be 35¬Ī14‚ÄČTg‚ÄČN‚ÄČyr‚ąí1, which could not be estimated using version¬†1 due to limited data availability. Furthermore, a comparison of N2 fixation rates obtained through different measurement methods at the same months, locations, and depths reveals that the conventional 15N2 bubble method yields lower rates in 69‚ÄČ% cases compared to the new 15N2 dissolution method. This updated version¬†of the database can facilitate future studies in marine ecology and biogeochemistry. The database is stored at the Figshare repository (https://doi.org/10.6084/m9.figshare.21677687; Shao et al., 2022).R√©sum√©. Les diazotrophes marins convertissent le diazote (N2) gazeux en azote (N) biodisponible, ce qui favorise la vie dans l'oc√©an mondial. En 2012, la premi√®re version de la base de donn√©es mondiale des diazotrophes oc√©aniques (version 1) a √©t√© publi√©e. Nous pr√©sentons ici une version actualis√©e de la base de donn√©es (version 2), augmentant de mani√®re significative le nombre de mesures diazotrophiques in situ de 13 565 √† 55 286. Les points de donn√©es pour les taux de fixation de N2, l'abondance des cellules diazotrophes et l'abondance des copies du g√®ne nifH ont augment√© de 184 %, 86 % et 809 %, respectivement. La version 2 comprend deux nouvelles fiches de donn√©es pour l'abondance des copies du g√®ne nifH des diazotrophes non cyanobact√©riens et les taux de fixation de N2 sp√©cifiques aux cellules. Les mesures des taux de fixation N2 suivent approximativement une distribution log-normale dans les versions 1 et 2. Cependant, la version 2 √©tend consid√©rablement les queues gauche et droite de la distribution. Par cons√©quent, lorsque l'on estime les taux de fixation de N2 dans l'oc√©an mondial en utilisant les moyennes g√©om√©triques des diff√©rents bassins oc√©aniques, la version 1 et la version 2 donnent des taux similaires (43-57 contre 45-63 Tg N an-1 ; fourchettes bas√©es sur une erreur g√©om√©trique type). En revanche, lorsque l'on utilise les moyennes arithm√©tiques, la version 2 sugg√®re un taux significativement plus √©lev√© de 223¬Ī30 Tg N an-1 (moyenne ¬Ī erreur standard ; idem ci-apr√®s) par rapport √† la version 1 (74¬Ī7 Tg N an-1). Plus pr√©cis√©ment, des augmentations substantielles du taux sont estim√©es pour l'oc√©an Pacifique Sud (88¬Ī23 contre 20¬Ī2 Tg N an-1), principalement gr√Ęce aux mesures effectu√©es dans les r√©gions subtropicales du sud-ouest, et pour l'oc√©an Atlantique Nord (40¬Ī9 contre 10¬Ī2 Tg N an-1). En outre, la version 2 estime le taux de fixation de N2 dans l'oc√©an Indien √† 35¬Ī14 Tg N an-1, ce qui n'a pas pu √™tre estim√© avec la version 1 en raison de la disponibilit√© limit√©e des donn√©es. En outre, une comparaison des taux de fixation de N2 obtenus par diff√©rentes m√©thodes de mesure aux m√™mes mois, lieux et profondeurs r√©v√®le que la m√©thode conventionnelle des bulles de 15N2 donne des taux inf√©rieurs dans 69 % des cas par rapport √† la nouvelle m√©thode de dissolution de 15N2. Cette version actualis√©e de la base de donn√©es peut faciliter les √©tudes futures en √©cologie marine et en biog√©ochimie. La base de donn√©es est stock√©e dans le d√©p√īt Figshare (https://doi.org/10.6084/m9.figshare.21677687 ; Shao et al., 2022)

    Global oceanic diazotroph database version 2 and elevated estimate of global oceanic N2 fixation

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    Marine diazotrophs convert dinitrogen (N2) gas into bioavailable nitrogen (N), supporting life in the global ocean. In 2012, the first version of the global oceanic diazotroph database (version 1) was published. Here, we present an updated version of the database (version 2), significantly increasing the number of in situ diazotrophic measurements from 13‚ÄČ565 to 55‚ÄČ286. Data points for N2 fixation rates, diazotrophic cell abundance, and nifH gene copy abundance have increased by 184‚ÄČ%, 86‚ÄČ%, and 809‚ÄČ%, respectively. Version 2 includes two new data sheets for the nifH gene copy abundance of non-cyanobacterial diazotrophs and cell-specific N2 fixation rates. The measurements of N2 fixation rates approximately follow a log-normal distribution in both version 1 and version 2. However, version 2 considerably extends both the left and right tails of the distribution. Consequently, when estimating global oceanic N2 fixation rates using the geometric means of different ocean basins, version 1 and version 2 yield similar rates (43‚Äď57 versus 45‚Äď63‚ÄČTg‚ÄČN‚ÄČyr‚ąí1; ranges based on one geometric standard error). In contrast, when using arithmetic means, version 2 suggests a significantly higher rate of 223¬Ī30‚ÄČTg‚ÄČN‚ÄČyr‚ąí1 (mean‚ÄȬĪ‚ÄČstandard error; same hereafter) compared to version 1 (74¬Ī7‚ÄČTg‚ÄČN‚ÄČyr‚ąí1). Specifically, substantial rate increases are estimated for the South Pacific Ocean (88¬Ī23 versus 20¬Ī2‚ÄČTg‚ÄČN‚ÄČyr‚ąí1), primarily driven by measurements in the southwestern subtropics, and for the North Atlantic Ocean (40¬Ī9 versus 10¬Ī2‚ÄČTg‚ÄČN‚ÄČyr‚ąí1). Moreover, version 2 estimates the N2 fixation rate in the Indian Ocean to be 35¬Ī14‚ÄČTg‚ÄČN‚ÄČyr‚ąí1, which could not be estimated using version 1 due to limited data availability. Furthermore, a comparison of N2 fixation rates obtained through different measurement methods at the same months, locations, and depths reveals that the conventional 15N2 bubble method yields lower rates in 69‚ÄČ% cases compared to the new 15N2 dissolution method. This updated version of the database can facilitate future studies in marine ecology and biogeochemistry. The database is stored at the Figshare repository (https://doi.org/10.6084/m9.figshare.21677687; Shao et al., 2022)
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