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  • 1
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    Concerns about quadrupole ICP-MS lead isotopic data and interpretations in the environment and health fields (2018)
    MDPI AG
    Details
    Publication Date: 2022-05-25
    Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in International Journal of Environmental Research and Public Health 15 (2018): 723, doi:10.3390/ijerph15040723.
    Description: There has been a massive increase in recent years of the use of lead (Pb) isotopes in attempts to better understand sources and pathways of Pb in the environment and in man or experimental animals. Unfortunately, there have been many cases where the quality of the isotopic data, especially that obtained by quadrupole inductively coupled plasma mass spectrometry (Q-ICP-MS), are questionable, resulting in questionable identification of potential sources, which, in turn, impacts study interpretation and conclusions. We present several cases where the isotopic data have compromised interpretation because of the use of only the major isotopes 208Pb/206Pb and 207Pb/206Pb, or their graphing in other combinations. We also present some examples comparing high precision data from thermal ionization (TIMS) or multi-collector plasma mass spectrometry (MC-ICP-MS) to illustrate the deficiency in the Q-ICP-MS data. In addition, we present cases where Pb isotopic ratios measured on Q-ICP-MS are virtually impossible for terrestrial samples. We also evaluate the Pb isotopic data for rat studies, which had concluded that Pb isotopic fractionation occurs between different organs and suggest that this notion of biological fractionation of Pb as an explanation for isotopic differences is not valid. Overall, the brief review of these case studies shows that Q-ICP-MS as commonly practiced is not a suitable technique for precise and accurate Pb isotopic analysis in the environment and health fields
    Keywords: Lead isotopes ; ICP-MS ; TIMS ; MC-ICP-MS ; Environment ; Humans ; Rats ; Fractionation
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
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    Comparison of phenology estimated from reflectance-based indices and solar-induced chlorophyll fluorescence (SIF) observations in a temperate forest using GPP-based phenology as the standard (2018)
    MDPI AG
    Details
    Publication Date: 2022-05-25
    Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 10 (2018): 932, doi:10.3390/rs10060932.
    Description: We assessed the performance of reflectance-based vegetation indices and solar-induced chlorophyll fluorescence (SIF) datasets with various spatial and temporal resolutions in monitoring the Gross Primary Production (GPP)-based phenology in a temperate deciduous forest. The reflectance-based indices include the green chromatic coordinate (GCC), field measured and satellite remotely sensed Normalized Difference Vegetation Index (NDVI); and the SIF datasets include ground-based measurement and satellite-based products. We found that, if negative impacts due to coarse spatial and temporal resolutions are effectively reduced, all these data can serve as good indicators of phenological metrics for spring. However, the autumn phenological metrics derived from all reflectance-based datasets are later than the those derived from ground-based GPP estimates (flux sites). This is because the reflectance-based observations estimate phenology by tracking physiological properties including leaf area index (LAI) and leaf chlorophyll content (Chl), which does not reflect instantaneous changes in phenophase transitions, and thus the estimated fall phenological events may be later than GPP-based phenology. In contrast, we found that SIF has a good potential to track seasonal transition of photosynthetic activities in both spring and fall seasons. The advantage of SIF in estimating the GPP-based phenology lies in its inherent link to photosynthesis activities such that SIF can respond quickly to all factors regulating phenological events. Despite uncertainties in phenological metrics estimated from current spaceborne SIF observations due to their coarse spatial and temporal resolutions, dates in middle spring and autumn—the two most important metrics—can still be reasonably estimated from satellite SIF. Our study reveals that SIF provides a better way to monitor GPP-based phenological metrics.
    Description: This research was supported by U. S. Department of Energy Office of Biological and Environmental Research Grant DE-SC0006951, National Science Foundation Grants DBI 959333 and AGS-1005663, and the University of Chicago and the MBL Lillie Research Innovation Award to Jianwu Tang and China Scholarship Council No. 201506190095 to Z. Liu. Xiaoliang Lu was also supported by the open project grant (LBKF201701) of Key Laboratory of Land Surface Pattern and Simulation, Chinese Academy of Sciences.
    Keywords: Solar-induced chlorophyll fluorescence ; Reflectance ; Phenology ; Fall phenological events
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
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    Dynamic reusable workflows for ocean science (2017)
    MDPI AG
    Details
    Publication Date: 2022-05-26
    Description: © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Marine Science and Engineering 4 (2016): 68, doi:10.3390/jmse4040068.
    Description: Digital catalogs of ocean data have been available for decades, but advances in standardized services and software for catalog searches and data access now make it possible to create catalog-driven workflows that automate—end-to-end—data search, analysis, and visualization of data from multiple distributed sources. Further, these workflows may be shared, reused, and adapted with ease. Here we describe a workflow developed within the US Integrated Ocean Observing System (IOOS) which automates the skill assessment of water temperature forecasts from multiple ocean forecast models, allowing improved forecast products to be delivered for an open water swim event. A series of Jupyter Notebooks are used to capture and document the end-to-end workflow using a collection of Python tools that facilitate working with standardized catalog and data services. The workflow first searches a catalog of metadata using the Open Geospatial Consortium (OGC) Catalog Service for the Web (CSW), then accesses data service endpoints found in the metadata records using the OGC Sensor Observation Service (SOS) for in situ sensor data and OPeNDAP services for remotely-sensed and model data. Skill metrics are computed and time series comparisons of forecast model and observed data are displayed interactively, leveraging the capabilities of modern web browsers. The resulting workflow not only solves a challenging specific problem, but highlights the benefits of dynamic, reusable workflows in general. These workflows adapt as new data enter the data system, facilitate reproducible science, provide templates from which new scientific workflows can be developed, and encourage data providers to use standardized services. As applied to the ocean swim event, the workflow exposed problems with two of the ocean forecast products which led to improved regional forecasts once errors were corrected. While the example is specific, the approach is general, and we hope to see increased use of dynamic notebooks across geoscience domains.
    Keywords: Numerical modeling ; Reproducibility ; Catalog services ; Data services ; Web services ; Metadata ; Ocean forecasting ; Ocean modeling ; Data management ; Data system ; Interoperability ; OPeNDAP ; THREDDS ; CSW ; Jupyter Notebooks
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 4
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    Evaluating remotely sensed phenological metrics in a dynamic ecosystem model (2014)
    MDPI AG
    Details
    Publication Date: 2022-05-26
    Description: © The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 6 (2014): 4660-4686, doi:10.3390/rs6064660.
    Description: Vegetation phenology plays an important role in regulating processes of terrestrial ecosystems. Dynamic ecosystem models (DEMs) require representation of phenology to simulate the exchange of matter and energy between the land and atmosphere. Location-specific parameterization with phenological observations can potentially improve the performance of phenological models embedded in DEMs. As ground-based phenological observations are limited, phenology derived from remote sensing can be used as an alternative to parameterize phenological models. It is important to evaluate to what extent remotely sensed phenological metrics are capturing the phenology observed on the ground. We evaluated six methods based on two vegetation indices (VIs) (i.e., Normalized Difference Vegetation Index and Enhanced Vegetation Index) for retrieving the phenology of temperate forest in the Agro-IBIS model. First, we compared the remotely sensed phenological metrics with observations at Harvard Forest and found that most of the methods have large biases regardless of the VI used. Only two methods for the leaf onset and one method for the leaf offset showed a moderate performance. When remotely sensed phenological metrics were used to parameterize phenological models, the bias is maintained, and errors propagate to predictions of gross primary productivity and net ecosystem production. Our results show that Agro-IBIS has different sensitivities to leaf onset and offset in terms of carbon assimilation, suggesting it might be better to examine the respective impact of leaf onset and offset rather than the overall impact of the growing season length.
    Keywords: Phenology ; Remote sensing ; Dynamic ecosystem model ; Agro-IBIS ; MODIS
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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