This data is in support of the publication in review "Using sensor data to dynamically map large-scale models to site-scale forecasts: A case study using the National Water Model". It is all the raw data extracted from the NWM flow forecasts for Iowa and the IFIS stage readings.
For the NWM data, each date has it's own tab-delimited file with columns being the time (hrs) and rows being the NHD site.
For the IFIS gages, each tab delimited file is for a single site for the period of record.
Included here are 1) a detailed description of each of the dataset's components, 2) a database of all finds from the 2015 survey, 3) a database of faunal bone compiled by specialist Damià Ramis, 4) a description of the finds by category to accompany these databases, 5) a PDF of notes taken in the field, 6) field photographs of survey units, 7) object photographs of all finds, and 8) drawings of diagnostic ceramics by time period.
Each pdf is an electronic version of the paper output for each experiment.
Each text file is the electronic version of the data on the computer cards for each experiment. These text files are directly readable by Excel. Once in Excel, the data can be manipulated as desired.
Additional information is in the theses.
Case 2 of Li et al. (2016) LES simulations for the DISCOVER-AQ 11 campaign, including three different grid resolutions (96, 197 and 320 grid cell resolutions), plus simulations at the 192 grid resolution with and without aqueous chemistry
This dataset was compiled as an attempt to understand how natural resource managers and research ecologists in the Great Lakes region integrate the ecosystem services (ES) paradigm into their work. The following text is the adapted abstract from a thesis associated with this data.
Ecosystem services, or the benefits people obtain from ecosystems, have gained much momentum in natural resource management in recent decades as a relatively comprehensive approach to provide quantitative tools for improving decision-making and policy design. However, to date we know little about whether and how natural resource practitioners, from natural resource managers to research ecologists (hereafter managers and ecologists respectively), have adopted the ES paradigm into their respective work. Here, we addressed this knowledge gap by asking managers and ecologists about whether and how they have adopted the ES paradigm into their respective work.
First, we surveyed federal, state, provincial and tribal managers in the Great Lakes region about their perception and use of ES as well as the relevance of specific services to their work. Although results indicate that fewer than 31% of the managers said they currently consider economic values of ES, 79% of managers said they would use economic information on ES if they had access to it. Additionally, managers reported that ES-related information was generally inadequate for their resource management needs. We also assessed managers by dividing them into identifiable groups (e.g. managers working in different types of government agencies or administrative levels) to evaluate differential ES integration. Overall, results suggest a desire among managers to transition from considering ES concepts in their management practices to quantifying economic metrics, indicating a need for practical and accessible valuation techniques.
Due to a sample of opportunity at the USGS Great Lakes Science Center (GLSC), we also evaluated GLSC research ecologists’ integration of the ES paradigm because they play an important role by contributing requisite ecological knowledge for ES models. Managers and ecologists almost unanimously agreed that it was appropriate to consider ES in resource management and also showed convergence on the high priority ES. However, ecologists appeared to overestimate the adequacy of ES-related information they provide as managers reported the information was inadequate for their needs. This divergence may reflect an underrepresentation of ecological economists in this system who can aid in translating ecological models into estimates of human well-being.
As a note, the dataset for the research ecologists has had some data removed as it could be considered personally identifiable information due to the small sample size in that population. The surveys associated with both datasets have also been included in PDF format.
Curation Notes: Three files were added to the data set on Dec 21, 2017. Two csv files: "Ecosystem services and Research Ecologists - Data Index.csv" and "Ecosystem services and Research Managers - Data Index.csv" and one text file: "Ecosystem Services Adoption Readme.txt". The file names of the original four files were altered to replace an ampersand with the word "and".
Tab delimited file containing the records of all papers published in JGR-Space Physics in 2012. The records were pulled from Thomsen-Reuters ISI-Web-of-Science on June 3, 2016 including citations. Gender was identified independently by the creator of the file.
Data are contained in an Excel spreadsheet formatted such that each row is a separate participant and each column is a separate question. This file is called: EbyEtAl-TransportCaregiver. A data dictionary that gives the text for each question and the response categories mappings is contained in another Excel Spreadsheet. This file is called: EbyEtAl-TransportCaregiverDictionary. The text of the survey, the development of weights, and response rate calculations can be found in the Deep Blue report discussed previously.