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  1. Understanding Ecosystem Services Adoption by Natural Resource Managers and Research Ecologists: Survey Data

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    Title: Understanding Ecosystem Services Adoption by Natural Resource Managers and Research Ecologists: Survey Data
    Creator: Schaeffer, Jeff, Engel, Daniel D, Low, Bobbi S, and Evans, Mary Anne
    Description: 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 ecologist 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, both CSV files in this dataset have two tabs: 1) the raw data, and 2) an index describing each column. 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.
  2. Marroquíes Bajos Bioarchaeological Project

    Work
    Title: Marroquíes Bajos Bioarchaeological Project
    Creator: Beck, Jess
    Description: These data include skeletal and dental inventories, assessments of skeletal and dental pathology, and the age and sex of individuals buried at Necropolis 1, Necropolis 2, and Necropolis 4 at the Copper Age site of Marroquíes Bajos. They are shared here in accordance with the NSF Data Management Plan associated with Doctoral Dissertation Improvement Grant BCS-1440017.
  3. Characteristics of Informal Caregivers who Provide Transportation Assistance to Older Adults

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    Title: Characteristics of Informal Caregivers who Provide Transportation Assistance to Older Adults
    Creator: Molnar, Lisa J and Eby, David W
    Description: Data can 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 are 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.
  4. Subjective Effect Reports of Food

    Work
    Title: Subjective Effect Reports of Food
    Creator: Schulte, Erica M
    Description: Abstract Objectives The current study investigates which foods may be most implicated in addictive-like eating by examining how nutritionally diverse foods relate to loss of control consumption and various subjective effect reports. Subjective effect reports assess the abuse liabilities of substances and may similarly provide insight into which foods may be reinforcing in a manner that triggers an addictive-like response for some individuals. Design Cross-sectional. Setting Online community. Participants 507 participants (n = 501 used in analyses) recruited through Amazon MTurk. Measurements Participants (n = 501) self-reported how likely they were to experience a loss of control over their consumption of 30 nutritionally diverse foods and rated each food on five subjective effect report questions that assess the abuse liability of substances (liking, pleasure, craving, averseness, intensity). Hierarchical cluster analytic techniques were used to examine how foods grouped together based on each question. Results Highly processed foods, with added fats and/or refined carbohydrates, clustered together and were associated with greater loss of control, liking, pleasure, and craving. The clusters yielded from the subjective effect reports assessing liking, pleasure, and craving were most similar to clusters formed based on loss of control over consumption, whereas the clusters yielded from averseness and intensity did not meaningfully differentiate food items. Conclusion The present work applies methodology used to assess the abuse liability of substances to understand whether foods may vary in their potential to be associated with addictive-like consumption. Highly processed foods (e.g., pizza, chocolate) appear to be most related to an indicator of addictive-like eating (loss of control) and several subjective effect reports (liking, pleasure, craving). Thus, these foods may be particularly reinforcing and capable of triggering an addictive-like response in some individuals. Future research is warranted to understand whether highly processed foods are related to these indicators of abuse liability at a similar magnitude as addictive substances.
  5. Neighborhood effects : Information and Education Environment

    Work
    Title: Neighborhood effects : Information and Education Environment
    Creator: Veinot, Tiffany C, Okullo, Dolorence, Clarke, Phillipa J., Reddy, Shruthi, Goodspeed, Robert, Gomez-Lopez, Iris N., and Data Driven Detroit
    Description: The information and education environment refers to: 1) the presence of information infrastructures such as broadband Internet access and public libraries in a location; 2) a person’s proximity to information infrastructures and sources; 3) the distribution of information infrastructures, sources and in a specific location; and 4) exposure to specific messages (information content) within a specific location. Coverage for all data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area.
  6. Neighborhood Effects: Food Environment

    Work
    Title: Neighborhood Effects: Food Environment
    Creator: Yan, Xiang (Jacob), Data Driven Detroit, Veinot, Tiffany C., Goodspeed, Robert, Gomez-Lopez, Iris N., and Okullo, Dolorence
    Description: The food environment is: 1) The physical presence of food that affects a person’s diet; 2) A person’s proximity to food store locations; 3) The distribution of food stores, food service, and any physical entity by which food may be obtained; or 4) A connected system that allows access to food. (Source: https://www.cdc.gov/healthyplaces/healthtopics/healthyfood/general.htm) Data included here concern: 1) Food access; and 2) Liquor access. Spatial Coverage for most data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area, Michigan, USA. See exception for grocery store data below.
  7. Data Supplement: Self-Confirming Price-Prediction Strategies for Simultaneous One-Shot Auctions

    Work
    Title: Data Supplement: Self-Confirming Price-Prediction Strategies for Simultaneous One-Shot Auctions
    Creator: Wellman, Michael P.
    Description: For each game: - file in JSON format with raw payoff data - text file with game-theoretic analysis results
  8. Neighborhood Effects : Community Characteristics and Health in Metropolitan Detroit

    Title: Neighborhood Effects : Community Characteristics and Health in Metropolitan Detroit
    Creator: Yan, Xiang (Jacob), Veinot, Tiffany C, Data Driven Detroit, Clarke, Phillipa J., Goodspeed, Robert, Gomez-Lopez, Iris N., and Okullo, Dolorence
    Description: This collection was produced as part of the project, “A ‘Big Data’ Approach to Understanding Neighborhood Effects in Chronic Illness Disparities.” The Investigators for the project are Tiffany Veinot, Veronica Berrocal, Phillipa Clarke, Robert Goodspeed, Daniel Romero, and VG Vinod Vydiswaran from the University of Michigan. The study took place from 2015-2016, with funding from the University of Michigan’s Social Sciences Annual Institute, MCubed, and the Sloan and Moore Foundations. Contact: Tiffany Veinot, MLS, PhD Office: 3443 North Quad Phone: 734/615-8281 Email: tveinot@umich.edu
  9. Neighborhood Effects Active Living Resources

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    Title: Neighborhood Effects Active Living Resources
    Creator: Data Driven Detroit, Reference USA, City of Detroit, Veinot, Tiffany C., and ESRI
    Description: Active living resources include spaces and organizations that facilitate physical activity, including 1) park land, 2) recreation areas (including parks, golf courses, amusement parks, beaches and other recreational landmarks); and 3) recreation centers (including gyms, dancing instruction, martial arts instruction, bowling centers, yoga instruction, sports clubs, fitness programs, golf course, pilates instruction, personal trainers, swimming pools, skating rinks, etc.) Coverage for all data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area.
  10. Neighborhood Effects: Social Environment

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    Title: Neighborhood Effects: Social Environment
    Creator: Yan, Xiang, Reference U.S.A., Okullo, Dolorence, Data-Driven Detroit, State of Michigan Department of Elections, Veinot, Tiffany C., and Goodspeed, Robert
    Description: The Social Environment refers to characteristics of the people and institutions in a census tract, including: 1) Religious organizations (churches and places of worship); and 2) Voter turnout for the 2012 Presidential Election. Coverage for all data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area.