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    Water We Doing: A Deep Dive Into Sustainable Ocean Management & Blue Economies
    This lesson explores the concept of blue economies and includes a detailing lesson in R that involves basic statistics and building complex graphics.
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    DNA Barcoding & Biodiversity databases
    This resource pairs DNA barcoding databases with Biodiversity databases. Students collect their insect specimens in the field and use BLAST and BOLD to identify their species. They then use...
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    Mysterious Occurrences Instructors Notes
    Answer Key associated with Mysterious Occurrences Module
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    Mutualism and Coevolution of Agave and Bats
    In this module, students will investigate the mutualistic relationship between Agave its bat pollinators and the effects of coevolution on the morphological adaptations of the species involved.
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    GBIF Tutorial - BLUE Resource
    A user guide and video instructions for GBIF
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    iDigBio Tutorial - BLUE Resource
    A user guide and video instructions for iDigBio
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    Arctos Tutorial - BLUE Resource
    A user guide and video instructions for Arctos
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    Biodiversity research using digitized, internet-based natural history collections
    Collections based research is a critical tool for organismal biology and biodiversity research. Yet natural history collections have a complicated past. This multi-class module examines the...
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    Investigating Evidence for Climate Change (Project EDDIE) with CO2 and 13CO2 data: adapted for R
    This is an adaptation to work in R of Investigating Evidence for Climate Change (Project) by Hage, M. 2020. Students will investigate geologic and modern evidence for global temperature and...
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    Long Term Self-assessment Bates College DCS 105
    This is a long-term self-assessment tool for students participating in the Bates College course DCS 105 Calling Bull: Data Literacy and Information Science. .
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    STEM Inclusive Teaching Practices Webinar Series: Socially Relevant Teaching in the Time of COVID-19
    Presents various mathematical modeling and data science activities created around analyzing and interpreting COVID-19 data. Much of the instructional guidance provided for the activities and...
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    Downloading and Visualizing Project Data from the iNaturalist Database
    In this activity you will learn how to create a query, export, and download data from iNaturalist; load data into R; explore pollinator-plant interactions with R, and create heat map, bipartite,...
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    Nature’s Flying Machines: The Evolutionary Relationship of Avian Form & Function
    In this series of activities, birds will be used as the model organism. The modules examine the connections between body form and function over time by investigating the relationship between avian...
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    The Power of Data Standards
    Investigate data standards within the context of the Alpine Chipmunk and the Grinnell Study.
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    Identifiers in Digital Natural History Collections
    This is a collection of resources focusing on GUIDs (Globally Unique Identifiers) on what they are, what role they play in digital natural history collections, and how to incorporate them in...
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    Following the Data
    The video and exercise provides insight into how researchers are using digital data resources to investigate biodiversity in prairie fen wetlands.
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    Communicating with Data: Infographic with Digital Data
    Working collaboratively in teams of 2-4 researchers, students engage in targeted projects to address critical information and research needs using digital biodiversity data.
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    Data is the New Science - Modified and combined with Following the Data Module
    In this module, students will be introduced to some emerging biodiversity data resources. They will be asked to think critically about the strengths and utility of these data resources and apply...
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    The nose knows: How tri-trophic interactions and natural history shape bird foraging behavior. An introduction to statistical analysis in animal behavior research
    Students investigate the role of olfaction and infochemicals on bird foraging behavior through two different quantitative activities where they generate hypotheses, create figures, conduct data...
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