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3rd Annual Digital Data Conference, Yale: Difference between revisions
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3rd Annual Digital Data Conference, Yale (view source)
Revision as of 14:08, 6 May 2019
, 6 May 2019→Wednesday, 12 June 2019
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| colspan="4" style="text-align:left; vertical-align:top; background-color:#eed1a9;"|'''Workshop 1- Mobilizing museum collections and citizen science data to predict species distribution<br>Facilitators: Erica Stuber and Walter Jetz<br>Location & Time: (Morning, exact time TBA)'''<br> | | colspan="4" style="text-align:left; vertical-align:top; background-color:#eed1a9;"|'''Workshop 1- Mobilizing museum collections and citizen science data to predict species distribution<br>Facilitators: Erica Stuber and Walter Jetz, Yale University<br>Location & Time: (Morning, exact time TBA)'''<br> | ||
Species distribution models (SDM) are powerful tools for inferring species ecology, response to environmental change, and biodiversity at multiple spatial and temporal scales. However, understanding species’ ranges at landscape or global scales typically requires moving beyond designed studies, which are relatively small scale, to capitalize on museum collections and citizen science projects which can represent data spanning entire species ranges across current and historic habitats. Understanding species’ range-wide distribution is a requirement for developing evidence-based conservation plans and predicting species’ response to global change, facilitated by digitization efforts and open-source observations databases. In this hands-on workshop, participants will review the state of the science in species distribution modelling, consider best-practices in mobilizing collections-based and citizen-science data sources for distribution modeling, and fit a basic SDM (i.e., access species and environmental data, process, and fit a statistical distribution model). Participants should bring their own laptop; hands-on sessions will use the free R programming environment. Example code and data for modeling will be provided, although some previous practice working with R will be useful.<br> | Species distribution models (SDM) are powerful tools for inferring species ecology, response to environmental change, and biodiversity at multiple spatial and temporal scales. However, understanding species’ ranges at landscape or global scales typically requires moving beyond designed studies, which are relatively small scale, to capitalize on museum collections and citizen science projects which can represent data spanning entire species ranges across current and historic habitats. Understanding species’ range-wide distribution is a requirement for developing evidence-based conservation plans and predicting species’ response to global change, facilitated by digitization efforts and open-source observations databases. In this hands-on workshop, participants will review the state of the science in species distribution modelling, consider best-practices in mobilizing collections-based and citizen-science data sources for distribution modeling, and fit a basic SDM (i.e., access species and environmental data, process, and fit a statistical distribution model). Participants should bring their own laptop; hands-on sessions will use the free R programming environment. Example code and data for modeling will be provided, although some previous practice working with R will be useful.<br> | ||
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