WK 9 - Work with Ecological Time Series Data in R

Sunday, August 7, 2016: 8:00 AM-11:30 AM
316, Ft Lauderdale Convention Center
Leah A. Wasser
Megan A. Jones
The temporal scale of ecological research is expanding given increased continental and global availability of time series data coming from long term data collection efforts such as NEON, LTER and Fluxnet. Given increased data availability, there is a need to implement efficient, well-documented and reproducible workflows in tools like R.

This workshop will teach participants how to import, manipulate, format and plot time series data stored in .csv format in R. We will use temperature, precipitation and PAR data - key drivers of phenology events. Key skills learned will include 1) working with data.frames in R, 2) converting timestamps stored as text strings to R date or datetime (e.g. POSIX) classes, 3) aggregating data across different time scales (day vs. month) and 4) plotting time series data. As a culminating demonstration, we will combine disparate datasets – specifically temperature data collected from sensors on a tower and greenness index values (NDVI) calculated from a raster time series.

The meteorology and phenology data used in this workshop complements the WK 20 Work With Spatial Raster Data & Raster Time Series in R workshop presented Sunday afternoon.

The content presented in this workshop will be based upon the tutorial series located on the neondataskills.org website: http://neondataskills.org/tutorial-series/tabular-time-series/

Participants attending this workshop should bring their own laptops. Participants should have a basic level of familiarity with working with data in R, including installing and loading libraries, data import and basic indexing and subsetting. All materials taught in this workshop were developed in collaborative effort between Data Carpentry and the National Ecological Observatory Network (NEON).

Please don’t wait to register for this workshop as it filled up and had a waiting list last year!

Registration Fee: $25

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