Topp et al (2020) Used the Landsat data to assess change in U.S. lake color from 1985-2020. Because their lake color data is built off the HydroLAKES database of lake shapefiles, they were able to merged lake color with the GLCP vis-a-vis consistent, unique identifiers for each lake. They then were able to use all GLCP variables as predictors of lake color change for over 26,000 lakes over 35 years!
Cuhn & Butman (2021) used the GLCP’s basin:lake matching scheme, which allowed them to merge lake color landsat, permafrost, climate, and morphometry data into a single analysis.
We – as a team – are so excited that others are using the GLCP for applications beyond our own intended analyses! While we have our own analyses coming down the pipe, we’d appreciate hearing from you. If you used or are currently using the GLCP, please reach out so we highlight your work!
Michael co-led a manuscript with Robert Ladwig (a postdoc at the Center for Limnology at University of Wisconsin Madison) to synthesize how six scientific societies either transitioned meetings to a virtual format or inaugurated new meetings altogether. In the manuscript, Michael and Robert had each society contribute a brief write-up generally addressing: What they did; What went well; what could have been better; what they would change. The manuscript had 30 co-authors, making it the most number of co-authors on a single publication in Limnology & Oceanography Bulletin’s history. You can read the Open Access publication here.
Following the publication of our L&O Bulletin piece on natural resource applications of the Global Lake area, Climate, and Population (GLCP) dataset, we were encouraged to submit a video abstract! The video abstract highlights the main features of the dataset, and also showcases how user-friendly the dataset is. Matt really hammers this point home in the video when he performs a live-coding demo, when in the span of 45-seconds, he is able to nearly recreate one of the analyses in the L&O Bulletin paper! Give it a look!
Today, a paper came out in L&O Bulletin, which Michael co-authored a manuscript with Jake Zwart, a Mendenhall Post-doctoral researcher with the US Geological Survey. The paper details what Michael and Jake learned while co-organizing the Virtual Summit: Incorporating Data Science and Open Science in Aquatic Research. Additionally, Michael and Jake look forward to seeing future Virtual Summits, and they welcome others to message them with questions or interest in presenting or co-organizing.
This week, Michael, Matt, and Stephanie were co-authors on a paper that came out in Limnology & Oceanography Bulletin! The manuscript builds on The Global Lake area, Climate, and Population dataset, which came out in Scientific Data earlier this year. The L&O Bulletin piece is meant to detail concrete, natural resource applications of the GLCP that span local, regional, and national scales. Matt also worked hard to document all scripts used in this paper, so that future users can have templates to reproduce certain analyses or tailor them for specific questions.
The paper is open access thanks to support from CANHRS and School of the Environment at Washington State University!
Michael and Jake Zwart (USGS) are teaming up to co-convene a “Virtual Summit: Incorporating Data Science and Open Science in Aquatic Research”! The virtual summit will feature 18 presenters from the US and Canada, all presenting on how they incorporate Data Science and Open Science Techniques in their research. The summit will occur on 23-24 July 2020 13:00-16:00 EDT via zoom and is free to attend. Registration will remain open until 22 July, but zoom login information (link, password, etc.) will be emailed on 20 and 22 July. Plenty of space remains, and we hope to see you there!
Recently, the team’s data paper came out in Scientific Data. The paper details how Michael, Steph Labou, and Matt created a global dataset of annual lake surface area with co-located basin temperature, precipitation, and human population for over 1.42 million lakes from 1995 through 2015. The team also had the opportunity to write-up a blog post for Scientific Data, where they gave a “Behind the Paper” perspective in how the project went from a casual conversation during a lab meeting to an full-fledged data product and data manuscript. The data, all scripts, and metadata are freely accessible on the Environmental Data Initiative, where the dataset is now EDI’s “New Featured Dataset” of the month! Congrats team!