National-scale, remotely sensed lake trophic state, 1984-2020

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1038/s41597-024-02921-0. This is version 2 of this Preprint.

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Authors

Michael Frederick Meyer , Simon Topp, Tyler V King, Robert Ladwig, Rachel M Pilla , Hilary Dugan, Jack R Eggleston, Stephanie E Hampton, Dina M Leech, Isabella Anna Oleksy, Jesse C Ross, Matthew RV Ross, R Iestyn Woolway, Xiao Yang, Matthew R Brousil, Kate C Fickas, Julie C Padowski, Amina I Pollard, Jianning Ren , Jacob Zwart 

Abstract

Lake trophic state is a key ecosystem property that integrates a lake’s physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used Landsat surface reflectance data to create the first compendium of annual lake trophic state for 55,662 lakes of at least 10 ha in size throughout the contiguous United States from 1984 through 2020. The dataset was constructed with FAIR data principles (Findable, Accessible, Interoperable, and Reproducible) in mind, where data are publicly available, relational keys from parent datasets are retained, and all data wrangling and modeling routines are scripted for future reuse. Together, this resource offers critical data to address basic and applied research questions about lake water quality at a suite of spatial and temporal scales.

DOI

https://doi.org/10.31223/X59H4W

Subjects

Biology, Life Sciences, Terrestrial and Aquatic Ecology

Keywords

remote sensing, Limnology, Aquatic Ecology, community ecology

Dates

Published: 2023-05-10 16:52

Last Updated: 2024-01-17 05:15

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License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
The authors declare no conflicts of interest.

Data Availability (Reason not available):
https://doi.org/10.6073/pasta/212a3172ac36e8dc6e1862f9c2522fa4