US Long-Term Ecological Research Network
Lake snow removal experiment snow, ice, and Secchi depth, 2019-2021

Abstract

Although it is a historically understudied season, winter is now recognized as a time of biological activity and relevant to the annual cycle of north-temperate lakes. Emerging research points to a future of reduced ice cover duration and changing snow conditions that will impact aquatic ecosystems. The aim of the study was to explore how altered snow and ice conditions, and subsequent changes to under-ice light environment, might impact ecosystem dynamics in a north, temperate bog lake in northern Wisconsin, USA. This dataset resulted from a snow removal experiment that spanned the periods of ice cover on South Sparkling Bog during the winters of 2019, 2020, and 2021. During the winters 2020 and 2021, snow was removed from the surface of South Sparkling Bog using an ARGO ATV with a snow plow attached. The 2019 season served as a reference year, and snow was not removed from the lake. This dataset represents the snow depths, black and white ice thickness, and Secchi depths during the period of ice cover each winter.<br/>
Dataset ID
419

Data Citation Suggestion

Socha, E. and A. Gorsky. 2022. Lake snow removal experiment snow, ice, and Secchi depth, 2019-2021 ver 1. Environmental Data Initiative. https://doi.org/10.6073/pasta/962fa57959ff9828eb6f1cbda79b82c0. Accessed 2023-02-01.

Date Range

-

Data Download

CSV file including measurements for average snow depth, ice thickness, and Secchi depth for the South Sparkling Bog snow manipulation experiment.

NTL Themes

LTER Keywords