Long-term dataset on aquatic responses to concurrent climate change and recovery from acidification

• Published in: Scientific data Vol. 5; no. 1; p. 180059
• Main Authors: Leach, Taylor H., Winslow, Luke A., Acker, Frank W., Bloomfield, Jay A., Boylen, Charles W., Bukaveckas, Paul A., Charles, Donald F., Daniels, Robert A., Driscoll, Charles T., Eichler, Lawrence W., Farrell, Jeremy L., Funk, Clara S., Goodrich, Christine A., Michelena, Toby M., Nierzwicki-Bauer, Sandra A., Roy, Karen M., Shaw, William H., Sutherland, James W., Swinton, Mark W., Winkler, David A., Rose, Kevin C.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 10.04.2018; Nature Publishing Group
• Subjects: 704/106/694/2739; 704/158/2445; 704/286; Acidification; Climate change; Data collection; Data Descriptor; Datasets; Ecosystems; Environmental changes; Freshwater ecosystems; Humanities and Social Sciences; Lakes; multidisciplinary; Science
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/sdata.2018.59

Concurrent regional and global environmental changes are affecting freshwater ecosystems. Decadal-scale data on lake ecosystems that can describe processes affected by these changes are important as multiple stressors often interact to alter the trajectory of key ecological phenomena in complex ways. Due to the practical challenges associated with long-term data collections, the majority of existing long-term data sets focus on only a small number of lakes or few response variables. Here we present physical, chemical, and biological data from 28 lakes in the Adirondack Mountains of northern New York State. These data span the period from 1994–2012 and harmonize multiple open and as-yet unpublished data sources. The dataset creation is reproducible and transparent; R code and all original files used to create the dataset are provided in an appendix. This dataset will be useful for examining ecological change in lakes undergoing multiple stressors. Design Type(s) observation design • time series design • data integration objective Measurement Type(s) geographic location • Physical Phenomenon or Property • Inorganic Chemistry • planktonic material • weather Technology Type(s) digital curation • data acquisition system • Analytical Chemistry • light microscopy Factor Type(s) Sample Characteristic(s) Adirondack Park • freshwater lake biome Machine-accessible metadata file describing the reported data (ISA-Tab format)