Watershed-based Stressors for the Great Lakes Basin

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Persistent link to this item

https://doi.org/10.13020/28r6-bq38
https://hdl.handle.net/11299/259970

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Keywords

Environment

Great Lakes

Land Cover

Population

Roads

Stress

Watershed

Collection period

Date completed

2015-08-31

Date updated

Time period coverage

Geographic coverage

Source information

Journal Title

Journal ISSN

Volume Title

Title

Watershed-based Stressors for the Great Lakes Basin

Published Date

2024-01-11

Authors

Host, George

Kovalenko, Katya

Brown, Terry

Johnson, Lucinda

Ciborowski, Jan

Group

Natural Resources Research Institute

Author Contact

Johnson, Lucinda
ljohnson@d.umn.edu

Type

Dataset
Spatial Data

Abstract

The Watershed-based Stressors for the Great Lakes Basin dataset includes component and aggregated measures of environmental stress to coastal ecosystems from watersheds of the Great Lakes Basin. Stressors include the amount of agricultural and developed land use, as well as road and population density. These summaries are based on a set of 5971 watersheds that cover the US and Canadian Great Lakes basin, derived using methods from Hollenhorst et al. (2007). Indices presented in this dataset include SumRel (Host et al. 2011) and the more recent combined Agriculture and Development - AgDev index (Host et al. 2019). These were developed as part of the Great Lakes Environmental Indicators II (GLEI-II) project, funded through the Great Lakes Restoration Initiative and used to quantify the response of biota (birds, fish, macroinvertebrates, diatoms and wetland vegetation) to varying degrees of watershed stress (Kovalenko et al. 2014). As of 2015, a more recent version of watersheds has been created by the Great Lakes Aquatic Habitat Framework and stressors recalculated based on those watersheds.

Description

The Watershed-based Stressors for the Great Lakes Basin dataset includes component and aggregated measures of environmental stress to coastal ecosystems from watersheds of the Great Lakes Basin. Stressors include the amount of agricultural and developed land use, as well as road and population density. These summaries are based on a set of 5971 watersheds that cover the US and Canadian Great Lakes basin, derived using methods from Hollenhorst et al. (2007). Indices presented in this dataset include SumRel (Host et al. 2011) and the more recent combined Agriculture and Development - AgDev index (Host et al. 2019). A brief description of the AgDev "Euclidean Distance" stressor integration, with R code, is here: https://github.com/NRRI/stressor_lib/tree/master/euc_distance Use agdevbasn in preference to sumrel. For historical reference, for SumRel: we evaluated a number of normalizing transformations for each variable, including log, ln, and arcsine transformations. The use of high-resolution watersheds resulted in a large number of zeros (i.e. non-occurrence of the stressor) for many of the variables. The best results were obtained using a log10 transformation of non-zero values. Each of the five variables data values (x) were transformed to log10 (x), using the minimum non-zero value of x to replace zero values. These transformed (x') values were then standardized, (x'-m)/s, with m and s being the mean and standard-deviation for all x', respectively. These standardized values (x'') were then normalized, (x''-min)/(max-min), with min and max being the minimum and maximum for all x'', respectively. Finally the five x'' values for each variable in each watershed were summed and the summed values normalized again to give a single number - SumRel - for each watershed. SumRel ranges from 0.0-1.0, with 1.0 representing the maximum composite stress within a geographic coverage of interest. Note that this design allows stressor scores to be calculated for any given spatial extent - from local watersheds to an ecoregion, lake, or basin.

Referenced by

Hollenhorst, T.P., Brown, T.N., Johnson, L.B., Ciborowski, J.J.H., Host, G.E., 2007. Methods for generating multi-scale watershed delineations for indicator development in Great Lake Coastal ecosystems. J. Great Lakes Res. 33 (Special Issue 3), 13–26.DOI: 10.3394/0380-1330(2007)33[13:MFGMWD]2.0.CO;2
Host, G.E., Brown, T.N., Hollenhorst, T.P., Johnson, L.B., Ciborowski, J.J.H., 2011. High resolution assessment and visualization of environmental stressors in the Lake Superior basin. Aquat. Ecosyst. Health Manag. 14, 376–385. DOI: 10.1080/14634988.2011.625340
Host, G.E., Kovalenko, K.E., Brown, T.N., Ciborowski, J.J.H., Johnson, L.B., 2019. Risk based classification and interactive map of watersheds contributing anthropogenic stress to Laurentian Great Lakes coastal ecosystems. J. Great Lakes Res. 45 (3), 609-618. DOI: 10.1016/j.jglr.2019.03.008
Kovalenko, K.E., Brady, V.J., Brown, T.N., Ciborowski, J.J.H., Danz, N.P., Gathman, J.P., Host, G.E., Howe, R.W., Johnson, L.B., Niemi, G.J., Reavie, E.D., 2014. Congruence of community thresholds in response to anthropogenic stress in Great Lakes coastal wetlands. Freshw. Sci. 33, 958–971. DOI: 10.1086/676913

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License

Attribution-NonCommercial-ShareAlike 4.0 International (CC-By-NC-SA). Commercial users are encouraged to contact the authors about potential commercial uses.

Publisher

Collections

Data Repository for U of M (DRUM)

Funding information

GLEI-II was funded by a Great Lakes Restoration Initiative grant through the U.S. Environmental Protection Agency Great Lakes National Program Office (GL-00E00623-0).

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Previously Published Citation

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Suggested citation

Host, George; Kovalenko, Katya; Brown, Terry; Johnson, Lucinda; Ciborowski, Jan. (2024). Watershed-based Stressors for the Great Lakes Basin. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/28r6-bq38.

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