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- Creator:
- Hong, Yi, Fry, Lauren M., Orendorf, Sophie, Ward, Jamie L., Mroczka, Bryan, Wright, David, and Gronewold, Andrew
- Description:
- Accurate estimation of hydro-meteorological variables is essential for adaptive water management in the North American Laurentian Great Lakes. However, only a limited number of monthly datasets are available nowadays that encompass all components of net basin supply (NBS), such as over-lake precipitation (P), evaporation (E), and total runoff (R). To address this gap, we developed a daily hydro-meteorological dataset covering an extended period from 1979 to 2022 for each of the Great Lakes. The daily P and E were derived from six global gridded reanalysis climate datasets (GGRCD) that include both P and E estimates, and R was calculated from National Water Model (NWM) simulations. Ensemble mean values of the difference between P and E (P – E) and NBS were obtained by analyzing daily P, E, and R. Monthly averaged values derived from our new daily dataset were validated against existing monthly datasets. This daily hydro-meteorological dataset has the potential to serve as a validation resource for current data and analysis of individual NBS components. Additionally, it could offer a comprehensive depiction of weather and hydrological processes in the Great Lakes region, including the ability to record extreme events, facilitate enhanced seasonal analysis, and support hydrologic model development and calibration. The source code and data representation/analysis figures are also made available in the data repository.
- Keyword:
- Great Lakes, Hydrometeorological, National Water Model, Daily, Overlake precipitation, Overlake evaporation, Total runoff, Net Basin Supply, and Water Balance
- Discipline:
- Science and Engineering
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- Creator:
- Fuller, Jennifer, Rowan, Erin, Landgraf, Ava, Alofs, Karen, Foufopoulos, Johannes, and Gronewold, Andrew
- Description:
- This study investigates the rapid decline of black tern (Chlidonias niger) over eight years in one of Michigan’s largest colonies, Lake St. Clair. 1. Nesting Success Model: A multiple logistic regression with a binomial (logit-link) fit using the glm() function from the ‘stats’ package in R (55) to determine the influence of habitat and biological predictors on nesting survival. 2. ArcMap visualization of Nesting Success: To visualize the geographic extent of the habitat’s potential to predispose nests’ vulnerability, the coefficients and intercept from our selected GLM were applied to raster layers in ArcMap using the Raster Calculator Tool. 3. Population Change & Habitat Extent: To quantify sub-colony breeding pair population size and their response to changes in sub-colony habitat in the geospatial model, we applied a general linear mixed model (GLMM) using the lmer() function from the ‘lme4’ package in R (55). Predictor variables were chosen a priori, and included the area of open water, uninhabitable vegetation (NDVI>0.72), any habitable area, and area with >50% hatch success.
- Keyword:
- black terns, wetlands, ecology, climate change, lake levels, Great Lakes, waterbirds, ornithology, general linear model, geospatial, GIS, nesting success, avian, and breeding
- Citation to related publication:
- Fuller, J., Rowan, E., Landgraf, A., Alofs, K., Foufopoulos, J., Gronewold, A., (2021). Collapse of a Black Tern Colony (Chlidonias niger) as a Result of Climate Change Driven Lake-Level Extremes and Anthropogenic Habitat Alteration [Data set]. University of Michigan - Deep Blue. and Fuller, J., et al. (2021). Shorebird colony collapses under climate driven lake-level rise and anthropogenic stressors. Forthcoming.
- Discipline:
- Science