MODULE DEVELOPMENT AND TESTING Module teaching materials were
developed by C.C. Carey, K.J. Farrell, and A.G. Hounshell to provide
instructors of undergraduate ecology courses with a ready-to-use,
adaptable module that could be implemented in a 3-4 hour time period.
As the fourth module within the suite of Macrosystems EDDIE
(www.macrosystemseddie.org) teaching materials, this module was
developed to teach students fundamental concepts about macrosystems
ecology, and how a macrosystems approach can be used to understand how
lakes are affected by drivers that operate on multiple, interconnected
temporal and spatial scales. As a secondary goal, Macrosystems EDDIE
modules introduce students to advanced computational tools as a way to
manage, analyze, visualize, and interpret high-frequency and long-term
ecological data sets.
The specific student learning goals for this module are that by the
end of the module, students will be able to: - Understand the concepts
of macrosystems ecology and macro-scale feedbacks, and how different
ecological processes can interact at local, regional, and continental
scales. - Simulate greenhouse gas fluxes in multiple lakes using
ecosystem models of lake water chemistry set up with
publicly-available high-frequency sensor datasets (Activity A). - Test
the effects of a climate scenario on the different lake models and
examine how the timing and magnitude of greenhouse gas fluxes change
with climate warming (Activity B). - Examine how local conditions may
alter the timing and magnitude of greenhouse gas fluxes from lakes to
affect global climate change (Activity C). - Predict how lake
greenhouse gas fluxes may both respond to and amplify changing
climate. - The module was assessed by volunteer faculty testers during
the 2018-2019 academic year. Faculty testers provided feedback that
was used to update and optimize teaching materials. Carey, Farrell,
and Hounshell also used student pre- and post-module assessment
questions to gauge effectiveness of teaching materials for achieving
module learning goals. Pedagogical specialists with the Science
Education Resource Center at Carleton College assisted with assessment
development and implementation.
UNDERLYING MODEL DATA The module uses the General Lake Model (GLM;
Hipsey et al. 2014), an open-source hydrodynamic simulation model, to
simulate lake temperatures and other physical limnology metrics over
the model time period. GLM in this module (version 2.2.0rc5) uses the
'GLMr' and 'glmtools' packages (Read and Winslow 2016, Winslow and
Read 2016), which allow the GLM model to be run and output analyzed
through the R statistical environment. Calibrated models were set up
for four lakes that are part of either the United States National
Ecological Observatory Network (NEON; www.neonscience.org) or the
Global Lakes Ecological Observatory Network (GLEON; http://gleon.org).
The four lakes are Falling Creek Reservoir (Virginia, USA), Lake
Mendota (Wisconsin, USA), Lake Sunapee (New Hampshire, USA), and
Toolik Lake (Alaska, USA), which encompass a range of geographic
location, trophic state, mixing regime, and watershed land use. The
model representation of each lake has been simplified in multiple ways
for the purpose of teaching this module: for example, lakes with
multiple surface inflows were simplified to one inflow in the model.
Within the module, lake configuration files (glm2.nml) have been
coarsely calibrated for each lake. Meteorological driver data
(met_hourly.csv) for each lake were compiled at an hourly time step
from the North American Land Data Assimilation System (NLDAS-2;
Cosgrove et al. 2003) and include air temperature, short and long wave
radiation, relative humidity, wind speed, and precipitation (rain and
snow). For lakes that include a substantial surface inflow, an inflow
file (inflow.csv) is included, which includes discharge volume, water
temperature, and inflow salt concentration at a daily timestep. For
lakes with a surface outflow, each lake model also includes a surface
outflow file (outflow.csv) that is estimated based on inflows to
maintain lake volume. Climate scenarios simulated +2oC, +4oC, and +6oC
warming scenarios by increasing observed surface air temperature from
2013-2014 by +2oC (met_hourly_plus2.csv), +4oC (met_hourly_plus4.csv),
and +6oC (met_hourly_plus6.csv), respectively for each of the 4 lake.
For more information, we refer users to the website and publications
listed below.
WEBSITE & PUBLICATIONS Carey, C.C., K.J. Farrell, and A.G.
Hounshell. 15 April 2020. Macrosystems EDDIE: Macro-scale feedbacks.
Macrosystems EDDIE Module 4, Version 1.
http://module4.macrosystemseddie.org.
Farrell, K.J., & C.C. Carey. 2018. Power, pitfalls, and potential
for integrating computational literacy into undergraduate ecology
courses. Ecology and Evolution 8: 7744-7751. DOI: 10.1002/ece3.4363
Carey, C. C. and Gougis, R. D. 2017. Simulation modeling of lakes in
undergraduate and graduate classrooms increases comprehension of
climate change concepts and interest in computational tools. Journal
of Science Education and Technology 26: 1-11. DOI:
10.1007/s10956-016-9644-2
NOTES AND COMMENTS Cosgrove, B. A., Lohmann, D., Mitchell, K. E.,
Houser, P. R., Wood, E. F., Schaake, J. C., Robock A., Marshall, C.,
Sheffield, J., Duan, Q., Luo, L., Higgins, R. W., Pinker, R. T.,
Tarpley, J. D., & Meng, J. (2003). Real-time and retrospective
forcing in the North American Land Data Assimilation System (NLDAS)
project. Journal of Geophysical Research: Atmospheres, 108(D22).
Hipsey, M. R., L.C. Bruce, and D.P. Hamilton. 2014. GLM- General Lake
Model: Model overview and user information. AED Report #26, The
University of Western Australia, Perth, Australia. 42 pp. Available:
http://aed.see.uwa.edu.au/research/models/GLM/
Hipsey, M.R., Bruce, L.C., Boon, C., Busch, B., Carey, C.C., Hamilton,
D.P., Hanson, P.C., Read, J.S., De Sousa, E., Weber, M., Winslow,
L.A., 2019. A General Lake Model (GLM 3.0) for linking with
high-frequency sensor data from the Global Lake Ecological Observatory
Network (GLEON). Geosci. Model Dev. 12, 473-523.
https://doi.org/10.5194/gmd-12-473-2019
Read, J.S., and L.A. Winslow. 2016. glmtools R package v.0.14.6.
Available: https://github.com/USGS-R/glmtools
Winslow, L.A., and J.S. Read. 2016. GLMr R package v.3.1.15 and GLMr R
package default files. GLMr: A General Lake Model (GLM) base package.
DOI: 10.5281/zenodo.595574
