Maximum carbon assimilation model for understory wood plants growing at Bagley Nature Area in Duluth, MN
2020-05-26
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2017/02/16
2018/11/11
2018/11/11
Date completed
2019/12/22
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Title
Maximum carbon assimilation model for understory wood plants growing at Bagley Nature Area in Duluth, MN
Published Date
2020-05-26
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O'Connell, Erin M
oconn877@d.umn.edu
oconn877@d.umn.edu
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Field Study Data
Observational Data
Programming Software Code
Field Study Data
Observational Data
Programming Software Code
Abstract
These data were collected and analyzed for a project comparing the leaf phenology, carbon gain, growth, and freezing susceptibility of invasive and native species. Maximum seasonal carbon assimilation was modeled for six plants per eight species growing in a 50-year-old mixed forest. The model is based on understory light availability on sunny days, carbon dioxide assimilation rates, and leaf area adjusted in the spring for expanding leaves and in the fall for senescing leaves.
Description
There is one readme file, one R file, and six CSV files. The R file contains code modeling maximum seasonal carbon assimilation for understory shrubs. All six CSV files are required inputs for the R code and contain data that are referenced throughout the model. The CSV files include data on leaf phenology, photosynthetic light response curves, and understory light.
Referenced by
O'Connell, E. and Savage, J. (2020). Extended leaf phenology has limited benefits for invasive species growing at northern latitudes. Biological Invasions 22(10): 2957-2974.
https://doi.org/10.1007/s10530-020-02301-w
https://doi.org/10.1007/s10530-020-02301-w
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National Science Foundation (IOS:1656318)
University of Minnesota – Duluth
Integrated Biosciences Graduate Program
University of Minnesota – Duluth
Integrated Biosciences Graduate Program
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O'Connell, Erin M; Savage, Jessica A. (2020). Maximum carbon assimilation model for understory wood plants growing at Bagley Nature Area in Duluth, MN. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/t9bg-vr86.
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