Work Description

Title: Hydrologic flushing rates drive nitrogen cycling and plant invasion in a freshwater coastal wetland model Open Access Deposited

Ecological Applications EAP20-0253 Reproducable Data Archive

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Attribute Value
Methodology
  • This dataset includes input and output ASCII files for a free ecosystem simulation model, MONDRIAN. When all inputs are entered into the model interface and once the model has completed, all model output is tabulated in a output ASCII file. Description of these data are provided within the ASCII file (each column of data has a description in the first rows of each .txt file) and in the .docx User Guide provided. Please refer to the 'readme' file for more information.
Description
  • Coastal wetlands intercept significant amounts of nitrogen (N) from watersheds, especially when surrounding land cover is dominated by agriculture and urban development. Through plant uptake, soil immobilization, and denitrification wetlands can remove excess N from flow through water sources and mitigate eutrophication of connected aquatic ecosystems. Excess N can also change plant community composition in wetlands, including communities threatened by invasive species. Understanding how variable hydrology and N loading impact wetland N removal and community composition can help attain desired management outcomes, including optimizing N removal and/or preventing invasion by non-natives. By using a dynamic, process-based ecosystem simulation model, we are able to simulate various levels of hydrology and N loading that would otherwise be difficult to manipulate. We investigate the effects of hydroperiod, hydrologic residence time, N loading, and the NH4+:NO3- ratio on both N removal and the invasion success of two non-native species (Typha x glauca or Phragmites australis) in temperate freshwater coastal wetlands using Mondrian, a process-based, wetland ecosystem simulation model. We found that when residence time increased, annual N removal increased up to 10-fold while longer hydroperiods also increased N removal, but only when residence time was >10 days and N loading was >30 g N m-2 y-1. N removal efficiency also increased with increasing residence time and hydroperiod, but was less affected by N loading. However, longer hydrologic residence time increased vulnerability of wetlands to invasion by both invasive plants at low to medium N loading rates where native communities are typically more resistant to invasion. This suggests a potential tradeoff between ecosystem services related to nitrogen removal and wetland invasibility. These results help elucidate complex interactions of community composition, N loading and hydrology on N removal, helping managers to prioritize N removal when N loading is high or controlling plant invasion in more vulnerable wetlands.
Creator
Depositor
  • sjsharp@umich.edu
Contact information
Discipline
Funding agency
  • Other Funding Agency
Other Funding agency
  • NASA Earth Sciences
ORSP grant number
  • 80NSSC17K0262
Keyword
Date coverage
  • 2020-01-10
Citations to related material
  • Currie, W. S., Goldberg, D. E., Martina, J., Wildova, R., Farrer, E., & Elgersma, K. J. (2014). Emergence of nutrient-cycling feedbacks related to plant size and invasion success in a wetland community–ecosystem model. Ecological Modelling, 282, 69–82. https://doi.org/10.1016/j.ecolmodel.2014.01.010
Resource type
Last modified
  • 11/19/2022
Published
  • 08/25/2020
Language
DOI
  • https://doi.org/10.7302/thef-4p55
License
To Cite this Work:
Sean Sharp. (2020). Hydrologic flushing rates drive nitrogen cycling and plant invasion in a freshwater coastal wetland model, Ecological Applications EAP20-0253 Reproducable Data Archive [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/thef-4p55

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Files (Count: 42; Size: 240 MB)

The files in this archive include ASCII input files (Mondrian-Seed-v43.txt, Mondrian-Para-v43.txt, Mondrian-Scenario-v43.txt, Mondrian-Batch-v43.txt) for an ecosystem simulation model Mondrian, .xlsx setup files that describe these inputs, including descriptions of column and row heading otherwise missing from the .txt files, and how to enter them properly (Mondrian-SeedFileSetup-v43.xlsx, Mondrian-ParaFileSetup-v43.xlsx, etc), and .txt model output files (MondrianResultsBGC_restime21_1.txt, MondrianResultsBGC_restime21_2.txt, etc.). The .xlsx setup files associated with each .txt input file describes what each column represents and how they are input into the model. The first 132 rows of the “MondrianResultsBGC…” output .txt files include metadata and descriptions of each data column below. Each output file corresponds to a certain combination of input files. The “workflow” tab in the included spreadsheet “restime_2.1.xlsx” describes each of these output files and what specific combinations they include. “restime_2.1.xlsx” also includes the objective and brief description of this project (“overview” tab) and details about the independent variables and how they were manipulated for this model experiment (tab “Model setup). Additionally, there is a comprehensive Mondrian User Guide word doc (.docx) that describes in more detail each of the files listed above, how they are used, and how the Mondrian model works for further reference. Finally, these is a .xlsx spreadsheet named “sentinel_site_calibration” which shows data from 5 selected sentinel sites that were used to calibrate a newly added denitrification process function in Mondrian. The tab titled “matrix” contains information used for calibration of two model scaling parameters (denitrif parm and nitrif parm) including field observations (heading = “Observed values from field studies”), best fitting scaling parameter value, (heading = “Chosen scaling parameter values”), model predictions (heading = “Model calibration output”), best estimates of field data for model input (heading = “Mondrian calibration input”). The text box on the “matrix” tab represents the final calibration values used for the model. The “denitrification calibration” tab includes output of iterative calibration simulations sets (Exercises 1-9) with brief description of what is different about this set of simulations in which ‘denitrif parm’, ‘nitrif parm’ and other values were ‘tweaked’ to achieve a least sum of squares value, which was them deemed “best fit” for these calibration parameters. The following tabs (“Old Woman Creek”, St Louis Bay”, etc) represent field data compiled from each study used for calibration, including best estimates of nitrogen loading rates, hydrologic flushing rates, water level and hydroperiod, plant communities, and regional climate data. The “conversions” tab includes brief conversion calculations used to standardize all data for comparison and model input.

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