Linking Groundwater and Nutrients to Monitor Fen Ecosystems Using Airborne Imaging Spectroscopy

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Linking Groundwater and Nutrients to Monitor Fen Ecosystems Using Airborne Imaging Spectroscopy
Project Number:

WR17R001

Other Project Number:

2018WI372B

Funding Year:

2018

Contract Period:

7/1/2017 - 6/30/2019

Funding Source:

UWS, USGS

Investigator(s):
PIs:
  • Eric Booth, UW-Madison
  • Steven Loheide, UW-Madison
  • David Bart, UW-Madison
  • Philip Townsend, UW-Madison

Abstract:

Fens are unique and often isolated ecosystems of high conservation value in Wisconsin because they provide habitat for many rare plant and animal species. Their identity is inextricably linked to an absolute dependence on a consistent discharge of groundwater that saturates the near surface for most of the growing season leading to the accumulation of carbon. Mineral-rich groundwater is the main water source to these wetlands and associated hydrochemical patterns limit the availability of nutrients such as nitrogen and phosphorus. The stresses resulting from consistent saturation and low-nutrient availability result in high native plant diversity including very high rare species richness compared to other ecosystems. Decreases in the saturation stress by reduced groundwater inputs (e.g., from nearby pumping) can result in losses of native diversity, rare-species abundance, and increased invasion by non-native species. Thus, fens can be viewed as ‘sentinel ecosystems’ that may indicate subtle changes to groundwater conditions. This project proposes to utilize a full-range imaging spectrometer to develop a novel methodology that exploits the mechanistic link between groundwater, plant nutrient availability, and hyperspectral characteristics of fen ecosystems. We will integrate traditional methods of ground-based field monitoring with modern remote sensing technologies to give an ultra-high spatial and spectral resolution view of complex wetland landscapes. We hypothesize that spectral characteristics from the remotely-sensed images are related to biophysical traits – such as leaf nitrogen, phosphorus, and water content – and will be important for distinguishing between fen and non-fen areas as well as varying levels of fen floristic quality. Further, we hypothesize that changes in foliar chemistry will enable remote detection of reductions in groundwater inputs to fens. Our methodology will enable water managers to 1) monitor fen ecosystems that may be influenced by changes in groundwater inputs, and 2) observe subtle changes in groundwater conditions across a landscape.

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