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Arctic Observing Networks: Collaborative Research: Sustaining and amplifying the ITEX AON through automation and increased interdisciplinarity of observations  

Project Summary poster (jpeg 1.4 M)

Arctic Observing Networks: Collaborative Research: Sustaining and amplifying the ITEX AON through automation and increased interdisciplinarity of observations.

Proposed activities
The International Tundra Experiment (ITEX) Arctic Observing Network (AON) collects data on phenology, plant growth, community composition and ecosystem properties as part of a greater effort to study environmental change in the Arctic.  The network, started in early 1990’s, now provides tremendous value for detecting changes within long-term experimentally warmed and control plots across a range of sites and ecosystems that span the major vegetation types of the Arctic.  While of great value, these manually collected measurements are labor intensive and time consuming, greatly restricting frequency and spatial extent of sampling.  Recent advances in sensor technology hold the promise to allow sampling of surrogates of these manual measurements rapidly and over large areas.  Here we will continue the ITEX AON observations and initiate a suite of related, non-intrusive structure, reflectance and thermal measurements using robotic sensor platforms (networked infomechanical systems, NIMS).  These new measurements will allow us to scale our measurements to the regional level by linking to existing 1 km2 sample vegetation grids and satellite imagery, providing urgently needed data critical to our understanding of the impacts of changing tundra vegetation on the interactions between the land and the atmosphere for the Arctic and the global system, including carbon and water fluxes and energy balance.

This project will specifically:
1) Build on the power of the ITEX experiment by continuing to monitor the long-term changes in phenology, vegetation structure and composition change, and their ecosystem consequences in response to experimental warming and background climate change.  The data, from which we have records going back over a decade, provide firm benchmarks to document change.  The small scale and extreme heterogeneity of tundra communities requires continued manual measurements of phenology and plant community composition, which we will conduct on our ITEX experimental and control plots.  To link phenology and community composition to ecosystem function we will continue measurement of key indices of ecosystem function including plant and soil stable isotopes ratios, nutrients, plot-level spectral reflectance, and components of CO2 exchange of the existing ITEX plots.

2) Establish vegetation grids at each location to increase spatial coverage.  We will monitor vegetation change at the landscape level with the use of existing 1 km2 ARCSS grids in Alaska and a new spatial grid in Greenland.  Within the grids we will monitor vegetation changes at the plot level for each vegetation type.  We will also use high-resolution satellite imagery to develop fine-scale vegetation maps of the ARCSS/ITEX grids at each site.

3) Install infrastructure for automated monitoring of surrogates for plant phenology, vegetation structure, and ecosystem function across our arctic transect.  We will install mobile sensor systems instrumented with a comprehensive suite of sensors and imagers within the vegetation grids at each site.  These platforms will provide the link between manual and automated measurements and increase the scale and frequency of sampling.  Because the sensor platforms are highly expandable, additional sensors can be added as new technology develops.  These measurements should greatly increase the scalability and interdisciplinary usage of the datasets.

(4) Scale up ITEX measurements using the ARCSS grids and multiple remote sensing approaches.  We will develop capacities for scaling metrics of plant and ecosystem function from the plot to regional level.  Spectral reflectance measurements will be made at the plot level, from a semi-autonomous robotic sensor array mounted on overhead cables, and from high spatial resolution satellite imagery.  Plant canopy structural measurements will be made at the plot level, from distance and range finder sensors on the robotic cable system, using geo-referenced ground based LiDAR.  Specifically, these measurements will permit the mechanistic drivers of change in plant and ecosystem spectral properties and canopy development and the implications of these on ecosystem function to be understood and traced across a range of spatial and temporal scales.


Steve Oberbauer - Florida International University (

William Gould - Institute of Tropical Forestry

Robert Hollister- Grand Valley State University

Craig E. Tweedie- University of Texas El-Paso

Jeff Welker - University of Alaska Anchorage

Nathan Healey (Jet Propulsion Lab)

Roxaneh Khorsand (Northern Colorado University)

Jose Luciani (Florida International University)

This material is based upon work supported by the National Science Foundation. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.