Background and Motivation

The distribution, abundance, and phenology of arctic flora are influenced by environmental factors operating at multiple spatial and temporal scales.  This drives patterns of vegetation heterogeneity that in turn impact processes across all levels of ecological organization, yet individual-level vegetation heterogeneity is poorly quantified in Arctic systems beyond the plot scale.  This data gap presents a challenge to both understanding and predicting ecological responses to rapid regional warming.  Furthermore, quantifying how the distribution, abundance, and phenology of individual plants varies across landscape extents (hundreds to thousands of meters) is critical to ultimately linking plot-based research with the broader-scale signals of vegetation change captured by satellites.

Carefully planned image acquisition from Unmanned Aerial Systems (UAS, i.e. drones) captures spatially continuous, individual-level information about plant productivity and its context in the environment via both structural and spectral models.  These data are relevant to many ecological research programs, but will hold greatest value to long-term records, cross-site syntheses, and comparisons with satellite records if they are gathered with consistent methods and philosophies.

For the 2017 High Latitude Drone Ecology Network (HiLDEN) data collection season, we propose implementing common UAS tundra mapping protocols with the immediate aim of producing data and insights for a concepts and synthesis paper (details below) and to act as a stimulus for funding applications.  These protocols are designed to apply across a variety of platforms and sensors (and are thus not optimized for any one particular set up) with a specific focus on cross-site comparisons. To participate, contributors will be asked to follow the guidelines below to collect and contribute high-quality, spatially referenced aerial photos of tundra landscapes captured during the peak of the 2017 growing season.  These images will be centrally hosted, processed, and analyzed with inputs from data contributors to address the following cross-site questions:

1) How does the relationship between landscape structure (microtopography/hydrology) and plant distribution/productivity predictably vary at sites across the arctic?

2) What is generalizable in how these relationships scale as a function of increasing spatial grain?

3) Do plant distribution/productivity patterns across scales correspond with satellite records among sites?