A quantitative strategy for collocating NEON’s long-term atmospheric measurements and field observations

Background/Question/Methods

The National Ecological Observatory Network (NEON) is a continental-scale research platform with a projected lifetime of 30 years. NEON’s purpose is to provide high-quality open source data that informs ecological research on the drivers of environmental change and enables forecasting its responses. To accomplish this, NEON is currently establishing 60 environmental research sites.

At these research sites, the terrestrial observing system (TOS) surveys in-situ biomass, insect populations etc. These inventories can be viewed as the boundary conditions or drivers for biophysical processes on much shorter time scales. On the other hand, NEON’s terrestrial infrastructure system (TIS) performs sensor-based measurements of the biophysical responses of an ecosystem, such as evapotranspiration. To establish valid relationships between these drivers and responses, two contradicting requirements must be fulfilled: Both types of observations shall be representative of the same ecosystem, while they shall not significantly influence one another.

Here we develop a procedure which quantitatively optimizes this trade-off through; (i) Determining the ratio of a user-defined impact threshold to effective impact area for different TOS activities. (ii) Quantifying the source area distributions of TIS measurements (iii) Determining the range of feasible distances between TIS locations and TOS activities by combining (i) and (ii).

Results/Conclusions

For a given TOS activity, the upwind distance from the TIS location required to stay below the same impact threshold differs among sites. These differences arise from site-specific environmental properties and corresponding differences in the TIS setups. As an example, we present results for three NEON sites going into operations in 2013 (Disney, Harvard, Sterling). For below- and above-ground biomass sampling, as well as insect traps the minimum distances vary among sites in the range of 30 m–70 m, 35 m–105 m, and 180 m–245 m, respectively. Analogously, the maximum distance for mutual representativeness (90% cumulative flux footprint) varies between 290 m–610 m.

This strategy provides an evidence-based and repeatable method for combining sensor-based measurements and field observations at pre-defined levels of disturbance and spatial representativeness. The developed algorithm represents a general framework which is applicable to other environmental research sites where similar collocation is desired. Such framework is essential prerequisite to warrant establishing reliable relationships between ecosystem drivers and responses that are captured by different observation methods. Ultimately, the ability to improve our understanding of continental-scale ecology depends on the comparability of these relationships among research sites.