Engaging academia: Using NEON data to improve the design of ecological experiments and surveys.

Background/Question/Methods

NEON promises to transform ecology through an open science model including unrestricted access to long term data collected consistently across the range of biomes in the US. NEON data products backed by best practice quality assurance and quality control (QA/QC) criteria raise the level at which the academic community can design experimental programs and surveys where the aim is discovery and verification of ecosystem processes. 

Results/Conclusions

Uses of NEON data to improve the design of experiments, surveys, and monitoring programs include:

1. A priori power analysis from extensive data sets.
2. Estimates of variance in a large suite of ecosystem variables at multiple space and time scales.
3. Dimensional analysis across a large selection of variables to identify spurious relations during the design stage of an experiment.
4. Transfer functions for spatial and temporal variance in these variables. 
5. Long term local control in BACI and BAGI monitoring programs.
6. Enormous increases in replication where experiments are designed to include NEON sites.
7. Placing local results in the context of long term variance at the scale of ecosystems.
8. Identification of those variables that produce the most effective stratification schemes.
9. Case-control analysis of changes in risk (cross sectional in place of longitudinal data).
10. Process based functions at multiple space and time scales.
11. Quality control in any program relative to probability distributions functions for NEON data.

In addition to these data based opportunities, the rapidly growing institutional knowledge of spatially extensive research protocols and logistics within NEON becomes available to the ecological community on an open science model.