Network of networks: Time series clustering of AmeriFlux sites
David E. Reed, Housen Chu, Brad G. Peter, Jiquan Chen, Michael Abraha, B. D. Amiro, Ray G. Anderson, M. Altaf Arain, Paulo Henrique Zanella de Arruda, Greg A. Barron‐Gafford, Carl J. Bernacchi, Daniel P. Beverly, Sebastien Christophe Biraud, T. A. Black, Peter D. Blanken, Gil Bohrer, Rebecca Bowler, D. R. Bowling, Marion Syndonia Bret-Harte, Mario Bretfeld · Agricultural and Forest Meteorology · 2025
• Air temperature and net radiation followed a latitude gradient in clustering. • Clustering of fluxes was related to mean annual temperature and precipitation. • Site uniqueness was quantified, and proximal sites pairs were more similar. • Unique sites were in urban, open water, mountains, Hawaii, and Latin America. Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under-sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.