USGS · 70268819
Network of networks: Time series clustering of AmeriFlux sites
Abstract
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 < 5), unique groups and a few large (> 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.
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David E. Reed, Housen Chu, Brad G. Peter, Jiquan Chen, Michael Abraha, Brian Amiro, Ray G. Anderson, M. Altaf Arain, Paulo Arruda, Greg A. Barron-Gafford, Carl Bernacchi, Daniel P. Beverly, Sebastien C. Biraud, T. Andrew Black, Peter D. Blanken, Gil Bohrer, Rebecca Bowler, David R. Bowling, M. Syndonia Bret-Harte, Mario Bretfeld, Nathaniel A. Brunsell, Stephen H. Bullock, Gerardo Celis, Xingyuan Chen, Aimee T. Classen, David R. Cook, Alejandro Cueva, Higo J. Dalmagro, Kenneth J. Davis, Ankur Desai, Alison J. Duff, Allison L. Dunn, David Durden, Colin W. Edgar, Eugenie Euskirchen, Rosvel Bracho, Brent E. Ewers, Lawrence B. Flanagan, Christopher R. Florian, Vanessa Foord, Inke Forbrich, Brandon R. Forsythe, John Frank, Jaime Garatuza-Payan, Sarah Goslee, Christopher M. Gough, Mark B. Green, Timothy Griffis, Manuel Helbig, Andrew C. Hill, Ross Hinkle, Jason Horne, Elyn Humphreys, Hiroki Ikawa, Go Iwahana, Rachhpal Jassal, Bruce K. Johnson, Mark S. Johnson, Steven A. Kannenberg, Eric Kelsey, John King, John F. Knowles, Sara Knox, Hideki Kobayashi, Thomas Kolb, Randy Kolka, Ken Krauss, Lars Kutzbach, Brian T. Lamb, Beverly E. Law, Sung-Ching Lee, Xuhui Lee, Heping Liu, Henry W. Loescher, Sparkle L. Malone, Roser Matamala, Marguerite Mauritz, Stefan Metzger, Gesa Meyer, Bhaskar Mitra, J. William Munger, Zoran Nesic, Asko Noormets, Thomas L. O'Halloran, Patrick T. O'Keeffe, Steven F. Oberbauer, Walter Oechel, Patty Oikawa, Paulo C. Olivas, Andrew Ouimette, Gilberto Pastorello, Jorge F. Perez-Quezada, Claire Phillips, Gabriela Posse, Bo Qu, William L. Quinton, Michele L. Reba, Andrew D. Richardson, Valentin Picasso, Adrian V. Rocha. 2025-06-24. Network of networks: Time series clustering of AmeriFlux sites. https://doi.org/10.1016/j.agrformet.2025.110686
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