Network of networks: Time series clustering of AmeriFlux sites

作者：David E. Reed, Housen Chu, B. 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, Sébastien Biraud, T. A. Black, Peter D. Blanken, Gil Bohrer, Rebecca Bowler, D. R. Bowling, M. Syndonia Bret‐Harte, Mario Bretfeld, N. A. Brunsell, Stephen H. Bullock, Gerardo Celis, Xingyuan Chen, Aimée T. Classen, David Cook, Alejandro Cueva, Higo J. Dalmagro, K. J. Davis, Ankur R. Desai, Alison J. Duff, Allison L. Dunn, David Durden, Colin W. Edgar, E. S. Euskirchen, Rosvel Bracho, B. E. Ewers, Lawrence B. Flanagan, Christopher Florian, Vanessa N. Foord, Inke Forbrich, Brandon Forsythe, J. M. Frank, Jaime Garatuza‐Payán, Sarah Goslee, Christopher M. Gough, Mark B. Green, Timothy J. Griffis, Manuel Helbig, Andrew C. Hill, Ross Hinkle, Jason Horne, Elyn Humphreys, Hiroki Ikawa, Go Iwahana, Rachhpal S. Jassal, Bruce L. Johnson, Mark S. Johnson, Steven A. Kannenberg, Eric P. Kelsey, John S. King, John F. Knowles, Sara Knox, Hideki Kobayashi, Thomas E. Kolb, Randy Kolka, Ken W. Krauss, Lars Kutzbach, Brian Lamb, B. 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, T. L. O’Halloran, P. O'Keeffe, Steven F. Oberbauer, Walter C. Oechel, Patty Oikawa, Paulo Olivas, Andrew P. Ouimette, Gilberto Pastorello, Jorge F. Pérez‐Quezada, Claire L. Phillips, Gabriela Posse, Bo Qu, William L. Quinton, Michele L. Reba, Andrew D. Richardson, Valentín Picasso, Adrian V. Rocha, Julio C. Rodríguez, Roel Ruzol, S. R. Saleska, Russell L. Scott, Adam P. Schreiner‐McGraw, Edward A. G. Schuur, Maria L. Silveira, Oliver Sonnentag, David L. Spittlehouse, Ralf M. Staebler, Gregory Starr, Christina L. Staudhammer, Christopher J. Still, Cove Sturtevant, Ryan C. Sullivan, Andy Suyker, David Trejo, Masahito Ueyama, Rodrigo Vargas, Brian Viner, Enrique R. Vivoni, Dong Wang, Eric J. Ward, Susanne Wiesner, Lisamarie Windham‐Myers, David Yannick, Enrico A. Yépez, Terenzio Zenone, Junbin Zhao, Donatella Zona · 发表于：Agricultural and Forest Meteorology · 年份：2025 · DOI：10.1016/j.agrformet.2025.110686 · 被引用次数：2 · 研究领域：Time Series Analysis and Forecasting、Plant Water Relations and Carbon Dynamics、Complex Systems and Time Series Analysis

• 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 < 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 flu...