Network of networks: Time series clustering of ameriflux sites
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...
| Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2025
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| Acceso en línea: | http://hdl.handle.net/20.500.12123/23028 https://www.sciencedirect.com/science/article/pii/S0168192325003065 https://doi.org/10.1016/j.agrformet.2025.110686 |
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| author | Reed, David E. Chu, Housen Peter, Brad G. Chen, Jiquan Abraha, Michael Amiro, Brian Anderson, Ray G. Arain, M. Altaf Arruda, Paulo Barron-Gafford, Greg A. Bernacchi, Carl Beverly, Daniel P. Biraud, Sebastien C. Black, T. Andrew Blanken, Peter D. Bohrer, Gil Bowler, Rebecca Bowling, David R. Forsythe, Brandon R. Posse Beaulieu, Gabriela Zona, Donatella |
| author_browse | Abraha, Michael Amiro, Brian Anderson, Ray G. Arain, M. Altaf Arruda, Paulo Barron-Gafford, Greg A. Bernacchi, Carl Beverly, Daniel P. Biraud, Sebastien C. Black, T. Andrew Blanken, Peter D. Bohrer, Gil Bowler, Rebecca Bowling, David R. Chen, Jiquan Chu, Housen Forsythe, Brandon R. Peter, Brad G. Posse Beaulieu, Gabriela Reed, David E. Zona, Donatella |
| author_facet | Reed, David E. Chu, Housen Peter, Brad G. Chen, Jiquan Abraha, Michael Amiro, Brian Anderson, Ray G. Arain, M. Altaf Arruda, Paulo Barron-Gafford, Greg A. Bernacchi, Carl Beverly, Daniel P. Biraud, Sebastien C. Black, T. Andrew Blanken, Peter D. Bohrer, Gil Bowler, Rebecca Bowling, David R. Forsythe, Brandon R. Posse Beaulieu, Gabriela Zona, Donatella |
| author_sort | Reed, David E. |
| collection | INTA Digital |
| description | 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 clus tering 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 hy drological 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 undersampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups. |
| format | Artículo |
| id | INTA23028 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | INTA230282025-07-16T10:58:32Z Network of networks: Time series clustering of ameriflux sites Reed, David E. Chu, Housen Peter, Brad G. Chen, Jiquan Abraha, Michael Amiro, Brian Anderson, Ray G. Arain, M. Altaf Arruda, Paulo Barron-Gafford, Greg A. Bernacchi, Carl Beverly, Daniel P. Biraud, Sebastien C. Black, T. Andrew Blanken, Peter D. Bohrer, Gil Bowler, Rebecca Bowling, David R. Forsythe, Brandon R. Posse Beaulieu, Gabriela Zona, Donatella Medio Ambiente Redes Environment Networks Ameriflux Network Red Ameriflux Singularidad del Sitio Agrupación de Sitios Site Uniqueness Site Clustering 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 clus tering 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 hy drological 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 undersampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups. Instituto de Clima y Agua Fil: Reed, David E. Yale University. Yale School of the Environment; Estados Unidos. University of Science and Arts of Oklahoma. Division of Science & Physical Education; Estados Unidos. Michigan State University. Department of Geography, Environment & Spatial Sciences; Estados Unidos Fil: Chun, Housen. Climate and Ecosystem Sciences Division. Lawrence Berkeley National Lab; Estados Unidos Fil: Peter, Brad G. University of Arkansas. Department of Geosciences; Estados Unidos Fil: Chen, Jiquan. Michigan State University. Department of Geography, Environment & Spatial Sciences; Estados Unidos. Michigan State University. Center for Global Change and Earth Observations; Estados Unidos Fil: Abraha, Michael. Michigan State University. Center for Global Change and Earth Observations; Estados Unidos. Fil: Amiro, Brian. University of Manitoba. Department of Soil Science; Canadá Fil: Anderson, Ray G.USDA-Agricultural Research Service. US Salinity Laboratory. Agricultural Water Efficiency and Salinity Research Unit; Estados Unidos Fil: Arain, M. Altaf. McMaster University. School of Earth, Environment and Society; Canadá Fil: Arruda, Paulo. Universidade Federal de Mato Grosso. Programa de Pos-Graduaçao em Física Ambiental; Brasil Fil: Barron - Gafford, Greg A. University of Arizona. School of Geography, Development, & Environment; Estados Unidos Fil: Bernacchi, Carl. USDA Agricultural Research Service. Global Change and Photosynthesis Research Unit; Estados Unidos Fil: Beverly, Daniel P. University of Indiana. Paul O’Neill School of Public and Environmental Affairs; Estados Unidos Fil: Biraud, Sebastien C. Climate and Ecosystem Sciences Division. Lawrence Berkeley National Lab; Estados Unidos Fil: Black, T. Andrew. University of British Columbia. Faculty of Land and Food Systems; Canadá Fil: Blanken, Peter D. Univesity of Colorado. Department of Geography; Estados Unidos Fil: Bohrer, Gil. The Ohio State University. Department of Civil, Environmental & Geodetic Engineering; Estados Unidos Fil: Bowler, Rebecca. British Columbia Ministry of Forests; Canadá Fil: Bowling, David R. The University of Utah. School of Biological Sciences; Estados Unidos Fil: Forsythe, Brandon R. Yale University. Yale School of the Environment; Estados Unidos. University of Arkansas. Department of Geosciences; Estados Unidos Fil: Posse Beaulieu, Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina Fil: Zona, Donatella. San Diego State University. Department of Biology; Estados Unidos 2025-07-16T10:23:45Z 2025-07-16T10:23:45Z 2025-06-05 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/23028 https://www.sciencedirect.com/science/article/pii/S0168192325003065 0168-1923 https://doi.org/10.1016/j.agrformet.2025.110686 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Elsevier Agricultural and Forest Meteorology : 110686 (September 2025) |
| spellingShingle | Medio Ambiente Redes Environment Networks Ameriflux Network Red Ameriflux Singularidad del Sitio Agrupación de Sitios Site Uniqueness Site Clustering Reed, David E. Chu, Housen Peter, Brad G. Chen, Jiquan Abraha, Michael Amiro, Brian Anderson, Ray G. Arain, M. Altaf Arruda, Paulo Barron-Gafford, Greg A. Bernacchi, Carl Beverly, Daniel P. Biraud, Sebastien C. Black, T. Andrew Blanken, Peter D. Bohrer, Gil Bowler, Rebecca Bowling, David R. Forsythe, Brandon R. Posse Beaulieu, Gabriela Zona, Donatella Network of networks: Time series clustering of ameriflux sites |
| title | Network of networks: Time series clustering of ameriflux sites |
| title_full | Network of networks: Time series clustering of ameriflux sites |
| title_fullStr | Network of networks: Time series clustering of ameriflux sites |
| title_full_unstemmed | Network of networks: Time series clustering of ameriflux sites |
| title_short | Network of networks: Time series clustering of ameriflux sites |
| title_sort | network of networks time series clustering of ameriflux sites |
| topic | Medio Ambiente Redes Environment Networks Ameriflux Network Red Ameriflux Singularidad del Sitio Agrupación de Sitios Site Uniqueness Site Clustering |
| url | http://hdl.handle.net/20.500.12123/23028 https://www.sciencedirect.com/science/article/pii/S0168192325003065 https://doi.org/10.1016/j.agrformet.2025.110686 |
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