Articles | Volume 21, issue 5
https://doi.org/10.5194/bg-21-1371-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-21-1371-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Comparison of carbon and water fluxes and the drivers of ecosystem water use efficiency in a temperate rainforest and a peatland in southern South America
Department of Environmental Sciences and Renewable Natural Resources, University of Chile, Santiago, Chile
Institute of Ecology and Biodiversity, Barrio Universitario Concepción, Chile
Cape Horn International Center, Punta Arenas, Chile
David Trejo
Department of Environmental Sciences and Renewable Natural Resources, University of Chile, Santiago, Chile
Institute of Ecology and Biodiversity, Barrio Universitario Concepción, Chile
Cape Horn International Center, Punta Arenas, Chile
Javier Lopatin
Faculty of Engineering and Science, Universidad Adolfo Ibáñez, Santiago, Chile
Centro de Ciencia del Clima y la Resiliencia, CR2, Santiago, Chile
Data Observatory Foundation, ANID Technology Center No. DO210001, Santiago, Chile
David Aguilera
Department of Environmental Sciences and Renewable Natural Resources, University of Chile, Santiago, Chile
Bruce Osborne
UCD School of Agriculture and Food Science, University College Dublin, Dublin 4, Ireland
UCD Earth Institute, University College Dublin, Dublin 4, Ireland
Mauricio Galleguillos
Department of Environmental Sciences and Renewable Natural Resources, University of Chile, Santiago, Chile
Faculty of Engineering and Science, Universidad Adolfo Ibáñez, Santiago, Chile
Centro de Ciencia del Clima y la Resiliencia, CR2, Santiago, Chile
Luca Zattera
Department of Environmental Sciences and Renewable Natural Resources, University of Chile, Santiago, Chile
Juan L. Celis-Diez
Institute of Ecology and Biodiversity, Barrio Universitario Concepción, Chile
Escuela de Agronomía, Pontificia Universidad Católica de Valparaíso, Quillota, Chile
Centro Regional de Investigación e Innovación para la Sostenibilidad de la Agricultura y los Territorios Rurales (CERES), Quillota, Chile
Juan J. Armesto
Institute of Ecology and Biodiversity, Barrio Universitario Concepción, Chile
Departamento de Ecología, Pontificia Universidad Católica de Chile, Santiago, Chile
deceased
Related authors
Frederic Thalasso, Julio A. Salas-Rabaza, Brenda Riquelme del Río, Jorge F. Perez-Quezada, Cristian Gajardo, and Matías Troncoso-Villar
EGUsphere, https://doi.org/10.5194/egusphere-2025-1357, https://doi.org/10.5194/egusphere-2025-1357, 2025
Short summary
Short summary
Peatlands are complex and widespread ecosystems that store large amounts of carbon through photosynthesis. Carbon fixation depends on solar irradiance, and the relationship between them is called the photosynthesis-irradiance or “PI” curve. We developed a simple, portable chamber to measure PI curves in peatlands, taking into account complex plant assemblages and microhabitat variability. This tool may help scientists better understand carbon dynamics in these ecosystems.
Daniel Nuñez-Ibarra, Mauricio Zambrano-Bigiarini, and Mauricio Galleguillos
EGUsphere, https://doi.org/10.5194/egusphere-2025-2606, https://doi.org/10.5194/egusphere-2025-2606, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Soil moisture plays a key role in how land and climate interact, yet it remains difficult to measure in remote or natural areas. This study compared four state-of-the-art soil moisture datasets against ground data from ten sites in Chile. Results show that some products perform better in humid areas, while others do better in dry regions. The work highlights which datasets are most reliable and suggests new ways to assess how well they track changes after rainfall events.
Frederic Thalasso, Julio A. Salas-Rabaza, Brenda Riquelme del Río, Jorge F. Perez-Quezada, Cristian Gajardo, and Matías Troncoso-Villar
EGUsphere, https://doi.org/10.5194/egusphere-2025-1357, https://doi.org/10.5194/egusphere-2025-1357, 2025
Short summary
Short summary
Peatlands are complex and widespread ecosystems that store large amounts of carbon through photosynthesis. Carbon fixation depends on solar irradiance, and the relationship between them is called the photosynthesis-irradiance or “PI” curve. We developed a simple, portable chamber to measure PI curves in peatlands, taking into account complex plant assemblages and microhabitat variability. This tool may help scientists better understand carbon dynamics in these ecosystems.
Anne F. Van Loon, Sarra Kchouk, Alessia Matanó, Faranak Tootoonchi, Camila Alvarez-Garreton, Khalid E. A. Hassaballah, Minchao Wu, Marthe L. K. Wens, Anastasiya Shyrokaya, Elena Ridolfi, Riccardo Biella, Viorica Nagavciuc, Marlies H. Barendrecht, Ana Bastos, Louise Cavalcante, Franciska T. de Vries, Margaret Garcia, Johanna Mård, Ileen N. Streefkerk, Claudia Teutschbein, Roshanak Tootoonchi, Ruben Weesie, Valentin Aich, Juan P. Boisier, Giuliano Di Baldassarre, Yiheng Du, Mauricio Galleguillos, René Garreaud, Monica Ionita, Sina Khatami, Johanna K. L. Koehler, Charles H. Luce, Shreedhar Maskey, Heidi D. Mendoza, Moses N. Mwangi, Ilias G. Pechlivanidis, Germano G. Ribeiro Neto, Tirthankar Roy, Robert Stefanski, Patricia Trambauer, Elizabeth A. Koebele, Giulia Vico, and Micha Werner
Nat. Hazards Earth Syst. Sci., 24, 3173–3205, https://doi.org/10.5194/nhess-24-3173-2024, https://doi.org/10.5194/nhess-24-3173-2024, 2024
Short summary
Short summary
Drought is a creeping phenomenon but is often still analysed and managed like an isolated event, without taking into account what happened before and after. Here, we review the literature and analyse five cases to discuss how droughts and their impacts develop over time. We find that the responses of hydrological, ecological, and social systems can be classified into four types and that the systems interact. We provide suggestions for further research and monitoring, modelling, and management.
Juan Pablo Boisier, Camila Alvarez-Garreton, Rodrigo Marinao, and Mauricio Galleguillos
EGUsphere, https://doi.org/10.5194/egusphere-2024-2695, https://doi.org/10.5194/egusphere-2024-2695, 2024
Short summary
Short summary
Our study examines water stress in Chile from mid-20th century to the end of the 21st century, using novel datasets on water availability, land use, and water use. We compute a water stress index for all basins in Chile and show that rising water use significantly contributes to water stress. We also show that a drier future is expected in central Chile and that the water stress index can be used as a tool for designing adaptation strategies.
Violeta Tolorza, Christian H. Mohr, Mauricio Zambrano-Bigiarini, Benjamín Sotomayor, Dagoberto Poblete-Caballero, Sebastien Carretier, Mauricio Galleguillos, and Oscar Seguel
Earth Surf. Dynam., 12, 841–861, https://doi.org/10.5194/esurf-12-841-2024, https://doi.org/10.5194/esurf-12-841-2024, 2024
Short summary
Short summary
We calculated disturbances and landscape-lowering rates across various timescales in a ~ 406 km2 catchment in the Chilean Coastal Range. Intensive management of exotic tree plantations involves short rotational cycles (planting and harvesting by replanting clear-cuts) lasting 9–25 years, dense forestry road networks (increasing connectivity), and a recent increase in wildfires. Concurrently, persistent drought conditions and the high water demand of fast-growing trees reduce water availability.
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Diego G. Miralles, Hylke E. Beck, Jonatan F. Siegmund, Camila Alvarez-Garreton, Koen Verbist, René Garreaud, Juan Pablo Boisier, and Mauricio Galleguillos
Hydrol. Earth Syst. Sci., 28, 1415–1439, https://doi.org/10.5194/hess-28-1415-2024, https://doi.org/10.5194/hess-28-1415-2024, 2024
Short summary
Short summary
Various drought indices exist, but there is no consensus on which index to use to assess streamflow droughts. This study addresses meteorological, soil moisture, and snow indices along with their temporal scales to assess streamflow drought across hydrologically diverse catchments. Using data from 100 Chilean catchments, findings suggest that there is not a single drought index that can be used for all catchments and that snow-influenced areas require drought indices with larger temporal scales.
Alejandro Miranda, Rayén Mentler, Ítalo Moletto-Lobos, Gabriela Alfaro, Leonardo Aliaga, Dana Balbontín, Maximiliano Barraza, Susanne Baumbach, Patricio Calderón, Fernando Cárdenas, Iván Castillo, Gonzalo Contreras, Felipe de la Barra, Mauricio Galleguillos, Mauro E. González, Carlos Hormazábal, Antonio Lara, Ian Mancilla, Francisca Muñoz, Cristian Oyarce, Francisca Pantoja, Rocío Ramírez, and Vicente Urrutia
Earth Syst. Sci. Data, 14, 3599–3613, https://doi.org/10.5194/essd-14-3599-2022, https://doi.org/10.5194/essd-14-3599-2022, 2022
Short summary
Short summary
Achieving a local understanding of fire regimes requires high-resolution, systematic and dynamic data. High-quality information can help to transform evidence into decision-making. Taking advantage of big-data and remote sensing technics we developed a flexible workflow to reconstruct burned area and fire severity data for more than 8000 individual fires in Chile. The framework developed for the database can be applied anywhere in the world with minimal adaptation.
Cited articles
Almazroui, M., Ashfaq, M., Islam, M. N., Rashid, I. U., Kamil, S., Abid, M. A., O’Brien, E., Ismail, M., Reboita, M. S., Sörensson, A. A., Arias, P. A., Alves, L. M., Tippett, M. K., Saeed, S., Haarsma, R., Doblas-Reyes, F. J., Saeed, F., Kucharski, F., Nadeem, I., Silva-Vidal, Y., Rivera, J. A., Ehsan, M. A., Martínez-Castro, D., Ángel G. Muñoz, Ali, M. A., Coppola, E., and Sylla, M. B.: Assessment of CMIP6 Performance and Projected Temperature and Precipitation Changes Over South America, Earth Syst. Environ., 5, 155–183, https://doi.org/10.1007/s41748-021-00233-6, 2021. a
Aurela, M., Laurila, T., and Tuovinen, J.: The timing of snow melt controls the annual CO2 balance in a subarctic fen, Geophys. Res. Lett., 31, L16119, https://doi.org/10.1029/2004GL020315, 2004. a
Bacon, M.: Water Use Efficiency in Plant Biology, Blackwell Publishing Ltd., ISBN 0-8493-2354-1, 2004. a
Balocchi, F., Galleguillos, M., Rivera, D., Stehr, A., Arumi, J. L., Pizarro, R., Garcia-Chevesich, P., Iroumé, A., Armesto, J. J., Hervé-Fernández, P., Oyarzún, C., Barría, P., Little, C., Mancilla, G., Yépez, S., Rodriguez, R., White, D. A., Silberstein, R. P., Neary, D. G., and de Arellano, P. R.: Forest hydrology in Chile: Past, present, and future, J. Hydrol., 616, 128681, https://doi.org/10.1016/j.jhydrol.2022.128681, 2023. a
Basagaña, X. and Barrera-Gómez, J.: Reflection on modern methods: visualizing the effects of collinearity in distributed lag models, Int. J. Epidemiol., 51, 334–344, 2022. a
Beck, H. E., Zimmermann, N. E., McVicar, T. R., Vergopolan, N., Berg, A., and Wood, E. F.: Present and future Köppen-Geiger climate classification maps at 1-km resolution, Sci. Data, 5, 180214, https://doi.org/10.1038/sdata.2018.214, 2018. a
Beer, C., Ciais, P., Reichstein, M., Baldocchi, D., Law, B. E., Papale, D., Soussana, J.-F., Ammann, C., Buchmann, N., Frank, D., Gianelle, D., Janssens, I. A., Knohl, A., Köstner, B., Moors, E., Roupsard, O., Verbeeck, H., Vesala, T., Williams, C. A., and Wohlfahrt, G.: Temporal and among-site variability of inherent water use efficiency at the ecosystem level, Global Biogeochem. Cy., 23, GB2018, https://doi.org/10.1029/2008GB003233, 2009. a, b, c, d, e, f
Boeck, H. J. D., Lemmens, C. M. H. M., Bossuyt, H., Malchair, S., Carnol, M., Merckx, R., Nijs, I., and Ceulemans, R.: How do climate warming and plant species richness affect water use in experimental grasslands?, Plant Soil, 288, 249–261, https://doi.org/10.1007/s11104-006-9112-5, 2006. a
Bréda, N., Huc, R., Granier, A., and Dreyer, E.: Temperate forest trees and stands under severe drought: a review of ecophysiological responses, adaptation processes and long-term consequences, Ann. Forest Sci., 63, 625–644, https://doi.org/10.1051/forest:2006042, 2006. a
Breiman, L.: Bagging predictors, Mach. Learn., 24, 123–140, 1996. a
Brümmer, C., Black, T. A., Jassal, R. S., Grant, N. J., Spittlehouse, D. L., Chen, B., Nesic, Z., Amiro, B. D., Arain, M. A., Barr, A. G., Bourque, C. P.-A., Coursolle, C., Dunn, A. L., Flanagan, L. B., Humphreys, E. R., Lafleur, P. M., Margolis, H. A., McCaughey, J. H., and Wofsy, S. C.: How climate and vegetation type influence evapotranspiration and water use efficiency in Canadian forest, peatland and grassland ecosystems, Agr. Forest Meteorol., 153, 14–30, https://doi.org/10.1016/j.agrformet.2011.04.008, 2012. a, b
Bustamante-Sánchez, M. A., Armesto, J. J., and Halpern, C. B.: Biotic and abiotic controls on tree colonization in three early successional communities of Chiloé Island, Chile, J. Ecol., 99, 288–299, https://doi.org/10.1111/j.1365-2745.2010.01737.x, 2011. a
Cabezas, J., Galleguillos, M., Valdés, A., Fuentes, J. P., Pérez, C., and Perez-Quezada, J. F.: Evaluation of impacts of management in an anthropogenic peatland using field and remote sensing data, Ecosphere, 6, 1–24, https://doi.org/10.1890/ES15-00232.1, 2015. a, b
Caretta, M., Mukherji, A., Arfanuzzaman, M., Betts, R., Gelfan, A., Hirabayashi, Y., Lissner, T., Liu, J., Gunn, E. L., Morgan, R., Mwanga, S., and Supratid, S.: Water, Cambridge University Press, https://doi.org/10.1017/9781009325844.006, 2023. a
Castellanos, E., Lemos, M., Astigarraga, L., Chacón, N., Cuvi, E., Huggel, C., Miranda, L., Vale, M. M., Ommeto, J., Peri, P., Postigo, J., Ramajo, L., Roco, L., and Rusticucci, M.: Central and South America, in: Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, https://doi.org/10.1017/9781009325844.014., 2022. a
Chapin, F. S., Matson, P. A., and Vitousek, P. M.: Principles of Terrestrial Ecosystem Ecology, Springer New York, 2nd Edn., ISBN 978-1-4419-9503-2, https://doi.org/10.1007/978-1-4419-9504-9, 2011. a
Centro de Información de Recursos Naturales (CIREN): Agrological Study in Los Lagos Region, Description of soils, Materials and symbols, CIREN, Vol. 123, ISBN: 956-7153-48-5, https://bibliotecadigital.ciren.cl/handle/20.500.13082/25572 (last access: 10 July 2023), 2003 (in Spanish). a
Cleveland, R. B., Cleveland, W. S., and Terpenning, I.: STL: A Seasonal-Trend Decomposition Procedure Based on Loess, J. Offic. Stat., 6, 3 pp., ISBN: 0282423X, 1990. a
Cui, J., Tian, L., Wei, Z., Huntingford, C., Wang, P., Cai, Z., Ma, N., and Wang, L.: Quantifying the Controls on Evapotranspiration Partitioning in the Highest Alpine Meadow Ecosystem, Water Resour. Res., 56, e2019WR024815, https://doi.org/10.1029/2019WR024815, 2020. a
Díaz, M. F., Bigelow, S., and Armesto, J. J.: Alteration of the hydrologic cycle due to forest clearing and its consequences for rainforest succession, Forest Ecol. Manag., 244, 32–40, https://doi.org/10.1016/j.foreco.2007.03.030, 2007. a
Ferner, J., Schmidtlein, S., Guuroh, R. T., Lopatin, J., and Linstädter, A.: Disentangling effects of climate and land-use change on West African drylands’ forage supply, Global Environ. Change, 53, 24–38, https://doi.org/10.1016/j.gloenvcha.2018.08.007, 2018. a
Ford, C. R., Hubbard, R. M., Kloeppel, B. D., and Vose, J. M.: A comparison of sap flux-based evapotranspiration estimates with catchment-scale water balance, Agr. Forest Meteorol., 145, 176–185, https://doi.org/10.1016/j.agrformet.2007.04.010, 2007. a
Frêne, C., Núñez-Ávila, M., Castro, B., and Armesto, J. J.: Seasonal Partitioning of Rainfall in Second-Growth Evergreen Temperate Rainforests in Chiloé Island, Southern Chile, Front. Forest. Glob. Change, 4, 781663, https://doi.org/10.3389/ffgc.2021.781663, 2022. a
Garreaud, R.: Record-breaking climate anomalies lead to severe drought and environmental disruption in Western Patagonia in 2016, Clim. Res., 74, 217–229, https://doi.org/10.3354/cr01505, 2018. a
Garreaud, R. D., Alvarez-Garreton, C., Barichivich, J., Boisier, J. P., Christie, D., Galleguillos, M., LeQuesne, C., McPhee, J., and Zambrano-Bigiarini, M.: The 2010–2015 megadrought in central Chile: impacts on regional hydroclimate and vegetation, Hydrol. Earth Syst. Sci., 21, 6307–6327, https://doi.org/10.5194/hess-21-6307-2017, 2017. a
Grace, J. B. and Bollen, K. A.: Interpreting the Results from Multiple Regression and Structural Equation Models, Bull. Ecol. Soc. Am., 86, 283–295, https://doi.org/10.1890/0012-9623(2005)86[283:itrfmr]2.0.co;2, 2005. a
Gutiérrez, A. G., Armesto, J. J., Díaz, M. F., and Huth, A.: Increased Drought Impacts on Temperate Rainforests from Southern South America: Results of a Process-Based, Dynamic Forest Model, PLoS ONE, 9, e103226, https://doi.org/10.1371/journal.pone.0103226, 2014. a, b
Hargreaves, G. H. and Samani, Z. A.: Estimating Potential Evapotranspiration, J. Irr. Drain. Div.-ASCE, 108, 225–230, https://doi.org/10.1061/JRCEA4.0001390, 1982. a
Hedin, L. O., Armesto, J. J., and Johnson, A. H.: Patterns of Nutrient Loss from Unpolluted, Old-Growth Temperate Forests: Evaluation of Biogeochemical Theory, Ecology, 76, 493–509, https://doi.org/10.2307/1941208, 1995. a
Huang, M., Piao, S., Sun, Y., Ciais, P., Cheng, L., Mao, J., Poulter, B., Shi, X., Zeng, Z., and Wang, Y.: Change in terrestrial ecosystem water‐use efficiency over the last three decades, Glob. Change Biol., 21, 2366–2378, https://doi.org/10.1111/gcb.12873, 2015. a
Humphreys, E. R., Lafleur, P. M., Flanagan, L. B., Hedstrom, N., Syed, K. H., Glenn, A. J., and Granger, R.: Summer carbon dioxide and water vapor fluxes across a range of northern peatlands, J. Geophys. Res.-Biogeo., 111, G04011, https://doi.org/10.1029/2005JG000111, 2006. a
Jasechko, S., Sharp, Z. D., Gibson, J. J., Birks, S. J., Yi, Y., and Fawcett, P. J.: Terrestrial water fluxes dominated by transpiration, Nature, 496, 347–350, https://doi.org/10.1038/nature11983, 2013. a
Keenan, T. F., Hollinger, D. Y., Bohrer, G., Dragoni, D., Munger, J. W., Schmid, H. P., and Richardson, A. D.: Increase in forest water-use efficiency as atmospheric carbon dioxide concentrations rise, Nature, 499, 324–327, https://doi.org/10.1038/nature12291, 2013. a, b
Kim, J. and Verma, S. B.: Surface exchange of water vapour between an open sphagnum fen and the atmosphere, Bound.-Lay. Meteorol., 79, 243–264, https://doi.org/10.1007/BF00119440, 1996. a, b
Kohavi, R.: A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection, in: Proceedings of the 14th International Joint Conference on Artificial Intelligence, Vol. 2, Montreal, Quebec, Canada, 1137–1143, 1995. a
Kozii, N., Haahti, K., Tor-ngern, P., Chi, J., Hasselquist, E. M., Laudon, H., Launiainen, S., Oren, R., Peichl, M., Wallerman, J., and Hasselquist, N. J.: Partitioning growing season water balance within a forested boreal catchment using sap flux, eddy covariance, and a process-based model, Hydrol. Earth Syst. Sci., 24, 2999–3014, https://doi.org/10.5194/hess-24-2999-2020, 2020. a
Kubota, S., Nishida, K., and Yoshida, S.: Correction to: Plant hydraulic resistance controls transpiration of soybean in rotational paddy fields under humid climates, Paddy Water Environ., 21, 415–415, https://doi.org/10.1007/s10333-023-00929-7, 2023. a
Lavergne, A., Graven, H., Kauwe, M. G. D., Keenan, T. F., Medlyn, B. E., and Prentice, I. C.: Observed and modelled historical trends in the water‐use efficiency of plants and ecosystems, Glo. Change Biol., 25, 2242–2257, https://doi.org/10.1111/gcb.14634, 2019. a, b
Liu, X., Chen, X., Li, R., Long, F., Lu, Zhang, Q., and Li, J.: Water-use efficiency of an old-growth forest in lower subtropical China, Sci. Rep., 7, 42761, https://doi.org/10.1038/srep42761, 2017. a, b
Liu, Z., Ji, X., Ye, L., and Jiang, J.: Inherent Water-Use Efficiency of Different Forest Ecosystems and Its Relations to Climatic Variables, Forests, 13, 775, https://doi.org/10.3390/f13050775, 2022. a, b
Lloyd, J., Shibistova, O., Zolotoukhine, D., Kolle, O., Arneth, A., Wirth, C., Styles, J. M., Tchebakova, N. M., and Schulze, E.-D.: Seasonal and annual variations in the photosynthetic productivity and carbon balance of a central Siberian pine forest, Tellus B, 54, 590–610, https://doi.org/10.3402/tellusb.v54i5.16689, 2002. a, b, c
Lopatin, J.: Interannual Variability of Remotely Sensed Phenology Relates to Plant Communities, IEEE Geosci. Remote Sens. Lett., 20, 1–5, https://doi.org/10.1109/LGRS.2023.3277364, 2023. a
Lopatin, J., Galleguillos, M., Fassnacht, F. E., Ceballos, A., and Hernandez, J.: Using a Multistructural Object-Based LiDAR Approach to Estimate Vascular Plant Richness in Mediterranean Forests With Complex Structure, IEEE Geosci. Remote Sens. Lett., 12, 1008–1012, https://doi.org/10.1109/LGRS.2014.2372875, 2015. a
Lopatin, J., Kattenborn, T., Galleguillos, M., Perez-Quezada, J. F., and Schmidtlein, S.: Using aboveground vegetation attributes as proxies for mapping peatland belowground carbon stocks, Remote Sens. Environ., 231, 111217, https://doi.org/10.1016/j.rse.2019.111217, 2019. a, b
Lopatin, J., Araya‐López, R., Galleguillos, M., and Perez‐Quezada, J. F.: Disturbance alters relationships between soil carbon pools and aboveground vegetation attributes in an anthropogenic peatland in Patagonia, Ecol. Evol., 12, e8694, https://doi.org/10.1002/ece3.8694, 2022. a
Masri, B. E., Schwalm, C., Huntzinger, D. N., Mao, J., Shi, X., Peng, C., Fisher, J. B., Jain, A. K., Tian, H., Poulter, B., and Michalak, A. M.: Carbon and Water Use Efficiencies: A Comparative Analysis of Ten Terrestrial Ecosystem Models under Changing Climate, Sci. Rep., 9, 14680, https://doi.org/10.1038/s41598-019-50808-7, 2019. a
Mauder, M. and Foken, T.: Documentation and instruction manual of the eddy covariance software package TK2, edited by: Foken, T., Universität Bayreuth, Abt. Mikrometeorologie, Bayreuth, ISSN: 1614-8924, 2004. a
Mauder, M. and Foken, T.: Impact of post-field data processing on eddy covariance flux estimates and energy balance closure, Meteorol. Z., 15, 597–609, https://doi.org/10.1127/0941-2948/2006/0167, 2006. a
Mauder, M., Cuntz, M., Drüe, C., Graf, A., Rebmann, C., Schmid, H. P., Schmidt, M., and Steinbrecher, R.: A strategy for quality and uncertainty assessment of long-term eddy-covariance measurements, Agr. Forest Meteorol., 169, 122–135, https://doi.org/10.1016/j.agrformet.2012.09.006, 2013. a, b
Meinzer, F. C., Goldstein, G., Jackson, P., Holbrook, N. M., Gutiérrez, M. V., and Cavelier, J.: Environmental and physiological regulation of transpiration in tropical forest gap species: the influence of boundary layer and hydraulic properties, Oecologia, 101, 514–522, https://doi.org/10.1007/BF00329432, 1995. a, b
Melo, D. C. D., Anache, J. A. A., Borges, V. P., Miralles, D. G., Martens, B., Fisher, J. B., Nóbrega, R. L. B., Moreno, A., Cabral, O. M. R., Rodrigues, T. R., Bezerra, B., Silva, C. M. S., Neto, A. A. M., Moura, M. S. B., Marques, T. V., Campos, S., Nogueira, J. S., Rosolem, R., Souza, R. M. S., Antonino, A. C. D., Holl, D., Galleguillos, M., Perez‐Quezada, J. F., Verhoef, A., Kutzbach, L., Lima, J. R. S., Souza, E. S., Gassman, M. I., Perez, C. F., Tonti, N., Posse, G., Rains, D., Oliveira, P. T. S., and Wendland, E.: Are Remote Sensing Evapotranspiration Models Reliable Across South American Ecoregions?, Water Resour. Res., 57, e2020WR028752, https://doi.org/10.1029/2020WR028752, 2021. a
Monteith, J. and Unsworth, M.: Principles of Environmental Physics, Butterworth Heinemann, Butterworth-Heinemann, Oxford, 2nd Edn., ISBN 071312931X, 1990. a
Murray, F. W.: On the Computation of Saturation Vapor Pressure, J. Appl. Meteorol., 6, 203–204, https://doi.org/10.1175/1520-0450(1967)006<0203:OTCOSV>2.0.CO;2, 1967. a
Negret, B. S., Pérez, F., Markesteijn, L., Castillo, M. J., and Armesto, J. J.: Diverging drought-tolerance strategies explain tree species distribution along a fog-dependent moisture gradient in a temperate rain forest, Oecologia, 173, 625–635, https://doi.org/10.1007/s00442-013-2650-7, 2013. a
Nelson, J. A., Carvalhais, N., Cuntz, M., Delpierre, N., Knauer, J., Ogée, J., Migliavacca, M., Reichstein, M., and Jung, M.: Coupling Water and Carbon Fluxes to Constrain Estimates of Transpiration: The TEA Algorithm, J. Geophys. Res.-Biogeo., 123, 3617–3632, https://doi.org/10.1029/2018JG004727, 2018. a
Nelson, J. A., Pérez‐Priego, O., Zhou, S., Poyatos, R., Zhang, Y., Blanken, P. D., Gimeno, T. E., Wohlfahrt, G., Desai, A. R., Gioli, B., Limousin, J., Bonal, D., Paul‐Limoges, E., Scott, R. L., Varlagin, A., Fuchs, K., Montagnani, L., Wolf, S., Delpierre, N., Berveiller, D., Gharun, M., Marchesini, L. B., Gianelle, D., Šigut, L., Mammarella, I., Siebicke, L., Black, T. A., Knohl, A., Hörtnagl, L., Magliulo, V., Besnard, S., Weber, U., Carvalhais, N., Migliavacca, M., Reichstein, M., and Jung, M.: Ecosystem transpiration and evaporation: Insights from three water flux partitioning methods across FLUXNET sites, Glob. Change Biol., 26, 6916–6930, https://doi.org/10.1111/gcb.15314, 2020. a
Pastorello, G., Trotta, C., Canfora, E., et al.: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data, Sci. Data, 7, 225, https://doi.org/10.1038/s41597-020-0534-3, 2020. a
Paul-Limoges, E., Wolf, S., Schneider, F. D., Longo, M., Moorcroft, P., Gharun, M., and Damm, A.: Partitioning evapotranspiration with concurrent eddy covariance measurements in a mixed forest, Agr. Forest Meteorol., 280, 107786, https://doi.org/10.1016/j.agrformet.2019.107786, 2020. a
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Édouard Duchesnay: Scikit-learn: Machine Learning in Python, J. Mach. Learn. Res., 12, 2825–2830, 2011. a
Perez-Quezada, J. and Armesto, J. J.: AmeriFlux BASE CL-SDF Senda Darwin Forest, Ver. 1–5, AmeriFlux AMP [data set], https://doi.org/10.17190/AMF/1902273, 2022a. a
Perez-Quezada, J. and Armesto, J. J.: AmeriFlux BASE CL-SDP Senda Darwin Peatland, Ver. 1-5, AmeriFlux AMP [data set], https://doi.org/10.17190/AMF/1902274, 2022b. a
Perez-Quezada, J. F., Pérez, C. A., Brito, C. E., Fuentes, J. P., Gaxiola, A., Aguilera-Riquelme, D., and Lopatin, J.: Biotic and abiotic drivers of carbon, nitrogen and phosphorus stocks in a temperate rainforest, Forest Ecol. Manag., 494, 119341, https://doi.org/10.1016/j.foreco.2021.119341, 2021a. a, b, c, d
Perez-Quezada, J. F., Urrutia, P., Olivares-Rojas, J., Meijide, A., Sánchez-Cañete, E. P., and Gaxiola, A.: Long term effects of fire on the soil greenhouse gas balance of an old-growth temperate rainforest, Sci. Total Environ., 755, 142442, https://doi.org/10.1016/j.scitotenv.2020.142442, 2021b. a
Perez‐Quezada, J. F., Celis‐Diez, J. L., Brito, C. E., Gaxiola, A., Nuñez‐Avila, M., Pugnaire, F. I., and Armesto, J. J.: Carbon fluxes from a temperate rainforest site in southern South America reveal a very sensitive sink, Ecosphere, 9, e02193, https://doi.org/10.1002/ecs2.2193, 2018. a, b
Perez‐Quezada, J. F., Barichivich, J., Urrutia‐Jalabert, R., Carrasco, E., Aguilera, D., Bacour, C., and Lara, A.: Warming and Drought Weaken the Carbon Sink Capacity of an Endangered Paleoendemic Temperate Rainforest in South America, J. Geophys. Res.-Biogeo., 128, e2022JG007258, https://doi.org/10.1029/2022JG007258, 2023. a, b
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grunwald, T., Havrankova, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J.-M., Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G., Vaccari, F., Vesala, T., Yakir, D., and Valentini, R.: On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm, Glob. Change Biol., 11, 1424–1439, https://doi.org/10.1111/j.1365-2486.2005.001002.x, 2005. a, b
Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., and Gudergan, S. P.: Estimation issues with PLS and CBSEM: Where the bias lies!, J. Bus. Res., 69, 3998–4010, https://doi.org/10.1016/j.jbusres.2016.06.007, 2016. a
Saurer, M., Siegwolf, R. T. W., and Schweingruber, F. H.: Carbon isotope discrimination indicates improving water-use efficiency of trees in northern Eurasia over the last 100 years, Glob. Change Biol., 10, 2109–2120, https://doi.org/10.1111/j.1365-2486.2004.00869.x, 2004. a
Schymanski, S. J. and Or, D.: Wind increases leaf water use efficiency, Plant Cell Environ., 39, 1448–1459, https://doi.org/10.1111/pce.12700, 2016. a
Shimizu, T., Kumagai, T., Kobayashi, M., Tamai, K., Iida, S., Kabeya, N., Ikawa, R., Tateishi, M., Miyazawa, Y., and Shimizu, A.: Estimation of annual forest evapotranspiration from a coniferous plantation watershed in Japan (2): Comparison of eddy covariance, water budget and sap-flow plus interception loss, J. Hydrol., 522, 250–264, https://doi.org/10.1016/j.jhydrol.2014.12.021, 2015. a
Soubie, R., Heinesch, B., Granier, A., Aubinet, M., and Vincke, C.: Evapotranspiration assessment of a mixed temperate forest by four methods: Eddy covariance, soil water budget, analytical and model, Agr. Forest Meteorol., 228-229, 191–204, https://doi.org/10.1016/j.agrformet.2016.07.001, 2016. a
Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M., and Lauro, C.: PLS path modeling, Comput. Stat. Data Anal., 48, 159–205, https://doi.org/10.1016/j.csda.2004.03.005, 2005. a
Terán, C. P., Naz, B. S., Graf, A., Qu, Y., Franssen, H.-J. H., Baatz, R., Ciais, P., and Vereecken, H.: Rising water-use efficiency in European grasslands is driven by increased primary production, Commun. Earth Environ., 4, 95, https://doi.org/10.1038/s43247-023-00757-x, 2023. a, b
Unsworth, M., Phillips, N., Link, T., Bond, B., Falk, M., Harmon, M., Hinckley, T., Marks, D., and U, K. P.: Components and Controls of Water Flux in an Old-growth Douglas-fir? Western Hemlock Ecosystem, Ecosystems, 7, 468–481, https://doi.org/10.1007/s10021-004-0138-3, 2004. a
Valdés-Barrera, A., Kutzbach, L., Celis-Diez, J. L., Armesto, J. J., Holl, D., and Perez-Quezada, J. F.: Effects of disturbance on the carbon dioxide balance of an anthropogenic peatland in northern Patagonia, Wetland. Ecol. Manag., 27, 635–650, https://doi.org/10.1007/s11273-019-09682-3, 2019. a, b
Yi, K., Maxwell, J. T., Wenzel, M. K., Roman, D. T., Sauer, P. E., Phillips, R. P., and Novick, K. A.: Linking variation in intrinsic water‐use efficiency to isohydricity: a comparison at multiple spatiotemporal scales, New Phytol., 221, 195–208, https://doi.org/10.1111/nph.15384, 2019. a
Zhang, Q., Ficklin, D. L., Manzoni, S., Wang, L., Way, D., Phillips, R. P., and Novick, K. A.: Response of ecosystem intrinsic water use efficiency and gross primary productivity to rising vapor pressure deficit, Environ. Res. Lett., 14, 074023, https://doi.org/10.1088/1748-9326/ab2603, 2019. a
Zhang, W., Jung, M., Migliavacca, M., Poyatos, R., Miralles, D. G., El-Madany, T. S., Galvagno, M., Carrara, A., Arriga, N., Ibrom, A., Mammarella, I., Papale, D., Cleverly, J. R., Liddell, M., Wohlfahrt, G., Markwitz, C., Mauder, M., Paul-Limoges, E., Schmidt, M., Wolf, S., Brümmer, C., Arain, M. A., Fares, S., Kato, T., Ardö, J., Oechel, W., Hanson, C., Korkiakoski, M., Biraud, S., Steinbrecher, R., Billesbach, D., Montagnani, L., Woodgate, W., Shao, C., Carvalhais, N., Reichstein, M., and Nelson, J. A.: The effect of relative humidity on eddy covariance latent heat flux measurements and its implication for partitioning into transpiration and evaporation, Agr. Forest Meteorol., 330, 109305, https://doi.org/10.1016/j.agrformet.2022.109305, 2023a. a, b
Zhang, Z., Zhang, L., Xu, H., Creed, I. F., Blanco, J. A., Wei, X., Sun, G., Asbjornsen, H., and Bishop, K.: Forest water-use efficiency: Effects of climate change and management on the coupling of carbon and water processes, Forest Ecol. Manag., 534, 120853, https://doi.org/10.1016/j.foreco.2023.120853, 2023b. a
Zhu, S., Clement, R., McCalmont, J., Davies, C. A., and Hill, T.: Stable gap-filling for longer eddy covariance data gaps: A globally validated machine-learning approach for carbon dioxide, water, and energy fluxes, Agr. Forest Meteorol., 314, 108777, https://doi.org/10.1016/j.agrformet.2021.108777, 2022. a
Short summary
For 8 years we sampled a temperate rainforest and a peatland in Chile to estimate their efficiency to capture carbon per unit of water lost. The efficiency is more related to the water lost than to the carbon captured and is mainly driven by evaporation instead of transpiration. This is the first report from southern South America and highlights that ecosystems might behave differently in this area, likely explained by the high annual precipitation (~ 2100 mm) and light-limited conditions.
For 8 years we sampled a temperate rainforest and a peatland in Chile to estimate their...
Altmetrics
Final-revised paper
Preprint