Title: Global transpiration data from sap flow measurements: the SAPFLUXNET database
Abstract. Plant transpiration links physiological responses ofvegetation to water supply and demand with hydrological, energy, and carbonbudgets at the land–atmosphere interface. However, despite being the mainland evaporative flux at the global scale, transpiration and its response toenvironmental drivers are currently not well constrained by observations.Here we introduce the first global compilation of whole-plant transpirationdata from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021).We harmonized and quality-controlled individual datasets supplied bycontributors worldwide in a semi-automatic data workflow implemented in theR programming language. Datasets include sub-daily time series of sap flowand hydrometeorological drivers for one or more growing seasons, as well asmetadata on the stand characteristics, plant attributes, and technicaldetails of the measurements. SAPFLUXNET contains 202 globally distributeddatasets with sap flow time series for 2714 plants, mostly trees, of 174species. SAPFLUXNET has a broad bioclimatic coverage, withwoodland/shrubland and temperate forest biomes especially well represented(80 % of the datasets). The measurements cover a wide variety of standstructural characteristics and plant sizes. The datasets encompass theperiod between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data areavailable for most of the datasets, while on-site soil water content isavailable for 56 % of the datasets. Many datasets contain data for speciesthat make up 90 % or more of the total stand basal area, allowing theestimation of stand transpiration in diverse ecological settings. SAPFLUXNETadds to existing plant trait datasets, ecosystem flux networks, and remotesensing products to help increase our understanding of plant water use,plant responses to drought, and ecohydrological processes. SAPFLUXNET version0.1.5 is freely available from the Zenodo repository (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The“sapfluxnetr” R package – designed to access, visualize, and processSAPFLUXNET data – is available from CRAN. more »« less
Van Wyk de Vries, Maximillian; Wickert, Andrew D.(
, The Cryosphere)
null
(Ed.)
Abstract. We present Glacier Image Velocimetry (GIV), an open-source and easy-to-use software toolkit for rapidly calculating high-spatial-resolutionglacier velocity fields. Glacier ice velocity fields reveal flow dynamics, ice-flux changes, and (with additional data and modelling) icethickness. Obtaining glacier velocity measurements over wide areas with field techniques is labour intensive and often associated with safetyrisks. The recent increased availability of high-resolution, short-repeat-time optical imagery allows us to obtain ice displacement fields using“feature tracking” based on matching persistent irregularities on the ice surface between images and hence, surface velocity over time. GIV isfully parallelized and automatically detects, filters, and extracts velocities from large datasets of images. Through this coupled toolchain and aneasy-to-use GUI, GIV can rapidly analyse hundreds to thousands of image pairs on a laptop or desktop computer. We present four example applicationsof the GIV toolkit in which we complement a glaciology field campaign (Glaciar Perito Moreno, Argentina) and calculate the velocity fields of smallmid-latitude (Glacier d'Argentière, France) and tropical glaciers (Volcán Chimborazo, Ecuador), as well as very large glaciers (Vavilov Ice Cap,Russia). Fully commented MATLAB code and a stand-alone app for GIV are available from GitHub and Zenodo (see https://doi.org/10.5281/zenodo.4624831, Van Wyk de Vries, 2021a).
Delwiche, Kyle B.; Knox, Sara Helen; Malhotra, Avni; Fluet-Chouinard, Etienne; McNicol, Gavin; Feron, Sarah; Ouyang, Zutao; Papale, Dario; Trotta, Carlo; Canfora, Eleonora; et al(
, Earth System Science Data)
null
(Ed.)
Abstract. Methane (CH4) emissions from natural landscapes constituteroughly half of global CH4 contributions to the atmosphere, yet largeuncertainties remain in the absolute magnitude and the seasonality ofemission quantities and drivers. Eddy covariance (EC) measurements ofCH4 flux are ideal for constraining ecosystem-scale CH4emissions due to quasi-continuous and high-temporal-resolution CH4flux measurements, coincident carbon dioxide, water, and energy fluxmeasurements, lack of ecosystem disturbance, and increased availability ofdatasets over the last decade. Here, we (1) describe the newly publisheddataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset ofCH4 EC measurements (available athttps://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4includes half-hourly and daily gap-filled and non-gap-filled aggregatedCH4 fluxes and meteorological data from 79 sites globally: 42freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drainedecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverageglobally because the majority of sites in FLUXNET-CH4 Version 1.0 arefreshwater wetlands which are a substantial source of total atmosphericCH4 emissions; and (3) we provide the first global estimates of theseasonal variability and seasonality predictors of freshwater wetlandCH4 fluxes. Our representativeness analysis suggests that thefreshwater wetland sites in the dataset cover global wetland bioclimaticattributes (encompassing energy, moisture, and vegetation-relatedparameters) in arctic, boreal, and temperate regions but only sparselycover humid tropical regions. Seasonality metrics of wetland CH4emissions vary considerably across latitudinal bands. In freshwater wetlands(except those between 20∘ S to 20∘ N) the spring onsetof elevated CH4 emissions starts 3 d earlier, and the CH4emission season lasts 4 d longer, for each degree Celsius increase in meanannual air temperature. On average, the spring onset of increasing CH4emissions lags behind soil warming by 1 month, with very few sites experiencingincreased CH4 emissions prior to the onset of soil warming. Incontrast, roughly half of these sites experience the spring onset of risingCH4 emissions prior to the spring increase in gross primaryproductivity (GPP). The timing of peak summer CH4 emissions does notcorrelate with the timing for either peak summer temperature or peak GPP.Our results provide seasonality parameters for CH4 modeling andhighlight seasonality metrics that cannot be predicted by temperature or GPP(i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resourcefor diagnosing and understanding the role of terrestrial ecosystems andclimate drivers in the global CH4 cycle, and future additions of sitesin tropical ecosystems and site years of data collection will provide addedvalue to this database. All seasonality parameters are available athttps://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021).Additionally, raw FLUXNET-CH4 data used to extract seasonality parameterscan be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a completelist of the 79 individual site data DOIs is provided in Table 2 of this paper.
Beslity, Justin; Shaw, Stephen B.; Pfautsch, ed., Sebastian(
, Tree Physiology)
Abstract
The accurate estimation of plant transpiration is critical to the fields of hydrology, plant physiology and ecology. Among the various methods of measuring transpiration in the field, the sap flow methods based on head pulses offers a cost-effective and energy-efficient option to directly measure the plant-level movement of water through the hydraulically active tissue. While authors have identified several possible sources of error in these measurements, one of the most common sources is misalignment of the sap flow probes due to user error. Though the effects of probe misalignment are well documented, no device or technique has been universally adopted to ensure the proper installation of sap flow probes. In this paper we compare the magnitude of misalignment errors among a 5 mm thick drilling template (DT), a 10 mm thick DT, and a custom designed, field-portable drill press. The different techniques were evaluated in the laboratory using a 7.5 cm wood block and in the field, comparing differences in measured sap flow. Based on analysis of holes drilled in the wood block, we found that the portable drill press was most effective in assuring that drill holes remained parallel, even at 7.5 cm depth. In field installations, nearly 50% of holes drilled with a 5 mm template needed to be redrilled while none needed to be when drilled with the drill press. Widespread use of a portable drill press when implementing the heat pulse method would minimize alignment uncertainty and allow a clearer understanding of other sources of uncertainty due to variability in tree species, age, or external drivers or transpiration.
Kropp, Heather; Loranty, Michael M.; Natali, Susan M.; Kholodov, Alexander L.; Alexander, Heather D.; Zimov, Nikita S.; Mack, Michelle C.; Spawn, Seth A.(
, Ecohydrology)
Abstract
Transpiration and stomatal conductance in deciduous needleleaf boreal forests of northern Siberia can be highly sensitive to water stress, permafrost thaw, and atmospheric dryness. Additionally, north‐eastern Siberian boreal forests are fire‐driven, and larch (Larixspp.) are the sole tree species. We examined differences in tree water use, stand characteristics, and stomatal responses to environmental drivers between high and low tree density stands that burned 76 years ago in north‐eastern Siberia. Our results provide process‐level insight to climate feedbacks related to boreal forest productivity, water cycles, and permafrost across Arctic regions. The high density stand had shallower permafrost thaw depths and deeper moss layers than the low density stand. Rooting depths and shallow root biomass were similar between stands. Daily transpiration was higher on average in the high‐density stand 0.12 L m−2 day−1(SE: 0.004) compared with the low density stand 0.10 L m−2 day−1(SE: 0.001) throughout the abnormally wet summer of 2016. Transpiration rates tended to be similar at both stands during the dry period in 2017 in both stands of 0.10 L m−2 day−1(SE: 0.002). The timing of precipitation impacted stomatal responses to environmental drivers, and the high density stand was more dependent on antecedent precipitation that occurred over longer periods in the past compared with the low density stand. Post‐fire tree density differences in plant–water relations may lead to different trajectories in plant mortality, water stress, and ecosystem water cycles across Siberian landscapes.
Quetin, Gregory R.; Anderegg, Leander D. L.; Konings, Alexandra G.; Trugman, Anna T.(
, Journal of Geophysical Research: Biogeosciences)
Abstract
Terrestrial photosynthesis requires the evaporation of water (transpiration) in exchange for CO2needed to form sugars. The water for transpiration is drawn up through plant roots, stem, and branches via a water potential gradient. However, this flow of water—or sap ascent—requires energy to lift the water to the canopy and to overcome the resistance of the plant’s water transporting xylem. Here, we use a combination of field measurements of plant physiology (hydraulic conductivity) and state‐of‐the‐science global estimates of transpiration to calculate how much energy is passively harvested by plants to power the sap ascent pump across the world’s terrestrial vegetation. Globally, we find that 0.06 W/m2is consumed in sap ascent over forest dominated ecosystems or 9.4 PWh/yr (equal to global hydropower energy production). Though small in comparison to other components of the Earth’s surface energy budget, sap ascent work in forests represents 14.2% of the energy compared to the energy consumed to create sugars through photosynthesis, with values up to 18% in temperate rainforests. The power needed for sap ascent generally increases with photosynthesis, but is moderated by both climate and plant physiology, as the most work is consumed in regions with large transpiration fluxes (such as the moist tropics) and in areas where vegetation has low conductivity (such as temperate rainforests dominated by conifer trees). Here, we present a bottom‐up analysis of sap ascent work that demonstrates its significant role in plant function across the globe.
@article{osti_10313986,
place = {Country unknown/Code not available},
title = {Global transpiration data from sap flow measurements: the SAPFLUXNET database},
url = {https://par.nsf.gov/biblio/10313986},
DOI = {10.5194/essd-13-2607-2021},
abstractNote = {Abstract. Plant transpiration links physiological responses ofvegetation to water supply and demand with hydrological, energy, and carbonbudgets at the land–atmosphere interface. However, despite being the mainland evaporative flux at the global scale, transpiration and its response toenvironmental drivers are currently not well constrained by observations.Here we introduce the first global compilation of whole-plant transpirationdata from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021).We harmonized and quality-controlled individual datasets supplied bycontributors worldwide in a semi-automatic data workflow implemented in theR programming language. Datasets include sub-daily time series of sap flowand hydrometeorological drivers for one or more growing seasons, as well asmetadata on the stand characteristics, plant attributes, and technicaldetails of the measurements. SAPFLUXNET contains 202 globally distributeddatasets with sap flow time series for 2714 plants, mostly trees, of 174species. SAPFLUXNET has a broad bioclimatic coverage, withwoodland/shrubland and temperate forest biomes especially well represented(80 % of the datasets). The measurements cover a wide variety of standstructural characteristics and plant sizes. The datasets encompass theperiod between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data areavailable for most of the datasets, while on-site soil water content isavailable for 56 % of the datasets. Many datasets contain data for speciesthat make up 90 % or more of the total stand basal area, allowing theestimation of stand transpiration in diverse ecological settings. SAPFLUXNETadds to existing plant trait datasets, ecosystem flux networks, and remotesensing products to help increase our understanding of plant water use,plant responses to drought, and ecohydrological processes. SAPFLUXNET version0.1.5 is freely available from the Zenodo repository (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The“sapfluxnetr” R package – designed to access, visualize, and processSAPFLUXNET data – is available from CRAN.},
journal = {Earth System Science Data},
volume = {13},
number = {6},
author = {Poyatos, Rafael and Granda, Víctor and Flo, Víctor and Adams, Mark A. and Adorján, Balázs and Aguadé, David and Aidar, Marcos P. and Allen, Scott and Alvarado-Barrientos, M. Susana and Anderson-Teixeira, Kristina J. and Aparecido, Luiza Maria and Arain, M. Altaf and Aranda, Ismael and Asbjornsen, Heidi and Baxter, Robert and Beamesderfer, Eric and Berry, Z. Carter and Berveiller, Daniel and Blakely, Bethany and Boggs, Johnny and Bohrer, Gil and Bolstad, Paul V. and Bonal, Damien and Bracho, Rosvel and Brito, Patricia and Brodeur, Jason and Casanoves, Fernando and Chave, Jérôme and Chen, Hui and Cisneros, Cesar and Clark, Kenneth and Cremonese, Edoardo and Dang, Hongzhong and David, Jorge S. and David, Teresa S. and Delpierre, Nicolas and Desai, Ankur R. and Do, Frederic C. and Dohnal, Michal and Domec, Jean-Christophe and Dzikiti, Sebinasi and Edgar, Colin and Eichstaedt, Rebekka and El-Madany, Tarek S. and Elbers, Jan and Eller, Cleiton B. and Euskirchen, Eugénie S. and Ewers, Brent and Fonti, Patrick and Forner, Alicia and Forrester, David I. and Freitas, Helber C. and Galvagno, Marta and Garcia-Tejera, Omar and Ghimire, Chandra Prasad and Gimeno, Teresa E. and Grace, John and Granier, André and Griebel, Anne and Guangyu, Yan and Gush, Mark B. and Hanson, Paul J. and Hasselquist, Niles J. and Heinrich, Ingo and Hernandez-Santana, Virginia and Herrmann, Valentine and Hölttä, Teemu and Holwerda, Friso and Irvine, James and Isarangkool Na Ayutthaya, Supat and Jarvis, Paul G. and Jochheim, Hubert and Joly, Carlos A. and Kaplick, Julia and Kim, Hyun Seok and Klemedtsson, Leif and Kropp, Heather and Lagergren, Fredrik and Lane, Patrick and Lang, Petra and Lapenas, Andrei and Lechuga, Víctor and Lee, Minsu and Leuschner, Christoph and Limousin, Jean-Marc and Linares, Juan Carlos and Linderson, Maj-Lena and Lindroth, Anders and Llorens, Pilar and López-Bernal, Álvaro and Loranty, Michael M. and Lüttschwager, Dietmar and Macinnis-Ng, Cate and Maréchaux, Isabelle and Martin, Timothy A. and Matheny, Ashley and McDowell, Nate and McMahon, Sean and Meir, Patrick and Mészáros, Ilona and Migliavacca, Mirco and Mitchell, Patrick and Mölder, Meelis and Montagnani, Leonardo and Moore, Georgianne W. and Nakada, Ryogo and Niu, Furong and Nolan, Rachael H. and Norby, Richard and Novick, Kimberly and Oberhuber, Walter and Obojes, Nikolaus and Oishi, A. Christopher and Oliveira, Rafael S. and Oren, Ram and Ourcival, Jean-Marc and Paljakka, Teemu and Perez-Priego, Oscar and Peri, Pablo L. and Peters, Richard L. and Pfautsch, Sebastian and Pockman, William T. and Preisler, Yakir and Rascher, Katherine and Robinson, George and Rocha, Humberto and Rocheteau, Alain and Röll, Alexander and Rosado, Bruno H. and Rowland, Lucy and Rubtsov, Alexey V. and Sabaté, Santiago and Salmon, Yann and Salomón, Roberto L. and Sánchez-Costa, Elisenda and Schäfer, Karina V. and Schuldt, Bernhard and Shashkin, Alexandr and Stahl, Clément and Stojanović, Marko and Suárez, Juan Carlos and Sun, Ge and Szatniewska, Justyna and Tatarinov, Fyodor and Tesař, Miroslav and Thomas, Frank M. and Tor-ngern, Pantana and Urban, Josef and Valladares, Fernando and van der Tol, Christiaan and van Meerveld, Ilja and Varlagin, Andrej and Voigt, Holm and Warren, Jeffrey and Werner, Christiane and Werner, Willy and Wieser, Gerhard and Wingate, Lisa and Wullschleger, Stan and Yi, Koong and Zweifel, Roman and Steppe, Kathy and Mencuccini, Maurizio and Martínez-Vilalta, Jordi},
}
Warning: Leaving National Science Foundation Website
You are now leaving the National Science Foundation website to go to a non-government website.
Website:
NSF takes no responsibility for and exercises no control over the views expressed or the accuracy of
the information contained on this site. Also be aware that NSF's privacy policy does not apply to this site.
