Global transpiration data from sap flow measurements: the SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land?atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets,while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes.Fil: Poyatos, Rafael. Universitat Autònoma de Barcelona; EspañaFil: Granda, Víctor. Universitat Autònoma de Barcelona; EspañaFil: Flo, Víctor. Universitat Autònoma de Barcelona; EspañaFil: Adams, Mark A.. Swinburne University of Technology; Australia. University of Sydney; AustraliaFil: Adorján, Balázs. University of Debrecen; HungríaFil: Aguadé, David. Universitat Autònoma de Barcelona; EspañaFil: Aidar, Marcos P. M.. Institute of Botany; BrasilFil: Allen, Scott. University of Nevada; Estados UnidosFil: Alvarado Barrientos, M. Susana. Instituto de Ecología A.C.; MéxicoFil: Anderson Teixeira, Kristina J.. Smithsonian Tropical Research Institute; PanamáFil: Aparecido, Luiza Maria. Arizona State University; Estados Unidos. Texas A&M University; Estados UnidosFil: Arain, M. Altaf. McMaster University; CanadáFil: Aranda, Ismael. National Institute for Agricultural and Food Research and Technology; EspañaFil: Asbjornsen, Heidi. University of New Hampshire; Estados UnidosFil: Robert Baxter. Durham University; Reino UnidoFil: Beamesderfer, Eric. McMaster University; Canadá. Northern Arizona University; Estados UnidosFil: Carter Berry, Z.. Chapman University; Estados UnidosFil: Berveiller, Daniel. Université Paris Saclay; Francia. Centre National de la Recherche Scientifique; FranciaFil: Blakely, Bethany. University of Illinois at Urbana-Champaign; Estados UnidosFil: Boggs, Johnny. United States Forest Service; Estados UnidosFil: Gil Bohrer. Ohio State University; Estados UnidosFil: Bolstad, Paul V.. University of Minnesota; Estados UnidosFil: Bonal, Damien. Université de Lorraine; FranciaFil: Bracho, Rosvel. University of Florida; Estados UnidosFil: Brito, Patricia. Universidad de La Laguna; EspañaFil: Brodeur, Jason. McMaster University; CanadáFil: Casanoves, Fernando. Centro Agronómico Tropical de Investigación y Enseñanza; Costa RicaFil: Chave, Jérôme. Université Paul Sabatier; FranciaFil: Chen, Hui. Xiamen University; ChinaFil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Tecnológica Nacional. Facultad Regional Santa Cruz. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia de Santa Cruz; Argentin

Carbon-nitrogen interactions in European forests and semi-natural vegetation - Part 1: Fluxes and budgets of carbon, nitrogen and greenhouse gases from ecosystem monitoring and modelling

The impact of atmospheric reactive nitrogen (N$_{r}$) deposition on carbon (C) sequestration in soils and biomass of unfertilized, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC/dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of N$_{r}$ deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2020) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet N$_{r}$ deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and N$_{r}$ inputs and losses, these data were also combined with in situ flux measurements of NO, N$_{2}$O and CH$_{4}$ fluxes; soil NO$_{3}$̅ leaching sampling; and results of soil incubation experiments for N and greenhouse gas (GHG) emissions, as well as surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling. Multi-year averages of net ecosystem productivity (NEP) in forests ranged from -70 to 826 gCm$^{-2}$ yr$^{-1}$ at total wet+dry inorganic N$_{r}$ deposition rates (N$_{dep}$) of 0.3 to 4.3 gNm$^{-2}$ yr$^{-1}$ and from -4 to 361 g Cm$^{-2}$ yr$^{-1}$ at N$_{dep}$ rates of 0.1 to 3.1 gNm$^{-2}$ yr$^{-1}$ in short semi-natural vegetation (moorlands, wetlands and unfertilized extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO$_{2}$ exchange, while CH$_{4}$ and N$_{2}$O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Uncertainties in elemental budgets were much larger for nitrogen than carbon, especially at sites with elevated N$_{dep}$ where N$_{r}$ leaching losses were also very large, and compounded by the lack of reliable data on organic nitrogen and N$_{2}$ losses by denitrification. Nitrogen losses in the form of NO, N$_{2}$O and especially NO$_{3}$̅ were on average 27%(range 6 %–54 %) of N$_{dep}$ at sites with N$_{dep}$ 3 gNm$^{-2}$ yr$^{-1}$. Such large levels of N$_{r}$ loss likely indicate that different stages of N saturation occurred at a number of sites. The joint analysis of the C and N budgets provided further hints that N saturation could be detected in altered patterns of forest growth. Net ecosystem productivity increased with N$_{r}$ deposition up to 2–2.5 gNm$^{-2}$ yr$^{-1}$, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP = GPP ratio). At elevated N$_{dep}$ levels (> 2.5 gNm$^{-2}$ yr$^{-1}$), where inorganic N$_{r}$ losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate N$_{dep}$ levels was partly the result of geographical cross-correlations between N$_{dep}$ and climate, indicating that the actual mean dC/dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. N$_{dep}$

Increasing stomatal conductance inresponse to rising atmospheric CO2

Background and Aims: Studies have indicated that plant stomatal conductance (gs) decreases in response to elevated atmospheric CO2, a phenomenon of significance for the global hydrological cycle. However, gs increases across certain CO2 ranges have been predicted by optimisation models. The aim of this work was to demonstrate that under certain environmental condition, gs can increase in response to elevated CO2. Methods: When using (i) an extensive, up-to-date, synthesis of gs responses in FACE experiments, (ii) in situ measurements across four biomes showing dynamic gs responses to a CO2 rise of ~50ppm (characterising the change in this greenhouse gas over the past three decades) and (iii) a photosynthesis-stomatal conductance model, it is demonstrated that gs can in some cases increase in response to increasing atmospheric CO2. Key Results: Field observations are corroborated by an extensive synthesis of gs responses in FACE experiments showing that 11.8% of gs responses under experimentally elevated CO2 are positive. They are further supported by a strong data-model fit (r2=0.607) using a stomatal optimization model applied to the field gs dataset. A parameter space identified in the Farquhar-Ball-Berry photosynthesis-stomatal conductance model confirms field observations of increasing gs under elevated CO2 in hot dry conditions. It was shown that contrary to the general assumption, positive gs responses to elevated CO2, although relatively rare, are a feature of woody taxa adapted to warm, low-humidity conditions, and that this response is also demonstrated in global simulations using the Community Land Model (CLM4). Conclusions: The results contradict the over-simplistic notion that global vegetation always responds with decreasing gs to elevated CO2, a finding that has important implications for predicting future vegetation feedbacks on the hydrological cycle at the regional level.Irish Research CouncilScience Foundation Irelan

Seasonal Dynamics of Mobile Carbon Supply in Quercus aquifolioides at the Upper Elevational Limit

Many studies have tried to explain the physiological mechanisms of the alpine treeline phenomenon, but the debate on the alpine treeline formation remains controversial due to opposite results from different studies. The present study explored the carbon-physiology of an alpine shrub species (Quercus aquifolioides) grown at its upper elevational limit compared to lower elevations, to test whether the elevational limit of alpine shrubs (<3 m in height) are determined by carbon limitation or growth limitation. We studied the seasonal variations in non-structural carbohydrate (NSC) and its pool size in Q. aquifolioides grown at 3000 m, 3500 m, and at its elevational limit of 3950 m above sea level (a.s.l.) on Zheduo Mt., SW China. The tissue NSC concentrations along the elevational gradient varied significantly with season, reflecting the season-dependent carbon balance. The NSC levels in tissues were lowest at the beginning of the growing season, indicating that plants used the winter reserve storage for re-growth in the early spring. During the growing season, plants grown at the elevational limit did not show lower NSC concentrations compared to plants at lower elevations, but during the winter season, storage tissues, especially roots, had significantly lower NSC concentrations in plants at the elevational limit compared to lower elevations. The present results suggest the significance of winter reserve in storage tissues, which may determine the winter survival and early-spring re-growth of Q. aquifolioides shrubs at high elevation, leading to the formation of the uppermost distribution limit. This result is consistent with a recent hypothesis for the alpine treeline formation

Global transpiration data from sap flow measurements: The SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land-atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80% of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50% of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56% of the datasets. Many datasets contain data for species that make up 90% or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (10.5281/zenodo.3971689; Poyatos et al., 2020a). The "sapfluxnetr"R package-designed to access, visualize, and process SAPFLUXNET data-is available from CRAN. © 2021 Rafael Poyatos et al.This research was supported by the Minis-terio de Economía y Competitividad (grant no. CGL2014-55883-JIN), the Ministerio de Ciencia e Innovación (grant no. RTI2018-095297-J-I00), the Ministerio de Ciencia e Innovación (grant no. CAS16/00207), the Agència de Gestió d’Ajuts Universitaris i de Recerca (grant no. SGR1001), the Alexander von Humboldt-Stiftung (Humboldt Research Fellowship for Experienced Researchers (RP)), and the Institució Catalana de Recerca i Estudis Avançats (Academia Award (JMV)). Víctor Flo was supported by the doctoral fellowship FPU15/03939 (MECD, Spain)

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible

Global transpiration data from sap flow measurements : the SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land-atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 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 process SAPFLUXNET data - is available from CRAN.Peer reviewe