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- Poyatos, R., et al.
(författare)
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Global transpiration data from sap flow measurements: the SAPFLUXNET database
- 2021
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Ingår i: Earth System Science Data. - : Copernicus GmbH. - 1866-3508 .- 1866-3516. ; 13:6, s. 2607-2649
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 2. |
- Schubert, Per, et al.
(författare)
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Modeling GPP in the Nordic forest landscape with MODIS time series data-Comparison with the MODIS GPP product
- 2012
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Ingår i: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257 .- 1879-0704. ; 126, s. 136-147
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Tidskriftsartikel (refereegranskat)abstract
- Satellite sensor-derived data are suitable for regional estimations of several important biophysical variables. Data with a finer spatial resolution should improve regional estimations of GPP (gross primary productivity), since they better capture the variation in a heterogeneous landscape. The main objective of this study was to investigate if MODIS 500 m reflectance data can be used to drive empirical models for regional estimations of GPP in Nordic forests. The performance of the proposed models was compared with the MODIS 1 km GPP product. Linear regression analyses were made on 8-day averages of eddy covariance GPP from three deciduous and ten coniferous sites in relation to MODIS 8-day composite data and 8-day averages of modeled incoming PPFD (photosynthetic photon flux density). Time series of EVI2 (two-band enhanced vegetation index) were calculated from MODIS 500 m reflectance data and smoothed by a curve fitting procedure. For most sites, GPP was fairly strongly to strongly related to the product of EVI2 and PPFD (Deciduous: R-2=0.45-0.86, Coniferous: R-2=0.49-0.90). Similar strengths were found between GPP and the product of EVI2 and MODIS 1 km daytime LST (land surface temperature) (R-2=0.55-0.81, 0.57-0.77) and between GPP and EVI2, PPFD and daytime LST in multiple linear regressions (R-2=0.73-0.89,0.65-0.93). One year of data was collected from all coniferous sites to derive a general empirical model for GPP versus (1) the product of EVI2 and PPFD (R-2=0.70), (2) the product of EVI2 and daytime LST (R-2=0.62) and (3) EVI2, PPFD and daytime LST (R-2=0.72). These three models were then validated at six sites for the remaining years by linearly relating eddy covariance GPP to modeled GPP, which resulted in fairly strong to strong relationships for most sites (R-2=0.49-0.91, RMSE=0.63-1.22 gC m(-2) day(-1), R-2=0.53-0.73, RMSE=0.90-1.43 gC m(-2) day(-1) R-2=0.56-0.87, RMSE=0.79-1.11 gC m(-2) day(-1)). In comparison, similar validation strengths were found for the latest collection 5.1 of the MODIS 1 km GPP product (R-2=0.59-0.88, RMSE=0.80-1.16 gC m(-2) day(-1)). The main conclusion is that the suggested empirical models driven by MODIS 500 m reflectance data can be used for regional estimations of Nordic forest GPP, while preserving a finer resolution than the MODIS 1 km GPP product. (C) 2012 Elsevier Inc. All rights reserved.
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