| 1. |
- Balzarolo, Manuela, et al.
(author)
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Ground-Based Optical Measurements at European Flux Sites: A Review of Methods, Instruments and Current Controversies
- 2011
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In: Sensors. - : MDPI AG. - 1424-8220. ; 11:8, s. 7954-7981
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Research review (peer-reviewed)abstract
- This paper reviews the currently available optical sensors, their limitations and opportunities for deployment at Eddy Covariance (EC) sites in Europe. This review is based on the results obtained from an online survey designed and disseminated by the Co-cooperation in Science and Technology (COST) Action ESO903-"Spectral Sampling Tools for Vegetation Biophysical Parameters and Flux Measurements in Europe" that provided a complete view on spectral sampling activities carried out within the different research teams in European countries. The results have highlighted that a wide variety of optical sensors are in use at flux sites across Europe, and responses further demonstrated that users were not always fully aware of the key issues underpinning repeatability and the reproducibility of their spectral measurements. The key findings of this survey point towards the need for greater awareness of the need for standardisation and development of a common protocol of optical sampling at the European EC sites.
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| 2. |
- Carrasco-Molina, Tania, et al.
(author)
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Validation and parametrization of the soil moisture index for stomatal conductance modelling and flux-based ozone risk assessment of Mediterranean plant species
- 2024
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In: Agricultural and Forest Meteorology. - 0168-1923. ; 354
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Journal article (peer-reviewed)abstract
- The Mediterranean region chronically experiences high levels of tropospheric ozone (O3) that can affect the health of vegetation. However, limiting plant growing conditions, such as low soil moisture, may restrict the stomatal phytotoxic ozone dose (POD) absorbed by vegetation, modulating O3 detrimental effects. Atmospheric chemistry transport models that estimate POD for O3 risk assessment of effects on vegetation species, such as the European Monitoring and Evaluation Programme (EMEP), have adopted the soil moisture index (SMI) to consider the influence of soil moisture on POD. The objectives of this study were the parametrization and validation of the SMI effect on stomatal conductance (gs) for improving the POD estimation and O3 risk assessment for different vegetation species under water-limiting growing conditions, using field data collected in Italy and Spain and a literature review. The modelled SMI from EMEP proved to be a good indicator of soil moisture dynamics across sites and years, although it showed a general tendency to overestimate soil moisture availability for plants, particularly in the driest seasons. New parametrizations derived for modelling SMI effects on gs under Mediterranean conditions proposed in this study stress the importance of using species-specific parameters for species showing contrasting water-saving strategies in contrast of the current approach of using a simple relation between SMI and gs for all the species. Furthermore, gs modelling parametrizations based on soil water potential (SWP) were found to be more suitable than SMI for local scale estimation of POD under water-limiting conditions. Further consideration of rooting depth and distribution will be required in the future to determine the soil depth at which the soil moisture should be measured in POD modelling, since these features represent one of the most important uncertainties affecting the estimation of POD that could not be addressed with the present database.
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| 3. |
- George, Jan Peter, et al.
(author)
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Method comparison of indirect assessments of understory leaf area index (LAIu) : A case study across the extended network of ICOS forest ecosystem sites in Europe
- 2021
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In: Ecological Indicators. - : Elsevier BV. - 1470-160X .- 1872-7034. ; 128
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Journal article (peer-reviewed)abstract
- Leaf area index (LAI) is a key ecological indicator for describing the structure of canopies and for modelling energy exchange between atmosphere and biosphere. While LAI of the forest overstory can be accurately assessed over large spatial scales via remote sensing, LAI of the forest understory (LAIu) is still largely ignored in ecological studies and ecosystem modelling due to the fact that it is often too complex to be destructively sampled or approximated by other site parameters. Additionally, so far only few attempts have been made to retrieve understory LAI via remote sensing, because dense canopies with high LAI are often hindering retrieval algorithms to produce meaningful estimates for understory LAI. Consequently, the forest understory still constitutes a poorly investigated research realm impeding ecological studies to properly account for its contribution to the energy absorption capacity of forest stands. This study aims to compare three conceptually different indirect retrieval methodologies for LAIu over a diverse panel of forest understory types distributed across Europe. For this we carried out near-to-surface measurements of understory reflectance spectra as well as digital surface photography over the extended network of Integrated Carbon Observation System (ICOS) forest ecosystem sites. LAIu was assessed by exploiting the empirical relationship between vegetation cover and light absorption (Beer-Lambert- Bouguer law) as well as by utilizing proposed relationships with two prominent vegetation indices: normalized difference vegetation index (NDVI) and simple ratio (SR). Retrievals from the three methods were significantly correlated with each other (r = 0.63–0.99, RMSE = 0.53–0.72), but exhibited also significant bias depending on the LAI scale. The NDVI based retrieval approach most likely overestimates LAI at productive sites when LAIu > 2, while the simple ratio algorithm overestimates LAIu at sites with sparse understory vegetation and presence of litter or bare soil. The purely empirical method based on the Beer-Lambert law of light absorption seems to offer a good compromise, since it provides reasonable LAIu values at both low and higher LAI ranges. Surprisingly, LAIu variation among sites seems to be largely decoupled from differences in climate and light permeability of the overstory, but significantly increased with vegetation diversity (expressed as species richness) and hence proposes new applications of LAIu in ecological modelling.
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| 4. |
- Migliavacca, Mirco, et al.
(author)
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Semiempirical modeling of abiotic and biotic factors controlling ecosystem respiration across eddy covariance sites
- 2011
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In: Global Change Biology. - : Wiley. - 1354-1013. ; 17:1, s. 390-409
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Journal article (peer-reviewed)abstract
- In this study we examined ecosystem respiration (R-ECO) data from 104 sites belonging to FLUXNET, the global network of eddy covariance flux measurements. The goal was to identify the main factors involved in the variability of R-ECO: temporally and between sites as affected by climate, vegetation structure and plant functional type (PFT) (evergreen needleleaf, grasslands, etc.). We demonstrated that a model using only climate drivers as predictors of R-ECO failed to describe part of the temporal variability in the data and that the dependency on gross primary production (GPP) needed to be included as an additional driver of R-ECO. The maximum seasonal leaf area index (LAI(MAX)) had an additional effect that explained the spatial variability of reference respiration (the respiration at reference temperature T-ref=15 degrees C, without stimulation introduced by photosynthetic activity and without water limitations), with a statistically significant linear relationship (r2=0.52, P < 0.001, n=104) even within each PFT. Besides LAI(MAX), we found that reference respiration may be explained partially by total soil carbon content (SoilC). For undisturbed temperate and boreal forests a negative control of total nitrogen deposition (N-depo) on reference respiration was also identified. We developed a new semiempirical model incorporating abiotic factors (climate), recent productivity (daily GPP), general site productivity and canopy structure (LAI(MAX)) which performed well in predicting the spatio-temporal variability of R-ECO, explaining > 70% of the variance for most vegetation types. Exceptions include tropical and Mediterranean broadleaf forests and deciduous broadleaf forests. Part of the variability in respiration that could not be described by our model may be attributed to a series of factors, including phenology in deciduous broadleaf forests and management practices in grasslands and croplands.
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| 5. |
- Papale, Dario, et al.
(author)
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Standards and Open Access are the ICOS Pillars Reply to "Comments on 'The Integrated Carbon Observation System in Europe'"
- 2023
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In: Bulletin of the American Meteorological Society. - 0003-0007. ; 104:12, s. 953-955
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Journal article (peer-reviewed)abstract
- In his comment (Kowalski 2023) on our recent publication (Heiskanen et al. 2022) where we present the Integrated Carbon Observation System (ICOS) research infrastructure, Andrew Kowalski introduces three important and, in our opinion, different potential issues in the definition, collection, and availability of field measurements made by the ICOS network, and he proposes possible solutions to these issues.
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| 6. |
- Pisek, Jan, et al.
(author)
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Retrieval and validation of forest background reflectivity from daily Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) data across European forests
- 2021
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In: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 18:2, s. 621-635
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Journal article (peer-reviewed)abstract
- Information about forest background reflectance is needed for accurate biophysical parameter retrieval from forest canopies (overstory) with remote sensing. Separating under- and overstory signals would enable more accurate modeling of forest carbon and energy fluxes. We retrieved values of the normalized difference vegetation index (NDVI) of the forest understory with the multi-angular Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo data (gridded 500 m daily Collection 6 product), using a method originally developed for boreal forests. The forest floor background reflectance estimates from the MODIS data were compared with in situ understory reflectance measurements carried out at an extensive set of forest ecosystem experimental sites across Europe. The reflectance estimates from MODIS data were, hence, tested across diverse forest conditions and phenological phases during the growing season to examine their applicability for ecosystems other than boreal forests. Here we report that the method can deliver good retrievals, especially over different forest types with open canopies (low foliage cover). The performance of the method was found to be limited over forests with closed canopies (high foliage cover), where the signal from understory becomes too attenuated. The spatial heterogeneity of individual field sites and the limitations and documented quality of the MODIS BRDF product are shown to be important for the correct assessment and validation of the retrievals obtained with remote sensing.
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| 7. |
- Wohlfahrt, Georg, et al.
(author)
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Biotic, Abiotic, and Management Controls on the Net Ecosystem CO2 Exchange of European Mountain Grassland Ecosystems
- 2008
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In: Ecosystems. - : Springer Science and Business Media LLC. - 1432-9840 .- 1435-0629. ; 11:8, s. 1338-1351
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Journal article (peer-reviewed)abstract
- was spring and autumn for the sites characterized by summer droughts (southern sites) and (peak) summer for the Alpine and northern study sites. This general pattern was interrupted by grassland management practices, that is, mowing and grazing, when the variability in NEE explained by PPFD decreased in concert with the amount of aboveground biomass (BMag). Temperature was the abiotic influence factor that explained most of the variability in ecosystem respiration at the Alpine and northern study sites, but not at the southern sites characterized by a pronouncedThe net ecosystem carbon dioxide (CO2) exchange (NEE) of nine European mountain grassland ecosystems was measured during 2002-2004 using the eddy covariance method. Overall, the availability of photosynthetically active radiation (PPFD) was the single most important abiotic influence factor for NEE. Its role changed markedly during the course of the season, PPFD being a better predictor for NEE during periods favorable for CO2 uptake, which summer drought, where soil water availability and the amount of aboveground biomass were more or equally important. The amount of assimilating plant area was the single most important biotic variable determining the maximum ecosystem carbon uptake potential, that is, the NEE at saturating PPFD. Good correspondence, in terms of the magnitude of NEE, was observed with many (semi-) natural grasslands around the world, but not with grasslands sown on fertile soils in lowland locations, which exhibited higher maximum carbon gains at lower respiratory costs. It is concluded that, through triggering rapid changes in the amount and area of the aboveground plant matter, the timing and frequency of land management practices is crucial for the short-term sensitivity of the NEE of the investigated mountain grassland ecosystems to climatic drivers.
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| 8. |
- Zhang, Weijie, et al.
(author)
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The effect of relative humidity on eddy covariance latent heat flux measurements and its implication for partitioning into transpiration and evaporation
- 2023
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In: Agricultural and Forest Meteorology. - : Elsevier BV. - 0168-1923. ; 330
-
Journal article (peer-reviewed)abstract
- While the eddy covariance (EC) technique is a well-established method for measuring water fluxes (i.e., evaporation or 'evapotranspiration’, ET), the measurement is susceptible to many uncertainties. One such issue is the potential underestimation of ET when relative humidity (RH) is high (>70%), due to low-pass filtering with some EC systems. Yet, this underestimation for different types of EC systems (e.g. open-path or closed-path sensors) has not been characterized for synthesis datasets such as the widely used FLUXNET2015 dataset. Here, we assess the RH-associated underestimation of latent heat fluxes (LE, or ET) from different EC systems for 163 sites in the FLUXNET2015 dataset. We found that the LE underestimation is most apparent during hours when RH is higher than 70%, predominantly observed at sites using closed-path EC systems, but the extent of the LE underestimation is highly site-specific. We then propose a machine learning based method to correct for this underestimation, and compare it to two energy balance closure based LE correction approaches (Bowen ratio correction, BRC, and attributing all errors to LE). Our correction increases LE by 189% for closed-path sites at high RH (>90%), while BRC increases LE by around 30% for all RH conditions. Additionally, we assess the influence of these corrections on ET-based transpiration (T) estimates using two different ET partitioning methods. Results show opposite responses (increasing vs. slightly decreasing T-to-ET ratios, T/ET) between the two methods when comparing T based on corrected and uncorrected LE. Overall, our results demonstrate the existence of a high RH bias in water fluxes in the FLUXNET2015 dataset and suggest that this bias is a pronounced source of uncertainty in ET measurements to be considered when estimating ecosystem T/ET and WUE.
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