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  • 1
    Publication Date: 2024-03-18
    Description: Various environmental variables drive gross primary productivity (GPP) and light use efficiency (LUE) of forest ecosystems. However, due to their intertwined nature and the complexity of measuring absorbed photosynthetically active radiation (APAR) of forest canopies, the assessment of LUE and the importance of its environmental drivers are difficult. Here, we present a unique combination of measurements during the 2021 growing season including eddy covariance derived GPP, sap flow, Sentinel‐2 derived canopy chlorophyll content and in situ measured APAR. The importance of environmental variables for GPP models is quantified with state‐of‐the‐art machine learning techniques. A special focus is put on photosynthesis‐limiting conditions, which are identified by a comparison of GPP and sap flow hysteretic responses to Vapor pressure deficit (VPD) and APAR. Results demonstrate that (a) LUE of the canopy's green part was on average 4.0% ± 2.3%, (b) canopy chlorophyll content as a seasonal variable for photosynthetic capacity was important for GPP predictions, and (c) on days with high VPD, tree‐scale sap flow and ecosystem‐scale GPP both shift to a clockwise hysteretic response to APAR. We demonstrate that the onset of such a clockwise hysteretic pattern of sap flow to APAR is a good indicator of stomatal closure related to water‐limiting conditions at the ecosystem‐scale.
    Description: Plain Language Summary: The efficiency by which a forest uses sunlight to perform photosynthesis is an important feature for climate and ecosystem modeling. However, the light that is actually captured by forests and is useable for photosynthesis is difficult to assess. Here, we show a sophisticated approach to estimate the light use efficiency of a spruce forest in Germany and analyze environmental influences on it and on photosynthesis. Our results indicate that about 4% of the light useable for photosynthesis was actually used by the forest during the 2021 growing season and that seasonal variations of chlorophyll in the canopy are a good indicator for carbon capture.
    Description: Key Points: A seasonal variable such as canopy chlorophyll content was useful to predict gross primary productivity with machine learning models. A clockwise hysteretic pattern of sap flow to radiation is a good indicator of water‐related stomatal closure. The light use efficiency of green parts of a spruce forest was 4.0% with a standard deviation of 2.3% during the 2021 growing season.
    Description: RWTH Aachen University http://dx.doi.org/10.13039/501100007210
    Description: University of Alberta http://dx.doi.org/10.13039/501100000190
    Description: Excellence Strategy of the Federal Government and the Länder
    Description: Waldklimafonds http://dx.doi.org/10.13039/501100010297
    Description: German Federal Ministry of Food and Agriculture
    Description: German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection
    Description: TERENO project
    Description: Helmholtz research infrastructure Modular Observation Solutions for Earth Systems
    Description: http://doi.org/10.5281/zenodo.7014604
    Description: https://www.opengeodata.nrw.de/produkte/geobasis/hm/3dm_l_las/3dm_l_las/
    Description: https://scihub.copernicus.eu/
    Keywords: ddc:634.9 ; photosynthetically active radiation ; canopy chlorophyll content ; hysteresis ; sap flow ; variable importance ; Picea abies
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2023-01-26
    Description: Cosmic‐ray neutron sensors (CRNS) enable noninvasive determination of field‐scale soil moisture content by exploiting the dependence of the intensity of aboveground epithermal neutrons on the hydrogen contained in soil moisture. However, there are other hydrogen pools besides soil moisture (e.g., biomass). Therefore, these hydrogen pools should be considered for accurate soil moisture content measurements, especially when they are changing dynamically (e.g., arable crops, deforestation, and reforestation). In this study, we test four approaches for the correction of biomass effects on soil moisture content measurements with CRNS using experiments with three crops (sugar beet, winter wheat, and maize) based on high‐quality reference soil moisture: (a) site‐specific functions based on in‐situ measured biomass, (b) a generic approach, (c) the thermal‐to‐epithermal neutron ratio (Nr), and (d) the thermal neutron intensity. Bare soil calibration of the CRNS resulted in high root mean square errors (RMSEs) of 0.097, 0.041, and 0.019 m³/m³ between estimated and reference soil moisture content for sugar beet, winter wheat, and maize, respectively. Considering in‐situ measured biomass for correction reduced the RMSE to 0.015, 0.018, and 0.009 m³/m³. The consideration of thermal neutron intensity for correction was similarly accurate. We also explored the use of CRNS for biomass estimation and found that Nr only provided accurate biomass estimates for sugar beet. In contrast, we found significant site‐specific relationships between biomass and thermal neutron intensity for all three crops, suggesting that thermal neutron intensity can be used both to improve CRNS‐based soil moisture content measurements and to quantify crop biomass.
    Description: Plain Language Summary: Water availability is a key challenge in agriculture, especially given the expected increase of droughts related to climate change. A promising noninvasive technique to monitor soil moisture content is cosmic‐ray neutron sensing (CRNS), which is based on the negative correlation between the number of near‐surface fast neutrons originating from cosmic radiation and the amount of hydrogen stored as soil moisture. However, hydrogen is also stored in other pools, such as biomass. These additional pools of hydrogen must be considered to accurately determine soil moisture content with CRNS. In this study, we used data from three experiments with different crops for comparing four methods for the correction of biomass effects on the measurement of soil moisture content with CRNS. We found that soil moisture content measurements were most accurate when locally measured biomass was considered for correction. We also found that changes in the amount of biomass of different crops can be quantified using thermal neutrons additionally detected by CRNS, that is, neutrons from cosmic rays that have a lower energy than fast neutrons. A correction of biomass effects using thermal neutron measurements also provided accurate soil moisture content measurements.
    Description: Key Points: Cosmic ray soil moisture measurements were most accurate when corrected with in‐situ biomass measurements or thermal neutron intensity. The effect of biomass on epithermal and thermal neutron intensity is plant‐specific. Biomass could be estimated from thermal neutron intensity for three crops, but not with the thermal‐to‐epithermal neutron ratio.
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: EU‐FP7
    Description: https://doi.org/10.34731/qb7h-6287
    Keywords: ddc:631.4 ; soil moisture ; cosmic ray neutron sensing ; biomass influence ; biomass estimation ; thermal neutrons
    Language: English
    Type: doc-type:article
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  • 3
    Publication Date: 2023-07-31
    Description: Dataset accompanying the publication "Soil moisture observation in a forested headwater catchment: combining a dense cosmic-ray neutron sensor network with (airborne) roving and hydrogravimetry" (ESSD, https://doi.org/10.5194/essd-2021-445) The publication contains records of cosmic ray neutron sensing (CRNS - stationary, roving, airborne roving), soil moisture (SoilNet, FDR, profile probes, gravimetric), hydro-gravimetry, soil properties (bulk density), vegetation / biomass surveys. An overview of the dataset as well as further technical details are provided in the README.pdf file.
    Type: info:eu-repo/semantics/workingPaper
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