The static chamber method (non-flow-through-non-steady-state chambers) is the most common method to measure fluxes of methane (CH4) from soils. Laboratory comparisons to quantify errors resulting from chamber design, operation and flux calculation methods are rare. We tested fifteen chambers against four flux levels (FL) ranging from 200 to 2300 mu g CH4 M-2 II-1. The measurements were conducted on a calibration tank using three quartz sand types with soil porosities of 53% (dry fine sand, S1), 47% (dry coarse sand, S2), and 33% (wetted fine sand, S3). The chambers tested ranged from 0.06 to 1.8 m in height, and 0.02 to 0.195 m(3) in volume, 7 of them were equipped with a fan, and 1 with a vent-tube. We applied linear and exponential flux calculation methods to the chamber data and compared these chamber fluxes to the reference fluxes from the calibration tank. The chambers underestimated the reference fluxes by on average 33% by the linear flux calculation method (R-Iin), whereas the chamber fluxes calculated by the exponential flux calculation method (R-exp) did not significantly differ from the reference fluxes (p <0.05). The flux under- or overestimations were chamber specific and independent of flux level. Increasing chamber height, area and volume significantly reduced the flux underestimation (p <0.05). Also, the use of non-linear flux calculation method significantly improved the flux estimation; however, simultaneously the uncertainty in the fluxes was increased. We provide correction factors, which can be used to correct the under- or overestimation of the fluxes by the chambers in the experiment. (C) 2012 Elsevier B.V. All rights reserved
A laboratory experiment was conducted with two types of closed static chambers to estimate the effects of chamber placement, manual headspace sampling and headspace mixing on methane (CH 4 ) fluxes. Chamber fluxes were compared to a known reference flux in a chamber calibration system. The measurements were conducted with three types of soils (coarse dry, fine dry and fine wet quarts sand) at five flux levels ranging from 60 to 2000 μg CH 4 m −2 h −1 . We found that the placement of a non-vented chamber disturbed the initial CH 4 concentration development within the chamber headspace for 10 to 30 s. Excluding this short period from the flux calculation resulted in a lower flux estimate (mean±SE) of 126±26 μg CH 4 m −2 h −1 compared to 134±26 μg CH 4 m −2 h −1 if data from time zero of the enclosure were included. We also found that in non-mixed chambers (no fan mixing) the gas sampling by syringes or gas bottles disturbed the development of CH 4 concentration during the enclosure. Furthermore, flux estimates in non-mixed chambers were significantly underestimated (on average 36%) compared to the measured reference fluxes. However, the use of fans to constantly mix the chamber headspace during enclosure significantly improved the goodnessof-fit of the regression analysis used to calculate the flux and further eliminated the disturbance of the manual sampling on the concentration development. We recommend that chambers should be vented during the placement of the chamber, and that fans are used as an integrated part of static chambers while headspace mixing with syringes should be avoided.
Background and aims Ecosystem respiration (R eco) is controlled by thermal and hydrologic regimes, but their relative importance in defining the CO 2 emissions in peatlands seems to be site specific. The aim
The photosynthetic, optical, and morphological characteristics of a chlorophyll-deficient (Chl-deficient) "yellow" soybean mutant (MinnGold) were examined in comparison with 2 green varieties (MN0095 and Eiko). Despite the large difference in Chl content, similar leaf photosynthesis rates were maintained in the Chl-deficient mutant by offsetting the reduced absorption of red photons by a small increase in photochemical efficiency and lower non-photochemical quenching. When grown in the field, at full canopy cover, the mutants reflected a significantly larger proportion of incoming shortwave radiation, but the total canopy light absorption was only slightly reduced, most likely due to a deeper penetration of light into the canopy space. As a consequence, canopy-scale gross primary production and ecosystem respiration were comparable between the Chl-deficient mutant and the green variety. However, total biomass production was lower in the mutant, which indicates that processes other than steady state photosynthesis caused a reduction in biomass accumulation over time. Analysis of non-photochemical quenching relaxation and gas exchange in Chl-deficient and green leaves after transitions from high to low light conditions suggested that dynamic photosynthesis might be responsible for the reduced biomass production in the Chl-deficient mutant under field conditions.
The global warming potential of nitrous oxide (N 2 O) and its long atmospheric lifetime mean its presence in the atmosphere is of major concern, and that methods are required to measure and reduce emissions. Large spatial and temporal variations means, however, that simple extrapolation of measured data is inappropriate, and that other methods of quantification are required. Although process-based models have been developed to simulate these emissions, they often require a large amount of input data that is not available at a regional scale, making regional and global emission estimates difficult to achieve. The spatial extent of organic soils means that quantification of emissions from these soil types is also required, but will not be achievable using a process-based model that has not been developed to simulate soil water contents above field capacity or organic soils. The ECOSSE model was developed to overcome these limitations, and with a requirement for only input data that is readily available at a regional scale, it can be used to quantify regional emissions and directly inform land-use change decisions. ECOSSE includes the major processes of nitrogen (N) turnover, with material being exchanged between pools of SOM at rates modified by temperature, soil moisture, soil pH and crop cover. Evaluation of its performance at sitescale is presented to demonstrate its ability to adequately simulate soil N contents and N 2 O emissions from cropland soils in Europe. Mitigation scenarios and sensitivity analyses are also presented to demonstrate how ECOSSE can be used to estimate the impact of future climate and land-use change on N 2 O emissions. C max A constant (set at 50 kg N ha -1 ) that adjusts the maximum rate of nitrification possible [this occurs at high levels of NH 4 ? and will be dependent on soil composition (Parton et al. 1996)] D p Potential denitrification rate (kg N ha -1 layer -1 day -1 ) k nitrif A rate constant for nitrification [set at 0.6 (Bradbury et al. (1993)] m b Biological activity rate modifier m NO 3 Modifies the amount of denitrification depending on soil NO 3 -content m pH A rate modifier due to soil pH m t A rate modifier due to soil temperature m w Soil water rate modifier for decomposition m w0 Soil water rate modifier for decomposition at permanent wilting point and saturation = 0.2 m 0 w Soil water rate modifier for denitrification N d The amount of N emitted from the soil during denitrification (kg N ha -1 layer -1 ) N d;N 2The amount of N 2 gas lost by denitrification (kg N ha -1 day -1 ) N d;N 2 O The amount of N 2 O gas lost by denitrification (kg N ha -1 day -1 ) N d50The soil nitrate content at which denitrification is 50% of its full potential (kg N ha -1 layer -1 ) N FERT N in NH 4 ? and urea in the added fertiliser (kg N ha -1 ) N n Nitrification rate (kg N ha -1 layer -1 ) N n;N 2 O The amount of N 2 O gas released during nitrification (kg N ha -1 day -1 ) N NH 4
High-resolution airborne thermal infrared (TIR) together with sun-induced fluorescence (SIF) and hyperspectral optical images (visible, near- and shortwave infrared; VNIR/SWIR) were jointly acquired over an experimental site. The objective of this study was to evaluate the potential of these state-of-the-art remote sensing techniques for detecting symptoms similar to those occurring during water stress (hereinafter referred to as ‘water stress symptoms’) at airborne level. Flights with two camera systems (Telops Hyper-Cam LW, Specim HyPlant) took place during 11th and 12th June 2014 in Latisana, Italy over a commercial grass (Festuca arundinacea and Poa pratense) farm with plots that were treated with an anti-transpirant agent (Vapor Gard®; VG) and a highly reflective powder (kaolin; KA). Both agents affect energy balance of the vegetation by reducing transpiration and thus reducing latent heat dissipation (VG) and by increasing albedo, i.e., decreasing energy absorption (KA). Concurrent in situ meteorological data from an on-site weather station, surface temperature and chamber flux measurements were obtained. Image data were processed to orthorectified maps of TIR indices (surface temperature (Ts), Crop Water Stress Index (CWSI)), SIF indices (F687, F780) and VNIR/SWIR indices (photochemical reflectance index (PRI), normalised difference vegetation index (NDVI), moisture stress index (MSI), etc.). A linear mixed effects model that respects the nested structure of the experimental setup was employed to analyse treatment effects on the remote sensing parameters. Airborne Ts were in good agreement (∆T < 0.35 K) compared to in situ Ts measurements. Maps and boxplots of TIR-based indices show diurnal changes: Ts was lowest in the early morning, increased by 6 K up to late morning as a consequence of increasing net radiation and air temperature (Tair) and remained stable towards noon due to the compensatory cooling effect of increased plant transpiration; this was also confirmed by the chamber measurements. In the early morning, VG treated plots revealed significantly higher Ts compared to control (CR) plots (p = 0.01), while SIF indices showed no significant difference (p = 1.00) at any of the overpasses. A comparative assessment of the spectral domains regarding their capabilities for water stress detection was limited due to: (i) synchronously overpasses of the two airborne sensors were not feasible, and (ii) instead of a real water stress occurrence only water stress symptoms were simulated by the chemical agents. Nevertheless, the results of the study show that the polymer di-1-p-menthene had an anti-transpiring effect on the plant while photosynthetic efficiency of light reactions remained unaffected. VNIR/SWIR indices as well as SIF indices were highly sensitive to KA, because of an overall increase in spectral reflectance and thus a reduced absorbed energy. On the contrary, the TIR domain was highly sensitive to subtle changes in the temperature regime as induced by VG and KA, whereas VNIR/SWIR and SIF domain were less affected by VG treatment. The benefit of a multi-sensor approach is not only to provide useful information about actual plant status but also on the causes of biophysical, physiological and photochemical changes.
China has experienced rapid agricultural development over recent decades, accompanied by increased fertilizer consumption in croplands; yet, the trend and drivers of the associated nitrous oxide (N2O) emissions remain uncertain. The primary sources of this uncertainty are the coarse spatial variation of activity data and the incomplete model representation of N2O emissions in response to agricultural management. Here, we provide new data‐driven estimates of cropland‐N2O emissions across China in 1990–2014, compiled using a global cropland‐N2O flux observation dataset, nationwide survey‐based reconstruction of N‐fertilization and irrigation, and an updated nonlinear model. In addition, we have evaluated the drivers behind changing cropland‐N2O patterns using an index decomposition analysis approach. We find that China's annual cropland‐N2O emissions increased on average by 11.2 Gg N/year2 (p < .001) from 1990 to 2003, after which emissions plateaued until 2014 (2.8 Gg N/year2, p = .02), consistent with the output from an ensemble of process‐based terrestrial biosphere models. The slowdown of the increase in cropland‐N2O emissions after 2003 was pervasive across two thirds of China's sowing areas. This change was mainly driven by the nationwide reduction in N‐fertilizer applied per area, partially due to the prevalence of nationwide technological adoptions. This reduction has almost offset the N2O emissions induced by policy‐driven expansion of sowing areas, particularly in the Northeast Plain and the lower Yangtze River Basin. Our results underline the importance of high‐resolution activity data and adoption of nonlinear model of N2O emission for capturing cropland‐N2O emission changes. Improving the representation of policy interventions is also recommended for future projections.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.