Manual closed‐chamber measurements are commonly used to quantify annual net CO2 ecosystem exchange (NEE) in a wide range of terrestrial ecosystems. However, differences in both the acquisition and gap filling of manual closed‐chamber data are large in the existing literature, complicating inter‐study comparisons and meta analyses. The aim of this study was to compare common approaches for quantifying CO2 exchange at three methodological levels. (1) The first level included two different CO2 flux measurement methods: one via measurements during mid‐day applying net coverages (mid‐day approach) and one via measurements from sunrise to noon (sunrise approach) to capture a span of light conditions for measurements of NEE with transparent chambers. (2) The second level included three different methods of pooling measured ecosystem respiration (RECO) fluxes for empirical modeling of RECO: campaign‐wise (19 single‐measurement‐day RECO models), season‐wise (one RECO model for the entire study period), and cluster‐wise (two RECO models representing a low and a high vegetation status). (3) The third level included two different methods of deriving fluxes of gross primary production (GPP): by subtracting either proximately measured RECO fluxes (direct GPP modeling) or empirically modeled RECO fluxes from measured NEE fluxes (indirect GPP modeling). Measurements were made during 2013–2014 in a lucerne‐clover‐grass field in NE Germany. Across the different combinations of measurement and gap‐filling options, the NEE balances of the agricultural field diverged strongly (–200 to 425 g CO2‐C m−2). NEE balances were most similar to previous studies when derived from sunrise measurements and indirect GPP modeling. Overall, the large variation in NEE balances resulting from different data‐acquisition or gap‐filling strategies indicates that these methodological decisions should be made very carefully and that they likely add to the overall uncertainty of greenhouse gas emission factors. Preferably, a standard approach should be developed to reduce the uncertainty of upscaled estimates.
Drought and the availability of mineable phosphorus minerals used for fertilization are two of the important issues agriculture is facing in the future. High phosphorus availability in soils is necessary to maintain high agricultural yields. Drought is one of the major threats for terrestrial ecosystem performance and crop production in future. Among the measures proposed to cope with the upcoming challenges of intensifying drought stress and to decrease the need for phosphorus fertilizer application is the fertilization with silica (Si). Here we tested the importance of soil Si fertilization on wheat phosphorus concentration as well as wheat performance during drought at the field scale. Our data clearly showed a higher soil moisture for the Si fertilized plots. This higher soil moisture contributes to a better plant performance in terms of higher photosynthetic activity and later senescence as well as faster stomata responses ensuring higher productivity during drought periods. The plant phosphorus concentration was also higher in Si fertilized compared to control plots. Overall, Si fertilization or management of the soil Si pools seem to be a promising tool to maintain crop production under predicted longer and more serve droughts in the future and reduces phosphorus fertilizer requirements.
<p>&#173;&#173;&#173;Improved agricultural practices sequestering additional atmospheric C within the soil are considered as one of the potential solution for mitigating global climate change. However, agricultural used landscapes are complex and their capacity to sequester additional atmospheric C might differ substantially in time and space. Hence, accurate and precise information on the complex spatio-temporal CO<sub>2</sub> flux pattern is needed to evaluate the effects/benefits of new agricultural practices aiming towards increasing soil organic carbon.</p><p>To date, different approaches are used to measure and quantify CO<sub>2</sub> flux dynamics of agricultural landscapes, such as e.g. eddy covariance, as well as manual and automatic chamber systems. However, all these methods fail to some extend in either accounting for small scale spatial heterogeneity (eddy covariance and automatic chambers) or short-term temporal variability (manual chambers). Although, automatic chambers are in principle capable to detect small-scale spatial differences of CO<sub>2 </sub>flux dynamics in a sufficient temporal resolution, these systems are usually limited to only a few spatial repetitions which is not sufficient to represent small scale soil heterogeneity such as present within the widespread hummocky ground moraine landscape of NE-Germany.</p><p>To overcome these challenges, we developed a novel robotic chamber system allowing to detect small-scale spatial heterogeneity and short-term temporal variability of CO<sub>2</sub> (as well as CH<sub>4</sub> and N<sub>2</sub>O) flux dynamics for a range of different fertilization and tillage management practices. The system is equipped with two canopy chambers, CR6 data logger, CDM-A116 analog multiplexer and multiple sensors to measure plant activity/biomass development in parallel. The measurements of the gaseous C exchange is performed by moving the system along the tracks with each chamber along one half of the gantry crane. Thus, each chamber measures 18 plots, out of 36 plots (2x3m; 12 per soil type) established in the study area.</p><p>Here, we present first CO<sub>2</sub> flux measurement results (spring barley; 3 different soil types) using this novel system, to prove its overall accuracy and precision. Our results show clear small-scale/within field spatial pattern and short-term temporal dynamics regarding measured ecosystem respiration, net ecosystem exchange as well as derived gross primary productivity.</p>
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