Publication Date:
2017-03-29
Description:
Manual closed-chamber measurements are commonly used to quantify annual net CO 2 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 CO 2 exchange at three methodological levels. (1) The first level included two different CO 2 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 (R ECO ) fluxes for empirical modeling of R ECO : campaign-wise (19 single-measurement-day R ECO models), season-wise (one R ECO model for the entire study period), and cluster-wise (two R ECO 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 R ECO fluxes (direct GPP modeling) or empirically modeled R ECO 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 CO 2 -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.
Print ISSN:
1436-8730
Electronic ISSN:
1522-2624
Topics:
Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
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