|Babel, W; Lüers, J; Hübner, J; Rebmann, C; Wichura, B; Thomas, CK; Serafimovich, A; Foken, T: Long-Term Carbon and Water Vapour Fluxes in Foken, T.: Energy and Matter Fluxes of a Spruce Forest Ecosystem, Springer(Ecological Studies Vol. 229), 73-96 (2017), doi:10.1007/978-3-319-49389-3_4 [Link]|
In this study we analyse eddy-covariance flux measurements of carbon dioxide and water vapour from 18 years at Waldstein–Weidenbrunnen (DE-Bay), a Norway spruce forest site in the Fichtelgebirge, Germany. Standard flux partitioning algorithms have been applied for separation of net ecosystem exchange NEE into gross primary production GPP and ecosystem respiration Reco, as well as gap-filling. The site has always been a carbon sink, and annual net uptake ( −NEE) shows a positive trend with values around 40 g C m−2 a−1 for 1997–1999 up to 615 ± 79 g C m−2 a−1 for 2011–2014. This is related to a strong increase in GPP, while Reco is slightly enhanced. Evapotranspiration increases coherently with NEE, while atmospheric demand, that is, potential evaporation, shows inter-annual variability, but no trend. Comparisons with studies from other warm-temperate coniferous forests show that our NEE estimates are at the upper range of the distribution, but still realistic. Also evapotranspiration estimates, evaluated in the Budyko framework, are in a similar range but with a large inter-annual variability. We identified instrumental problems and variability from different flux partitioning algorithms as a large source of uncertainty, but with only minor influence on the trends found. Warming and rising CO2-concentrations are consistent with the observed trend, but cannot be disentangled from site-specific changes such as the recovery from forest decline after liming and an increase in heterogeneity after a wind-throw, which likely plays the most important role in the observed dynamics. As such transitions from an “ideal” to a disturbed or heterogeneous site are likely more-often the case at FLUXNET stations built 10–20 years ago, a systematic bias in regional studies can only be avoided by taking each single site history into account.