Semiempirical modeling of abiotic and biotic factors controlling ecosystem respiration across eddy covariance sites

Abstract

In this study we examined ecosystem respiration (RECO) data from 104 sites belonging to FLUXNET, the global network of eddy covariance flux measurements. The goal was to identify the main factors involved in the variability of RECO: temporally and between sites as affected by climate, vegetation structure and plant functional type (PFT) (evergreen needleleaf, grasslands, etc.). We demonstrated that a model using only climate drivers as predictors of RECO failed to describe part of the temporal variability in the data and that the dependency on gross primary production (GPP) needed to be included as an additional driver of RECO. The maximum seasonal leaf area index (LAIMAX) had an additional effect that explained the spatial variability of reference respiration (the respiration at reference temperature Tref=15 °C, without stimulation introduced by photosynthetic activity and without water limitations), with a statistically significant linear relationship (r2=0.52, P<0.001, n=104) even within each PFT. Besides LAIMAX, we found that reference respiration may be explained partially by total soil carbon content (SoilC). For undisturbed temperate and boreal forests a negative control of total nitrogen deposition (Ndepo) on reference respiration was also identified. We developed a new semiempirical model incorporating abiotic factors (climate), recent productivity (daily GPP), general site productivity and canopy structure (LAIMAX) which performed well in predicting the spatio‐temporal variability of RECO, explaining >70% of the variance for most vegetation types. Exceptions include tropical and Mediterranean broadleaf forests and deciduous broadleaf forests. Part of the variability in respiration that could not be described by our model may be attributed to a series of factors, including phenology in deciduous broadleaf forests and management practices in grasslands and croplands.

Covariation between gross primary production and ecosystem respiration across space and the underlying mechanisms: A global synthesis

“…From these findings, researchers have gradually recognized that GPP and RE are not independent, but are two strongly associated ecological processes. RE is strongly coupled with GPP across timescales (Dunn et al, 2007;Migliavacca et al, 2011). For example, RE follows the same dynamic patterns as GPP from daily to seasonal scales (Krishnan et al, 2009; et al, 2011; Thomas et al, 2009).…”

A remote sensing model to estimate ecosystem respiration in Northern China and the Tibetan Plateau

“…6b). Previous studies also indicated that reference respiration depends strongly on mean annual GPP (e.g., Yuan et al, 2011), and can be estimated by LAI max (e.g., Migliavacca et al, 2011) or mean annual springtime EVI (e.g., Jägermeyr et al, 2014).…”

Impacts of droughts and extreme temperature events on gross primary production and ecosystem respiration: a systematic assessment across ecosystems and climate zones

“…However, it is important to understand that the tight coupling between GPP and R eco in most ecosystems (Irvine et al, 2008;Mahecha et al, 2010;Migliavacca et al, 2010;van der Molen et al, 2011;Peichl et al, 2013;Rambal et al, 2014) complicates systematic assessments across sites. For example, heterotrophic respiration is not only a function of the environment, but is also strongly driven by the availability of recently assimilated carbon (Irvine et al, 2005;Granier et al, 2007;Ruehr et al, 25 2012).…”