Global patterns of forest autotrophic carbon fluxes

Abstract

Carbon (C) fixation, allocation, and metabolism by trees set the basis for energy and material flows in forest ecosystems and define their interactions with Earth's changing climate. However, while many studies have considered variation in productivity with latitude and climate, we lack a cohesive synthesis on how forest carbon fluxes vary globally with respect to climate and one another. Here, we draw upon 1,319 records from the Global Forest Carbon Database, representing all major forest types and the nine most significant autotrophic carbon fluxes, to comprehensively review how annual C cycling in mature, undisturbed forests varies with latitude and climate on a global scale. Across all flux variables analyzed, rates of C cycling decreased continuously with absolute latitude-a finding that confirms multiple previous studies and contradicts the idea that net primary productivity of temperate forests rivals that of tropical forests. C flux variables generally displayed similar trends across latitude and multiple climate variables, with no differences in allocation detected at this global scale. Temperature variables in general, and mean annual temperature or temperature seasonality in particular, were the best single predictors of C flux, explaining 19%-71% of variation in the C fluxes analyzed. The effects of temperature were modified by moisture availability, with C flux reduced under hot and dry conditions and sometimes under very high precipitation. Annual C fluxes increased with growing season length and were also influenced by growing season climate. These findings clarify how forest C flux varies with latitude and climate on a global scale. In an era when forests will play a critical yet uncertain role in shaping Earth's rapidly changing climate, our synthesis provides a foundation for understanding global patterns in forest C cycling.

Warmer spring temperatures in temperate deciduous forests advance the timing of tree growth but have little effect on annual woody productivity

“…Moreover, acclimation of trees to warming temperatures 44 and, on longer time scales, species adaptations and shifts in community composition 45 are likely to alter the phenology of forest C cycling. If we look across spatial gradients where the latter have had time to play out, we see that warmer spring temperatures are associated with earlier leaf-out 6 and longer growing seasons, which in turn are are correlated with greater tree growth 46 , woody productivity 47 , and NEE 48 . Thus, warming spring temperatures are expected to increase the biophysical potential for annual tree growth, but that potential is not being realized on an interannual time frame.…”

Shifts in leaf senescence across the Northern Hemisphere in response to seasonal warming

“…The copyright holder for this preprint (which this version posted July 24, 2021. ; https://doi.org/10.1101/2021.07.23.453498 doi: bioRxiv preprint 10 2020). The FLUXNET2015 dataset has been processed using a uniform pipeline to reduce the uncertainty and improve the consistency across different sites (Pastorello et al 2020), which has been widely applied to study the impact of climate change on carbon cycling in terrestrial ecosystems (Liu et al 2019;Banbury Morgan et al 2021).…”

“…org/data/fluxnet2015-dataset/, which provides data on the exchange of carbon, water and energy of 212 sites across the globe, including over 10 2020). The FLUXNET2015 dataset has been processed using a uniform pipeline to reduce the uncertainty and improve the consistency across different sites (Pastorello et al 2020), which has been widely applied to study the impact of climate change on carbon cycling in terrestrial ecosystems (Liu et al 2019;Banbury Morgan et al 2021).…”

Comparing an exponential respiration model to alternative models for soil respiration components in a Canadian wildfire chronosequence (FireResp v1.0)

“…7). Measured autotrophic respiration in actively growing highlatitude boreal forests (Bond-Lamberty et al, 2004;Vogel et al, 2005Vogel et al, , 2014Pumpanen et al, 2015) or inferred from synthesis studies (Ribeiro-Kumara et al, 2020b;Morgan et al, 2021) can range from 0.5-4 g C m −2 d −1 . Most of the modeled values of R A for all the parameter estimation ap-proaches are within that range.…”