Leaf and fine root carbon stocks and turnover are coupled across Arctic ecosystems

Abstract

Estimates of vegetation carbon pools and their turnover rates are central to understanding and modelling ecosystem responses to climate change and their feedbacks to climate. In the Arctic, a region containing globally important stores of soil carbon, and where the most rapid climate change is expected over the coming century, plant communities have on average sixfold more biomass below ground than above ground, but knowledge of the root carbon pool sizes and turnover rates is limited. Here, we show that across eight plant communities, there is a significant positive relationship between leaf and fine root turnover rates (r(2) = 0.68, P < 0.05), and that the turnover rates of both leaf (r(2) = 0.63, P < 0.05) and fine root (r(2) = 0.55, P < 0.05) pools are strongly correlated with leaf area index (LAI, leaf area per unit ground area). This coupling of root and leaf dynamics supports the theory of a whole-plant economics spectrum. We also show that the size of the fine root carbon pool initially increases linearly with increasing LAI, and then levels off at LAI = 1 m(2) m(-2), suggesting a functional balance between investment in leaves and fine roots at the whole community scale. These ecological relationships not only demonstrate close links between above and below-ground plant carbon dynamics but also allow plant carbon pool sizes and their turnover rates to be predicted from the single readily quantifiable (and remotely sensed) parameter of LAI, including the possibility of estimating root data from satellites.

The application of ecological stoichiometry to plant–microbial–soil organic matter transformations

“…Changes in plant debris production across major biomes (Fig. Fine-litter and fine-root production fluxes in TUN were calculated from the single studies (Chapin et al 1988, Sullivan et al 2007, Campioli et al 2009, Sloan et al 2013. Data for biome plant detritus production fluxes were compiled or calculated from the following sources: fine-litter production (Potter and Klooster 1997, Hui and Jackson 2006, Zhang et al 2014, fine-root production Jackson 2006, Finer et al 2011a, b), and CWD production (Potter andKlooster 1997, Palace et al 2008).…”

Hyperspectral remote sensing of peatland floristic gradients

“…Instead, PFTs created through the grouping of species into functional groups, which reflect functionprocess-vegetation relationships, are often used to model the responses of peatlands to environmental change and are heavily used for carbon modelling in northern biomes (Gray et al, 2013;Kuiper, Mooij, Bragazza, & Robroek, 2014;Sloan, Fletcher, Press, Williams, & Phoenix, 2013;Ward, Bardgett, McNamara, & Ostle, 2009). Shrubs, graminoids (sedges, rushes, grasses), bryophytes (nonvascular plants such as mosses), lichens, forbs (other herbaceous plants) and trees are all found in peatlands, although shrubs, graminoids and bryophytes are often the three most dominant PFTs (Frolking et al 2009).…”

Evaluation of terrestrial pan-Arctic carbon cycling using a data-assimilation system

“…In order to decrease uncertainties around the balance of photosynthetic inputs and respiratory outputs, future explorations on SOC decomposition by microbial activity (Xenakis and Williams, 2014), nutrient interaction with carbon (Thomas and Williams, 2014), plant traits relationships across pan-arctic regions Sloan et al, 2013), the mechanisims driving carbon use efficiency (Bradford and Crowther, 2013;Street et al, 2013) and the drivers of gross flux 410 coupling , or the effect of fine-scale disturbances such as moth outbreaks (Heliasz et al, 2011;López-Blanco et al, 2017;Lund et al, 2017) should be addressed at the pan-Arctic scale. From a modelling perspective, we consider that more field observations are crucial, specifically on plant and soil decomposition (C stocks turnover rates) (He et al, 2016) and respiratory processes (partitioning of R eco into R a and R h ) (Hobbie et al, 2000;McGuire et al, 2000), not only across the growing season, but also during wintertime (Commane et al, 2017;Zona et al, 2016).…”