Rhizodeposition: a carbon efflux often neglected in functional-structural plant models (Title: Times New Roman 14 pts, bold)

Pekka Nygren1 and Jari Perttunen2 (Times New Roman 11 pts, bold)

1Department of Forest Sciences, PO Box 27, 00014 University of Helsinki, Finland, 2Vantaa Res. Ctr, Finnish Forest Research Institute, PO Box 18, 01301 Vantaa, Finland (Times New Roman 11 pts, italics)

*correspondence:

Highlights:Rhizodeposition of carbon to soil and rhizospheric microbiota may account for 20% of C assimilated in photosynthesis. Neglecting rhizodeposition in functional-structural plant models may cause serious underestimations of C assimilation if the models are validated using C balance without rhizodeposition, or serious overestimations of biomass production if photosynthesis is accurately estimated.

Keywords:Carbon balance, LIGNUM model, Populus deltoides, root respiration

INTRODUCTION (Chapter headings: Times New Roman 11 pts, CAPS; centered)

Roots are a site of strong carbon efflux from trees: C is used for fine root respiration, rhizodeposition of C from roots to soil is active forming the rhizosphere, and C-heterotrophic mycorrhizal fungi are an important C sink (Jones et al. 2009). Högberg et al. (2008) have shown that much of the C lost from the roots of Pinus sylvestris L. in rhizodeposition is recently fixed C; this C is not used for forming tree structure but is directly transported from leaves to roots. Carbon efflux in rhizodeposition varies between plant species, plant developmental stage, and environmental conditions but it may be up to 2030% of C allocated to roots (Jones et al. 2009). (Text body: Times New Roman, 11 pts; paragraph justified, first line indented by 0.5 cm)

Rhizodeposition is the sum of several processes (Jones et al. 2009): i) root cap and border cell loss; ii) death and lysis of root cells; iii) C flow to symbiotic associates in soil; iv) gaseous losses; v) leakage of solutes from living cells (root exudation); and vi) insoluble polymer secretion from living cells (mucilage). It is very difficult to distinguish these processes even under laboratory conditions and, consequently, our understanding on their ecological significance is still limited in spite of the ca. 5000 physiological studies published on rhizodeposition.

Fine root respiration is another important belowground C efflux. It is relatively better known than rhizodeposition yet important knowledge gaps exist; especially under field conditions. It is difficult to distinguish between respiration by fine roots themselves and by mycorrhizal fungi. In boreal ecosystems, root and mycorrhizal respiration seems to be about half of the total CO2 efflux from soil (Bhupinderpal-Singh et al. 2003) and fine root respiration may account up to 20% of C fixed in photosynthesis (Horwath et al. 1994).

In functional-structural plant models (FSPM), belowground C allocation is often modelled with fewer details than aboveground development. Many of these models, like the LIGNUM tree model (Perttunen et al. 1996), use C balance-based estimation for the allocation of photosynthates to different tree compartments, including the root system. If net C assimilation is accurately estimated, ignoring rhizodeposition in the C balance may cause serious underestimation of the C allocation to belowground and, consequently, serious overestimation of shoot biomass. Or, if the model results are validated using observed standing biomass, net C assimilation is probably strongly underestimated because C lost in rhizodeposition is not accounted for.

Our aim was to test a few concepts of rhizodeposition and their effects on C balance and net C assimilation estimates of eastern cottonwood (Populus deltoides W. Bartram ex Marshall) produced by the LIGNUM model. Although separation of fine root and mycorrhizal respiration is difficult in the field, we conceptually separated root respiration from rhizodeposition and included all C flux to mycorrhizal fungi to the latter for testing their potential effects on C balance.

SIMULATIONS

We made simulations with the LIGNUM model as modified by Lu (2006): i) radiation interception, photosynthesis, and leaf respiration were modelled with half-hourly time steps, ii) accumulated net C assimilation was allocated to different tree compartments, including roots, four times during a growing season, iii) tree structure was updated at these times according to the C balance, and iv) the model was parameterised for P. deltoides. We simulated four cases: i) root system was considered homogeneous and rhizodeposition was not included (“basic”); ii) root system was divided into fine and coarse roots with high turnover and respiration rate for fine roots (“RR” case); iii) case “RR” + 30% of root C lost in rhizodeposition (“RR + RD 30%”), the highest estimate by Jones et al. (2009); and “RR + RD 70%” case, i.e. root respiration with the very high rhizodeposition rate, in which 70% of root C is lost in rhizodeposition.

Combining data from several sources, we estimated that fine roots formed ca. 50% of the root mass of P. deltoides (Coyle and Coleman 2005) and fine root respiration was ca. 0.3 g[C]g1[BM] (Horwath et al. 1994; Coleman et al. 2000). Fine root turnover rate was assumed to be equivalent to renewal of all fine root biomass within a growing season (Block et al. 2006). We compared the model results with data from the field site used for model parameterisation.

RESULTS AND DISCUSSION

Fig. 1. Total woody biomass of Populus deltoides at 4-yr-age in a field site and according to four simulation cases with the LIGNUM model. Error bar for the field data shows the 95% confidence interval of the mean. (Figure captions and tables: Times New Roman 10 pts) / Fig. 2. Evolution of annual net C assimilation (leaf photosynthesis – leaf respiration) of P. deltoides under four different rhizodeposition simulation scenarios with the LIGNUM model

The simulation cases “basic” and “RR” resulted in clear overestimation of woody biomass (stem, branches, and roots) of 4-yr-old P. deltoides in comparison to field observations (Fig. 1). Both cases involving rhizodeposition resulted in woody biomass that was within the 95% confidence interval of the field-measured mean, the case “RR + RD 70%” being the closest. When simulations were continued over eight years, the case “RR” resulted in such a high fine root respiration at year 8 that whole tree respiration exceeded the net C assimilation (photosynthesis – leaf respiration), and the tree collapsed. Thus, case “RR” stops at year 7 in Fig. 2. The “RR + RD70%” produced visibly more leaf biomass than the other cases (Fig. 3): the leaf biomass in 7-yr-old trees was 3.51 kg in case “basic”, 2.59 kg in “RR”, 3.18 kg in “RR + RD30%”, and 5.12 kg in “RR + RD70%”. The respective root:shoot ratios were 1.08, 1.25, 0.71, and 0.29; the root:shoot ratio observed in the field was ca. 0.30 (Pallardy et al. 2003).

Several recent studies indicate fine root turnover rate to be much slower than assumed and C may reside in them for several years (Gaudinski et al. 2001; Matamala et al. 2003). This has important implications to tree C balance: e.g. the C allocation to fine roots of P. sylvestris may be grossly overestimated and respirational loss of C underestimated if fine root turnover is too high (Högberg et al. 2002). Our simulations indicate that excessive fine root turnover rate may even cause tree collapse in modelling (case “RR”). Further, the best match between observations and simulations was achieved by a case of very high rhizodeposition rate in comparison to C allocation to roots. The “RR + RD30%” corresponds to high end of cases reported by Jones et al. (2009) while the best-fit case at 4 yrs, “RR + RD70%” implies rhizodeposition at double the highest rate suggested by them. These results clearly indicate that C allocation to fine root turnover vs. rhizodeposition in functional-structural tree modelling requires further study. Thus, rhizodeposition should be included to FSPMs. Especially, model validation with C balance ignoring rhizodeposition may lead to acceptance of a model with serious underestimation of net C assimilation. Future research related to FSPM should consider the means of modelling and parameterising rhizodeposition among the processes considered in the model. The modellers may learn a lot from root scientists while modelling results may inspire new root research.

Fig. 3. Seven-year-old P. deltoides trees simulated according to the “basic” case (left) and the “RR + RD70%” case (right).

LITERATURE CITED

Bhudinpardel-Singh, Nordgren A, Ottosson Löfvenius M, Högberg MN, Mellander P-E, Högberg P. 2003. Tree root and soil heterotrophic respiration revealed by girdling of boreal Scots pine forest: extending observations beyond the first year. Plant, Cell & Environment 26:12871296. (Times New Roman, 10 pts, follow example for bold and italics; paragraph formatting justified, hanging by 0.5 cm)

Block RMA, van Rees KCJ, Knight JD. 2006. A review of fine root dynamics in Populus plantations. Agroforestry Systems 67:7384.

Coleman MD, Dickson RE, Isebrands JG. 2000. Contrasting fine-root production, survival and soil CO2 efflux in pine and poplar plantations. Plant and Soil 225:129-139.

Coyle DR, Coleman MD. 2005. Forest production responses to irrigation and fertilization are not explained by shifts in allocation. Forest Ecology and Management 208:137152.

Gaudinski JB, Trumbore SE, Davidson EA, Cook AC, Markewitz D, Richter DD. 2001. The age of fine-root carbon in three forests of the eastern United States measured by radiocarbon. Oecologia 129:420429.

Horwath WR, Pregitzer KS, Paul EA. 1994. 14C allocation in tree-soil system. Tree Physiology 14:11631176.

Högberg P, Högberg MN, Göttlicher SG, et al. 2008. High temporal resolution tracing of photosynthate carbon from the tree canopy to forest soil microorganisms. New Phytologist 177:220228.

Högberg P, Nordgren A, Ågren GI. 2002. Carbon allocation between tree root growth and root respiration in a boreal pine forest. Oecologia 132:579581.

Jones DL, Nguyen C, Finlay RD. 2009. Carbon flow in the rhizosphere: carbon trading at the soil-root interface. Plant and Soil 321:533.

Lu M. 2006. Simulating cottonwood tree growth in flood plains using the LIGNUM modeling method. Ph.D. thesis, University of Missouri–Columbia, USA. 174 p.

Matamala R, González-Meler MA, Jastrow JD, Norby RJ, Schlesinger WH. 2003. Impacts of fine root turnover on forest NPP and soil C sequestration potential. Science 302:13851387.

Pallardy SG, Gibbins DE, Rhoads JL. 2003. Biomass production by two-year-old poplar clones on floodplain sites in the Lower Midwest, USA. Agroforestry Systems 59:2126.

Perttunen J, Sievänen R, Nikinmaa E, Salminen H, Saarenmaa H, Väkevä J 1996. LIGNUM: A tree model based on simple structural units. Annals of Botany 77: 8798.