Spatial distribution of fine root biomass in a remnant Eucalyptus tereticornis woodland in Eastern Australia
In forests, the majority of fine roots are located within the upper soil horizons, and fine root biomass decreases with depth. We evaluated spatial patterns in the distribution of fine root biomass and determined relationships with soil properties and vegetation structure in a Eucalyptus tereticornis woodland in East Australia. Fine root biomass (0–50 cm depth) was 678 (± 96.9) g m−2 and decreased exponentially with depth. Total fine root biomass was positively related to aboveground herbaceous biomass and increased with increasing proximity to larger trees, reflecting contributions from both herbaceous understorey plants and mature trees. Plants produced more fine roots in soil patches with lower organic matter content, possibly as a functional response to increase acquisition of essential nutrients in more nutrient-depleted soils. Aboveground plant attributes were more important predictors of fine roots in the shallowest layer, while water availability was a stronger predictor of fine root biomass in deeper layers, likely reflecting the harsh climatic conditions prior to sampling. Fine roots represent an important gap in many ecosystem models despite being key for biogeochemical cycling. Here, we showed that the spatial patterns of fine root biomass can be inferred from soil and vegetation characteristics across remnant Australian Eucalyptus woodlands.
KeywordsFine roots Eucalyptus woodland Path analysis Soil properties
The experimental site is part of a TERN Super-site facility. We thank Mr. John Hughes who contributed with sample collection and processing. We also thank Mingkai Jiang for useful and constructive comments on an early version of the draft. R.O.-H. is financially supported by a Ramón y Cajal Fellowship from MICIU (RYC-2017-22032).
Compliance with ethical standards
Conflict of interest
The authors declare no conflict of interest.
- Gale MR, Grigal DF, Harding RB (1991) Soil productivity index: predictions of site quality for white spruce plantations. Soil Sci Soc Am J 55:1701–1708. https://doi.org/10.2136/sssaj1991.03615995005500060033x CrossRefGoogle Scholar
- Gonzalez M, Augusto L, Gallet-Budynek A, Xue J, Yauschew-Raguenes N, Guyon D, Trichet P, Delerue F, Niollet S, Andreasson F, Achat DL, Bakker MR (2013) Contribution of understory species to total ecosystem aboveground and belowground biomass in temperate Pinus pinaster Ait. forests. For Ecol Manage 289:38–47. https://doi.org/10.1016/j.foreco.2012.10.026 CrossRefGoogle Scholar
- Leuschner C, Hertel D, Schmid I, Koch O, Muhs A, Hölscher D (2004) Stand fine root biomass and fine root morphology in old-growth beech forests as a function of precipitation and soil fertility. Plant Soil 258:43–56. https://doi.org/10.1023/B:PLSO.0000016508.20173.80 CrossRefGoogle Scholar
- Mccormack ML, Dickie IA, Eissenstat DM, Fahey TJ, Fernandez CW, Guo D, Helmisaari HS, Hobbie EA, Iversen CM, Jackson RB, Leppälammi-Kujansuu J, Norby RJ, Phillips RP, Pregitzer KS, Pritchard SG, Rewald B, Zadworny M (2015) Redefining fine roots improves understanding of below-ground contributions to terrestrial biosphere processes. New Phytol 207:505–518. https://doi.org/10.1111/nph.13363 CrossRefPubMedGoogle Scholar
- Ochoa-Hueso R, Hughes J, Delgado-Baquerizo M, Drake JE, Tjoelker MG, Piñeiro J, Power SA (2017) Rhizosphere-driven increase in nitrogen and phosphorus availability under elevated atmospheric CO2 in a mature Eucalyptus woodland. Plant Soil 416:283–295. https://doi.org/10.1007/s11104-017-3212-2 CrossRefGoogle Scholar
- Pinheiro J, Bates D, DebRoy S, Sarkar D, Authors E, Heisterkamp S, Van Willigen B (2017) Package “nlme”: linear and nonlinear mixed effects models. R Package Version 3.1-131Google Scholar
- Power SA, Barnett KL, Ochoa-Hueso R, Facey SL, Gibson-Forty EVJ, Hartley SE, Nielsen UN, Tissue DT, Johnson SN (2016) DRI-Grass: a new experimental platform for addressing grassland ecosystem responses to future precipitation scenarios in South-East Australia. Front Plant Sci 7:1373. https://doi.org/10.3389/fpls.2016.01373 CrossRefPubMedPubMedCentralGoogle Scholar
- R Core Team (2017) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
- Schmidt MWII, Torn MS, Abiven S, Dittmar T, Guggenberger G, Janssens IA, Kleber M, Kögel-Knabner I, Lehmann J, Manning DACC, Nannipieri P, Rasse DP, Weiner S, Trumbore SE (2011) Persistence of soil organic matter as an ecosystem property. Nature 478:49–56. https://doi.org/10.1038/nature10386 CrossRefPubMedGoogle Scholar