Plant Ecology and Evolution 154(1): 5-14, doi: 10.5091/plecevo.2021.1570
Shrubland biomass and root-shoot allocation along a climate gradient in China
expand article infoJiangchao Guo, Yaoxin Guo, Yongfu Chai, Xiao Liu, Ming Yue
‡ Key Laboratory of Resource Biology and Biotechnology in Western China (Ministry of Education), Northwest University, No. 229 Taibai Road, Xi’an 710069, Shaanxi province, China
Open Access
Abstract

Background – Shrublands are receiving increasing attention because of climate change. However, knowledge about biomass allocation of shrublands at the community level and how this is regulated by climate is of limited availability but critical for accurately estimating carbon stocks and predicting global carbon cycles.

Methods – We sampled 50 typical shrublands along a climate gradient in China and investigated the biomass allocation of shrubland at the community level and the effect of climate on biomass allocation. Shrub biomass was estimated using species-specific allometric relationships and the biomass of understory herbs was collected by excavating the whole plant. Regression analysis was used to examine the relationships between the biomass and the climate factors. RMA were conducted to establish the allometric relationships between the root and the shoot biomass at the community level.

Key results – Shoot, root, and total biomass of shrub communities across different sites were estimated with median values of 206.5, 145.8, and 344.5 g/m2, respectively. Shoot, root, and total biomass of herb communities were estimated at 68.2, 58.9, and 117.2 g/m2, respectively. The median value of the R/S ratio of shrub communities was 0.58 and that of herb communities was 0.84. The R/S ratio of the shrub community showed a negative relationship with mean annual temperature and mean annual precipitation and a positive relationship with total annual sunshine and the aridity index. The R/S ratio of the herb community however showed a weak relationship with climate factors. Shoot biomass of the shrub community was nearly proportional to root biomass with a scaling exponent of 1.17, whereas shoot biomass of the herb community was disproportional to root biomass with a scaling exponent of 2.1.

Conclusions – In shrublands, root biomass was more affected than shoot biomass by climate factors and this is related to water availability as a result of biomass allocation change of the shrub community. The understory herb community was less affected by climate due to the modification of the overstory–understory interaction to the climate-induced biomass allocation pattern. Shoot biomass of shrubs scales isometrically with root biomass at the community level, which supports the isometric theory of above-ground and below-ground biomass partitioning.

Keywords
allometric relationship, biomass allocation, China, climate, shrublands

References

  • Cahoon S.M., Sullivan P.F., Shaver G.R., Welker J.M. & Post E. 2012. Interactions among shrub cover and the soil microclimate may determine future Arctic carbon budgets. Ecology Letters 15(12): 1415–1422. https://doi.org/10.1111/j.1461-0248.2012.01865.x
  • Cairns M.A., Brown S., Helmer E.H., Baumgardner G.A. & Helmer E.H. 1997. Root biomass allocation in the world’s upland forests. Oecologia 111: 1–11. https://doi.org/10.1007/s004420050201
  • Castro H. & Freitas H. 2009. Above-ground biomass and productivity in the Montado: from herbaceous to shrub dominated communities. Journal of Arid Environments 73(4–5): 506–511. https://doi.org/10.1016/j.jaridenv.2008.12.009
  • Chen M.R. 1983. Climate and agriculture in the Qinling Mountains. Shaanxi People’s Press, Xi’an.
  • Cheng D.L. & Niklas K.J. 2006. Above- and below-ground biomass relationships across 1534 forested communities. Annals of Botany 99(1): 95–102. https://doi.org/10.1093/aob/mcl206
  • Chew R.M. & Chew A.E. 1965. The primary productivity of a desert-shrub (Larrea tridentata) community. Ecological Monographs 35(4): 355–375. https://doi.org/10.2307/1942146
  • Corona P., Pasta S., Giardina G., La Mantia T. & Giardina G. 2012. Assessing the biomass of shrubs typical of Mediterranean pre-forest communities. Plant Biosystems 146(2): 252–257. https://doi.org/10.1080/11263504.2011.593200
  • de Martonne E. 1926. L’indice d’aridité. Bulletin de l’Association de Géographes français 3: 3–5.
  • Ding Y. & Dai X. 1994. Temperature variation in China during the last 100 years. Meteorological Monthly 20(12): 19–26. [In Chinese].
  • Fang J.Y., Oikawa T., Kato T., Mo W.H. & Wang Z.H. 2005. Biomass carbon accumulation by Japan’s forests from 1947 to 1995. Global Biogeochemical Cycles 19(2): GB2004. https://doi.org/10.1029/2004GB002253
  • He J., Wang Q. & Hu D. 1997. Studies on the biomass of typical shrubland and their regeneration capacity after cutting. Acta Phytoecologica Sinica 21(6): 512–520. [In Chinese].
  • Hu H.F., Wang Z.H., Liu G.H. & Fu B.J. 2006. Vegetation carbon storage of major shrublands in China. Journal of Plant Ecology 30(4): 539–544. [In Chinese].
  • IPCC 2007. Climate change 2007: impacts, adaptation, and vulnerability. Cambridge University Press, New York.
  • Jackson R.B., Canadell J., Ehleringer J.R., Mooney H.A., Sala O.E. & Schulze E.D. 1996. A global analysis of root distributions for terrestrial biomes. Oecologia 108: 389–411. https://doi.org/10.1007/BF00333714
  • Lambers H., Shane M.W., Cramer M.D., Cramer M.D., Pearse S.J. & Veneklaas E.J. 2006. Root structure and functioning for efficient acquisition of phosphorus: matching morphological and physiological traits. Annals of Botany 98(4): 693–713. https://doi.org/10.1093/aob/mcl114
  • Lecerf A., Evangelista C., Cucherousset J. & Boiché A. 2016. Riparian overstory–understory interactions and their potential implications for forest-stream linkages. Forest Ecology and Management 367: 112–119. https://doi.org/10.1016/j.foreco.2016.02.031
  • Li C.P. & Xiao C.W. 2007. Above- and belowground biomass of Artemisia ordosica communities in three contrasting habitats of the Mu Us desert, northern China. Journal of Arid Environment 70(2): 195–207. https://doi.org/10.1016/j.jaridenv.2006.12.017
  • Li Y., Li K., Tao B. & Xu M. 2010. Simulating and assessing the adaptability of geographic distribution of vegetation to climate change in China. Progress in Geography 29(11): 1326–1332.
  • Liu C., Zhang X. & Zhang Y. 2002. Determination of daily evaporation and evapotranspiration of winter wheat and maize by large-scale weighing lysimeter and micro-lysimeter. Agricultural and Forest Meteorology 111(2): 109–120. https://doi.org/10.1016/S0168-1923(02)00015-1
  • Moreno G., Bartolome J.W., Gea-Izquierdo G. & Cañellas I. 2013. Overstory–understory relationships. In: Campos P. et al. (eds) Mediterranean oak woodland working landscapes. Landscape Series, vol. 16: 145–179. Dordrecht, Springer. https://doi.org/10.1007/978-94-007-6707-2_6
  • Návar J., Méndez E., Nájera A., Graciano J., Dale V. & Parresol B. 2004. Biomass equations for shrub species of Tamaulipan thornscrub of North-eastern Mexico. Journal of Arid Environments 59(4): 657–674. https://doi.org/10.1016/j.jaridenv.2004.02.010
  • Nemani R.R., Keeling C.D., Hashimoto H., et al. 2003. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science 300(5625): 1560–1563. https://doi.org/10.1126/science.1082750
  • Piñeiro G., Paruelo J.M., Jobbágy E.G., Jackson R.B. & Oesterheld M. 2009. Grazing effects on belowground C and N stocks along a network of cattle enclosures in temperate and subtropical grasslands of South America. Global Biogeochemical Cycles 23(2): GB2003. https://doi.org/10.1029/2007GB003168
  • Poorter H., Jagodzinski A.M., Ruiz‐Peinado R., et al. 2015. How does biomass distribution change with size and differ among species? An analysis for 1200 plant species from five continents. New Phytologist 208(3): 736–749. https://doi.org/10.1111/nph.13571
  • Poorter H., Niklas K.J., Reich P.B., Oleksyn J., Poot P. & Mommer L. 2012. Biomass allocation to leaves, stems and roots: meta-analyses of interspecific variation and environmental control. New Phytologist 193(1): 30–50. https://doi.org/10.1111/j.1469-8137.2011.03952.x
  • QGIS Development Team 2012. QGIS Geographic Information System. Version 2.14. Open Source Geospatial Foundation Project. Available from https://qgis.org [accessed 3 Aug. 2020].
  • Ren G., Guo J., Xu M., et al. 2005. Climate changes of China’s mainland over the past half century. Acta Meteorologica Sinica 63: 942–956. [In Chinese].
  • Sah J.P., Ross M.S., Koptur S. & Snyder J.R. 2004. Estimating aboveground biomass of broadleaved woody plants in the understory of Florida Keys pine forests. Forest Ecology and Management 203(1–3): 319–329. https://doi.org/10.1016/j.foreco.2004.07.059
  • Schimel D.S., House J.I., Hibbard K.A., et al. 2001. Recent patterns and mechanisms of carbon exchange by terrestrial ecosystems. Nature 414: 169–172. https://doi.org/10.1038/35102500
  • Serreze M.C., Walsh J.E., Chapin F.S., et al. 2000. Observational evidence of recent change in the northern high-latitude environment. Climatic Change 46: 159–207. https://doi.org/10.1023/A:1005504031923
  • Throop H.L., Reichmann L.G, Sala O.E. & Archer S.R. 2012. Response of dominant grass and shrub species to water manipulation: an ecophysiological basis for shrub invasion in a Chihuahuan Desert Grassland. Oecologia 169: 373–383. https://doi.org/10.1007/s00442-011-2217-4