Relating Biomass and Leaf Area Index to Non-destructive Measurements in Order to Monitor Changes in Arctic Vegetation

  • Wenjun Chen
  • Junhua Li
  • Yu Zhang
  • Fuqun Zhou
  • Klaus Koehler
  • Sylvain LeBlanc
  • Robert Fraser
  • Ian Olthof
  • Yinsuo Zhang
  • Jixin Wang
Keywords: monitoring, aboveground biomass, foliage biomass, LAI, percent cover, mean height, vegetation, seasonal change, long-term change, Arctic


This paper reports an alternative method for seasonal and long-term monitoring of biomass and the leaf area index (LAI) at Arctic tundra sites. Information related to the historical and projected change in abundance and distribution of biomass and LAI is required to address numerous environmental and resource management issues. Observations of earth from satellites could potentially be used to derive seasonal and long-term changes in biomass and the LAI. To realize this potential, seasonal and long-term ground monitoring data for validation are essential; however, the conventional destructive sampling method for measuring biomass and the LAI does not allow repetitive measurements at the same plots and thus is not suitable for monitoring change over time. Alternative methods, such as sampling nearby similar plots, can be laborious and easily subject to large sampling errors, especially in Arctic tundra sites with low vegetation cover. In this study, we developed a practical method for relating non-destructive measurements (percent cover and mean height) to biomass and the LAI for 13 major Arctic plant groups, or seven plant functional types, on the basis of measurements at 196 plots across Canada’s Arctic tundra ecosystems. Using the method at the plant group level to estimate plot total vascular aboveground biomass, foliage biomass, and LAI, we had r2 = 0.91–0.95 and relative mean absolute error of 25–29%. By this method, one could monitor seasonal and long-term changes in biomass and the LAI through repeated, non-destructive observations of percent cover and mean height at the same permanent plots.