SEARCH

SEARCH BY CITATION

Keywords:

  • climate change;
  • forest productivity;
  • growth enhancement;
  • temperate-maritime forest

Abstract

To understand how environmental changes have influenced forest productivity, stemwood biomass (B) dynamics were analyzed at 1267 permanent inventory plots, covering a combined 209 ha area of unmanaged temperate-maritime forest in southwest British Columbia, Canada. Net stemwood production (ΔB) was derived from periodic remeasurements of B collected over a 40-year measurement period (1959–1998) in stands ranging from 20 to 150 years old. Comparison between the integrated age response of net stemwood production, ΔB(A), and the age response of stemwood biomass, B(A), suggested a 58 ± 11% increase in ΔB between the first 40 years of the chronosequence period (1859–1898) and the measurement period. To estimate extrinsic forcing on ΔB, several different candidate models were developed to remove variation explained by intrinsic factors. All models exhibited temporal bias, with positive trends in (observed minus predicted) residual ΔB ranging between of 0.40 and 0.64% yr−1. Applying the same methods to stemwood growth (G) indicated residual increases ranging from 0.43 and 0.67% yr−1. Higher trend estimates corresponded with models that included site index (SI) as a predictor, which may reflect exaggeration of the age-decline in SI tables. Choosing a model that excluded SI, suggested that ΔB increased by 0.40 ± 0.18% yr−1, while G increased by 0.43 ± 0.12% yr−1 over the measurement period. Residual G was significantly correlated with atmospheric carbon dioxide (CO2), temperature (T), and climate moisture index (CMI). However, models driven with climate and CO2, alone, could not simultaneously explain long-term and measurement-period trends without additional representation of indirect effects, perhaps reflecting compound interest on direct physiological responses to environmental change. Evidence of accelerating forest regrowth highlights the value of permanent inventories to detect and understand systematic changes in forest productivity caused by environmental change.