Abstract
Pine wilt disease (PWD) is considered as the most destructive forest-invasive alien species in China. We measured gas exchange parameters and foliar carbon isotope ratios (δ(13)C) of different infection phases of Masson pine in order to investigate the effect of Bursaphelenchus xylophilus infection on photosynthetic responses and resource-use efficiency. The results showed that net photosynthetic rate (P(n)), transpiration rate (T), stomatal conductance (g(s)), and internal CO (2) concentrations (C(i)) decreased in the infested trees at photosynthetic photon flux density (PPFD) levels from 0 to 2,000 μmol m(-2) s(-1) compared with controls. The maximum net photosynthetic rate (P(max)) was significantly declined in the infected trees than in controls (p < .05). There also exist significant differences in dark respiration rate (R(d)) among different infection phases (p < .05), but the value is highest in the middle infection phase, followed by the control and then the terminal infection phase. This indicates that Pinus massoniana plants need to consume more photosynthetic products during the middle infection phase in order to defend against pine sawyer beetle feeding and PWD infection. Isotopic analysis revealed a significant decrease of the foliar δ(13)C (p < .05), as much as 2.5‰ lower in the infected trees. The mean leaf N content was about 12.94% less in the middle infection phase and 27.06% less in the terminal infection phase, causing a significant increase of the foliar C:N ratio in infested trees. Both of the net photosynthetic rates and foliar δ(13)C were linearly correlated with the foliar N content. We also found a significant decrease (p < .05) of resource-use efficiency in PWD-induced P. massoniana plants, which can be attributed to the closure of stomatal pores and the inactivation or loss of both Rubisco and other key Calvin cycle enzymes. This study highlights the impact of photosynthetic characteristics, foliar carbon isotope ratios, and resource-use efficiency of PWD-induced trees, which can help identify PWD infestations at the photosynthetic and physiological levels so as to better facilitate management actions.