Assessment of air toxicity in the megalopolis of Krasnoyarsk using long-term monitoring of suburban pine forests

Integr Environ Assess Manag. 2023 Jul;19(4):980-987. doi: 10.1002/ieam.4675. Epub 2022 Sep 26.

Abstract

The present study develops the application of suburban forests as bioindicators, with the industrial metropolis of Krasnoyarsk (Central Siberia, Russia) taken as an example. Huge forests, such as those found in large Siberian territories, are climate-forming for the entire planet. Hence, their conservation is essential at both the local and global scales. During the period 2002-2021, the vigor state of two pine forests was evaluated using several inventory and morphological parameters: needle damage, deterioration in tree condition, increased entropy, and tree mortality. Additionally, an original bioindication parameter was applied: episodic increase in the size of needles was analyzed. We hypothesized that this increase in needle size was related to the activation of tree protection at the initial stage of tree damage; the mechanism assumes a redirection of sugar transport into the crown to aid tree regeneration. All parameters were measured annually on six permanent sample plots; each plot included 200-300 numbered trees of similar age (approximately 60-80 years). The long-term parameter changes were analyzed and attributed to chronic exposure to industrial air pollution. Significant changes in pine-forest parameters observed over the past few years (2019-2021) may indicate an approaching stage of irreversible toxic damage that is the destruction of the entire forest system. The results encourage involving forest-based bioindication in the regional system of ecological monitoring. Forest-based bioindication can be used as a tool for evaluating the efficiency of long-term governmental activity on air quality in industrial metropolises. Integr Environ Assess Manag 2023;19:980-987. © 2022 SETAC.

Keywords: Air pollution; Metropolis in Central Siberia; Needle discoloration; Suburban pine forests; Tree mortality.

MeSH terms

  • Air Pollution*
  • Climate
  • Forests*
  • Siberia
  • Trees