Extensive tree health monitoring networks are useful in revealing the impacts of widespread biotic damage in boreal forests

Environ Monit Assess. 2010 Sep;168(1-4):159-71. doi: 10.1007/s10661-009-1100-9. Epub 2009 Jul 24.

Abstract

We surveyed the regional distribution of conifer defoliation in Finland with an extensive monitoring network during 1995-2006 (EU Forest Focus Level I). The average defoliation in the whole Finland was 10.3% in pine and 19.9% in spruce. The sharp changes were often related to abiotic and biotic factors. The mean age of the stand explained more than one half of the between-plot variance in defoliation. In a variance component analysis, the main effect of years was negligible, while most of the random variation was due to plot main effect and plot x year interaction. About one fifth of the defoliation could be attributed to abiotic or biotic damage, and there were strong local correlations, e.g., between the changes in defoliation and degree of pine sawfly (Diprionidae) damage. There were clear temporal and spatial patterns in the incidence of the most important causes [Scots pine: Scleroderris canker (Gremmeniella abietina), pine shoot beetles (Tomicus sp.), and pine sawflies (Diprion pini, Neodiprion sertifer); Norway spruce: rust fungi (primarily Chrysomyxa ledi)]. Our results suggest that extensive monitoring networks can reveal useful information about the widespread outbreaks of pest organisms (insects and fungi) already in their increase phases, giving some time for management decisions. In a changing climate, large-scale, regular monitoring of tree health, including abiotic and biotic causes, is more important than ever before.

MeSH terms

  • Biodiversity
  • Conservation of Natural Resources
  • Environmental Monitoring*
  • Environmental Pollution / analysis
  • Environmental Pollution / statistics & numerical data
  • Epidemiological Monitoring
  • Finland
  • Forestry*
  • Mycoses / epidemiology
  • Plant Diseases / microbiology
  • Plant Diseases / parasitology
  • Plant Diseases / statistics & numerical data*
  • Trees / growth & development*
  • Trees / microbiology
  • Trees / parasitology