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Browsing by Subject "pilkkumäntypistiäinen"

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  • Lyytikäinen, Minna (2013)
    Climate change and following extreme weather patterns can increase forest damages caused by pest insects especially in higher latitudes. The number, density and intensity of damages by pest insects already have increased because of the changing conditions. Pest insects can e.g. cause reduced tree growth and even tree death. Defoliation by the Common Pine Sawfly (Diprion pini L.) causes severe growth losses and tree mortality of Scots Pine (Pinus sylvestris L.). D. pini has caused damages in Finland over 500 000 hectares between years 1997–2001. The field work was carried out in Palokangas area, Ilomantsi, eastern Finland in years 2002–2010. Stand- and tree-wise characteristics were measured on 11 plots. Tree-wise defoliation with 10% accuracy and amount of D. pini cocoons and fallen shoots of P. sylvestris were estimated annually. In addition, radial tree growths were measured from total of n trees in 2010. The aim this study was to estimate the effect of the natural enemies on population densities of D. pini. The aim was also to estimate the effect of the defoliation caused by D. pini on tree growth. In addition, the aim was also to estimate the consequence of a beetle attack by pith borers (Tomicus spp.) to the defoliation. Effect of natural enemies as regulative factors was estimated from D. pini cocoons. Natural enemies were divided into birds, small mammals and to insect families of Ichneumonidae, Chalcidoidea, Tachinidae, Elateridae and Carabidae. Consequence of beetle attack was assessed from fallen shoots. Tree growth simulation was used to estimate economic losses. Growth losses were estimated from drill chip sample. Logistic regression was used to explicate tree-wise defoliation with tree- and stand-wise variables. Two different classification schemes with threshold values of 20% (class 1) and 30% (class 2) of defoliation were used in regression. The major regulative factor was Ichneumonid parasites (22%) and the second powerful regulative factor was small mammals (21%). Relative proportion of natural enemies increased along the research period as defoliation percentages decreased. Consequence of beetle attack was most violent in 2004 (17 shoots/ m²). Plot-wise defoliation level varied significantly between the years and the plots. The mean defoliation level was 37% in 2002 and 22% in 2010. The most substantial defoliation was in plot 9 in 2005, over 99%. Simulated economic losses were perceptible only on plots 9 and 16; 2785 € and 1623 € per hectare, respectively. Defoliation by D. pini caused growth losses for radial growth in different defoliation classes. The mean growth loss of severe damaged trees (70–100% of defoliation) was approximately 65% and of trees with low defoliation level (0–10% of defoliation) 40%. Classification accuracy of logistic regression for class 1 was 92.4% with kappa value of 0.81 and 94.2% and 0.84 for class 2, respectively. The results of this study showed that control of natural enemies effected on D. pini density. Population density of D. pini affected the defoliation level; when population density was low the defoliation was milder. Peak sawfly densities can affect tree growth during outbreaks. Consequence beetle attack by the pith borers was only slight and delayed.
  • Puolakka, Paula (2010)
    Leaf and needle biomasses are key factors in forest health. Insects that feed on needles cause growth losses and tree mortality. Insect outbreaks in Finnish forests have increased rapidly during the last decade and due to climate change the damages are expected to become more serious. There is a need for cost-efficient methods for inventorying these outbreaks. Remote sensing is a promising means for estimating forests and damages. The purpose of this study is to investigate the usability of airborne laser scanning in estimating Scots pine defoliation caused by the common pine sawfly (Diprion pini L.). The study area is situated in Ilomantsi district, eastern Finland. Study materials included high-pulse airborne laser scannings from July and October 2008. Reference data consisted of 90 circular field plots measured in May-June 2009. Defoliation percentage on these field plots was estimated visually. The study was made on plot-level and methods used were linear regression, unsupervised classification, Maximum likelihood method, and stepwise linear regression. Field plots were divided in defoliation classes in two different ways: When divided in two classes the defoliation percentages used were 0–20 % and 20–100 % and when divided in four classes 0–10 %, 10–20 %, 20–30 % and 30–100 %. The results varied depending on method and laser scanning. In the first laser scanning the best results were obtained with stepwise linear regression. The kappa value was 0,47 when using two classes and 0,37 when divided in four classes. In the second laser scanning the best results were obtained with Maximum likelihood. The kappa values were 0,42 and 0,37, correspondingly. The feature that explained defoliation best was vegetation index (pulses reflected from height > 2m / all pulses). There was no significant difference in the results between the two laser scannings so the seasonal change in defoliation could not be detected in this study.