A Non-Invasive Method of Estimating Populations of Tomicus Piniperda on Scots Pine (Pinus Sylvestris L.)

• Published in: Insects (Basel, Switzerland) Vol. 13; no. 11; p. 1071
• Main Authors: Zubek, Karol, Czerwik-Marcinkowska, Joanna, Borkowski, Andrzej
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 20.11.2022; MDPI
• Subjects: Bark; Biodiversity; Climate change; Climate effects; Estimation; Evergreen trees; Forest management; Forestry; Forests; Galleries; larger pine shoot beetle; Methods; Nature reserves; Pests; Pine; Pine trees; Pinus sylvestris; Population (statistical); population density estimation; Population dynamics; Sea level; Stand structure; statistical model; Stems; Tomicus piniperda; Traps; Trees; Tunnels; larger pine shoot beetle; statistical model; biodiversity; population density estimation; forest management
• ISSN: 2075-4450; 2075-4450
• DOI: 10.3390/insects13111071

The fully non-invasive method presented here can be used to evaluate Tomicus piniperda L. population sizes in areas subject to strict protection. Data were collected in 2021–2022 in forests containing P. sylvestris, with different stand structures, in the Suchedniowsko-Oblęgorski Landscape Park, Poland. Entomological analyses were carried out on natural traps made from live uncolonised trees. Stepwise regression was used to describe the size of T. piniperda populations. From a set of features representing stem colonisation parameters, stem traits and habitat, the following had a significant effect (p < 0.05) on the total number of galleries of T. piniperda on stems: (1) the number of T. piniperda maternal tunnels in the sixth stem section covering 2.5% of the total length, (2) the length of the stem section with bark thickness greater than 7 mm, and (3) stand structure (homogeneous Scots pine stands). The model can explain 93% (Radj2=0.9333) of the variability in the total number of T. piniperda galleries on trap trees. The mean relative error of estimation is 20.1%. The proposed method is particularly valuable in a climate context. The data obtained enable the prediction of the direct effects of climate change on the population dynamics of T. piniperda in natural forests.