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

SIMPLE SUMMARY: Larger pine shoot beetle (Tomicus piniperda), which occupies a dominant position among secondary pests of Eurasian pine stands, is also a species whose activity leads to a number of favourable effects in relation to the functioning of ecosystems and broadly defined biodiversity. Thus it is necessary to have available an accurate, statistically based method for estimating its population. A fully non-invasive method for determining the numbers of T. piniperda can explain approximately 93% of the variation in the number of galleries in natural traps. The method may serve as a valuable supplement to existing methods used in the monitoring of T. pinierda populations. It may be used in nature reserves and in conservation-oriented forestry. ABSTRACT: 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% [Formula: see text] 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.