Current issue: 58(4)
A sensitive framework has been developed for modelling young radiata pine (Pinus radiata D. Don) survival, its growth and size class distribution, from time of planting to age 5 or 6 years. The data and analysis refer to the Central North Island region of New Zealand. The survival function is derived from a Weibull probability density function, to reflect diminishing mortality with the passage of time in young stands. An anamorphic family of trends was used, as very little between-tree competition can be expected in young stands. An exponential height function was found to fit best the lower portion of its sigmoid form. The most appropriate basal area/ha exponential function included an allometric adjustment which resulted in compatible mean height and basal area/ha models. Each of these equations successfully represented the effects of several establishment practices by making coefficients linear functions of site factors, management activities and their interactions. Height and diameter distribution modelling techniques that ensured compatibility with stand values were employed to represent the effects of management practices on crop variation. Model parameters for this research were estimated using data from site preparation experiments in the region and were tested with some independent data sets.
The pine weevil Hylobius abietis L. is an economically important pest insect that kills high proportions of conifer seedlings in reforestation areas. It is present in conifer forests all over Europe but weevil abundance and risk for damage varies considerably between areas. This study aimed to obtain a useful model for predicting damage risks by analyzing survey data from 292 regular forest plantations in northern Sweden. A model of pine weevil attack was constructed using various site characteristics, including both climatic factors and factors related to forest management activities. The optimal model was rather imprecise but showed that the risk of pine weevil attack can be predicted approximatively with three principal variables: 1) the proportion of seedlings expected to be planted in mineral soil rather than soil covered with duff and debris, 2) age of clear-cut at the time of planting, and 3) calculated temperature sum at the location. The model was constructed using long-run average temperature sums for epoch 2010, and so effects of climate change can be inferred from the model by adjustment to future epochs. Increased damage risks with a warmer climate are strongly indicated by the model. Effects of a warmer climate on the geographical distribution and abundance of the pine weevil are also discussed. The new tool to better estimate the risk of damage should provide a basis for foresters in their choice of countermeasures against pine weevil damage in northern Europe.