Current issue: 55(4)
Under compilation: 55(5)
Thekopsora areolata (Fr.) Magnus is a serious cone pathogen that reduces seed crop of Picea abies (L.) Karst. and other Picea spp. Natural sporulation of T. areolata was investigated in nine Norway spruce seed orchards suffering from severe successive T. areolata epidemics in Finland. Habitats occupied by Vaccinium myrtillus L., V. vitis-idaea L., Empetrum nigrum L. and Calluna vulgaris (L.) Hull, and a number of other wild species belonging to ground flora were investigated for Thekopsora areolata uredinia 9–10 times in May–September 2018–2019. Occurrence of Thekopsora uredinia was estimated in current-year leaves of the plants in ca. 25 sample plots of 1 m2 in each seed orchard. A sample of plant leaves with rust uredinia or necrotic pustules were collected from each plot. No rust fruiting stages of T. areolata were found on any of the test species of ground flora. However, rust uredinia were observed regularly on leaves of V. myrtillus and V. vitis-idaea in all seed orchards between mid-July and the end of September. Rust sporulation started on V. myrtillus in July and on V. vitis-idaea in August. Based on symptoms, uredinia and spore morphology, the rust on both V. myrtillus and V. vitis-idaea was identified as blueberry rust, Naohidemyces vaccinii (Jørst.) S. Sato, Katsuya & Y. Hirats. ex Vanderwegen & Fraiture. The uredinial stage of the rust on Vaccinium spp. were described. No evidence of natural sporulation of T. areolata on wild plant species other than Prunus was observed in Finnish Norway spruce seed orchards.
Our main objective was to determine whether various genetically improved reproductive materials of Scots pine (Pinus sylvestris L.) differ in growth rhythm, autumn cold acclimation and resilience from unimproved materials. The study consisted of two successive indoor experiments with Scots pine seedlings representing four levels of genetic gain (unimproved natural stands, first-generation seed orchards, 1.5-generation seed orchards and seed orchards established with freezing-tested parents) and a wide range of geographical origins within Finland. The seedlings were assessed for terminal shoot elongation, growth cessation, bud set, freezing injuries and bud flushing over the first growth period. All the adaptive traits showed a latitudinal trend regardless of the genetic level. Seed orchard progenies and natural stand progenies did not differ significantly in the timing of growth cessation, bud set, and the flushing rate of the frost-injured seedlings, after the trait variation was adjusted to the latitude of origin. The differences in autumn frost hardiness were insignificant, too, except for the somewhat higher injury rate displayed by the first-generation seed orchard materials. The finding was not conclusive due to ambiguous results from the two experiments. Overall, we did not find evidence of alarming compromises in the adaptive performance of genetically improved materials.
Spectral mixture analysis was used to estimate the contribution of woody elements to tree level reflectance from airborne hyperspectral data in boreal forest stands in Finland. Knowledge of the contribution of woody elements to tree or forest reflectance is important in the context of lea area index (LAI) estimation and, e.g., in the estimation of defoliation due to insect outbreaks, from remote sensing data. Field measurements from four Scots pine (Pinus sylvestris L.), five Norway spruce (Picea abies (L.) Karst.) and four birch (Betula pendula Roth and Betula pubescens Ehrh.) dominated plots, spectral measurements of needles, leaves, bark, and forest floor, airborne hyperspectral as well as airborne laser scanning data were used together with a physically-based forest reflectance model. We compared the results based on simple linear combinations of measured bark and needle/leaf spectra to those obtained by accounting for multiple scattering of radiation within the canopy using a physically-based forest reflectance model. The contribution of forest floor to reflectance was additionally considered. The resulted mean woody element contribution estimates varied from 0.140 to 0.186 for Scots pine, from 0.116 to 0.196 for birches and from 0.090 to 0.095 for Norway spruce, depending on the model used. The contribution of woody elements to tree reflectance had a weak connection to plot level forest variables.