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Tervetuloa käyttämään Jukuria, Luonnonvarakeskuksen (Luke) avointa julkaisuarkistoa. Jukurissa on tiedot Luken julkaisutuotannosta. Osa julkaisuista on vapaasti ladattavissa. Luken muodostaneiden tutkimuslaitosten aikaisemmasta julkaisutuotannosta osan tiedot ovat järjestelmässä jo nyt ja kattavuus paranee jatkuvasti.

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Viimeksi tallennetut

  • Predicting forest inventory variables with remote sensing data : the role of number and locality of the training plots
    Pitkänen, Timo P; Kangas, Annika; Myllymäki, Mari; Packalen, Petteri
    Forestry : 4 (Oxford University Press, 2026)
    Field measurements of national forest inventories (NFIs) and auxiliary data derived from remote sensing can be used to model forest inventory variables. Because NFI observations typically cover large areas, training data for modeling is often limited by the number and proximity of the available plots. Determining suitable thresholds for these, however, is complicated and depends on various factors. In this study, we examine how the number and locality of the NFI plots affect the modeling accuracy. With locality, we refer to the spatial proximity of the training plots to the target location, which is often considered a proxy of their representativeness. We used field measurements from the Finnish NFI, collected mainly from managed, conifer-dominated boreal forests, and modeled growing stock volumes and trees’ dominant heights with Sentinel-2 and airborne laser scanning (ALS) data. We then compared prediction errors derived from varying numbers of training plots and modeling attempts where we purposely excluded the nearby plots within a specific radius. As a special case of training plots’ representativeness, we also assessed if models estimated using ALS features were transferable over the production area borders, i.e. scanned with similar quality standards but at different times and using different scanners. Our results indicated that a set of 100 training plots could be regarded as the minimum preferred count regardless of the auxiliary data. Locality affected modeling bias, which increased when the exclusion radius was extended to 50 km or beyond. This bias connected particularly to models’ abilities for adapting to local conditions which resulted in regional under- and overestimates, but these effects were only mildly observable through global statistics over all the applied validation data. Differences between ALS production areas were generally small, but they varied by inventory variable and were more pronounced for features derived from first echoes than from last or all echoes.
  • From breeding to landscape : how genetic improvement and forest management shape multifunctionality in Norway
    Vergarechea, M; Sevillano, I; Steffenrem, A; Ahtikoski, Anssi; Holmström, H; Anton-Fernandez, C
    Journal of environmental management (Elsevier, 2026)
    Balancing wood production, biodiversity, and climate regulation is increasingly challenging for forest management, particularly as societal demands intensify. Despite growing interest in genetic improvement to enhance forest productivity, its implications for multiple ecosystem services (FES) remain poorly quantified. To address this gap, we assessed how genetically improved regeneration material, combined with alternative management regimes, influences FES provision in Norway. Using National Forest Inventory data, a climate-sensitive single-tree simulator, and multi-objective optimization, we projected 100-year outcomes under three strategies: no genetic gain, growth-focused improvement, and combined improvement in growth and wood quality. The strongest responses occurred when genetic improvement targeted both growth and wood quality. Under this scenario, harvest net value increased, ecological hotspot areas expanded, and larger set-aside areas were maintained while meeting national harvest demands. Carbon storage in harvested wood products also increased, whereas carbon sequestration in living biomass showed no consistent trend. Genetic gain reinforced positive interactions between bioenergy and climate regulation but left most other FES relationships broadly unchanged. Varying genetic gain levels produced only minor differences across most indicators, suggesting that long-term outcomes depend more on how improved material is integrated within a flexible management portfolio than on the exact magnitude of genetic gain. Positive responses in the structural biodiversity indicators should be interpreted cautiously, as these proxies capture only a limited subset of ecological dimensions and likely underestimate broader biodiversity trade-offs. Overall, genetically improved material represents a complementary tool for enhancing forest multifunctionality when integrated with adaptive, landscape-scale management.
  • Japanin palamaton pihlaja
    Nuorteva, Heikki
    Metsälehti : 16/2026 (Tapio, 2026)
  • Suomipoika ja kiinalainen puu
    Nuorteva, Heikki
    Metsälehti : 15/2026 (Tapio, 2026)
  • Dendrologinen arvio Katajarannan punaisen tuvan hirsistä
    Helama, Samuli; Sarajärvi, Eemeli; Herva, Hannu
    Totto (Rovaniemen Totto, 2026)