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Articles by Mervi Talvitie

Category : Research article

article id 1615, category Research article
Minna Blomqvist, Päivi Lyytikäinen-Saarenmaa, Tuula Kantola, Maiju Kosunen, Mervi Talvitie, Markus Holopainen. (2016). Impacts of natural enemies and stand characteristics on cocoon mortality of the pine sawfly Diprion pini in a Fennoscandian boreal forest. Silva Fennica vol. 50 no. 5 article id 1615. https://doi.org/10.14214/sf.1615
Keywords: needle loss; Diprionidae; population dynamics; forest floor vegetation; parasitism; predation
Highlights: Annual cocoon mortality caused by natural enemies varied between 66% and 80% during the six-year study period, most of it caused by the family Ichneumonidae; Basal area, and coverage of lichen (Lichenes) and lingonberry (Vaccinium vitis-idaea L.) best explained cocoon parasitism and predation; Combination of suitable stand characteristics, abiotic environmental factors, and incomplete control by natural enemies enabled pest species to extend its gradation phase.
Abstract | Full text in HTML | Full text in PDF | Author Info

We investigated the impact of natural enemies on the cocoon mortality of the common pine sawfly (Diprion pini L.) during a six-year period in eastern Finland. The enemies were classified into parasitoids (insect families Chalcidoidea, Ichneumonidae, and Tachinidae), and predators (birds, small mammals, and insect families Elateridae and Carabidae). The appearance of D. pini was estimated as the intensity of annual defoliation. The impact of stand characteristics on the performance of parasitoids and predators was also investigated. Influence of the natural enemy complex on cocoon mortality of D. pini was nearly stable, but defoliation intensity slowly declined towards the end of the study period. Annual cocoon mortality by natural enemies varied between 66% and 80%. Our results verified that the most significant mortality factors were ichneumonid parasitoids and small mammals. Random Forest classification indicated that stand characteristics, such as basal area, and coverage of lichen (Lichenes) and lingonberry (Vaccinium vitis-idaea L.) affected the performance of parasites and predators. We suggest that a combination of optimal stand characteristics, abiotic environmental factors and mild to moderate control by natural enemies acted as drivers, which drove the pine sawfly population to extended gradation. For future forest health management, detailed information on abiotic and biotic regulating factors, along with long-term monitoring campaigns for conifer sawflies are needed to adapt Fennoscandian forests to altered climatic and silvicultural conditions.

  • Blomqvist, University of Helsinki, Department of Forest Sciences, P.O. Box 27 (Latokartanonkaari 7), FI-00014 University of Helsinki, Finland ORCID http://orcid.org/0000-0003-2328-8839 E-mail: minna.blomqvist@helsinki.fi (email)
  • Lyytikäinen-Saarenmaa, University of Helsinki, Department of Forest Sciences, P.O. Box 27 (Latokartanonkaari 7), FI-00014 University of Helsinki, Finland E-mail: paivi.lyytikainen-saarenmaa@helsinki.fi
  • Kantola, Knowledge Engineering Laboratory, Department of Entomology, Texas A&M University, College Station, TX 77843-2475, USA E-mail: tuula.kantola@helsinki.fi
  • Kosunen, University of Helsinki, Department of Forest Sciences, P.O. Box 27 (Latokartanonkaari 7), FI-00014 University of Helsinki, Finland E-mail: maiju.kosunen@helsinki.fi
  • Talvitie, University of Helsinki, Department of Forest Sciences, P.O. Box 27 (Latokartanonkaari 7), FI-00014 University of Helsinki, Finland E-mail: mervi.talvitie@dnainternet.net
  • Holopainen, University of Helsinki, Department of Forest Sciences, P.O. Box 27 (Latokartanonkaari 7), FI-00014 University of Helsinki, Finland E-mail: markus.holopainen@helsinki.fi
article id 335, category Research article
Markus Holopainen, Mervi Talvitie. (2006). Effect of data acquisition accuracy on timing of stand harvests and expected net present value. Silva Fennica vol. 40 no. 3 article id 335. https://doi.org/10.14214/sf.335
Keywords: forest inventory; laser scanning; digital aerial photographs; digital photogrammetry; net present value; expected net present value loss
Abstract | View details | Full text in PDF | Author Info
Modern remote sensing provides cost-efficient spatial digital data that are more accurate than before. However, the influence of increased accuracy and cost-efficiency on simulations of forest management planning has not been evaluated. The aim of the present study was to analyse the effect of data acquisition accuracy on standwise forest inventory by comparing the accuracy and cost of traditional compartmentwise inventory methods with 2D and 3D measurements of digital aerial photographs and airborne laser scanning. Comparison was based on the expected net present value (NPV), i.e. economic losses that consisted of the inventory costs and incorrect timings of treatments. The reference data, totalling 700 ha, were measured from Central Park in the city of Helsinki, Finland. The data were simulated to final cut with a MOTTI simulator, which is a stand-level analysis tool that can be used to assess the effects of alternative forest management practices on growth and timber yield. The results showed that when inventory costs were not considered there were no significant differences between the expected NPV losses in 3D measurements of digital aerial photographs, laser scanning and the compartmentwise method. When inventory costs were taken into account, the compartmentwise method was still the most efficient inventory method in the study area. Forest inventories, however, are usually directed to larger areas when the costs per hectare of remote-sensing methods decrease. As a result of better accuracies, 3D and compartmentwise methods always produce better results than the 2D method when NPV losses are accounted. Simulations of this type are based on the accuracies and costs of the 3D data available today, assuming that the data can be used in tree-level measurements.
  • Holopainen, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: markus.holopainen@helsinki.fi (email)
  • Talvitie, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: mt@nn.fi
article id 354, category Research article
Mervi Talvitie, Olli Leino, Markus Holopainen. (2006). Inventory of sparse forest populations using adaptive cluster sampling. Silva Fennica vol. 40 no. 1 article id 354. https://doi.org/10.14214/sf.354
Keywords: coarse woody debris; adaptive cluster sampling; simple random sampling; drought damage; efficiency
Abstract | View details | Full text in PDF | Author Info
In many studies, adaptive cluster sampling (ACS) proved to be a powerful tool for assessing rare clustered populations that are difficult to estimate by means of conventional sampling methods. During 2002 and 2003, severe drought-caused damage was observed in the park forests of the City of Helsinki, Finland, especially in barren site pine and spruce stands. The aim of the present study was to examine sampling and measurement methods for assessing drought damage by analysing the effectiveness of ACS compared with simple random sampling (SRS). Horvitz-Thompson and Hansen-Hurwitz estimators of the ACS method were used for estimating the population mean and variance of the variable of interest. ACS was considerably more effective than SRS in assessing rare clustered populations such as those resulting from drought damage. The variances in the ACS methods were significantly smaller and the inventory efficiency in the field better than in SRS.
  • Talvitie, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: mervi.talvitie@helsinki.fi (email)
  • Leino, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ol@nn.fi
  • Holopainen, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ah@nn.fi

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