Hannu Yli-Kojola’s research while affiliated with Finnish Forest Research Institute and other places

This report illustrates case studies with an in-depth analysis of the interactions of energy efficiency measures with farm economics and the environmental impact (GHG) of the measures across Europe. The analyses followed a common methodology considering the farm gate as the system boundary. Therefore, considerable energy use in the post-processing of agricultural products were only taken into account, when they can be assumed to be realized on the farm. The analyses of the energy use, economic and environmental effects follow an LCA approach taking into account all costs of the production, including those for machines according to the concept of “useful life” of the machines used. The environmental effects of energy saving were illustrated with the greenhouse gas emission effect of the energy efficiency measures. The case studies are only a selection of specific energy saving measures across Europe and therefore cannot be regarded as representative for all Europe. Nevertheless, they will help to understand constraints and opportunities for increased energy efficiency in agriculture, which can be used to translate to an agenda of practical action or applied research. The findings are valid sometimes only in the specific regional settings, sometimes they are of general validity.

A multi-source forest inventory method is applied to the estimation of forest resources in the area of the Hebei Forest Bureau in Heilongjiang province in North-East China. A stratified systematic cluster sampling design was utilised in field measurements. The design was constructed on the basis of information from earlier stand-level inventories, aerial orthophotographs, experiences from other sampling inventories and the available budget. Sample tree volumes were estimated by means of existing models. New models were constructed and their parameters estimated for tallied tree volumes and volume increments. The estimates for the area of the Bureau were computed from field measurements, and for the areas of the forest farms estimated from field measurements and satellite images. A k-nearest neighbour method was utilised. This method employing satellite image data makes it possible to estimate all variables, particularly for smaller areas than that possible using field measurements only. The methods presented, or their modifications, could also be applied to the planning and realisation of forest inventories elsewhere in Temperate or Boreal zones. The inventory in question gave an estimate of 114 m3/ha (the multi-source inventory 119 m3/ha) instead of 72 m3/ha as previously estimated from available information. Totally nineteen tree species, genera of species or tree species groups were identified (Appendix 1). The forests were relatively young, 60% of them younger than 40 years and 85% younger than 60 years.

Data from the eighth National Forest Inventory (NFI) and annual surveys of the vitality of forests was used in this study. Abiotic damage (wind, snow, frost or edaphic factors) was present on 8.4% of forest land, on 1.68 million hectares during 1986–1994. It decreased the silvicultural quality of the stand in 5.2% of forest land. Abiotic damage was more frequent in northern than in southern Finland. Especially snow damage was important in northern Finland in Scots pine stands.The defoliation of conifers and various damage forms showed significant co-occurrence. Temporal and spatial patterns were evident in the occurrence and importance of different causal agents. Abiotic damage increased the defoliation in Picea abies more than in Pinus sylvestris, but in the latter species the damage was locally more severe.Sudden changes in defoliation were related to abiotic and biotic damage, and the effect of these injuries can be so remarkable that they mask the possible trend in defoliation. The analysis of these injuries may aid monitoring of forest condition by simplifying interpretation of national and regional patterns of forest damage.

8.VMI, yli 24000 koealaa E-S:ssa. Versosurma yleisin taudinaiheuttaja (6,5 % kaikista metsiköistä E-S:ssa, 10,5 % mäntyvaltaisista). Vs.tuhot suurimmaksi osaksi lieviä. Tervasroso 1,4 %, muut sienitaudit 5,8 %. Eläintuhoista hirvi tärkein (2,2 %)

Pysyvillä 85-86 Lapissa enemmän tuhoja kuin E-S:ssa,erit. latvavaurioita ja kuoll.puita. Koko maassa 12:ssa koealoja jonkinasteisia vaurioita, hiukan pienemmät arviot E.S.ssa inv. kertakoealoilta (86-88) vast. alueelta. Lapissa paljon tuntem. jääneitä + abioott. tuhoja (puut, VMI-8 P). Tuhojen osuus nousee harsuuntumisen kasvaessa (8.VMI-P, hars.kohdepuut, + vuot. seurannan kohdepuut 86-88). Erilaiset tuhot merkittäviä eri vuosina harsuuntumisen lisääjänä. Versosurma lisäsi harsuuntumista K+ L-Suomessa 1988.

Theoretical and practical aspects of permanent sample plots are discussed in this paper. A study material of 6,871 permanent sample plots was generated using increment sample plots of the 7th National Forest Inventory of Finland. The effect of measurement errors and use of increment functions as ”a priori” information was studied via simulation experiments. The change in the growing stock volume between two consecutive measurement rounds was divided into the components drain, growth and mortality. Finally, a hypothetical inventory design using permanent sample plots was evaluated. The PDF includes an abstract in Finnish.

Contribution to the International Co-operative Programme on the Assessment and Monitoring of Air Pollution Effects in Forests