Articles containing the keyword 'accuracy'

The productivity of Scots pine (Pinus sylvestris L.) under changing climatic conditions in the southern part of Finland was studied by scenario analysis with a gap-type forest ecosystem model. Standard simulations with the model predicted an increased rate of growth and hence increased productivity as a result of climatic warming. The gap-type model was refined by introducing an overwintering sub-model describing the annual growth cycle, frost hardiness, and frost damage of the trees. Simulations with the refined gap-type model produced results conflicting with those of the standard simulation, i.e., drastically decreased productivity caused by mortality and growth-reducing damage due to premature dehardening in the changing climate. The overwintering sub-model was tested with frost hardiness data from Scots pine saplings growing at their natural site 1) under natural conditions and 2) under elevated temperature condition, both in open-top chambers. The model predicted the frost hardiness dynamics quite accurately for the natural conditions while underestimating the frost hardiness of the saplings for the elevated temperature conditions. These findings show that 1) the overwintering sub-model requires further development, and 2) the possible reduction of productivity caused by frost damage in a changing climate is less drastic than predicted in the scenario analysis. The results as a whole demonstrated the need to consider the overwintering of trees in scenario analysis carried out with ecosystem model for boreal conditions. More generally, the results revealed a problem that exists in scenario analysis with ecological models: the accuracy of a model in predicting the ecosystem functioning under present climatic condition does not guarantee the realism of the model, nor for this reason the accuracy for predicting the ecosystem functioning under changing climatic conditions. This finding calls for the continuous rigorous experimental testing of ecological models used for assessing the ecological implications of climatic change.

• Hänninen, E-mail: hh@mm.unknown
• Kellomäki, E-mail: sk@mm.unknown
• Leinonen, E-mail: il@mm.unknown
• Repo, E-mail: tr@mm.unknown

The concepts of the terms compartment and compartment-wise forest inventory have been studied empirically by repeated delineation and intensive systematic plot samples. The material consisted of 16 study areas of some 8–90 hectares in size in Southern Finland and of more than 1,000 relascope plots. Stands and compartments were found to be rather heterogenous. Alternative photographs, working techniques and test persons were studied. An endeavour for better accuracy in compartment inventories is recommended.

The PDF includes a summary in English.

• Poso, E-mail: sp@mm.unknown

The aim of this investigation is to study, for north European conditions, some overall standards of accuracy attainable in the estimation in a number of forest characteristics from aerial photographs. Field data was acquired in three areas, comprising whole stands, fixed and variable size sample plots and sections of survey strips.  

The results show that land use classes could be estimated to a rather high degree of precision from aerial photographs. The accuracy of determination of the main tree species (Scots pine, Norway spruce and deciduous trees) was more moderate; three quarters of all stands were interpreted correctly from the present photographs. The estimate of pure stands was noticeable better than those for mixed stands. In general, the agreement between treatment class stratification in the field and from aerial photographs was poor, as only one-third of all cases the class was same. The dominant height was estimated with relative lack of bias for small stands, but systematic underestimation of nearly 2 m existed for high stands.  

The emphasis in this investigation was laid on determination of the volume of growing stock. Stand volumes in the small and medium volume classes were overestimated, against clear under-estimate for high volume stands. The standard error of difference, including bias, was ±43 both in m3 and as a percentage. 

The variance data available provide a basis for the conclusion that under some conditions photo stratification within the forest land seems to improve the efficiency of volume estimation, whereas in some other cases the stratification is hardly an economic proposition. Alternative computations made from the data of an experimental survey indicated the likelihood that no gain was deprived from the use of aerial photographs for volume class estimation. 

The PDF includes a summary in Finnish.

• Nyyssönen, E-mail: an@mm.unknown
• Poso, E-mail: sp@mm.unknown
• Keil, E-mail: ck@mm.unknown

A comparison was made between two alternative methods of continuous national forest inventory. In method 1, samples measured annually are taken throughout the country, in method 2 samples are confined to one section of the country each year. The figures are derived from national forest inventories carried out in the North-European countries Finland, Norway and Sweden. Systematic sampling on the ground has been employed without remeasured sample plots. Field work consisted of survey tracts.

For the whole country, method 1 gives results, which are continuously up-to-date, although detailed information requires observation over a period of several years. On an average, the results obtained from method 2 area at least n/2 years old (survey cycle n years). For a specific section of the country, method 1 gives preliminary results already in 1-2 years, but more accurate results are at least n/2 years old. Method 2 gives accurate results every n^th year. Thus, method 2 is not always to be recommended, even if the emphasis is laid on regional information and planning.

To gain knowledge of annual timber removals, often necessary in assessing the forest resource situation, stump measurements can be used, either exclusively or by way of control. The corresponding sampling must be affected throughout the whole country, and this can be done only when method 1 is used. Other information required annually, such as estimates of seed crops, occurrence of pests or annual variation of growth due to the climate, favour method 1.

It can be concluded that method 1 has important advantages, although these must be bought at higher costs. A comparison of inventory costs shows, assuming the same degree of accuracy, that the total expenditure for method 2 is 7-8% lower than that for method 1, owing to the difference in transport requirements. Also, other aspects may affect the choice of method, for example, the use of aerial photographs may be arranged more efficiently in method 2.

• Nyyssönen, E-mail: an@mm.unknown

• Stenman, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland https://orcid.org/0000-0003-1176-7840 E-mail: virpi.stenman@helsinki.fi
• Kangas, Natural Resources Institute Finland (Luke), Bio­economy and Environment, P.O. Box 68, FI-80101 Joensuu, Finland https://orcid.org/0000-0002-8637-5668 E-mail: annika.kangas@luke.fi
• 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

• Trubins, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Box 49, 230 53 Alnarp, Sweden E-mail: renats.trubins@slu.se
• Sallnäs, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Box 49, 230 53 Alnarp, Sweden E-mail: ola.sallnas@slu.se

• Nuutinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: yrjo.nuutinen@metla.fi
• Väätäinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: kv@nn.fi
• Heinonen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jh@nn.fi
• Asikainen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: aa@nn.fi
• Röser, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: dr@nn.fi

• Kangas, University of Helsinki, Dept. of Forest Resources Management, P.O. Box 27, 00014 University of Helsinki, Finland E-mail: annika.kangas@helsinki.fi
• Maltamo, University of Joensuu, Faculty of Forestry, P.O. Box 111, 80101 Joensuu, Finland E-mail: mm@nn.fi