Articles containing the keyword 'National Forest Inventory'

Silva Fennica Issue 39 includes presentations held in professional development courses in 1935 that were arranged for foresters working in public administration. The presentations focus on practical issues in forest management and administration, especially in regional level.

This presentation lists statistics available on forestry.

• Saari, E-mail: es@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

The distances between the lines in the line survey in the first two National Inventories of Finland were too long to supply data for every State Forest district. Consequently, the Third National Forest Inventory offered an opportunity to supplement the inventory for State Forests in 1954 and 1955, and to gather data on forest resources of the State Fforests. On the basis of the results, a management plan for the State Forests was drafted. The first part of the paper describes the inventory procedure and results of the inventory, the second deduces future cuttings and a forest management programme.
In 1955 the total land area of the State Forests was 9.49 million ha. Drained peatlands cover 126,000 ha, drainable peatlands 798,000 ha and undrainable peatlands 2,621,000 ha. The average volume of growing stock in all State Forests was 55.2 m³/ha, including productive and unproductive forest land. The average increment in all State Forests was 1,39 m³/ha on productive land and in all lands in average 1,14 m³/ha.
Cutting budgets for the progressive yield were prepared by checking the silvicultural cut and estimating the allowable cut. They were made by age classes, developmental stages and for each region. The stock development was forecasted for a period of 40 years. In average the allowable cut was larger during the first decade than during the second. Allowable cut was estimated by the tree species and by timber assortments. The management plan included future forest management work, such as intermediate fellings, regeneration fellings, site preparation, artificial regenereation, tending of seedling stands, and draining of peatland.
The PDF includes a summary in English.

• Linnamies, E-mail: ol@mm.unknown

The first estimates on the forest resources of Finland were presented in the middle of the 1900^th century. The first line survey was conducted in 1912 in Central Finland. In 1921-1923 a survey of the forests of the whole country was commenced. The method consisted in measurement of sample plots in conjunction with ocular estimation of all the stands within the range of the lines. The methods were further developed in the second National Forest Survey in 1936-1938, which payed special attention to the silvicultural condition of the forests, and the growth in the light of climatic variation. When 3.3 million ha of forests were ceded to the Soviet Union in the peace treaty of 1944, the results of the survey had to be recalculated. The next survey was conducted 1951-1953. In this survey, the recovery of stands on drained peatlands was studied. The results of the inventories show that forest resources of Finland had icreased since the 1936-1938 survey.

The first investigation of wood utilization in Finland was carried out in 1927, after the first National Forest Survey had provided information on the forest resources, and knowledge of the other side of the forest balance was desired. The most difficult part was to determine the domestic wood consumption of the rural population. This was accomplished by studying 1,337 sample farms. The second investigation was commenced in 1938, and third in 1954.

These two investigations have made it possible to determine the annual removal and annual growth, and by comparing these results, growth balance. A forest balance is an essential condition for judicious forestry.

The Acta Forestalia Fennica issue 61 was published in honour of professor Eino Saari’s 60th birthday.

• Ilvessalo, E-mail: yi@mm.unknown

The field of work of the 7th National Forest Inventory was carried out during 1977–84. This report consists of the analysis of the forest resources, long-term development of forests and the results by ownership categories in Finland.

The area of forestry land, 26.4 million ha, has decreased slightly because of the increase of build-up areas and communication routes. Forest land, which is suitable to growing wood profitably, amounted 20.1 million ha. It has increased, although not as fast as earlier, due to drainage and fertilization of scrub and waste land swamps and the afforestation of agricultural land.

The growing stock volume was 1,660 million m³ and the estimated gross annual increment 68.4 million m³. A large quantity of young, rapidly growing stands, and fellings markedly below the increment, are the principal factors increasing the growing stock. The volume of Scots pine (Pinus sylvestris L.) has increased most but the greatest proportional increase has been in the volume of broadleaved trees.

The silvicultural quality of stands has improved and the increase in saw log tree volume has resulted in an increase in the total growing stock volume. The proportional volume of saw logs, however, has decreased. Both aging mature stands and postponed thinnings increase the risk of losses due to mortality and decay. Too dense stands retard the diameter growth of trees. The proportion of unsuccessful artificial regeneration has increased.

The area of private forests has slightly decreased, while companies and collective bodies have increased their ownership. Non-farmer private ownership already accounts for one half of the area of private forests. The silvicultural quality of company forests is best and the increase of the growing stock and its increment is proportionally greatest in these forests.

The PDF includes a summary in English.

• Kuusela, E-mail: kk@mm.unknown
• Salminen, E-mail: ss@mm.unknown

• Peltoniemi, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: mikko.peltoniemi@metla.fi
• Thürig, Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland; European Forest Institute, Joensuu, Finland E-mail: et@nn.ch
• Ogle, Natural Resources Ecology Laboratory, Colorado State University, Fort Collins, USA E-mail: so@nn.us
• Palosuo, European Forest Institute, Joensuu, Finland E-mail: tp@nn.fi
• Schrumpf, Max-Planck-Institute for Biogeochemistry, Jena, Germany E-mail: ms@nn.de
• Wutzler, Max-Planck-Institute for Biogeochemistry, Jena, Germany E-mail: tw@nn.de
• Butterbach-Bahl, Institute for Meteorology and Climate Research, Forschungszentrum Karlsruhe GmbH, Garmisch-Partenkirchen, Germany E-mail: kbb@nn.de
• Chertov, St. Petersburg State University, St. Petersburg-Peterhof, Russia E-mail: oc@nn.ru
• Komarov, Institute of Physicochemical and Biological Problems in Soil Science of Russian Academy of Sciences, Pushchino, Russia E-mail: ak@nn.ru
• Mikhailov, Institute of Physicochemical and Biological Problems in Soil Science of Russian Academy of Sciences, Pushchino, Russia E-mail: am@nn.ru
• Gärdenäs, Dept. of Soil Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden E-mail: ag@nn.se
• Perry, USDA Forest Service, Northern Research Station, St. Paul, MN USA E-mail: cp@nn.us
• Liski, Finnish Environment Institute, Helsinki, Finland E-mail: jl@nn.fi
• Smith, School of Biological Sciences, University of Aberdeen, Aberdeen, UK E-mail: ps@nn.uk
• Mäkipää, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: raisa.makipaa@metla.fi

In 2019–2023 the 13th Finnish National Forest Inventory (NFI) was implemented by measuring a total of 62 266 sample plots across the country. The methodology of the sampling and measurements was similar as in the previous inventory, but the proportion and number of remeasured permanent plots was increased to improve the monitoring of annual increment and other changes in the forests. Only 6.2 M ha (14%) of Finland’s total land area (30.4 M ha) is other land than forestry land. Productive and poorly productive forests cover 22.9 M ha (75%) of the total land area.  The forest area has remained stable in recent decades but the forest area available for wood supply (FAWS) has decreased due to increased forest protection – 23% of the forestry land and 10% of the productive forest are not available for wood supply. Compared to the previous inventory, forest resources have continued to increase but the average annual increment has declined from 107.8 M m³ to 103.0 M m³. The quality of forests from the timber production point of view has remained relatively good or improved slightly. The area of observed forest damage on FAWS is 8.4 M ha (46% of FAWS area), half of these minor damages with no impact on stand quality. Although the area of forest damage has not increased, the amount of mortality has continued to increase, and is now 8.8 M m³ year^–1. The amount of dead wood has continued to increase in South Finland, while in North Finland the declining trend has turned into a slight increase. Since the 1920s, the area of forestry land has remained stable, but the area of productive forest has increased due to the drainage of poorly productive or treeless peatlands. The total volume of growing stock has increased by 84% and annual increment has more than doubled.

• Korhonen, Natural Resources Institute Finland (Luke), P.O.Box 68, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-6198-853X E-mail: kari.t.korhonen@luke.fi
• Räty, Natural Resources Institute Finland (Luke), P.O.Box 2, FI-00790, Helsinki, Finland https://orcid.org/0000-0001-9898-8712 E-mail: minna.raty@luke.fi
• Haakana, Natural Resources Institute Finland (Luke), P.O.Box 2, FI-00790, Helsinki, Finland E-mail: helena.haakana@luke.fi
• Heikkinen, Natural Resources Institute Finland (Luke), P.O.Box 2, FI-00790, Helsinki, Finland https://orcid.org/0000-0003-3527-774X E-mail: juha.heikkinen@luke.fi
• Hotanen, Natural Resources Institute Finland (Luke), P.O.Box 68, FI-80100 Joensuu, Finland E-mail: juha-pekka.hotanen@luke.fi
• Kuronen, Natural Resources Institute Finland (Luke), P.O.Box 2, FI-00790, Helsinki, Finland https://orcid.org/0000-0002-8089-7895 E-mail: mikko.kuronen@luke.fi
• Pitkänen, Natural Resources Institute Finland (Luke), P.O.Box 68, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-7583-6297 E-mail: juho.pitkanen@luke.fi

Models that predict forest development are essential for sustainable forest management. Constructing growth models via regression analysis or fitting a family of sigmoid equations to construct compatible growth and yield models are two ways these models can be developed. In this study, four species-specific models were developed and compared. A compatible growth and yield stand basal area model and a five-year stand basal area growth model were developed for Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.). The models were developed using data from permanent inventory plots from the Swedish national forest inventory and long-term experiments. The species-specific models were compared, using independent data from long-term experiments, with a stand basal area growth model currently used in the Swedish forest planning system Heureka (Elfving model). All new models had a good, relatively unbiased fit. There were no apparent differences between the models in their ability to predict basal area development, except for the slightly worse predictions for the Norway spruce growth model. The lack of difference in the model comparison showed that despite the simplicity of the compatible growth and yield models, these models could be recommended, especially when data availability is limited. Also, despite using more and newer data for model development in this study, the currently used Elfving model was equally good at predicting basal area. The lack of model difference indicate that future studies should instead focus on model development for heterogeneous forests which are common but lack in growth and yield modelling research.

• Goude, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, SE-230 53 Alnarp, Sweden https://orcid.org/0000-0002-2179-292X E-mail: martin.goude@slu.se
• Nilsson, Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, SE-230 53 Alnarp, Sweden E-mail: urban.nilsson@slu.se
• Mason, School of Forestry, University of Canterbury, Private Bag 4800, Christchurch, New Zealand E-mail: euan.mason@canterbury.ac.nz
• Vico, Department of Crop Production Ecology, Swedish University of Agricultural Sciences, SE-750 07 Uppsala, Sweden E-mail: giulia.vico@slu.se

We describe the methodology applied in the 12th national forest inventory of Finland (NFI12) and describe the state of Finland’s forests as well as the development of some key parameters since 1920s. According to the NFI12, the area of forestry land (consisting of productive and poorly productive forest, unproductive land, and other forestry land) is 26.2 M ha. The area of forestry land has decreased from 1920s to 1960s due to expansion of agriculture and built-up land. 20% of the forestry land is not available for wood supply and 13% is only partly available for wood supply. The area of peatlands is 8.8 M ha, which is one third of the forestry land. 53% of the current area of peatlands is drained. The volume of growing stock, 2500 M m³, is 1.7 times the volume estimated in NFI1 in the 1920s for the current territory of Finland. The estimated annual volume increment is 107.8 M m³. The increment estimate has doubled since the estimate of NFI2 implemented in late 1930s. The annual mortality is estimated to 7 M m³, which is 0.5 M m³ more than according to the previous inventory. Serious or complete damage was observed on 2% of the productive forest available for wood supply. The amount of dead wood is on average 5.8 m³ ha^–1 in productive forests. Since the NFI9 (1996–2003) the amount of dead wood has increased in South Finland and decreased in North Finland both in protected forests and forests available for wood supply (FAWS). The area of natural or almost natural forests on productive forest is 380 000 ha, out of this, 42 000 ha are in FAWS and 340 000 ha in protected forests.

• Korhonen, Natural Resources Institute Finland (Luke), P.O. Box 68, FI-80100 Joensuu, Finland E-mail: kari.t.korhonen@luke.fi
• Ahola, Natural Resources Institute Finland (Luke), P.O. Box 2, FI-00790, Helsinki, Finland E-mail: arto.ahola@luke.fi
• Heikkinen, Natural Resources Institute Finland (Luke), P.O. Box 2, FI-00790, Helsinki, Finland E-mail: juha.heikkinen@luke.fi
• Henttonen, Natural Resources Institute Finland (Luke), P.O. Box 2, FI-00790, Helsinki, Finland E-mail: helena.henttonen@luke.fi
• Hotanen, Natural Resources Institute Finland (Luke), P.O. Box 68, FI-80100 Joensuu, Finland E-mail: juha-pekka.hotanen@luke.fi
• Ihalainen, Natural Resources Institute Finland (Luke), P.O. Box 2, FI-00790, Helsinki, Finland E-mail: anttivj.ihalainen@elisanet.fi
• Melin, Natural Resources Institute Finland (Luke), P.O. Box 68, FI-80100 Joensuu, Finland E-mail: markus.melin@luke.fi
• Pitkänen, Natural Resources Institute Finland (Luke), P.O. Box 68, FI-80100 Joensuu, Finland E-mail: juho.pitkanen@luke.fi
• Räty, Natural Resources Institute Finland (Luke), P.O. Box 2, FI-00790, Helsinki, Finland E-mail: minna.raty@luke.fi
• Sirviö, Natural Resources Institute Finland (Luke), P.O. Box 2, FI-00790, Helsinki, Finland E-mail: maria.sirvio@uudenmaanliitto.fi
• Strandström, Natural Resources Institute Finland (Luke), P.O. Box 2, FI-00790, Helsinki, Finland E-mail: mikael.strandstrom@luke.fi

Since the 1990’s, forest resource maps and small area estimates have been produced by combining national forest inventory (NFI) field plot data, optical satellite images and numerical map data using a non-parametric k-nearest neighbour method. In Finland, thematic maps of forest variables have been produced by the means of multi-source NFI (MS-NFI) for eight to ten times depending on the geographical area, but the resulting time series have not been systematically utilized. The objective of this study was to explore the possibilities of the time series for monitoring the key ecosystem condition indicators for forests. To this end, a contextual Mann-Kendall (CMK) test was applied to detect trends in time-series of two decades of thematic maps. The usefulness of the observed trends may depend both on the scale of the phenomena themselves and the uncertainties involved in the maps. Thus, several spatial scales were tested: the MS-NFI maps at 16 × 16 m² pixel size and units of 240 × 240 m², 1200 × 1200 m² and 12  000 × 12  000 m² aggregated from the MS-NFI map data. The CMK test detected areas of significant increasing trends of mean volume on both study sites and at various unit sizes except for the original thematic map pixel size. For other variables such as the mean volume of tree species groups, the proportion of broadleaved tree species and the stand age, significant trends were mostly found only for the largest unit size, 12  000 × 12  000 m². The multiple testing corrections decreased the amount of significant p-values from the CMK test strongly. The study showed that significant trends can be detected enabling indicators of ecosystem services to be monitored from a time-series of satellite image-based thematic forest maps.

• Katila, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Latokartanonkaari 9, FI-00790 Helsinki, Finland; https://orcid.org/0000-0001-6946-5736 E-mail: matti.katila@luke.fi
• Rajala, Natural Resources Institute Finland (Luke), Natural resources, Latokartanonkaari 9, FI-00790 Helsinki, Finland E-mail: tuomas.rajala@luke.fi
• Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Yliopistokatu 6, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-8637-5668 E-mail: annika.kangas@luke.fi

Exploring the possibility to produce nation-wide forest attribute maps using stereophotogrammetry of aerial images, the national terrain model and data from the National Forest Inventory (NFI). The study areas are four image acquisition blocks in mid- and south Sweden. Regression models were developed and applied to 12.5 m × 12.5 m raster cells for each block and validation was done with an independent dataset of forest stands. Model performance was compared for eight different forest types separately and the accuracies between forest types clearly differs for both image- and LiDAR methods, but between methods the difference in accuracy is small at plot level. At stand level, the root mean square error in percent of the mean (RMSE%) were ranging: from 7.7% to 10.5% for mean height; from 12.0% to 17.8% for mean diameter; from 21.8% to 22.8% for stem volume; and from 17.7% to 21.1% for basal area. This study clearly shows that aerial images from the national image program together with field sample plots from the NFI can be used for large area forest attribute mapping.

• Bohlin, Department of Forest Resource Management, Swedish University of Agricultural Sciences, S-901 35 Umeå, Sweden http://orcid.org/0000-0002-3318-5967 E-mail: jonas.bohlin@slu.se
• Bohlin, Department of Forest Resource Management, Swedish University of Agricultural Sciences, S-901 35 Umeå, Sweden http://orcid.org/0000-0003-1224-6684 E-mail: inka.bohlin@slu.se
• Jonzén, Department of Forest Resource Management, Swedish University of Agricultural Sciences, S-901 35 Umeå, Sweden E-mail: jonas.jonzen@slu.se
• Nilsson, Department of Forest Resource Management, Swedish University of Agricultural Sciences, S-901 35 Umeå, Sweden http://orcid.org/0000-0001-7394-6305 E-mail: mats.nilsson@slu.se

• Tuominen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: sakari.tuominen@metla.fi
• Pitkänen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: juho.pitkanen@metla.fi
• Balazs, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: andras.balazs@metla.fi
• Korhonen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: kari.t.korhonen@metla.fi
• Hyvönen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: pekka.hyvonen@metla.fi
• Muinonen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: eero.muinonen@metla.fi

• Kitahara, Graduate School of Bioresource and Bioenvironmental Science, Kyushu University, 6-10-1 Hakozaki, Higashiku, Fukuoka 812-8581, Japan E-mail: bunsho@ffpri.affrc.go.jp
• Mizoue, Faculty of Agriculture, Kyushu University, Fukuoka, Japan E-mail: nm@nn.jp
• Yoshida, Faculty of Agriculture, Kyushu University, Fukuoka, Japan E-mail: sy@nn.jp

• Tuominen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: sakari.tuominen@metla.fi
• Eerikäinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: ke@nn.fi
• Schibalski, University of Potsdam, Karl-Liebknecht-Strasse 24–25, 14476 Potsdam, Germany E-mail: as@nn.de
• Haakana, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: mh@nn.fi
• Lehtonen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: al@nn.fi

• Nuutinen, European Forest Institute, Torikatu 34, FI-80100 Joensuu, Finland E-mail: tuula.nuutinen@efi.int
• Kilpeläinen, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: ak@nn.fi
• Hirvelä, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: hh@nn.fi
• Härkönen, Finnish Forest Research Institute, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: kh@nn.fi
• Ikonen, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: vpi@nn.fi
• Lempinen, Finnish Forest Research Institute, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: rl@nn.fi
• Peltola, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: hp@nn.fi
• Wilhelmsson, Skogforsk, Uppsala Science Park, SE-751 83 Uppsala, Sweden E-mail: lw@nn.fi
• Kellomäki, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: sk@nn.fi

• Pakkala, Finnish Museum of Natural History, University of Helsinki, P.O. Box 17, FIN-00014 University of Helsinki, Finland E-mail: timo.pakkala@helsinki.fi
• Hanski, Department of Ecology and Systematics, University of Helsinki, P.O. Box 47, FIN-00014 University of Helsinki, Finland E-mail: ih@nn.fi
• Tomppo, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland E-mail: et@nn.fi

• Jalkanen, Finnish Forest Research Institute, Unioninkatu 40 A, FIN-00170 Helsinki, Finland E-mail: anneli.jalkanen@metla.fi

• Mattila, Finnish Forest Research Institute, Joensuu Research Station, P.O. Box 68, FIN-80101 Joensuu, Finland E-mail: eero.mattila@metla.fi

There is growing interest in the use of Landsat data to enable forest monitoring over large areas. Free and open data access combined with high performance computing have enabled new approaches to Landsat data analysis that use the best observation for any given pixel to generate an annual, cloud-free, gap-free, surface reflectance image composite. Finland has a long history of incorporating Landsat data into its National Forest Inventory to produce forest information in the form of thematic maps and small area statistics on a variety of forest attributes. Herein we explore the spatial and temporal characteristics of the Landsat archive in the context of forest monitoring in Finland. The United States Geological Survey Landsat archive holds a total of 30 076 images (1972–2017) for 66 scenes (each 185 km by 185 km in size) representing the terrestrial area of Finland, of which 93.6% were acquired since 1984 with a spatial resolution of 30 m. Approximately 16.3% of the archived images have desired compositing characteristics (acquired within August 1 ±30 days, <70% cloud cover, 30 m spatial resolution). Data from the Landsat archive can augment forest monitoring efforts in Finland, provide new information for science and applications, and enable retrospective, systematic analyses to characterize the development of Finnish forests over the past three decades. The capacity to monitor trends based upon this multi-decadal record with the addition of new measurements is of benefit to multisource inventories and offers nationally comprehensive spatially-explicit datasets for a wide range of stakeholders and applications.

• Saarinen, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 University of Helsinki, Finland; School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland https://orcid.org/0000-0003-2730-8892 E-mail: ninni.saarinen@helsinki.fi
• White, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 University of Helsinki, Finland; Canadian Forest Service, (Pacific Forestry Center), Natural Resources Canada, 506 West Burnside Road, Victoria, BC, V8Z 1M5, Canada http://orcid.org/0000-0003-4674-0373 E-mail: joanne.white@canada.ca
• Wulder, Canadian Forest Service, (Pacific Forestry Center), Natural Resources Canada, 506 West Burnside Road, Victoria, BC, V8Z 1M5, Canada https://orcid.org/0000-0002-6942-1896 E-mail: mike.wulder@canada.ca
• Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: annika.kangas@luke.fi
• Tuominen, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Latokartanonkaari 9, FI-00790 Helsinki, Finland E-mail: sakari.tuominen@luke.fi
• Kankare, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ville.kankare@helsinki.fi
• Holopainen, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: markus.holopainen@helsinki.fi
• Hyyppä, Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02431 Masala, Finland E-mail: juha.hyyppa@nls.fi
• Vastaranta, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland https://orcid.org/0000-0001-6552-9122 E-mail: mikko.vastaranta@uef.fi

Dieback of the common ash (Fraxinus excelsior L.) has been spreading throughout Europe since the 1990s, causing severe ecological and economical consequences; however, detailed statistics on its dynamics have been published rarely. This paper presents the dynamics of mature ash-dominated stands in Latvia for the period 2005–2015. Data from the national forest inventory and a permanent sampling plot network were summarised. According to the official statistics, the dieback has caused a twofold decrease in area of the ash stands (from 21 891 to 13 011 ha, which respectively comprised ca. 0.8 to ca. 0.4% of the total forest area). The official statistics on standing volume appeared biased, as they did not account for increased mortality. According to the permanent sampling plots, standing volume and stand density have been affected even more, having decreased by 53.1 and 69.9%, respectively, compared to 2005 (the stand density and standing volume of ash in 2015 was 77 individuals ha^–1 and 151 m³ ha^–1, respectively). The mortality of the trees has not been stable. Stand density decreased faster during 2005–2009 compared to 2010–2015, with mortality rates of 9.6 and 8.2% year^–1, respectively. In contrast, the decrease in standing volume in 2005–2009 was slower than in 2010–2015 (mortality rates were 4.7 and 7.7% year^–1, respectively) because trees with smaller dimensions were more susceptible to the dieback. Nevertheless, the observed mortality rates clearly indicate negative prospects for ash stands in Latvia.

• Matisone, Latvian State Forest Research Institute (LSFRI) Silava, Rigas str. 111, Salaspils, Latvia, LV2169 E-mail: ilze.matisone@silava.lv
• Matisons, Latvian State Forest Research Institute (LSFRI) Silava, Rigas str. 111, Salaspils, Latvia, LV2169 E-mail: robism@inbox.lv
• Laiviņš, Latvian State Forest Research Institute (LSFRI) Silava, Rigas str. 111, Salaspils, Latvia, LV2169 E-mail: maris.laivins@silava.lv
• Gaitnieks, Latvian State Forest Research Institute (LSFRI) Silava, Rigas str. 111, Salaspils, Latvia, LV2169 E-mail: talis.gaitnieks@silava.lv