Improved large-area forest increment information in Europe through harmonisation of National Forest Inventories

14 Pág.Consistent knowledge about the increment in European forests gained amplified importance in European policies and decision processes related to forest-based bioeconomy, carbon sequestration, sustainable forest management and environmental changes. Until now, large-area increment information from European countries was lacking international comparability. In this study we present a harmonisation framework in accordance with the principles and the approach established for the harmonisation of National Forest Inventories (NFIs) in Europe. 11 European NFIs, representing a broad range of increment measurement and estimation methods, developed unified reference definitions and methods that were subsequently implemented to provide harmonised increment estimates by NUTS regions (Nomenclature of territorial units for statistics of the European Union), main forest types and tree species groups, and to rate the impact of harmonisation measures. The main emphasis was on gross annual increment (GAI), however, also annual natural losses (ANL) and net annual increment (NAI) were estimated. The data from the latest available NFI cycles were processed. The participating countries represent a forest area of about 130 million ha, and 82% of the European Unions’ (EU) forest area, respectively. The increments were estimated in terms of volume (m³ year−1, m³ ha−1 year−1) and above-ground biomass (t year−1, t ha−1 year−1). The harmonised GAI volume estimates deviate in a range of +12.3% to −26.5% from the estimates according to the national definitions and estimation methods. Within the study area, the harmonised estimates show a considerable range over the NUTS regions for GAI, from 0.6 to 12.3 m³ ha−1 year−1, and 0.8–6.4 t ha−1 year−1, of volume and above-ground biomass, respectively. The largest increment estimates are found in Central Europe and gradually decrease towards the North, South, West and East. In most countries coniferous forests show larger increment estimates per hectare than broadleaved forests while mixed forests are at an intermediate level. However, in some instances, the differences were small or mixed forests revealed the largest increment estimates. The most important tree species groups in the study area are Pinus spp. and Picea spp., contributing 29% and 26% of the estimated total GAI volume, respectively. The shares of the prevalent broadleaved species are smaller with contributions of 9%, 7% and 6% by Quercus spp., Fagus sylvatica and Betula spp. The results underline the importance of harmonisation in international forest statistics. Looking ahead, harmonised large-area increment estimation is pivotal for accurate monitoring and evidence-based policy decisions in the changing context of future forest ecosystems dynamics, management strategies and wood availability.This research was supported by the Specific Contracts No. 20 and 21 “Use of National Forest Inventories data to harmonise and improve the current knowledge on forest increment in Europe” in the context of the “Framework contract for the provision of forest data and services in support to the JRC activities and applications on forest resources (Contract Number 934340)” of the Joint Research Centre of the European Commission.Peer reviewe

Harmonised statistics and maps of forest biomass and increment in Europe.

peer reviewedForest biomass is an essential resource in relation to the green transition and its assessment is key for the sustainable management of forest resources. Here, we present a forest biomass dataset for Europe based on the best available inventory and satellite data, with a higher level of harmonisation and spatial resolution than other existing data. This database provides statistics and maps of the forest area, biomass stock and their share available for wood supply in the year 2020, and statistics on gross and net volume increment in 2010-2020, for 38 European countries. The statistics of most countries are available at a sub-national scale and are derived from National Forest Inventory data, harmonised using common reference definitions and estimation methodology, and updated to a common year using a modelling approach. For those counties without harmonised statistics, data were derived from the State of Europe's Forest 2020 Report at the national scale. The maps are coherent with the statistics and depict the spatial distribution of the forest variables at 100 m resolution

Forest inventory method based on stratified sampling using a stand growth model

The paper presents a new variant of the method for determining the stand volume of age classes in a forest district or inspectorate (subdistrict). The methodological basis for this variant of the method is a branch of mathematical statistics called the "representative method", which is based on stratified sampling, similar to the variant of forest inventory currently used in forestry. In the new variant of the method, strata are formed based on the age of the main tree species and the stand volume, which is determined by the stand growth model, while in the variant currently used, strata are formed based on the stand's main tree species and its age. In the new variant of the stand volume determination method, 13 stages are distinguished, which can be divided into the initial and the main part. First, data from the State Forest Information System (SILP) database are processed: the age of the stand's main tree species and characteristics that allow to determine the volume of each stand of the forest district or inspectorate using a stand growth model. Based on the age and stand volume, strata for the forest district or inspectorate can be formed and the number of samples for each of these strata can be determined. The main part of the new variant of the method starts with the measurement of DBH and tree height on the sample plots. The results of these measurements are then processed using, for example, a stand growth model. The volume of individual strata, age classes, and the entire forest district is determined. When using a growth model, many other stand characteristics are also determined, including volume increment, degree of windthrow hazard, rotation, and 10-year size of final and intermediate fellings. The evaluation of the accuracy of the method was based on data from 73 forest inspectorates in Poland. This was preceded by studies on the dispersion measures of the sum of tree volume on sample plots of different sizes. The new variant of the forest inventory method proved to be about 30% more accurate than the previously used variant

Potential Areas in Poland for Forestry Plantation

Plantations have many advantages when compared to natural or semi-natural forests, such as shortening production cycles, the production of wood with specific characteristics, and near-market production concentrations. The intensive development of this form of industrial wood production is practiced all over the world. The wood industry in Poland struggles in recent years, with a large shortage of wood. The deficit of wood has been accumulated for several years and is steadily increasing. One of the possibilities to change this trend can be development of fast-growing trees plantations. The main aim of this study was to determine the potential of land in Poland, which could be used for the cultivation of fast-growing trees plantations. The analyses took into account the area and marginal agricultural land. The potential plantation land areas were determined for poplar cultivar “Hybrid 275” and European larch (Larix decidua Mill.). The results show a possibility to generate a considerable area that can be developed into plantations of fast-growing trees in Poland. According to the analyses carried out for the purpose of this study, with only 5% use of the sown area and 5% use of forest lands, as well as the boscage (wooded land and bushy land), it is possible to obtain approximately 0.6 MM ha of land for fast-growing tree plantations. In the case of planting 50% of these lands with larch and 50% with poplar, and if a 50% capacity of the plantation is assumed, it will be possible to obtain nearly 6 MM m3 of wood per year

What Can We Learn from an Early Test on the Adaptation of Silver Fir Populations to Marginal Environments?

In order to determine the adaptive potential of silver fir in the southeast of Poland, the stability of the height of its five-year-old progeny was analyzed. The study was conducted in two different population groups in a total of four environments, including one ecologically marginal environment. The linear mixed model was used to evaluate the differentiation of populations in terms of height growth. The genotype and genotype-by-environment interaction biplot (GGE) were used to verify the stability of height. The climate of populations origin, in relation to actual fir distribution in Poland, was verified based on principal components analysis (PCA) of bioclimatic parameters. The highest total variability was explained by the genotype-environment interaction effect (GE) (54.50%), while the genotype effect (G) explained 41.27% and only 4.23% was explained by the site effect. The result of height growth variations revealed the Komańcza site as the most representative among study sites, while the Lesko site characterized the highest discriminating ability. The progeny occurring in climatic conditions most different from the average testing conditions showed a heterogeneous growth reaction, only adapting to the marginal environment, while the progeny of the second population in this region as well as the northernmost one was characterized by a mean but stable growth. The westernmost population revealed maladaptation. The assessment of the adaptability of silver fir depends on the broad spectrum of test conditions considering the ecologically marginal environments

Predicted range shifts of alien tree species in Europe

Alien tree species are considered both a threat to nature conservation and a base for forest management. We compiled species occurrences from biodiversity databases, forest inventories, and literature data. We modeled the availability of potential niches using the MaxEnt method and bioclimatic variables for current conditions, 2041-2060, and 2061-2080 periods. We used four climate scenarios: SSP126, SSP245, SSP370, and SSP485. The results confirm our hypotheses that, (i) coniferous species will contract, and deciduous trees will expand their climatic niche, (ii) a significant part of the areas where the studied species currently occur will be outside their climatic optimum in the coming decades; (iii) changes in the climatic optimum distribution will be greater in the 2041-2060 period than in 2061-2080. These predicted shifts are relevant for evidence-based management in sites already occupied by the studied alien trees. Our results are also relevant to the development of prevention and early detection measures in areas predicted to become climatically suitable for the studied species

Harmonised statistics and maps of forest biomass and increment in Europe

Abstract Forest biomass is an essential resource in relation to the green transition and its assessment is key for the sustainable management of forest resources. Here, we present a forest biomass dataset for Europe based on the best available inventory and satellite data, with a higher level of harmonisation and spatial resolution than other existing data. This database provides statistics and maps of the forest area, biomass stock and their share available for wood supply in the year 2020, and statistics on gross and net volume increment in 2010–2020, for 38 European countries. The statistics of most countries are available at a sub-national scale and are derived from National Forest Inventory data, harmonised using common reference definitions and estimation methodology, and updated to a common year using a modelling approach. For those counties without harmonised statistics, data were derived from the State of Europe’s Forest 2020 Report at the national scale. The maps are coherent with the statistics and depict the spatial distribution of the forest variables at 100 m resolution