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Persistence of standing dead trees (snags) is an important determinant for their role for biodiversity and dead wood associated carbon fluxes. How fast snags fall varies widely among species and regions and is further influenced by a variety of stand‐ and tree‐level factors. However, our understanding of this variation is fragmentary at best, partly due to lack of empirical data.Here, we took advantage of the accruing time series of snag observations in the Finnish, Norwegian and Swedish National Forest Inventories that have been followed in these programs since the mid‐1990s. We first harmonized observations from slightly different inventory protocols and then, using this harmonized dataset of ca. 43,000 observations that had a consistent 5‐year census interval, we modelled the probability of snags of the main boreal tree species Pinus sylvestris, Picea abies and Betula spp. falling, as a function of tree‐ and stand‐level variables, using Bayesian logistic regression modelling.The models were moderately good at predicting snags remaining standing or falling, with a correct classification rate ranging from 68% to 75% among species.In general, snag persistence increased with tree size and climatic wetness, and decreased with temperature sum, advancing stage of decay, site productivity and disturbance intensity (mainly harvesting).Synthesis and applications: The effect of harvesting demonstrates that an efficient avenue to increase the amount of snags in managed forests is protecting them during silvicultural operations. In the warmer future, negative relationship between snag persistence and temperature suggests decreasing the time snags remain standing and hence decreasing habitat availability for associated species. As decomposition rates generally increase after fall, decreasing snag persistence also implies substantially faster release of carbon from dead wood. [ABSTRACT FROM AUTHOR]

The article discusses the controversy surrounding whether the locations of National Forest Inventory (NFI) plots should be openly accessible or only accessible in justified exceptions. The authors argue that the exact location of NFI sample plots should remain unknown to the public in order to maintain the representativeness and randomness of the sample. They provide examples of adverse effects that can occur if plot locations are shared, such as tampering with the results of the inventory or breaching data protection regulations. The authors suggest making case-by-case decisions for granting access to plot information, considering the purpose of the study and compliance with data protection regulations. They also acknowledge the different challenges faced by forest inventories in the Global South and the need to consider socioeconomic factors in the discussion. [Extracted from the article]

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This study's objectives were to suggest harmonised criteria for the definition of mixed forests for two Nordic countries, describe their principal mixture types, and provide an overview of their current extent. We used national forest inventory data compiled in Finland and Sweden, considering the forest available for wood supply (FAWS), excluding seedling and sapling plots before canopy closure. The definition of the mixed forest was based on the threshold criteria, which indicate the basal area proportion of the dominant tree species of the total in a stand. The proportion of mixed forests increased with higher threshold criteria: 21% to 42% in Finland and 24% to 49% in Sweden, as the threshold criterion was changed from 65% to 85%. With a threshold criterion of 75%, the area of mixed FAWS was 5.6 million ha (31% of FAWS) in Finland and 6.5 million ha (36%) in Sweden. The dominant mixture type was the pine-spruce-birches mixture (31%) in Finland and the pine-spruce mixture (29%) in Sweden. The proportion of peatland forest of mixed forests was similar in the countries: 9-10%. The mixed forests proportion increased from north boreal to hemiboreal, increasing with more mature development classes. [ABSTRACT FROM AUTHOR]

According to protection targets of EU Biodiversity Strategy 2030, 30% of EU's land and sea area should be legally protected by 2030. While the actual targets and even terms are still to be defined, the strategy's possible impacts can be simulated for policy support purposes. The strategy aims to increase protection by setting aside forests and extending closer-to-nature forest management practices. We simulated Finland's forest resources with the European Forestry Dynamics Model (EFDM) considering the protection targets. According to our simulations, the total growing stock and net present value will be lower with the additional protection than by carrying on the business-as-usual management. The additional protection resulted in intensified harvesting in the remaining forest area available for wood supply with the current harvest level. This may weaken the positive ecological impacts of protection. Reducing the harvest level from the current level is not a likely alternative either, because the demand for biomass is predicted to increase in the future, while the supply is insufficient, and EU policies aim to avoid shifting the negative impacts of resource extraction outside the EU. The feasibility of the additional protection depends on the actual implementation and definitions. [ABSTRACT FROM AUTHOR]

Author(s): Iddo K. Wernick [sup.1] , Philippe Ciais [sup.2] , Jonas Fridman [sup.3] , Peter Högberg [sup.4] , Kari T. Korhonen [sup.5] , Annika Nordin [sup.4] , Pekka E. Kauppi [...]

With climate change, natural disturbances such as storm or fire are reshuffled, inducing pervasive shifts in forest dynamics. To predict how it will impact forest structure and composition, it is crucial to understand how tree species differ in their sensitivity to disturbances. In this study, we investigated how functional traits and species mean climate affect their sensitivity to disturbances while controlling for tree size and stand structure. With data on 130,594 trees located on 7617 plots that were disturbed by storm, fire, snow, biotic or other disturbances from the French, Spanish, and Finnish National Forest Inventory, we modeled annual mortality probability for 40 European tree species as a function of tree size, dominance status, disturbance type, and intensity. We tested the correlation of our estimated species probability of disturbance mortality with their traits and their mean climate niches. We found that different trait combinations controlled species sensitivity to disturbances. Storm-sensitive species had a high height-dbh ratio, low wood density and high maximum growth, while fire-sensitive species had low bark thickness and high P50. Species from warmer and drier climates, where fires are more frequent, were more resistant to fire. The ranking in disturbance sensitivity between species was overall consistent across disturbance types. Productive conifer species were the most disturbance sensitive, while Mediterranean oaks were the least disturbance sensitive. Our study identified key relations between species functional traits and disturbance sensitivity, that allows more reliable predictions of how changing climate and disturbance regimes will impact future forest structure and species composition at large spatial scales. [ABSTRACT FROM AUTHOR]

Accurate mensuration of forest stands for pre-harvest planning will pose high costs if carried out by a professional forester as an on-site evaluation. The costs could be reduced if a person with limited mensuration expertise could collect the required data using a smartphone-based system such as TRESTIMA® Forest Inventory System. Without prior information, the field sample with sufficient number of measurement points over the whole stand should be selected, so that the entire variation will be covered. We present and test a rational framework based on selecting the sampling locations according to auxiliary data. As auxiliary variables, we use various spatial data sources indicating forests' structural or spectral variation, as well as previously predicted inventory variables. We construct two variants of sampling schemes based on the local pivotal method, weighted by the auxiliary data, and compare the results to simple random sampling (SRS) with corresponding sample sizes. According to our findings, the benefits of auxiliary data depend on the considered stand, species and timber assortment. The use of auxiliary data leads generally to improved results and up to three times higher efficiency (i.e. lower variance) as compared with SRS. We conclude that the framework of applying auxiliary data has high capabilities in rationalizing the sampling efforts with little drawbacks, consequently providing potential to improve the results with similar sample size and possibility to use of non-specialists for the pre-harvest inventory. [ABSTRACT FROM AUTHOR]

Finnish forest structures vary from even-aged planted forests to two- and multi-storied mixed stands. Also, the range of silvicultural systems in use has increased because thinning from above and continuous cover management are gaining popularity. The data currently available for modelling stand dynamics are insufficient to allow the development of unbiased and reliable models for the simulation of all possible transitions between various current and future stand conditions. Therefore, the models should allow temporal and regional calibration along the accumulation of new information on forest development. If the calibration process is automated, the simulators that use these models constitute a self-learning system that adapts to the properties of new data on stand dynamics. The current study first developed such a model set for stand dynamics that is technically suitable for simulating the stand development in all stand structures, silvicultural systems and their transitions. The model set consists of individual-tree models for diameter increment and survival and a stand-level model for ingrowth. The models were based on the permanent sample plots of the 10th and 11th national forest inventories of Finland. Second, a system for calibrating the models based on additional data was presented. This optimization-based system allows different types and degrees of calibration, depending on the intended use of the models and the amount of data available for calibration. The calibration method was demonstrated with two external datasets where a set of sample plots had been measured two times at varying measurement intervals. [ABSTRACT FROM AUTHOR]

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. [Display omitted] • Increment estimation approaches differ among European NFIs. • Harmonisation framework developed for gross and net annual increment. • Common increment estimation method implemented by 10 European countries. • Harmonised increments estimated for NUTS regions, forest types and tree species. • Harmonised increments improve the comparability of international forest statistics. [ABSTRACT FROM AUTHOR]

BACKGROUND Moose (Alces alces L.) populations and moose damage in forests are debated in Nordic countries with dense moose populations. Moose populations and food resources vary greatly, both spatially and temporally, and reliable data covering both variables simultaneously at the same scale have seldom been available. We modelled the effect of moose population density and forest resources on the area of moose damage at regional scale, referring to moose management areas (MMA). Forest data and moose damage data originated from the Finnish National Forest Inventory, and the moose population data came from a Bayesian moose model. For modelling, average values of moose population, damage and forest variables were calculated for the periods 2004–2008 and 2009–2013 for each MMA. The MMAs were further classified into one of four larger geographical zones. The area of moose damage was used as a dependent variable, and the proportions of different types of forests and moose population densities per land area or area of seedling stands as explanatory variables. The relationships were modelled with a linear mixed‐effects model with an exponential spatial correlation structure. RESULTS: The area of moose damage was best explained by total forest area, proportions of plantations and mature forests, and moose population density per land area or the proportion of plantations. There were differences among the biogeographical zones in how different variables explained the amount of damage. CONCLUSION: The results provide tools for analyzing the regional effects of moose population density and the amount of food resources on the amount of moose damage. This information can be used in reconciling sustainable moose population levels and the amount of damage. [ABSTRACT FROM AUTHOR]

We evaluated the impacts of juvenile stand management on wood production based on a nationwide scenario analysis. Measured plot-level information of the Finnish 11th National Forest Inventory (NFI) from juvenile stands formed the initial data for the analysis. To represent a total of 2.5 million hectares of productive forest land available for wood production, 6900 sample plots were selected. We predicted the development of the sample-plot stands for the next 100 years using the Motti stand simulator. We examined the impacts of juvenile stand management, including early cleaning and precommercial thinning, with three scenarios of different intensities of early-stage management (intensive, no management and business-as-usual). The results showed the benefits of juvenile stand management: earlier harvesting revenues, larger total removals, more valuable wood in the removals, and additional benefits that are associated with the first commercial thinning (i.e. no need for clearing before thinning, a larger stem size of removed trees). The main downside of juvenile stand management was the cost of the early cleaning and precommercial thinning. According to the results, a €560 million increase in costs would result in a €1700 million increase in stumpage earnings in Finnish forests during the next 100-year period. The 34 million m3 increase in the sawlog yield together with 28 million m3 decrease in the pulpwood yield also demonstrated the nationwide potential for increasing valuable sawlog production by intensive management of juvenile stands. [ABSTRACT FROM AUTHOR]

Planning a forest inventory comprises making decisions related to the sampling strategy: cluster configuration, sample size and sample allocation within the survey area. Cluster configuration includes deciding on the number of sample plots within the cluster and distances between them. Available resources set the limit for field work in terms of man-days. If the time consumption for measurements is known, the sample size can be determined under the constraint. In this study, we simulated the second phase of inventory sampling with fixed time resources by replicating sample selection with a spatially balanced sampling utilizing local pivotal method (LPM) for different cluster configurations to find the most efficient. As a result, the temporary cluster configuration was changed from 9 to 5-sample plot configuration in a pilot inventory. Further, the sample selection was performed with LPM having total growing stock volume and broadleaf volume proportion as auxiliary information. The pilot results were aligned with the time series in respect to forest area and total growing stock volume, but in tree species groups deviations were observed in growing stock volume. A more comprehensive optimization should include the travelling routes, the plot-to-plot distances and the plot design. In any case, the result is region specific. [ABSTRACT FROM AUTHOR]

Assessing the need for and timing of tending in seedling stands is based on the stem numbers and heights of crop trees and competing broadleaves, as well as the expected forthcoming development of stand. The assessment is partly an outcome of field worker’s opinion and experience. The tending need of Norway spruce- and Scots pine-dominated seedling stands was modeled using the National Forest Inventory (NFI) data from southern Finland. The models predict the probabilities that the NFI field team leader’s proposal falls in the following four categories: tending is late, during the first or second 5-year period or no need for tending. The predictors such as stem numbers, tree heights, site fertility, regeneration method and accomplished tending logically explained the tending need. The overall accuracy of the models was only fair: 54% (kappa 0.27) for spruce and 55% (kappa 0.33) for pine. However, about 95% of the stands needing immediate tending were classified as stands needing immediate or first 5-year period tending. The surveyor-specific random effects were statistically significant, and the surveyors were likely to propose tending similarly in spruce and pine stands. The models can be utilized in forest planning systems and practical forest inventory. [ABSTRACT FROM AUTHOR]

The Nordic countries have long traditions in forest inventory and remote sensing (RS). In sample-based national forest inventories (NFIs), utilization of aerial photographs started during the 1960s, satellite images during the 1980s, laser scanning during the 2000s, and photogrammetric point clouds during the 2010s. In forest management inventories (FMI), utilization of aerial photos started during the 1940s and laser scanning during the 2000s. However, so far, RS has mostly been used for map production and research rather than for estimation of regional parameters or inference on their accuracy. In recent years, the RS technology has been developing very fast. At the same time, the needs for information are constantly increasing. New technologies have created possibilities for cost-efficient production of accurate, large area forest data sets, which also will change the way forest inventories are done in the future. In this study, we analyse the state-of-the-art both in the NFIs and FMIs in the Nordic countries. We identify the benefits and drawbacks of different RS materials and data acquisition approaches with different user perspectives. Based on the analysis, we identify the needs for further development and emerging research questions. We also discuss alternatives for ownership of the data and cost-sharing between different actors in the field. [ABSTRACT FROM AUTHOR]

Forests are important sources of livelihoods to millions of people and contribute to national economic development of many countries. In addition, they are vital sources and sinks of carbon and contribute to the rate of climate change. The UN Food and Agriculture Organization has been collecting and presenting data on global forest resources and forest cover since 1948. This paper builds on data from FAO’s 2015 Global Forest Resource Assessment (FRA) and presents information on growing stock, biomass, carbon stock, wood removals, and changes of forest area primarily designated for production and multiple use of the world’s forests. Between 1990 and 2015, the total growing stock volume has increased in East Asia, Caribbean, Western and Central Asia, North America, Europe (including the Russian Federation), and Oceania with the highest relative increase in East Asia and the Caribbean. In all other subregions the total growing stock volume decreased. North and Central America, Europe and Asia report forest C stock increases while South America and Africa report strong decreases and Oceania reports stable forest C stocks. The annual rate of decrease of forest C stock weakened between 1990 and 2015. The total volume of annual wood removals including woodfuel removals increased between 1990 and 2011, but shows a remarkable decline during the 2008–2009 economic crisis. Forest areas designated for production purposes differ considerably between subregions. The percentage of production area out of total forest area ranges between 16 percent in South America and 53 percent in Europe. Globally about one quarter of the forest area is designated to multiple use forestry. The balance between biomass growth and removals shows considerable sub-regional differences and related implications for the sustainable use of forests. [ABSTRACT FROM AUTHOR]

A pan-European forest cover map (FMAP2006) was produced using a novel automated classification approach using remotely sensed data from fine resolution satellite instruments. In contrast to previous classification accuracy assessments of such continental scale land cover products, the current study aimed for a reliable assessment at different geographical levels: pan-European, regional and local level. A unique data set consisting of detailed field inventory plots was provided via a collaboration with the national forest inventories (NFIs) in Europe. Close to 900,000 field plots were available for the assessment. The fine spatial resolution of the FMAP2006 facilitated the label assignment of the field plots to subsets of mapped pixels for the accuracy assessment process, thereby overcoming scale and definition difficulties encountered in previous studies with coarser resolution products. An overall accuracy of 88% was achieved at pan-European level based on the field plots of the NFIs. It is demonstrated that important differences exist for the class accuracies in different geographical regions, particularly at the regional and local level. [ABSTRACT FROM PUBLISHER]

Abstract: The growing stock more than doubled from 1.6 to 3.4millionm3 between 1912 and 2005 in forests on an area of 387km2 in southern Finland. The stock expansion continued for 93 years noting interim results, which were available for 1959, 1982, 1994 and 1999. Forested area in the region hardly changed. Carbon sequestration was mainly a result of a long-term recovery from forest degradation, a legacy of land use in the 18th and 19th centuries. Tree demography responded to management change especially of mature stands: Average tree size and stocking density of stands increased. On average the expanding biomass stock sequestered 18tons C annually per km2 (18g C per m2). In comparison, the emissions of fossil carbon in the region were estimated at 12tons C per km2 (12g C per m2) on average. However, fossil CO2 emissions exceeded biomass sequestration in recent decades. The powerful and persistent expansion of the carbon stock was an unintended co-benefit of forestry, which was motivated by the intention to improve timber yield. On the more negative side the change in management introduced clear-cuts, and a loss of diverse elements of the pre-industrial biota. [Copyright &y& Elsevier]

Sources: Landsskogtakseringen, 1933/NIBIO; BFW; BMLRT. [Display omitted] • Early wood shortage in European history caused the need to explore and plan the utilisation of wood resources. • Current NFI methods reflect country-specific conditions, inventory traditions and information needs. • Harmonisation of European NFIs provides internationally comparable growing stock estimations. • Ongoing NFI innovations integrate remote sensing for higher spatial and temporal resolution. • Emerging data requirements relate to forest resilience and stability of growing stocks. Wood resources have been essential for human welfare throughout history. Also nowadays, the volume of growing stock (GS) is considered one of the most important forest attributes monitored by National Forest Inventories (NFIs) to inform policy decisions and forest management planning. The origins of forest inventories closely relate to times of early wood shortage in Europe causing the need to explore and plan the utilisation of GS in the catchment areas of mines, saltworks and settlements. Over time, forest surveys became more detailed and their scope turned to larger areas, although they were still conceived as stand-wise inventories. In the 1920s, the first sample-based NFIs were introduced in the northern European countries. Since the earliest beginnings, GS monitoring approaches have considerably evolved. Current NFI methods differ due to country-specific conditions, inventory traditions, and information needs. Consequently, GS estimates were lacking international comparability and were therefore subject to recent harmonisation efforts to meet the increasing demand for consistent forest resource information at European level. As primary large-area monitoring programmes in most European countries, NFIs assess a multitude of variables, describing various aspects of sustainable forest management, including for example wood supply, carbon sequestration, and biodiversity. Many of these contemporary subject matters involve considerations about GS and its changes, at different geographic levels and time frames from past to future developments according to scenario simulations. Due to its historical, continued and currently increasing importance, we provide an up-to-date review focussing on large-area GS monitoring where we i) describe the origins and historical development of European NFIs, ii) address the terminology and present GS definitions of NFIs, iii) summarise the current methods of 23 European NFIs including sampling methods, tree measurements, volume models, estimators, uncertainty components, and the use of air- and space-borne data sources, iv) present the recent progress in NFI harmonisation in Europe, and v) provide an outlook under changing climate and forest-based bioeconomy objectives. [ABSTRACT FROM AUTHOR]

Two decades after the pan-European set of indicators for sustainable forest management was adopted, the European Commission published the New EU Forest Strategy for 2030. We compared the documents on the basis of a content analysis to determine whether they share the same understanding of sustainable forest management. We looked at whether, and to what extent, the existing indicator set is fit for purpose to monitor progress towards the Strategy's objectives, and the delivery of policy commitments. About two thirds of the identified objectives and commitments in the Strategy can be monitored at least partially by the pan-European set of indicators, whereas new indicators or approaches need to be developed for the remaining third. Several of the indicators are not linked to the Strategy, and some of them are only weakly linked to the policy issues addressed in the Strategy. Our comparison shows a few significant differences between the comprehensive vision of sustainable forest management formulated in the indicator set and the scope of the objectives and commitments in the Strategy. In particular, the forest policy concerns reflected in the Strategy address several issues which are not fully covered in the pan-European indicator set. [ABSTRACT FROM AUTHOR]

We analysed the regional level effects of juvenile stand management (early cleaning and precommercial thinning), shortly termed tending on wood production and the profitability of forest management. Altogether ca. 0.4 million hectares of juvenile stands from two significant forestry regions of Finland, South and North Savo, were examined. We used plot-level data of the 11th National Forest Inventory to represent the current status of juvenile stands in the study area, and the Motti stand simulator to predict the future developments of those stands for the next 100 years. We applied three scenarios: (i) Timely tending, (ii) delayed tending, and (iii) no tending, to examine differences between these alternative levels of juvenile stand management. The results showed the benefits of tending at a regional level. Timely tending was the most profitable option when low or modest interest rates (2–3%) were applied in the assessment. Even a short delay in tending clearly increased the tending costs. Delaying and neglecting tending resulted in significant losses, especially in sawlog removals and stumpage earnings. The financial gain from tending was the highest on fertile sites. Due to the high growth rate of trees, the situation may change very quickly on such sites. For the operational forestry, this means that fertile sites should have a high priority when conducting timely tendings. [ABSTRACT FROM AUTHOR]

Forest information is needed at global, national and local scales. This review aimed at providing insights of potential of national forest inventories (NFIs) as well as challenges they have to cater to those needs. Within NFIs, the authors address the methodological challenges introduced by the multitude of scales the forest data are needed, and the challenges in acknowledging the errors due to the measurements and models in addition to sampling errors. Between NFIs, the challenges related to the different harmonization tasks were reviewed. While a design-based approach is often considered more attractive than a model-based approach as it is guaranteed to provide unbiased results, the model-based approach is needed for downscaling the information to smaller scales and acknowledging the measurement and model errors. However, while a model-based inference is possible in small areas, the unknown random effects introduce biased estimators. The NFIs need to cater for the national information requirements and maintain the existing time series, while at the same time providing comparable information across the countries. In upscaling the NFI information to continental and global information needs, representative samples across the area are of utmost importance. Without representative data, the model-based approaches enable provision of forest information with unknown and indeterminable biases. Both design-based and model-based approaches need to be applied to cater to all information needs. This must be accomplished in a comprehensive way In particular, a need to have standardized quality requirements has been identified, acknowledging the possibility for bias and its implications, for all data used in policy making. [ABSTRACT FROM AUTHOR]

Litter input drives dynamic soil models that are used to understand the flows and stocks of soil carbon. In estimation of above-ground litterfall, much of the uncertainty lies in the turnover rate of branches. The objective of this study was to develop a model for estimating the branch litterfall of Scots pine stands.Here the potential litterfall of branches was modelled as a function of tree diameter. First, the vertical biomass distribution of branches was predicted on the basis of branch biomass data collected from trees sampled in southern Finland. Second, to predict annual branch mortality and potential litterfall, this information was combined with data on measured changes in height of the crown base.Depending on stem dbh (diameter at breast height), the proportion of annual litterfall of branches from the total biomass of branches varied from 6% to 0.5%, being highest in small trees. According to the results of this study, the litterfall of branches depends on tree size and stocking density. When the estimates were tested against data on collection of branch litter, it was found that the method underestimates litterfall in very old stands but agrees with the measurements in other stands.Application of this model to rates of branch litter production improves the accuracy of the estimated litter input to the dynamic soil model, therefore also improving the precision of soil carbon estimates. [Copyright &y& Elsevier]