Mean species cover: a harmonized indicator of shrub cover for forest inventories

Because shrub cover is related to many forest ecosystem functions, it is one of the most relevant variables for describing these communities. Nevertheless, a harmonized indicator of shrub cover for large-scale reporting is lacking. The aims of the study were threefold: to define a shrub indicator that can be used by European countries for harmonized shrub cover estimation using data from their respective national forest inventories (NFIs); to quantify the effects of using different NFI field cover scales; and to establish bridges to facilitate harmonized estimation. Data for shrub species cover from the Third Spanish NFI together with scales for cover assessment from 16 European NFIs were used. The indicator, mean species cover (MSC), was defined for each species and each European forest category. Estimates of MSC calculated using species covers recorded for field plots, with 1% interval widths (MSCobs), were compared with the MSC values that would be obtained for the same data with the different European cover scales (MSCpred). Residuals calculated as differences between MSCobs and MSCpred were analyzed, and a linear mixed model was used as bridging function to adjust predictions and thus further harmonize estimates. Scales with only two or three intervals produced the greatest residuals, while all the other analyzed scales had residuals less than 5%. Most scales, except those most similar to Braun-Blanquet, displayed a tendency to be unreliable for larger covers. The proposed mean species cover indicator provides comparable estimates for shrub communities at large scales. The linear models improved the harmonization of MSC for the scales having two and three intervals.     

Estimates of stem wood increments in forest resources: comparison of different approaches in forest inventory: consequences for international reporting: case studyof European forests

Key message

Quality and reliability of forest resource assessments depend on the ability of national forest inventories (NFIs) to supply necessary and high-quality data. Over the last decades and especially since the 1990s, the NFIs in European countries have been rapidly developing. Possibilities for obtaining reliable and accurate data on annual increment from different inventory types were evaluated, and sample-based inventories have been found to be superior to standwise inventories in providing reliable data. Simplified methods may be employed when increment cannot be directly estimated from inventory data.

Context

An increasing intensity of forest resource use requires more accurate, detailed and reliable information, not only on forest area and growing stock but also on forest stand productivity, wood increment and its components.

Aims

The main objectives were to assess the capacities of forest inventories, the methods used for estimation of gross increment and its components and their accuracy and to demonstrate an effective method for estimation of increment when direct inventory methods are not available.

Methods

Data about national forest inventory methods were obtained from 30 responses to a questionnaire, distributed amongst national correspondents of all European countries; reports of COST Actions E43 and FP 1001, databases of Temperate and Boreal Forest Resource Assessment (TBFRA) 2000 and State of Europe’s Forests (SoEF) 2011 were used as well. Analysis and comparison of results from different forest inventories were used for evaluation of data reliability. Relationships between growing stock and gross increment in European forests were also analysed, and corresponding models were proposed.

Results

Seventy-nine percent of European forest area is covered by national forest inventories (NFIs) based on sampling methods and the rest on stand-level inventory and other inventory methods. Data obtained by aggregating standwise data usually underestimate growing stock by 15–20 % and gross increment even more. Almost half of the European forest area (47 %) is monitored using permanent plots, measured twice or more, allowing the estimation of gross increment and its components to be made directly.

Conclusion

Implementation of NFIs based on sampling methods, especially with permanent plots, resulted in an improvement of data quality and in most cases an increase of growing stock and gross increment. The estimation of natural losses is the weakest link in today’s NFIs and in the current assessment of European forest resources. The proposed default values for gross increment and its components is an option to be used in countries not having NFI at all or those which have started it only recently.

     

Comparison of methods used in European National Forest Inventories for the estimation of volume increment: towards harmonisation

Key message

The increment estimation methods of European NFIs were explored by means of 12 essential NFI features. The results indicate various differences among NFIs within the commonly acknowledged methodological frame. The perspectives for harmonisation at the European level are promising.

Context

The estimation of increment is implemented differently in European National Forest Inventories (NFIs) due to different historical origins of NFIs and sampling designs and field assessments accommodated to country-specific conditions. The aspired harmonisation of increment estimation requires a comparison and an analysis of NFI methods.

Aims

The objective was to investigate the differences in volume increment estimation methods used in European NFIs. The conducted work shall set a basis for harmonisation at the European level which is needed to improve information on forest resources for various strategic processes.

Methods

A comprehensive enquiry was conducted during Cost Action FP1001 to explore the methods of increment estimation of 29 European NFIs. The enquiry built upon the preceding Cost Action E43 and was complemented by an analysis of literature to demonstrate the methodological backgrounds.

Results

The comparison of methods revealed differences concerning the NFI features such as sampling grids, periodicity of assessments, permanent and temporary plots, use of remote sensing, sample tree selection, components of forest growth, forest area changes, sampling thresholds, field measurements, drain assessment, involved models and tree parts included in estimates.

Conclusion

Increment estimation methods differ considerably among European NFIs. Their harmonisation introduces new issues into the harmonisation process. Recent accomplishments and the increased use of sample-based inventories in Europe make perspectives for harmonised reporting of increment estimation promising.

     

Contribution of large-scale forest inventories to biodiversity assessment and monitoring

Statistically-designed inventories and biodiversity monitoring programs are gaining relevance for biological conservation and natural resources management. Mandated periodic surveys provide unique opportunities to identify and satisfy natural resources management information needs. However, this is not an end in itself but rather is the beginning of a process that should lead to sound decision-making in biodiversity conservation. Forest inventories are currently evolving towards multipurpose resource surveys and are broadening their scope in several directions: (i) expansion of the target population to include non-traditional attributes such as trees outside the forest and urban forests; (ii) forest carbon pools and carbon sequestration estimation; (iii) assessment of forest health; and (iv) inclusion of additional variables such as biodiversity attributes that are not directly related to timber assessment and wood harvesting.There is an on-going debate regarding the role of forest inventories in biodiversity assessment and monitoring. This paper presents a review on the topic that aims at providing updated knowledge on the current contribution of forest inventories to the assessment and monitoring of forest biodiversity conditions on a large scale. Specific objectives are fourfold: (i) to highlight the types of forest biodiversity indicators that can be estimated from data collected in the framework of standard forest inventories and the implications of different sampling methods on the estimation of the indicators; (ii) to outline current possibilities for harmonized estimation of biodiversity indicators in Europe from National Forest Inventory data; (iii) to show the added value for forest biodiversity monitoring of framing biodiversity indicators into ecologically meaningful forest type units; and (iv) to examine the potential of forest inventory sample data for estimating landscape biodiversity metrics.     

Defining the forest landowner’s utility–loss compensative subsidy level for a biodiversity object

New, cost efficient and voluntary biodiversity protection tools may require bidding price definition on part of the seller. Both the seller and the buyer can withdraw from negotiations if they find that the conditions of the protection contract are unacceptable. However, it can be very difficult for non-industrial, private landowners to define the bidding price demand for their biodiversity objects. The terms of the protection contract, the production possibilities of the forest holding, the forest owner’s multiple forest management goals and their substitutability, and the possible monetary subsidy paid for biodiversity protection should all be simultaneously taken into account when estimating the owner’s price demand for protecting the biodiversity object. This study strives to provide relief in resolving this problem by presenting an approach in which the landowner’s utility–loss compensative subsidy can be defined based on the owner’s forest-holding level utility function and the production possibilities of the holding. The properties of the approach are illustrated by four planning cases in which the length of the protection period (permanent or 20-year temporary protection) and the holding-level goals were varied. The utility functions of the cases were derived by selecting numeric goal variables for the goals, and by defining weights and sub-utility functions for these variables. Varying subsidies for protecting an old-growth spruce stand were included into the simulation of “No treatment” schedules for the examined stand, and the holding-level total utility was maximized for every price level. The utility–loss compensative subsidy was found when the holding-level total utility equaled the total utility achieved in the plan where the stand was regenerated. This subsidy, however, is not necessarily the exact price that the owner should ask from the buyer; all prices above the defined subsidy level will increase owner’s utility if the buyer accepts them. It was concluded that the presented approach provided consistent results in the four cases and that it thus offers valuable decision support for current biodiversity-protection programs.     

Estimating tree species diversity across geographic scales

The relationship between number of species and area observed has been described using numerous approaches and has been discussed for more than a century. The general objectives of our study were fourfold: (1) to evaluate the behaviour of species–area curves across geographic scales, (2) to determine sample sizes necessary to produce acceptably precise estimates of tree species diversity, (3) to evaluate relationships among estimates of tree species diversity for local to large geographic scales, and (4) to determine whether the proportion of native tree species may be precisely estimated using sample sizes smaller than those necessary to estimate total tree species diversity. Such investigations are necessary to improve biodiversity monitoring at large scales. The analytical approaches included Monte Carlo bootstrap simulations and two geospatial methods and relied on a database populated with data for more than 12,000 national forest inventory plots (NFI) from 16 regional units, 13 European countries and three ecoprovinces of the United States of America (USA). Four primary results were obtained. First, tree species diversity may be precisely estimated using observations for a random subsample of 2,000–4,000 NFI plots. Second, large sample sizes are necessary to estimate tree species diversity for regional units or forest categories, except possibly for boreal forests for which the number of tree species is small. Third, estimates of the proportion of native tree species may be precisely estimated using tree species information for a random sample of approximately 30 NFI plots. Finally, our estimated species–area curves show that the curve shapes and relationships among estimates of tree species diversity at large scales clearly depend on the relative geographic location of the anchor regional unit (a European country or ecoprovince of the USA) relative to the other regional units. None of the well-known models for species–area curves adequately describes our results. The conclusion was that the uncertainties of the estimates reflect the unfavourable state of global biodiversity monitoring of species groups. The total numbers of tree species in our regional units, which cannot be adequately estimated, are small relative to other tree species-rich regions. Consequently, monitoring of tree species diversity is currently a highly uncertain enterprise at large scales.     

Governance of forest conservation and co-benefits for Bangladesh under changing climate

We focused on key aspects of forest governance for biodiver- sity conservation in implementing new climate change policies. The national forest institutions must be adaptive to identify the existing pitfalls of prior conservation policies to take advantage of new climate change policies. Strengthening roles and technical capacity of national institutions for systematic biodiversity monitoring and carbon stock assessment is required in developing and least developed countries. Community participation needs careful analysis to ensure equitable ac- cess of particular social groups to local decision-making processes and to sustain optional livelihoods. The livelihood options around forest reserves or protected areas must be taken into account to enhance forest-based adaptation.     

Interactive Method for Supporting Forest Owners in Biodiversity Protection Decisions

Voluntary biodiversity protection tools have been adopted for practical use in many countries where non-industrial private forest ownership includes invaluable biodiversity resources. This has created a new kind of decision problem for individual forest owners: they should be able to define their conditions for entering into a biodiversity protection contract including sometimes a predetermined subsidy. This study presents a holding-level method for examining this decision problem. The method is based on utilization of interactive optimization where the possible subsidy has been included in the protection (no treatment) alternative of the examined stand. Generally, interactive optimization means that the landowner pinpoints the best plan by interactively studying and learning the production possibilities of his/her forest holding. Following changes made to the objective function by the forest owner, new solutions are presented for forest owners’ evaluation. If the “No treatments” option is selected in optimization for these areas, the forest owner would benefit more—in the current location of the production frontier and with the current subsidy—from entering into the protection contract than from cutting the specific forest area. In the case study, we demonstrate that the values of the holding-level goals, production possibilities of the planning area and the levels of the subsidy have a significant effect on the optimal decisions relating to biodiversity protection on the stand level.     

Explaining gender differences in private forest risk management

In many countries, lower levels of forest management activities have been observed among female forest owners compared to male owners. The present study examined potential explanations for gender differences in private forest risk management among forest owners in Sweden (n?=?1482) using a questionnaire. Results from this study confirmed a slightly lower level of forest risk management among female owners in proactively combating damage caused by climate change and animal browsing when compared to their male counterparts. Further gender differences were revealed on a structural level. For example, female owners displayed higher levels of education and were more often non-resident owners and urban owners, as compared to their male counterparts. In addition, female and male owners differed regarding social-psychological variables (e.g. forest values and threat and coping appraisals). However the greatest gender difference was found in involvement in forest planning and forestry work. Even though gender differences were evident on multiple levels, involvement in forest issues and forest planning were found to be most important for explaining gender differences in forest risk management. By disentangling predictors of gender differences in private forest risk management, this study may contribute to a more strategic gender approach to forest risk governance.     

Assessment of bias due to random measurement errors in stem volume growth estimation by the Swedish National Forest Inventory

Abstract

We evaluated the performance of two methods for estimating stem volume increment at individual tree level with respect to bias due to random measurement errors. Here, growth is either predicted as the difference between two consecutive volume estimates where single-tree volume functions are applied to data from repeated measurements or by a regression model that is applied to data from a single survey and includes radial increment. In national forest inventories (NFIs), the first method is typically used for permanent plots, the second for temporary plots. The Swedish NFI combines estimates from both plot types to assess growth at national and regional scales and it is, therefore, important that the two methods provide similar results. The accuracy of these estimates is affected by random measurement errors in the independent variables, which may lead to systematic errors in predicted variables due to model non-linearity. Using Taylor series expansion and empirical data from the Swedish NFI we compared the expected bias in stem volume growth estimates for different diameter classes of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.). Our results indicate that both methods are fairly insensitive to random measurement errors of the size that occur in the Swedish NFI. The empirical comparison between the two methods showed greater differences for large diameter trees of both pine and spruce. A likely explanation is that the regressions are uncertain because few large trees were available for developing the models.     

全国森林资源年度出数方法探讨

以我国现行森林资源清查体系为基础,研究提出了3种全国森林资源年度出数的方法,并针对目前可行的年度滚动和更新预测两种方法,利用第五次到第八次的全国森林资源清查结果,从数据时效性、稳定性和确定性等方面进行了对比分析。结果表明:更新预测方法能有效解决数据的时效性问题,确保年度数据稳定可靠,是目前值得推荐使用的可行方法。     

国家级森林资源清查地面样地设计

对世界主要国家森林资源清查地面样地设计进行了述评, 包括样本单元的构成、样地大小、形状、样本单元中树木的选择方法、调查因子和调查周期。发现样本单元多采用群团样地或样地群, 圆形样地应用较多, 调查因子除森林资源外, 还包括森林健康、生物多样性、碳和土壤等。结合我国森林资源清查在样地设计方面的问题, 提出了相应的对策和建议。     

Estimating forest data for analyses of forest production and utilization possibilities at local level by means of multi-source National Forest Inventory

The sample plot data of National Forest Inventories (NFI) are widely used in the analysis of forest production and utilization possibilities to support national and regional forest policy. However, there is an increasing interest for similar impact and scenario analyses for strategic planning at the local level. As the fairly sparse network of field plots only provides calculations for large areas, satellite image data have been applied to produce forest information for smaller areas. The aim of this study was to test the feasibility of generating forest data for a Finnish forest analysis tool, the MELA system, by means of the Landsat satellite imagery and the NFI sample plot data. The study was part of the preparation of a local forestry programme, where a strategic scenario analysis for the forest area of two villages (ca 8000 ha) was carried out. Management units that approximate forest stands were delineated by image segmentation. Stand volume and other parameters for each forest segment were estimated from weighted means of the NFI sample plots, where the individual sample plot weights were estimated by the k nearest neighbour (kNN) method. Two different spectral features were tested: single pixel values and average pixel values within a segment. The estimated forest data were compared with the forest data based on independent stand-level field assessments in two subareas, a national park and an area of forest managed for timber production.In the national park, the estimated mean volume of the growing stock from both spectral feature sets (about 160 m³ ha⁻¹) was clearly lower than that obtained from stand-level field assessment (186 m³ ha⁻¹). Using average pixel values within a segment resulted in a higher proportion of pine and a lower proportion of spruce volume than using single pixel values. It also resulted in an estimated felling potential nearly 10% higher over the first 10-year period in the scenario analysis of the area dedicated to timber production. However, the maximum long-term sustainable removal was at the same level (about 30,000 m³ year⁻¹) for both feature sets over the simulated 30-year period. The resulting annual felling area in the first 10-year period was 12% lower when the segment averages were applied, but the difference subsequently levelled off. The kNN approach in estimating initial forest data for scenario analyses at the local level was found promising.     

Determining sample size in national forest inventories by cost-plus-loss analysis: an exploratory case study

National forest inventories provide information for strategic decisions in a large number of countries. In general, they cover a wide range of variables, from timber-related features to biodiversity and carbon sequestration. Often, it is difficult to decide the exact scope and design of this type of inventory; especially, it is difficult to decide the appropriate sample size. In planning inventories, trade-offs between cost and precision for core variables frequently are made; however, this approach does not fully acknowledge the fact that data typically are collected to form the basis for decisions. In theory, cost-plus-loss analysis provides a more holistic approach to inventory planning, since both inventory costs and losses due to information deficiencies in the decision-making processes are considered. However, whilst it is normally straightforward to determine cost functions, loss functions are difficult to establish; an important reason is that the linkages between data and decisions must be clearly understood. In this study, we explored the possibilities for using cost-plus-loss analysis in connection with determining the appropriate sample size of a national forest inventory. We used Sweden as a case and restricted the analysis to consider the use of data for determining sustainable harvesting levels. The results indicated that the number of plot clusters in Sweden should be in the order of 1,300–2,400 annually, whereas it is currently about 1,400. However, our main objective of the study was not to determine an exact answer for the case of Sweden, but rather to suggest pathways for how cost-plus-loss analysis could be used to support decisions related to determining the appropriate sample size of national forest inventories.     

国家森林资源调查体系改进探讨

通过对国内外国家森林资源连续清查体系的抽样设计、样地设计以及调查因子的介绍和对比,揭示了国内国家森林资源监测的不足和面临的挑战,指出国内国家森林资源监测需要进一步完善,以适应国内外不断扩张的信息需求.并从抽样设计、样地设计以及调查因子等方面给出了现有调查体系改进的可能性.     

Deadwood volume assessment in the third Swiss National Forest Inventory: methods and first results

The Swiss National Forest Inventory (NFI) is expected to provide reliable data about the current state of the Swiss forests and recent changes. Since the first Swiss NFI (1982–1986) a deadwood assessment has been part of the inventory. However, the definition of deadwood used was restricted and only parts of the total deadwood volume were assessed. A broader definition was therefore used in the second NFI (1993–1995) and coarse wood debris (CWD) was also assessed using line intersect sampling in the third NFI (2004–2006). This paper discusses the development of the definition of deadwood from the first to the third Swiss NFI, as well as the tally rules and estimators used in assessing deadwood in the ongoing third NFI. Different definitions of deadwood were applied in two Swiss regions and the resulting volume estimates were compared. The definition of deadwood appears to be crucial for the estimate of deadwood volumes, which were significantly underestimated in the first and second Swiss NFI. The minimum diameter and other limits applied must be chosen with special care. Up to 30 m³/ha of deadwood was found in Swiss forests varying with the region. There was little evidence of significant correlations between deadwood volume and such forest parameters as management, site or stand attributes. The proposed target values for the volume of deadwood have been generally reached, whereas the number of snags per hectare has not.     

Large-scale dynamics of a heterogeneous forest resource are driven jointly by geographically varying growth conditions, tree species composition and stand structure

? Context

Forest resource projections are required as part of an appropriate framework for sustainable forest management. Suitable large-scale projection models are usually based on national forest inventory (NFI) data. However, sound projections are difficult to make for heterogeneous resources as they vary greatly with respect to the factors that are assumed to drive forest dynamics on a large spatial scale, e.g. geographically varying growth conditions (here represented by NFI regions), tree species composition (here broadleaf-dominated, conifer-dominated and broadleaf-conifer mixed stands) and stand structure (here high forest, coppice forest and high-coppice forest mixture).

? Question and objective

Our question was how does the variance of forest dynamics parameters (i.e. growth, felling and mortality, and recruitment processes) and that of 20-year forest resource projections partition between these factors (NFI region, tree species composition and stand structure), including their interactions. Our objective was to capitalise on the suitability of an existing multi-strata, diameter class matrix model for the purposes of making projections for the highly heterogeneous French forest resource.

? Methods

The model was newly calibrated for the entire territory of metropolitan France based on most recent NFI data, i.e. for years 2006?C2008. The forest resource was divided into strata by crossing the factors NFI region, tree species composition and stand structure. The variance partitioning of the parameters and projections was assessed based on a model sensitivity analysis.

? Results

Growth, felling and mortality varied mainly with NFI region and species composition. Recruitment varied mainly with NFI region and stand structure. All three factors caused variations in resource projections, but with unequal intensities. Factor impacts included first order and interaction effects.

? Conclusions

We found, by considering both first order and interaction effects, that NFI region, species composition and stand structure are ecologically relevant factors that jointly drive the dynamics of a heterogeneous forest resource. Their impacts, in our study, varied depending on the forest dynamics process under consideration. Recruitment would appear to have a particularly great impact on resource changes over time.     

Developing an airborne laser scanning dominant height model from a countrywide scanning survey and national forest inventory data

Abstract

An airborne laser scanning (ALS) dominant height model was developed based on data from a national scanning survey with the aim of developing a digital terrain model (DTM) for Denmark. Data obtained in the ongoing Danish national forest inventory (NFI) were used as reference data. The data comprised a total of 2072 measurements of dominant height on NFI sample plots inventoried in 2006–2007 and their corresponding ALS data. The dominant height model included four variables derived from the ALS point cloud distribution. The variables were related to canopy height, canopy density and species composition on individual plots. The RMSE of the final model was 2.25 m and the model explained 93.9% of the variation (R ²). The model was successful in predicting dominant height across a wide range of forest tree species, stand heights, stand densities, canopy cover and growing conditions. The study demonstrated how low-density ALS data obtained in a survey not specifically aimed at forest applications may be used for obtaining biophysical forest properties such as dominant height, thereby reducing the overall forest inventory costs.     

Remote sensing and forest inventories in Nordic countries – roadmap for the future

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.