Total Growing-stock Volume Research Articles

Carbon stock in living biomass of Russian forests: new quantification based on data from the first cycle of the State Forest Inventory

Abstract The carbon stock in living forest biomass was quantified based on first-cycle State Forest Inventory (SFI) measurements in permanent sample plots. The total carbon stock in above- and below-ground living biomass was assessed to be 46.9 ±0.4 × 109 tons C and average carbon stock at 52.1 ±0.5 t C ha–1 as of 2020. The State Forest Register (SFR), the primary source of consolidated information on Russia’s forests, estimates the forest growing stock to be 83.1 × 109 m3. The total growing stock volume in the forests, according to the SFI amounted to 113.1 × 109 m3. Owing to the updated and significantly higher growing stock volume, the estimate of carbon stock in living bio-mass is approximately 35% higher than previously reported. The uncertainty of the total and average carbon stocks based on SFI data was substantially lower (approximately ±1%) than that reported in previous studies (±15–30%). Methods of accounting for the carbon stock in living biomass, the results of calculations for forest lands throughout the country, units of the administrative division, and forest zoning were considered. Assessment of living biomass based on representative sampling can substantially improve the relevance and reliability of national forest reporting.

A Comparison of Model-Assisted Estimators, With and Without Data-Driven Transformations of Auxiliary Variables, With Application to Forest Inventory

Forest information is requested at many levels and for many purposes. Sampling-based national forest inventories (NFIs) can provide reliable estimates on national and regional levels. By combining expensive field plot data with different sources of remotely sensed information, from airplanes and/or satellite platforms, the precision in estimators of forest variables can be improved. This paper focuses on the design-based model-assisted approach to using NFI data together with remotely sensed data to estimate forest variables for small areas, where the variables studied are total growing stock volume, volume of Norway spruce (Picea abies), and volume of broad-leaved trees. Remote sensing variables may be highly correlated with one another and some may have poor predictive ability for target forest variables, and therefore model selection and/or coefficient shrinkage may be appropriate to improve the efficiency of model-assisted estimators of forest variables. For this purpose, one can use modern shrinkage estimators based on lasso, ridge, and elastic net regression methods. In a simulation study using real NFI data, Sentinel 2 remote-sensing data, and a national airborne laser scanning (ALS) campaign, we show that shrinkage estimators offer advantages over the (weighted) ordinary least-squares (OLS) estimator in a model-assisted setting. For example, for a sample size n of about 900 and with 72 auxiliary variables, the RMSE was up to 41% larger when based on OLS. We propose a data-driven method for finding suitable transformations of auxiliary variables, and show that it can improve estimators of forest variables. For example, when estimating volume of Norway spruce, using a smaller expert selection of auxiliary variables, transformations reduced the RMSE by up to 10%. The overall best results in terms of RMSE were obtained using shrinkage estimators and a larger set of 72 auxiliary variables. However, for this larger set of variables, the use of transformations yielded at most small improvements of RMSE, and at worst large increases of RMSE, except in combination with ridge and elastic net regression.

Effect of cluster configuration and auxiliary variables on the efficiency of local pivotal method for national forest inventory

ABSTRACTPlanning 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.

Mapping growing stock volume and biomass carbon storage of larch plantations in Northeast China with L-band ALOS PALSAR backscatter mosaics

ABSTRACTReliable spatial information on growing stock volume (GSV) and biomass is critical for creating management strategies for plantation forests. This study developed empirical models to map the GSV and biomass of larch plantations (LPs) in Northeast China (1.25 million km2 total area) by integrating L-band synthetic aperture radar (SAR) data with ground-based survey data. The best correlation model was used to map the GSVs and biomasses of LPs. The total GSV and biomass carbon storage were estimated at 224.3 ± 59.0 million m3 and 113.0 ± 29.7 × 1012 g C with average densities of 85.1 m3 ha−1 and 42.9 106 g × C ha−1, respectively, over a total area of 2.64 million ha. The saturation effect of SAR was determined beyond 260 m3 ha−1, which was expected to influence the estimations for a small proportion of the study area. The accuracy of the estimations has limitations mainly due to the uncertainties in the GSV inventories, discrimination of natural larch and the SAR dataset. Based on the mapping results of the GSVs of LPs, a planning strategy for multipurpose management was tentatively proposed. This study can inform policies and management practices to assure broader and sustainable benefits from plantation forests in the future.

Stereo-imagery-based post-stratification by regression-tree modelling in Swiss National Forest Inventory

Swiss National Forest Inventory (NFI) produces estimates of characteristics related to the state and change of the forest resources in the whole country as well as in smaller regions and domains. The estimates are based on measurements on permanent field plots placed on a systematic grid over the country. Digital stereo aerial images are an important source of auxiliary information that can be used with post-stratified estimation to increase the precision of the estimates. We examined post-stratification based on stereo image information, available on a much denser grid than the field plots, for the estimation of forest area, total growing-stock volume and growing-stock volume per unit of accessible forest area. We considered 31 post-stratification schemes that consisted of (1) forest/non-forest stratification by four alternative methods based on manual or semi-automated stereo image interpretation, and (2) sub-stratification within the forest stratum by regression-tree models constructed between field-measured growing-stock volume and stereo-image-retrieved vegetation height characteristics. We applied the schemes in two real NFI estimation cycles, and found that the most precise schemes reduced the variance of the whole-country estimators of forest area, total growing-stock volume and growing-stock volume per unit of accessible forest area by 81%, 67% and 34%, respectively, compared to the estimator without post-stratification. Based on this study, we consider regression-tree modelling well-suited for post-stratification, as it produces stratum boundaries as a direct result of modelling, appears robust against deviating values in fitting data, and avoids problems with unrealistic model predictions in application.

Changes in forest production, biomass and carbon: Results from the 2015 UN FAO Global Forest Resource Assessment

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.

Results of 20 years old Douglas-fir provenance experiment established on the northern slopes of Rila Mountain in Bulgaria

The purpose of this study is to facilitate the detection of provenances relevant to the reforestation practice in Bulgaria. Studies were carried out in a Douglas-fir provenance trial plantation established at an altitude of 800 m a.s.l. on the northern slopes of Rila Mountain. To establish the productivity, assess the stands and rank provenances biometric procedures, methods of descriptive statistics and ANOVA were used. The diameter at breast height, average height, dominant height, total growing stock volume, assortment timber structure and survival of trees were analyzed in the stands of 55 Douglas-fir provenances. The provenances were characterized in terms of productivity of forest stands at 20 years of age and their ability to produce high quality timber was evaluated. Provenances: Newhalem No. 4 (Seed zone 402), Darrington No. 7 (Seed zone 403), Parkdale No. 19 (Seed zone 661) and Idanha No. 29 (Seed zone 452) have been recommended. Among the recommended provenances are those with growing stock volume with branches from 296 to 354 m<sup>3</sup>·ha<sup>–1</sup>, mean annual increment from 14.8 to 17.7 m<sup>3</sup>·ha<sup>–1</sup> and dominant heights of up to 17.9 m.  

Growth Indicators of Lebanon Cedar (Cedrus libani A. Rich.) and Brutia Pine (Pinus brutia Ten.) in the Cool Supra-Mediterranean Bioclimatic Zone of the Syrian Coastal Mountains

Lebanon Cedar (Cedrus libani A. Rich.) and Brutia pine (Pinus brutia Ten.) growth performance in the Cool Supra-Mediterranean bioclimatic zone of the Syrian Coastal Mountains at Almawla Hassan afforestation site was evaluated. The Pluviothermal quotient of Emberger and the aridity index for the site is 199 and 53.1 consecutively, whereas, summer drought spans for 120 days. The site is dominated by oak Maqui with 80 species distributed equivocally on site aspects. Lebanon Cedar was superior to Brutia pine in all growth indicators. It achieved mean height of 17.97m compared to 14.07m in Brutia pine with significant effects of exposures on the later. Furthermore, it realized a diameter of 27.37cm compared to 23.95cm in Brutia pine with significant effects of exposures on the later species. Basal area (BA) median tree of Lebanon Cedar was 0.058m2, equivalent to 64.78m2/ha. compared with 0.045m2 Brutia pine median tree BA, equivalent to 62.18m2/ha. The growing stock volume (GSV) of Lebanon Cedar median tree was 0.494 m3, and total GSV for its stand was 549.45 m3/ha. whereas, average annual growth reached 13.73 m3/ha/yr. On the other side, GSV of Brutia pine median tree was 0.335 m3, and GSV for its stand was 461.90m3/ha. In the meantime, the species average growth was 11.84 m3 /ha /yr. Tree form factor was greater in Brutia pine. Width of average annual growth rings of the Lebanon Cedar was 4.34 mm/yr. of which 82% of growth was formed in fall compared with 2.42 mm of Brutia pine of which fall growth formed 76%. It is suggested that Lebanon cedar be afforested to similar mountain aspects within this bioclimatic regime along the coastal range mountains.

Milestones and millstones: A retrospective on 50 years of research to improve productivity in loblolly pine plantations

The productive potential of plantations together with the expansion of the pulp and paper industry in the region prompted a broadly based program of research and development in southern pine plantation establishment and management. The first major research contribution to pine plantation forestry in the South was the USDA-Forest Service Publication, Agricultural Monograph No. 18, Planting the Southern Pines by P.C. Wakeley. This publication summarized 30 years of research by Wakeley and his colleagues at the Southern Forest Experiment Station and served as a road map for essentially every agency and organization, public and private that wished to establish and manage plantations of southern pine. In 1951, the Texas Forest Service and Texas A&M University established the first southern pine tree improvement program. This program not only introduced a new area of forest research in the South, it established a new way to conduct research through the creation of a forest industry–university–government research cooperative. The passage of the McIntire–Stennis Cooperative Forestry Research Act of 1962 greatly expanded the forestry research potential at state universities and soon thereafter a number of cooperatives were formed in pine tree improvement, forest fertilization, competing vegetation management, forest biology, nursery management, growth and yield, hardwood tree improvement, and hardwood silviculture. These cooperative endeavors fostered creativity and innovation and provided a network for the rapid testing and dissemination of ideas and discoveries. Naturally regenerated second growth stands of southern pine typically had a mean annual increment of 2–3 m 3 ha −1 year −1. Today, operational plantations of genetically improved loblolly pine with basic site preparation will produce 9–12 m 3 ha −1 year −1 over a 25-year rotation while experimental plantations with complete competition control and annual fertilization have achieved mean annual increments as high as 34 m 3 ha −1 year −1 by age 12 years. In 1999, planted forests accounted for only 11% of the South's total growing-stock volume, but contributed 41% of the softwood net annual growth and 29% of the softwood harvest. These figures are forecast to increase during the first half of the 21st century.

Accuracy assessment of a large-scale forest cover map of central Siberia from synthetic aperture radar

Russia's boreal forests host 11% of the world's live forest biomass. They play a critical role in Russia's economy and in stabilizing the global climate. The boreal forests of central and western Siberia represent the largest unbroken tracts of forest in the world. The European Commission funded SIBERIA project aimed at producing a forest map covering an area of 1.2 million square kilometres. Three synthetic aperture radars (SAR) on board the European remote sensing satellites ERS-1 and ERS-2 and the Japanese Earth resources satellite JERS-1 were used to collect remote sensing data. Radar is the only sensor capable of penetrating cloud cover and imaging at night. An adaptive, model-based, contextual classification to derive ranked total growing stock volume classes suitable for large-scale mapping is described. The accuracy assessment of the Siberian forest cover map is presented. The weighted coefficient of agreement κw is calculated to quantify the agreement between the classified map and the reference data. First, the classified map is compared with Russian forest inventory data (κw = 0.72). The inherent uncertainty in the forest inventory data is simulated by allowing for fuzziness. The effect of uncertainty on the unweighted coefficient of agreement κ is stronger than that on the weighted coefficient of agreement κw. Second, the map is compared with a more reliable, independent posterior ground survey by Russian forestry experts (κw = 0.94). The follow-on project SIBERIA-II started in January 2002 and is striving to develop multisensor concepts for greenhouse gas accounting (www.siberia2.uni-jena.de).

Sustainability of Siberia and Far East Russia's Forest Resource

The objective of this study is to project the sustainability of Siberia and Far East Russia's forest resource. This projection involves using empirical data to evaluate the impact of increased ecological protection and increased management activities, such as fire prevention, pest management, and regeneration efforts. As a result of these projections, we quantify a biologically sustainable harvesting level. In 1988, there were an estimated 551.6 million hectares of forested area in Siberia and Far East Russia in the major forest types. Of this total, about 55 percent are nonexploitable forests which are protected from harvesting due to ecological limitations. Exploitable forests contained an estimated total growing-stock volume of 29.8 billion cubic meters and nonexploitable forests contained 30.7 billion cubic meters. Projections based on implementation of selected management actions on exploitable forests show a potential to maintain a sustainable harvest level of almost 260 million cubic meters by 2028, and more than 275 million cubic meters by 2068.

Forest overstory-understory relationships in Alabama forests

This study developed regional overstory-understory models for four forest types in southeastern Alabama and tested the ability of these models to predict understory vegetation using overstory data from southern and southwestern Alabama. Cross-sectional data from the USDA Forest Service Forest Inventory and Analysis Unit Multiresource Survey of Alabama was used to analyze the relationship between timber stand characteristics and herbaceous cover under planted pine, natural pine, mixed pine-hardwoods, and upland hardwoods. Herbaceous cover was significantly related to total growing stock volume of timber in all forest types. Stand characteristics and management activities that affected herbaceous cover varied by forest type. The models for planted pine, mixed pine-hardwoods, and upland hardwoods captured a significant amount of the variation in the original data. Extrapolation of southeastern Alabama overstory-understory relationship to southern and southwestern forests was not possible with these models.

Forests of the USSR

The USSR has the world's richest endowment of forest resources. Its total growing stock volume accounts for over 22% and that of conifers for over 53% of the world's totals. Relative to Canada, the USSR is 2.2 times larger in area, has roughly 3 times the forested land and its growing stock is 3.7 times larger. The volume of Soviet growing stock in larch alone is slightly larger than Canada's total. Forests occupy over 36% of the USSR and about 55% of this is considered accessible. Over 60% of the growing stock volume is mature and overmature. Most of the forest resources are east of the Ural Mountains. The Uralo-European part, which supports 74% of the population, accounts for 25.5% of the forested area and 27.3% of the growing stock. Fifty-one percent of the total allowable cut in the accessible and potentially accessible forests is utilized, but only 39% of the total wood volume on all the forested land. Only 35% of the total mean annual increment is utilized. Currently, the USSR regenerates annually an area larger than it clearcuts. Establishment of highly efficient spruce monocultures in close proximity to the existing pulp and paper mills in the Uralo-European part of the country is strongly emphasized. Key words: Accessibility, actual cut, allowable cut, forest land, forest regeneration forest resourses inventory, geographical distribution, growing stock, mean annual increment, species, tenure, USSR.