Modelling forest management within a global vegetation model—Part 1: Model structure and general behaviour

This article describes a new forest management module (FMM) that explicitly simulates forest stand growth and management within a process-based global vegetation model (GVM) called ORCHIDEE. The net primary productivity simulated by ORCHIDEE is used as an input to the FMM. The FMM then calculates stand and management characteristics such as stand density, tree size distribution, tree growth, the timing and intensity of thinnings and clear-cuts, wood extraction and litter generated after thinning. Some of these variables are then fed back to ORCHIDEE. These computations are made possible with a distribution-based modelling of individual tree size. The model derives natural mortality from the relative density index (rdi), a competition index based on tree size and stand density. Based on the common forestry management principle of avoiding natural mortality, a set of rules is defined to calculate the recurrent intensity and frequency of forestry operations during the stand lifetime. The new-coupled model is called ORCHIDEE-FM (forest management).The general behaviour of ORCHIDEE-FM is analysed for a broadleaf forest in north-eastern France. Flux simulation throughout a forest rotation compare well with the literature values, both in absolute values and dynamics.Results from ORCHIDEE-FM highlight the impact of forest management on ecosystem C-cycling, both in terms of carbon fluxes and stocks. In particular, the average net ecosystem productivity (NEP) of 225 gC m⁻² year⁻¹ is close to the biome average of 311 gC m⁻² year⁻¹. The NEP of the “unmanaged” case is 40% lower, leading us to conclude that management explains 40% of the cumulated carbon sink over 150 years. A sensitivity analysis reveals 4 major avenues for improvement: a better determination of initial conditions, an improved allocation scheme to explain age-related decline in productivity, and an increased specificity of both the self-thinning curve and the biomass-diameter allometry.     

Modeling net primary production of a fast-growing forest using a light use efficiency model

As interest grows in the quantification of global carbon cycles, Light Use Efficiency (LUE) model predictions of the forest net primary production (NPP) are being developed at an accelerating rate. Such models can provide useful predictions at large scales, but evaluating their performance has been difficult. In this study, a remote sensing-based LUE model was established to estimate forest NPP. Using the forest inventory data (FID) from the regional forest inventory survey in China and established allometric biomass equations, we calculated the biomass, the biomass increment, and the NPP of Eucalyptus urophylla (E. urophylla) plantation plots in the forestry jurisdiction of the Leizhou Forestry Bureau, Southern China. The FID-based NPP and the NPP from LUE model predictions were then compared to each other. Results show that the NPP from model predictions at a spatial resolution of 30 m × 30 m varied from 0 to 265 gC/(m² month) and showed regional differences. In addition, the stand age had variable effects on the average individual biomass of the E. urophylla plantation plots. The average individual biomass of the young and mid-age forests increased exponentially and logarithmically with the stand age (R² = 0.9178 and R² = 0.8683), respectively. For young and mid-age E. urophylla plantation plots, the LUE model-predicted NPP was fairly consistent with the FID-based NPP, but the model predictions of the NPP were higher than the estimates from FID. Through the analysis of the causes of uncertainty and the possible reasons for the discrepancy between the model-based NPP and FID-based NPP, the FID-derived estimates provided a foundation for model evaluation.     

Using forest inventory data to assess fisher resting habitat suitability in California.

The fisher (Martes pennanti) is a forest-dwelling carnivore whose current distribution and association with late-seral forest conditions make it vulnerable to stand-altering human activities or natural disturbances. Fishers select a variety of structures for daily resting bouts. These habitat elements, together with foraging and reproductive (denning) habitat, constitute the habitat requirements of fishers. We develop a model capable of predicting the suitability of fisher resting habitat using standard forest vegetation inventory data. The inventory data were derived from Forest Inventory and Analysis (FIA), a nationwide probability-based sample used to estimate forest characteristics. We developed the model by comparing vegetation and topographic data at 75 randomly selected fisher resting structures in the southern Sierra Nevada with 232 forest inventory plots. We collected vegetation data at fisher resting locations using the FIA vegetation sampling protocol and centering the 1-ha FIA plot on the resting structure. To distinguish used and available inventory plots, we used nonparametric logistic regression to evaluate a set of a priori biological models. The top model represented a dominant portion of the Akaike weights (0.87), explained 31.5% of the deviance, and included the following variables: average canopy closure, basal area of trees <51 cm diameter breast height (dbh), average hardwood dbh, maximum tree dbh, percentage slope, and the dbh of the largest conifer snag. Our use of routinely collected forest inventory data allows the assessment and monitoring of change in fisher resting habitat suitability over large regions with no additional sampling effort. Although models were constrained to include only variables available from the list of those measured using the FIA protocol, we did not find this to be a shortcoming. The model makes it possible to compare average resting habitat suitability values before and after forest management treatments, among administrative units, across regions and over time. Considering hundreds of plot estimates as a sample of habitat conditions over large spatial scales can bring a broad perspective, at high resolution, and efficiency to the assessment and monitoring of wildlife habitat.     

CBM-CFS3: A model of carbon-dynamics in forestry and land-use change implementing IPCC standards

The scientific community, forest managers, environmental organizations, carbon-offset trading systems and policy-makers require tools to account for forest carbon stocks and carbon stock changes. In this paper we describe updates to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) implemented over the past years. This model of carbon-dynamics implements a Tier 3 approach of the Intergovernmental Panel on Climate Change (IPCC) Good Practice Guidance for reporting on carbon stocks and carbon stock changes resulting from Land Use, Land-use Change and Forestry (LULUCF). The CBM-CFS3 is a generic modelling framework that can be applied at the stand, landscape and national levels. The model provides a spatially referenced, hierarchical system for integrating datasets originating from different forest inventory and monitoring programs and includes a structure that allows for tracking of land areas by different land-use and land-use change classes. Ecosystem pools in CBM-CFS3 can be easily mapped to IPCC-defined pools and validated against field measurements. The model uses sophisticated algorithms for converting volume to biomass and explicitly simulates individual annual disturbance events (natural and anthropogenic). Several important scientific updates have been made to improve the representation of ecosystem structure and processes from previous versions of CBM-CFS. These include: (1) an expanded representation of dead organic matter and soil carbon, particularly standing dead trees, and a new algorithm for initializing these pools prior to simulation, (2) a change in the input data requirement for simulating growth from biomass to readily available merchantable volume curves, and new algorithms for converting volume to biomass, (3) improved prediction of belowground biomass, and (4) improved parameters for soil organic matter decay, fire, insect disturbances, and forest management. In addition, an operational-scale version of CBM-CFS3 is freely available and includes tools to import data in standard formats, including the output of several timber supply models that are commonly used in Canada. Although developed for Canadian forests, the flexible nature of the model has enabled it to be adapted for use in several other countries.     

Scaling up of biomass simulation for Eucalyptus plantations based on landsenses ecology

ABSTRACT

Sustainable forest management on a regional scale requires accurate biomass estimation. At present, technologically comprehensive forecasting estimates are generated using process-based ecological models. However, isolation of the ecological factors that cause uncertainty in model behavior is difficult. To solve this problem, this study aimed to construct a meliorization model evaluation framework to explain uncertainty in model behavior with respect to both the mechanisms and algorithms involved in ecological forecasting based on the principle of landsenses ecology. We introduce a complicated ecological driving mechanism to the process-based ecological model using analytical software and algorithms. Subsequently, as a case study, we apply the meliorization model evaluation framework to detect Eucalyptus biomass forest patches at a regional scale (196,158 ha) using the 3PG2 (Physiological Principles in Predicting Growth) model. Our results show that this technique improves the accuracy of ecological simulation for ecological forecasting and prevents new uncertainties from being produced by adding a new driving mechanism to the original model structure. This result was supported by our Eucalyptus biomass simulation using the 3PG2 model, in which ecological factors caused 21.83% and 9.05% uncertainty in model behavior temporal and spatial forecasting, respectively. In conclusion, the systematic meliorization model evaluation framework reported here provides a new method that could be applied to research requiring comprehensive ecological forecasting. Sustainable forest management on regional scales contributes to accurate forest biomass simulation through the principle of landsenses ecology, in which mix-marching data and a meliorization model are combined.     

Assessing aboveground tropical forest biomass using Google Earth canopy images

Reducing Emissions from Deforestation and Forest Degradation (REDD) in efforts to combat climate change requires participating countries to periodically assess their forest resources on a national scale. Such a process is particularly challenging in the tropics because of technical difficulties related to large aboveground forest biomass stocks, restricted availability of affordable, appropriate remote-sensing images, and a lack of accurate forest inventory data. In this paper, we apply the Fourier-based FOTO method of canopy texture analysis to Google Earth's very-high-resolution images of the wet evergreen forests in the Western Ghats of India in order to (1) assess the predictive power of the method on aboveground biomass of tropical forests, (2) test the merits of free Google Earth images relative to their native commercial IKONOS counterparts and (3) highlight further research needs for affordable, accurate regional aboveground biomass estimations. We used the FOTO method to ordinate Fourier spectra of 1436 square canopy images (125 x 125 m) with respect to a canopy grain texture gradient (i.e., a combination of size distribution and spatial pattern of tree crowns), benchmarked against virtual canopy scenes simulated from a set of known forest structure parameters and a 3-D light interception model. We then used 15 1-ha ground plots to demonstrate that both texture gradients provided by Google Earth and IKONOS images strongly correlated with field-observed stand structure parameters such as the density of large trees, total basal area, and aboveground biomass estimated from a regional allometric model. Our results highlight the great potential of the FOTO method applied to Google Earth data for biomass retrieval because the texture-biomass relationship is only subject to 15% relative error, on average, and does not show obvious saturation trends at large biomass values. We also provide the first reliable map of tropical forest aboveground biomass predicted from free Google Earth images.     

Characterization of soil erosion and its implication to forest management

Forests have traditionally been managed to maximize timber production or economic profit, completely neglecting other forest values. Nowadays, however, forests are being managed for multiple uses. The basic requirement of multiple use forestry is to identify and quantify forest values and to determine management objectives. The priorities of management objectives, however, must be decided. In this study, a model predicting the soil loss for multi objective forest management was developed. The model was based on data from remeasurement of permanent sample plots. The data were gathered from 132 sample plots. Approximately 80% of the observations were used for model development and 20% for validation. The model was designed for even aged and uneven aged forests, as well as for forests with mixed and pure species composition. The explicatory variables in the model were mean diameter and number of trees. All parameter estimates were found highly significant (p < 0.001) in predicting soil loss. The model fit and validation tests were fairly good. The soil loss model presented in this paper was considered to have an appropriate level of reliability. It can be used in the overall multi-objective forest management planning, but, it should be limited to the conditions for which the data were gathered.     

Restoration of ecosystems for biodiversity and carbon sequestration: Simulating growth dynamics of brigalow vegetation communities in Australia

Restoration of abandoned and degraded ecosystems through enhanced management of mature remnant patches and naturally regenerating (regrowth) forests is currently being used in the recovery of ecosystems for biodiversity protection and carbon sequestration. Knowledge of long-term dynamics of these ecosystems is often very limited. Vegetation models that examine long-term forest growth and succession of uneven aged, mixed-species forest ecosystems are integral to the planning and assessment of the recovery process of biodiversity values and biomass accumulation. This paper examined the use of the Ecosystem Dynamics Simulator (EDS) in projecting growth dynamics of mature remnant brigalow forest communities and recovery process of regrowth brigalow thickets. We used data from 188 long-term monitored plots of remnant and regrowth forests measured between 1963 and 2010. In this study the model was parameterised for 34 tree and shrub species and tested with independent long-term measurements. The model closely approximated actual development trajectories of mature forests and regrowth thickets but some inaccuracies in estimating regeneration through asexual reproduction and mortality were noted as reflected in stem density projections of remnant plots that had a mean of absolute relative bias of 46.2 (±12.4)%. Changes in species composition in remnant forests were projected with a 10% error. Basal area values observed in all remnant plots ranged from 6 to 29 m² ha⁻¹ and EDS projections between 1966 and 2005 (39 years) were 68.2 (±10.9)% of the observed basal area. Projected live aboveground biomass of remnant plots had a mean of 93.5 (±5.9) t ha⁻¹ compared to a mean of 91.3 (±8.0) t ha⁻¹ observed in the plots. In regrowth thicket, the model produced satisfactory projections of tree density (91%), basal area (89%), height (87%) and aboveground biomass (84%) compared to the observed attributes. Basal area and biomass accumulation in 45-year-old regrowth plots was approximately similar to that in remnant forests but recovery of woody understorey was very slow. The model projected that it would take 95 years for the regrowth to thin down to similar densities observed in original or remnant brigalow forests. These results indicated that EDS can produce relatively accurate projections of growth dynamics of brigalow regrowth forests necessary for informing restoration planning and projecting biomass accumulation.     

Biogeochemical model (BGC-ES) and its basin-level application for evaluating ecosystem services under forest management practices

It is important for humans to live in harmony with ecosystems. Evaluation of ecosystem services (ES) may be helpful in achieving this objective. In Japan, forest ecosystems need to be re-evaluated to prevent their degradation due to lack of forest management.In order to evaluate the effects of forest management on forest ES, we developed a process-based biogeochemical model to estimate water, carbon, and nitrogen cycles in forest ecosystems (BGC-ES). This model consists of four submodels: biomass, water cycle, carbon-nitrogen (CN) cycles, and forest management. The biomass submodel can calculate growth of forest biomass under forest managements.Several parameters of the model were calibrated using data from observations of evapotranspiration flux and quality of stream flow in forests. The model results were compared with observations of runoff water from a dam catchment site and with carbon flux observations.Our model was coupled with a basin-level GIS database of forests. Evaluations under various forest management scenarios were carried out for forests in a basin contained in the Ise Bay basin (Chubu region, Japan), where plantations (artificial forests) seemed to have degraded from poor forest management.Comparing our simulation results with those of forests without management in the basin, we found that the amounts of absorbed carbon and runoff were larger in managed forests. In addition, the volume of harvested timber was larger and its quality (diameter) was better in managed forests. Changes of ES within the various scenarios were estimated for their economic value and were compared with the cost of forest management.     

苏南快速城市化地区森林生物量时空变化及影响分析

随着我国城镇化进程的快速推进,城镇密集区城市扩张带来的负面生态环境问题得到广泛关注。森林生态系统具有固碳释氧等多种生态服务功能,对减小城市化的负面效应、改善生态环境具有积极作用。近年来我国植树造林成效明显,森林资源总量和质量持续提升,科学评估森林生物量动态对理解碳源汇变化及制定森林保护政策具有重要的意义,但当前对快速城市化地区长时期生物量变化及影响因素研究较少。苏南地区处于我国最大的城镇密集区长江三角洲的中心,近年来该地区森林面积和质量不断增加,而受中低卫星遥感数据分辨率影响,以往对该地区生态系统生物量研究未探测到这种变化。利用1990、2005年江苏省森林资源调查数据及2010年江苏省森林覆盖监测数据,采用换算因子连续函数法和平均生物量法等计算苏南地区三个时期森林生物量,研究20年来苏南快速城市化地区森林植被生物量的时空变化,并结合社会经济数据探讨了生物量变化与经济人口的关联。结果表明：20年来,苏南地区森林植被面积、生物量和生物量密度总体呈显著增加趋势,生物量从7.15 Tg增长到16.72 Tg,乔木林的生物量密度由29.32 t＆#183;hm-2上升至39.82 t＆#183;hm-2,但远低于同期全国的均值;各市生物量分布不均匀,2010年生物量总量从大到小依次是南京、无锡、镇江、常州和苏州;各市森林生物量总量主要由森林面积和地形决定,森林面积增加是生物量增加的主要因素,阔叶林比例和林龄的增长也促进了生物量增加,随着区域森林林龄不断增长,森林生物量仍将不断增加;政府政策和经济利益等影响下的森林建设是区域森林生物量增加的主要原因,较高的经济发展水平促进了各市森林资源数量增长,而高人口密度未对森林面积和生物量未产生显著负面?     

Potentials and limitations of using large-scale forest inventory data for evaluating forest succession models

Forest gap models have been applied widely to examine forest development under natural conditions and to investigate the effect of climate change on forest succession. Due to the complexity and parameter requirements of such models a rigorous evaluation is required to build confidence in the simulation results. However, appropriate data for model assessment are scarce at the large spatial and temporal scales of successional dynamics. In this study, we explore a data source for the evaluation of forest gap models that has been used only little in the past, i.e., large-scale National Forest Inventory data. The key objectives of this study were (a) to examine the potentials and limitations of using large-scale forest inventory data for evaluating the performance of forest gap models and (b) to test two particular models as case studies to derive recommendations for their future improvement.     

The importance of age-related decline in forest NPP for modeling regional carbon balances.

We show the implications of the commonly observed age-related decline in aboveground productivity of forests, and hence forest age structure, on the carbon dynamics of European forests in response to historical changes in environmental conditions. Size-dependent carbon allocation in trees to counteract increasing hydraulic resistance with tree height has been hypothesized to be responsible for this decline. Incorporated into a global terrestrial biosphere model (the Lund-Potsdam-Jena model, LPJ), this hypothesis improves the simulated increase in biomass with stand age. Application of the advanced model, including a generic representation of forest management in even-aged stands, for 77 European provinces shows that model-based estimates of biomass development with age compare favorably with inventory-based estimates for different tree species. Model estimates of biomass densities on province and country levels, and trends in growth increment along an annual mean temperature gradient are in broad agreement with inventory data. However, the level of agreement between modeled and inventory-based estimates varies markedly between countries and provinces. The model is able to reproduce the present-day age structure of forests and the ratio of biomass removals to increment on a European scale based on observed changes in climate, atmospheric CO2 concentration, forest area, and wood demand between 1948 and 2000. Vegetation in European forests is modeled to sequester carbon at a rate of 100 Tg C/yr, which corresponds well to forest inventory-based estimates.     

珠江三角洲森林的生物量和生产力研究

利用森林资源清查资料和经过实地校正的相关森林生物量和生产力估算方程,对珠江三角洲森林植被的生物量和生产力进行了研究。结果表明,珠江三角洲森林的生物量为132 404 963 t,总净生产量为26 273 769 t.a-1。区域森林生物量主要分布在珠江三角洲的外围,其中,马尾松林和常绿阔叶林的生物量占区域森林总生物量的52.18%;生态公益林的生物量只到达用材林的48.68%;中幼龄林生物量所占比例很大,总体质量不高,但如果现有森林得到更好地保护和管理,珠江三角洲地区的森林会有较大的发展潜力,并在维护区域生态环境上起着主导作用。     

Wood Density as a Conservation Tool: Quantification of Disturbance and Identification of Conservation‐Priority Areas in Tropical Forests

Abstract: Inventories of tree species are often conducted to guide conservation efforts in tropical forests. Such surveys are time consuming, demanding of expertise, and expensive to perform and interpret. Approaches to make survey efforts simpler or more effective would be valuable. In particular, it would be good to be able to easily identify areas of old‐growth forest. The average density of the wood of a tree species is closely linked to its successional status. We used tree inventory data from eastern Borneo to determine whether wood density can be used to quantify forest disturbance and conservation importance. The average density of wood in a plot was significantly and negatively related to disturbance levels, with plots with higher wood densities occurring almost exclusively in old‐growth forests. Average wood density was unimodally related to the diversity of tree species, indicating that the average wood density in a plot might be a better indicator of old‐growth forest than species diversity. In addition, Borneo endemics had significantly heavier wood than species that are common throughout the Malesian region, and they were more common in plots with higher average wood density. We concluded that wood density at the plot level could be a powerful tool for identifying areas of conservation priority in the tropical rain forests of Southeast Asia.     

基于生态过程模型和森林清查数据的森林生长量估算对比研究

利用遥感驱动的生态过程模型-Boreal Ecosystem Productivity Simulator （BEPS）、2001-2006年国家森林资源连续清查数据（一类清查-样地尺度）和2003-2009年森林资源规划设计调查数据（二类调查-区域尺度）,分别计算江西省吉安市的森林生态系统生长量,从不同空间尺度和森林类型对3种数据源估算的森林生长量进行了分析。结果表明,样点尺度上,BEPS模型模拟的森林生长量（4.18 Mg·hm^-2·a^-1）低于群落生长量（5.86 Mg·hm^-2·a^-1）,与乔木层生长量（4.29 Mg·hm^-2·a^-1）基本一致,模型模拟结果与两者的拟合R2分别为0.48和0.43。区域尺度上,BEPS模型模拟、二类调查数据计算的群落及乔木层生长量分别为4.65、4.36和3.34 Mg·hm^-2·a^-1,BEPS模型估算的吉安市各县森林总生长量与二类调查数据计算的群落、乔木层生长总量拟合R2分别达0.84和0.83。一类清查数据计算结果高于二类清查数据计算结果,BEPS模型模拟森林生长量分别与基于一类清查数据计算的乔木层生长量及二类调查数据群落生长量较为一致。从研究区两种主要森林类型来看,常绿阔叶林年平均生长量高于常绿针叶林,常绿针叶林与模型估算结果差异小于常绿阔叶林。最后利用模型估算了研究区2001-2010年平均生长量,为认识研究区的森林生长空间分布差异及更新森林生物量提供支持。     

A geospatial model of forest dynamics with controlled trend surface

This paper proposes a method of controlled trend surface to simultaneously account for large-scale spatial trends and non-spatial local effects. With this method, a geospatial model of forest dynamics was developed for the Alaska boreal forest from 446 constantly monitored permanent sample plots. The geospatial component of this model represented large-scale spatial trends in recruitment, diameter growth, and mortality. The model was tested on two sets of validation plots which represented temporal and spatial extensions of the current sample coverage. The results suggest that the controlled trend surface model was generally more accurate than both the non-spatial and conventional trend surface models. With this model, we mapped the forest dynamics of the entire Alaska boreal region by aggregating predicted stand states across the region. It was predicted that under current conditions of climate and natural disturbances, most of the Alaska boreal forest region may undergo a major shift from deciduous-dominant to conifer-dominant, with an average increase of 0.33 m² ha year⁻¹ in basal area over the Twenty-First Century.     

南亚热带中幼龄针阔混交林碳储量及其分配格局

以南亚热带中幼龄针阔混交林为研究对象,通过典型样地调查法,对森林生态系统各个层次进行取样调查,采用12个样地实测数据和已有生物量模型相结合的方法计算乔木层生物量,灌木层、草本层和凋落物层采用全部收获法测得其生物量,对土壤层的调查采用剖面法加土钻法,代表性样品碳含量的测定采用重铬酸钾-水合加热法。在此基础上,分析了中幼龄针阔混交林碳储量及其分配格局。结果表明,主要造林树种树根、树杆、树枝和树叶碳含量均值分别为45.07%、46.73%、46.30%和47.72%。植物碳含量表现为乔木〉灌木〉草本。乔木碳储量占植被总碳储量比例介于63.38%-94.08%之间,灌木碳储量所占比例介于3.55%-12.67%之间,而草本碳储量仅介于为1.28%-23.95%之间,不同林龄段乔木和灌木碳储量均值随林龄的增加呈上升趋势,而草本碳储量呈下降趋势。土壤碳储量介于106.73-136.61 t·hm^-2之间,土壤碳储量随林龄的增加呈现出先降低后升高的趋势。针阔混交林总碳储量介于134.79-162.60 t·hm^-2之间,分配格局表现为土壤层〉植被层〉凋落物层。土壤层碳储量所占总碳储量比例范围为78.34%-94.45%,植被层所占比例介于4.84%-20.16%之间,凋落物层仅介于0.71%-1.50%之间,中幼龄针阔混交林碳储量主要以土壤固碳为主。研究结果为树种选择、人工林生态系统固碳潜力以及人工碳汇林的经营管理等研究提供科学参考。     

Modelling carbon and nitrogen dynamics in forest ecosystems of Central Russia under different climate change scenarios and forest management regimes

The individual-based stand-level model EFIMOD was used for large-scale simulations using standard data on forest inventories as model inputs. The model was verified for the case-study of field observations, and possible sources of uncertainties were analysed. The approach developed kept the ability for fine-tuning to account for spatial discontinuity in the simulated area. Several forest management regimes were simulated as well as forest wildfires and climate changes. The greatest carbon and nitrogen accumulations were observed for the regime without cuttings. It was shown that cuttings and wildfires strongly influence the processes of carbon and nitrogen accumulations in both soil and forest vegetation. Modelling also showed that the increase in annual average temperatures resulted in the partial relocation of carbon and nitrogen stocks from soil to plant biomass. However, forest management, particularly harvesting, has a greater effect on the dynamics of forest ecosystems than the prescribed climate change.     

Forest growth in the light of the thermodynamic theory of ecological systems

The observed growth of a particular forest stand can be described by many models and explained by some of them. The forest growth models are also successfully applied for extrapolating the growth curve. However, the known models of forest growth are not “one-point” models. They are not designed to predict the future growth of a forest stand from its current state: the model parameters either are not directly measurable or cannot be measured with relevant accuracy. This article is an attempt to use Jørgensen–Svirezhev theory as a new clue to the choice of variables that determines forest growth. The postulates of this theory combined with the pipe theory of tree growth lead to conclusion that biomass of a stand should be proportional to the four-fifths power of its age. Empirical validation, however, disclosed that calendar age is rather approximate measure of ecosystem ontogeny. Delayed development or intensive thinning of a forest stand at the early stages leads to rejuvenation bias. Thus derived 4/5-law model approximates well-known Chapman–Richards model in the neighborhood of the inflection point, and is applicable to middle-aged forest stands.