Connecting an architectural plant model to a forest stand dynamics model—application to Austrian black pine stand visualization

Mixing increases drought exposure through a faster growth in beech, but not in oak

Karri (Eucalyptus diversicolor F. Muell.) forest is an endemic forest type of southwest Western Australia (SWWA), noted for having the tallest trees in the region, and providing commercial, ecological and conservation value. To inform management aimed at optimising these values, a thinning trial was commenced in 1992. The aim of this study was to evaluate the effects of thinning on individual tree growth, stand level growth and allometry of karri trees in even-aged stands. Mixed effect models were used to compare the effect of different levels of thinning on individual tree growth and stand level growth of karri. We developed allometric equations modelling the relationship between diameter at breast height (DBH) and height, and tested whether thinning affected this allometric relationship. Thinning enhanced DBH, height and crown width (CW) growth of individual trees by up to 149%, 56% and 108% respectively in heavily thinned stands, with stand basal area growth optimised at retained basal areas of 13 m2 ha−1. Thinning had a significant effect on allometry of DBH with height, height-DBH ratio (HDR) and CW. Reduction in stand density through thinning from below increased diameter growth of individual trees. Stand level basal area growth is optimised at an intermediate level of thinning. Thinning can be a good management tool for even-aged karri forest because it may promote the diameter and thereby basal area growth, good health of individual trees, and potential ecological benefits including accelerated development of larger tree crowns typical of mature forest.

Facing an uncertain future, european forests are expected to fulfill a range of forest ecosystem services (FES), including timber supply, carbon storage or biodiversity. Using criteria and indicators forest managers can evaluate alternative management options and decision support systems (DSS) help them make decisions considering multiple objectives. Such tools need input on forest development under various scenarios, to obtain robust decisions, such as provided by forest models. We use the simulation results from the project “OptFor-EU” generated by the hybrid forest model PICUS v1.5 for four case study areas in Austria, Italy, Germany and Romania. We utilize six different climate input (3 RCPs, 2 regional climate models) and up to nine management alternatives in simulations until year 2100. The initial stand structure was derived using forest inventory data. We aggregated forest stands (represented by forest types) assuming even distribution of age classes in a hypothetical landscape or region of interest.We found positive tradeoffs between key forest ecosystem services, FES (carbon sink, biodiversity, harvested wood volume) for selected forest management alternatives. Under a “no active management” scenario, most of the simulated forest stands in the case study areas reached their potential carbon storage in the second half of the century and thus their carbon sink becomes neutral during that period. A surprising result was that selected biodiversity indicators were higher under management scenarios than no management, at least for certain time periods and age classes. Less extensive forest management alternatives may offer tradeoffs between FESs. Next steps are expanding the simulations to additional case study areas and refining and optimizing the forest management, considering more realistic age class distributions and/or varying management by age class. ReferencesIrauschek, W. Rammer, M.J. Lexer, Evaluating multifunctionality and adaptive capacity of mountain forest management alternatives under climate change in the Eastern Alps, Eur. J. For. Res. 136 (2017) 1051–1069. https://doi.org/10.1007/s10342-017-1051-6.Lexer, M. J. and K. Hönninger. 2001. A modified 3D-patch model for spatially explicit simulation of vegetation composition in heterogeneous landscapes. Forest Ecology and Management 144:43–65.

ABSTRACTImproved monitoring and understanding of tree growth and its responses to controlling factors are important for tree growth modeling. Airborne Laser Scanning (ALS) can be used to enhance the efficiency and accuracy of large-scale forest surveys in delineating three-dimensional forest structures and under-canopy terrains. This study proposed an ALS-based framework to quantify tree growth and competition. Bi-temporal ALS data were used to quantify tree growth in height (ΔH), crown area (ΔA), crown volume (ΔV), and tree competition for 114,000 individual trees in two conifer-dominant Sierra Nevada forests. We analyzed the correlations between tree growth attributes and controlling factors (i.e. tree sizes, competition, forest structure, and topographic parameters) at multiple levels. At the individual tree level, ΔH had no consistent correlations with controlling factors, ΔA and ΔV were positively related to original tree sizes (R > 0.3) and negatively related to competition indices (R < −0.3). At the forest-stand level, ΔH and ΔA were highly correlated to topographic wetness index (|R| > 0.7), ΔV was positively related to original tree sizes (|R| > 0.8). Multivariate regression models were simulated at individual tree level for ΔH, ΔA, and ΔV with the R2 ranged from 0.1 to 0.43. The ALS-based tree height estimation and growth analysis results were consistent with field measurements.

High-value timber species play an important economic role in forest management. The individual tree information for such species is necessary for practical forest management and for conservation purposes. Digital aerial photogrammetry derived from an unmanned aerial vehicle (UAV-DAP) can provide fine spatial and spectral information, as well as information on the three-dimensional (3D) structure of a forest canopy. Light detection and ranging (LiDAR) data enable area-wide 3D tree mapping and provide accurate forest floor terrain information. In this study, we evaluated the potential use of UAV-DAP and LiDAR data for the estimation of individual tree location and diameter at breast height (DBH) values of large-size high-value timber species in northern Japanese mixed-wood forests. We performed multiresolution segmentation of UAV-DAP orthophotographs to derive individual tree crown. We used object-based image analysis and random forest algorithm to classify the forest canopy into five categories: three high-value timber species, other broadleaf species, and conifer species. The UAV-DAP technique produced overall accuracy values of 73% and 63% for classification of the forest canopy in two forest management sub-compartments. In addition, we estimated individual tree DBH Values of high-value timber species through field survey, LiDAR, and UAV-DAP data. The results indicated that UAV-DAP can predict individual tree DBH Values, with comparable accuracy to DBH prediction using field and LiDAR data. The results of this study are useful for forest managers when searching for high-value timber trees and estimating tree size in large mixed-wood forests and can be applied in single-tree management systems for high-value timber species.

Los bosques mixtos tienen cada vez mayor relevancia en el manejo forestal debido a la creciente evidencia de su mayor potencial para suministrar servicios ecosistémicos. El presente estudio analiza a múltiples niveles (desde el nivel árbol a rodal) y escalas (temporales y espaciales), cómo las interacciones de las especies afectan los procesos involucrados en el crecimiento y productividad del pino albar y el pino negral en bosques mixtos en un ambiente mediterráneo. La hipótesis principal fue que las diferencias en los rasgos estructurales entre especies podrían inducir interacciones que tiene efectos en la productividad del rodal, crecimiento de las especies y cambios en los rasgos estructurales a nivel de rodal y especie; modificando así la dinámica de crecimiento comparada con bosques monoespecíficos. La aproximación metodológica y las funciones predictivas desarrolladas en esta tesis pueden ayudar a los investigadores y gestores a comprender mejor las dinámicas de los bosques mixtos, y desarrollar herramienta para la planificación y evaluación diferentes opciones de manejo.

There is an increasing need for accurate measurement of forest cover both in terms of its spatial and temporal variation for improvements in forest management. Forest cover can be estimated using Normalised Difference Vegetation Index (NDVI) from satellite data. The objective of this study was to assess leaf area of the forest cover from the spectral reflectance measured by satellite. This paper analyses the relationship between NDVI and different ages of managed pine plantation from 1994 - 1997 in the Kings Forest, East Anglia, UK. The Satellite data used were four - SPOT 2 HRV2 multi spectral images for June 1994, 1995, 1996 and 1997. Secondary data on forest management were derived from compartment records supplied by the Forestry Commission. Age is an important variable in forest growth. Therefore this study investigated changes of NDVI in different age groups &lt;8, 8-18, 18-38, 38-58 and &gt;58 years. The study found that during the period 1994- 1997 NDVI changed fairly little from 0.4-0.7. However in each age group slight changes can be easily recognised. There was a significant high positive correlation between NDVI and age in all four years with R2 values of 0.68, 0.66, 0.79 and 0.78 for 1994, 1995, 1996 and 1997 respectively. The results show that the NDVI changes provide important information on vegetation growth in a plantation forest. The results of comparing NDVI and age were also encouraging but further work is needed to determine the potential use of earth observation data in forest growth and management.

Classification of species at the individual tree level would be beneficial to many applications including forest landscape visualization, forest management, and biodiversity monitoring. This article develops a patch-based classification algorithm of individual tree species based on convolutional neural network. The individual trees are first detected using the local maximum method from the canopy height model, as derived from light detection and ranging (LiDAR) data. The detected individual trees are then cropped into patches for classification based on the tree apexes, and three spatial scale image patches are chosen for analysis and discussion. A modified ResNet50 deep network is further employed for the cropped individual tree patches classification. The patch-based method accounts for the contexture information of a tree and does not require the feature selection or the feature reduction processes. About 1388 training samples including Ficus microcarpa Linn. f., Delonix regia, Chorisia speciosa A.St.-Hil., Dimocarpus longan Lour., Musa nana Lour., Carica papaya, and Others (the other tree species except the above six) were collected from both field work and visual interpretation. Aerial images, LiDAR data, and Worldview images were used for the tree species classification. For 362 test tree samples, the results of patch size 64 achieve the best accuracies, and the proposed method outperforms the traditional machine learning method with the overall accuracy of 89.06% + 0.58% using aerial images only. Transferability Study to the Luhu Park also indicated the feasibility of our method. While challenges in individual tree detection and multisource data fusion remain, the solution shows the potential in characterizing tree species at the individual tree level using remote sensing data.

Different types of models have been developed and applied to address various problems and issues in forestry. This paper reviews modelling trends in four areas, namely, forest management planning and decision-making, forest dynamics and growth projection, forest landscape and spatial models and participatory forest management models. The first type includes decision models generally structured as optimization models applied to forest planning. These models evolved from single objective to multiple objectives with spatial dimensions, including visualization. The second type includes forest dynamics models designed to examine the growth response of trees using process-based empirical or conceptual models. Demands for 'close to nature' forest management created new challenges for modellers to provide models with expanded capabilities to deal with tree growth, succession, and competition in stands with many species and wide range of tree sizes. The third type takes advantage of increased computational and graphic capabilities to model landscapes and display them as 'virtual' realities. These models combine spatial models such as geographical information systems (GIS), visualization tools and analytical models to form an integrated decision support system. The fourth type includes participatory models designed to accommodate multiple stakeholders in addressing collaborative forest management. These models are particularly adaptable to community-based forest management. Finally, the uses of models as 'learning' tools and as 'problem structuring' tools are also described.

Numerous investigations have indicated that projected climate change will impact strongly on forest growth and composition. To adapt managed forests to changing environmental conditions it may be necessary to modify traditional forest management strategies. An extended version of a forest gap model was applied to a managed forest district in northeastern Germany. The model was initialized with forest inventory data and run using routines devised to simulate three management scenarios: (1) maximized timber production, (2) climatically well-adapted forest composition, and (3) maximized tree species diversity. The strategies were compared with a baseline scenario of traditional management without any response to climate change. The comparisons were based on simulated wood production and species composition after 110 years of development. The results underline the important influence that management strategies have on forest growth. Forest management may adopt a variety of strategies to respond to the expected changes in climate. Process-oriented forest gap models can aid in the assessment of these strategies.

SummaryTasmania's giant trees are among the world's tallest flowering plants and Australia's greatest eucalypts. However, they are not well protected in National Parks or extensive reserves.Of the 69 known trees that meet the official criteria for protection as giants, almost 90% are in State forests managed for wood harvesting. Several of the giants are within coupes that were scheduled for clearfelling under the Tasmanian 2004–2007 three-year wood production plan, and recent harvesting operations have threatened or killed several others.Fifty-five per cent (38) of the known Tasmanian giants, including the tallest trees, the tallest stand, the tallest stringybark, and the second most massive stringybark, exist in the middle of the Styx Valley. Harvesting and regeneration burning operations indirectly threaten most of these trees, because they stand close to scheduled or recently clearfelled coupes. More importantly, increasing the proportion of young, dense, highly flammable eucalypt regrowth forest, at the expense and fragmentation of less flammable old—growth forest, seriously exacerbates the risk of wildfire, and invites annihilation of all the Styx Valley giants.Nominal protection of individual giant trees in small (100-m radius) management decision classification zones, or stands of trees in reserves of a few hundred hectares surrounded by production forest, does not provide effective protection in the long term. Numerous historic and recent examples in Tasmania and Victoria show the failures of these well-intentioned small-scale conservation efforts. Giant tree conservation requires very long-term preservation of large areas of forest in which the frequency of wildfire is very low; it is incompatible with current Tasmanian forest harvesting and regeneration practices.The Styx Valley contains the greatest number of, and many of the finest, giants existing in Tasmania. It also has high potential to produce another generation of great trees to stimulate wonder and admiration for the next half millennium. The best plan to ensure their long-term survival is to desist from forest harvesting and regeneration by fire, and to transform the entire valley into Australia's first large reserve dedicated to giant tree conservation.

Individual modelling is a foundational approach to study the natural forest growth and in this paper, we develop a serial distance-depended individual tree model for some species in natural forest which would provide prediction and characteristics for natural species. The data used to develop individual model for natural mixed forests were collected from 712 remeasured 10-year periodic permanent sample plots of in Baihe Forest Bureau of Changbai Mountains, northeast China. Based on analyzing relationship between diameter increment of individual trees with tree size, competitive status, and site condition and finding out the major independent variables, the growth models for individual trees of 15 species in the natural mixed forests, that have good predicting precision, and easily applicable, were developed using stepwise regression method. The individual growth model developed in this study can reflect the tree increment of 15 species and be generally well suited for simulating tree and stand growth for natural mixed forests in Changbai Mountains. The research results for individual trees growth model of each species showed that main variable to influence on diameter increment of individual trees for natural mixed forests were tree size (D) and then competition index. The site condition was not related with diameter increment. The natural logarithm of DBH (lnD) and square diameter (D2) were included in the predicting models of diameter increment for all 15 species. The diameter increment was directly proportional to tree diameter for each species. For the competitive indexes in growth model, the relative diameter (RD), canopy closure (P), and the ratio of diameter of subject tree with maximum diameter (DDM) were related to diameter increment and the stand density measures were not significantly influenced on diameter increment. As canopy closure increase, tree increment decreases. The site conditions were performance less of factors in increment predictions in the model.

The relationship between scenic beauty grade and measured tree indicators was studied through evaluation of 427 photos of individual Pinus tabulaeformis trees by using the scenic beauty estimation (SBE) method. Thirteen indices to reflect trunk, crown and stem-to-canopy ratios of individual trees were evaluated by invited students. Results showed that students preferred large diameters at breast height, full canopies and straight stems or some trees with minor crook stems. Tree height had a minor contribution to individual tree quality. Correlation analysis and factor analysis were employed to select indices and to integrate them into a comprehensive index. The stepwise method of nonlinear model incorporation of four comprehensive indices—tree crown form, stem-crown coordination, tree growth and stem for—were proven valuable in order to evaluate the scenic beauty of individual trees.

The relationship between biodiversity and productivity has stimulated an increasing body of research over the past decades, and this topic still occupies a central place in ecology. While most studies have focused on biomass production in quadrats or plots, few have investigated the scale‐dependent relationship from an individual plant perspective. We present an analysis of the effects of biodiversity (species diversity and functional diversity) on individual tree growth with a data set of 16,060 growth records from a 30‐ha temperate forest plot using spatially explicit individual tree‐based methods. A significant relationship between species diversity and tree growth was found at the individual tree level in our study. The magnitude and direction of biodiversity effects varies with the spatial scale. We found positive effects of species diversity on tree growth at scales exceeding 9 m. Individual tree growth rates increased when there was a greater diversity of species in the neighborhood of the focal tree, which provides evidence of a niche complementarity effect. At small scales (3–5 m), species diversity had negative effects on tree growth, suggesting that competition is more prevalent than complementarity or facilitation in these close neighborhoods. The results also revealed many confounding factors which influence tree growth, such as elevation and available sun light. We conclude that the use of individual tree‐based methods may lead to a better understanding of the biodiversity‐productivity relationship in forest communities.

Abstract. Estonian forest management is based traditionally on long rotations. Recent trends in wood industry and wood consumption promote also production of small-size timber for bioenergy and timber products. This opens a discussion about shorter rotations and intensive forest management again in Estonia. In current study, profitability of Scots pine, Norway spruce and silver birch stand management on fertile soils was analyzed according to three different rotation lengths: traditional long rotation, short rotation and economically optimal rotation according Finnish TAPIO rules. Stand simulation software MOTTI was used to simulate and optimize forest growth and management. Simulation results were compared with actual data on forest growth and yield in Estonia. Economically optimal rotations were for Scots pine stand 58 years, Norway spruce stand 53 years and silver birch stand 41 years. Short and optimal rotation length enable 5.9-6.5% profitability for forest owner, traditional long rotation length enables 4.8-5.4% profitability. Rotation forestry is challenging task. Based on our analysis, it is likely that applied practices can intensify wood production and reduce forest management risks. However, theoretical approach is not enough for assessing practical feasibility of short rotations. Thus further studies and experiments are needed for careful analysis and recommendations