Forest Sub-compartment Research Articles

Forest Site and Stand Structure Affecting the Distribution of Emerald Ash Borer, Agrilus planipennis Fairmaire, 1888 (Coleoptera: Buprestidae), in Eastern Ukraine

The Emerald ash borer (EAB), Agrilus planipennis Fairmaire, 1888 (Coleoptera: Buprestidae), an invasive phloem-boring beetle, was first detected in the Luhansk Region of Ukraine in 2019. Subsequently, it rapidly expanded its presence to encompass a significant portion of the Kharkiv region and the parks of Kyiv. Previous research has established that the climatic conditions in Luhansk and its neighboring regions are conducive to the EAB, and the absence of a host plant (Fraxinus sp.) does not act as a deterrent to the pest’s expansion in Ukraine. Recognizing the urgency of identifying infested trees, our current research aimed to identify the most attractive EAB forest subcompartments based on forest site conditions and stand structure. Utilizing the MaxEnt model, we achieved an average performance in predicting the potential distribution of the EAB (AUC = 0.842). The six most impactful variables, contributing to 88.2% of the model, include “age of trees, years”, “area of forest subcompartment, ha”, “mean height of trees, m”, “proportion of Fraxinus excelsior in the stand composition, %”, “hygrotope index (humidity level), point”, and “number of neighboring-non-forest subcompartments”. Most likely, EAB occurrence is expected in the driest forest site conditions; the well-lit and warmed-up parts of stands, in particular; small subcompartments surrounded by non-forest landscapes; and forest shelter belts near roads and fields. However, the data obtained can be considered preliminary. To enhance the accuracy of our forecasting, it may be imperative to consider data on road localization, along which the pest can spread passively, as well as dominant wind speed.

Forest Fire Spread Hazard and Landscape Pattern Characteristics in the Mountainous District, Beijing

Objective: This study established an index system for assessing forest fire spread hazards and conducted a forest fire spread hazard assessment in the mountainous district of Beijing (including Fangshan, Mentougou, Changping, Yanqing, Huairou, Miyun, and Pinggu). The relationship between forested landscape spatial pattern and forest fire spread hazard was explored; this method provided the basis for the establishment of a landscape forest fire security guarantee system. Methods: The forest fire spread hazard assessment index system was constructed from four aspects: forest fuel, meteorological factors, topographic factors, and fire behavior. The weighted comprehensive evaluation method and area-weighted average method were used to calculate the forest fire spread hazard indices at the subcompartment scale and township scale. Moran’s I index was selected as the spatial autocorrelation index to analyze the autocorrelation degree and spatial distribution of the forest fire spread hazard index. Eleven representative landscape pattern indices were selected to analyze the main landscape spatial pattern affecting forest fire spread hazard by correlation analysis and principal component analysis. Results: (1) The areas with high, medium–high, medium-low, and low forest fire spread hazard grades accounted for 39.87%, 33.10%, 11.37%, and 15.66% of the study area, respectively, at the subcompartment scale and for 52.36%, 22.58%, 18.39%, and 6.67% of the study area, respectively, at the township scale. (2) The forest fire spread hazard index results obtained at the subcompartment and township scales in the Mountainous District of Beijing showed a spatial agglomeration distribution law. (3) The forest fire spread hazard was influenced mainly by landscape diversity (SHDI and PRD), landscape aggregation (AI, CONTAG, and PD), and landscape area (TA). Conclusions: The overall forest fire spread hazard in the mountainous district of Beijing showed a gradual increase from plains to mountainous areas. The land types of the high-spread hazard subcompartment mainly included general shrubbery and coniferous forestlands, and the dominant species in the high-spread hazard arbor forest subcompartment were mainly Platycladus orientalis, Pinus tabuliformis, and Quercus mongolica.

The Re-parametrization of the DAS Model Based on 2016-2021 Data of the National Forestry Database: New Results on Cutting Age Distributions

This paper presents the DAS forest model (Distributions Applied on Stands model), a forest stand-based model suitable for projecting standing volume, increment, harvest, and carbon sequestration on the stand, regional, or country levels. The forest subcompartment is the modelling unit of the DAS model, which uses National Forestry Database (NFD) data, including geospatial data. The model is suitable for further processing spatially explicit input parameters such as climate change forecasts. The model output is also georeferenced and can be further processed using GIS software. The model handles the data of approximately 600,000 forest subcompartments. Data on tree species, origin, age, growing stock, increment etc. of each subcompartment are stored in “tree-species rows”, which are the sub-units of the model. The DAS model simultaneously processes the data of 1.2 million tree species rows and describes their development in time. It uses parameters based on the actual processes of the reference period. It also uses empiric cutting age distributions and a regeneration matrix derived from historic NFD data. The ForestLab project (TKP2021-NKTA-43) is currently engaged in the re-parametrization of the model based on 2016–2021 data. This study discusses the functions of the harvesting ratio distribution in the modelling process and in determining the subcompartments selected for harvest. The paper presents the latest results regarding the 2016–2021 cutting age distributions and the preparation of the new set of species-specific and yield class-specific average harvesting ratio distributions.

Natural Factors Play a Dominant Role in the Short-Distance Transmission of Pine Wilt Disease

Pine wilt disease (PWD) is regarded as one of the most serious conifer diseases affecting pines worldwide. To date, an in-depth study of the driving mechanisms behind short-distance PWD spread is lacking. In this study, we collected PWD forest subcompartment data in Fushun, China, and analysed the effects of factors on the short-distance transmission of PWD; the analysed factors included the number of neighbouring PWD-infected forest subcompartments, the canopy density, the slope direction, and different traffic corridor types. The results suggested that the spatial spill-over effect of nearby PWD-infected subcompartments contributed the most to short-distance PWD transmission, with an impact of up to 78% on its propagation. The impact of the traffic corridor was 20%. With the help of a beetle vector, PWD can spread to nearby forest subcompartments, and this spatial PWD spill-over effect showed a linearly decaying trend as the distance to neighbouring subcompartments increased. Different traffic corridor types exhibited significant PWD transmission impact differences. County roadways and highways had great impacts, while others had relatively small impacts. For each additional 100 m of distance from a county roadway, highway, national, or provincial roadway, the PWD infection risks in forest subcompartments were reduced by 18%, 11%, 5%, and 3%, respectively. In this study, we quantified the influence of driving factors on the short-distance spread of PWD and provided a theoretical basis for the control of PWD transmission; the results obtained herein are critical for maintaining the ecological security of forests, promoting ecological forest management and stabilising forest carbon sinks.

Forest Structure Simulation of Eucalyptus Plantation Using Remote-Sensing-Based Forest Age Data and 3-PG Model

Eucalyptus plantations play an important role in the timber supply and global warming mitigation around the world. Forest age is a critical factor for evaluating and modeling forest structure (e.g., diameter at breast height (DBH), height (H), aboveground carbon stocks (ACS)) and their dynamics. Recently, the spatial distribution of forest age at different scales based on time series remote sensing data has been widely investigated. However, it is unclear whether such data can effectively support the simulation and assessment of forest structure, especially in fast-growing plantation forests. In this study, the physiological principles in predicting growth (3-PG) model was firstly optimized and calibrated using survey and UAV lidar data at the sample plot (SP) scale, and was then applied at the forest sub-compartment (FSC) scale by designing different simulation scenarios driven by different forest age data sources and adjustments. The sensitivity of the simulated forest structure parameters to forest age was assessed at the SP and FSC levels. The results show that both the survey forest age data and the remote-sensing-derived forest age data could accurately estimate the DBH, H, and ACS of eucalyptus plantations with the coefficients of determination (R2) ranging from 0.87 to 0.94, and the relative root mean square error (RRMSE) below 20% at SP level. At the FSC level, the simulation results based on remotely sensed forest age data are significantly better than FSC forest age data from surveys by forestry bureaus, with R2 of ACS 0.7, RMSE 9.12 Mg/ha, and RRMSE 28.24%. The results of the sensitivity analysis show that the DBH, H, and ACS show different degrees of variation under different adjusted forest ages at SP and FSC level. The maximum difference in ACS is 82.91% at the SP scale if the forest age decreases 12 months and 41.23% at the FSC scale if the forest age increases 12 months. This study provides an important reference for future studies using forest age data obtained by remote sensing to drive the forest carbon model in a large spatial scale.

An integrated multi-scale approach to restoring a degraded secondary forest ecosystem: A case study in the Changbai Mountains, northeastern China

Large-scale forest degradation has led to a drastic alteration of forest landscapes worldwide with severe consequences for human well-being and ecosystem services. The extent and spatial composition of forests within a landscape mosaic play a crucial role in processes and functions ranging from stand to landscape scales. A fundamental task for forest landscape restoration is the identification of potential forest types and species for restoration. In this study, we demonstrated how to restore and manage a degraded secondary forest accounting stand condition while simultaneously targeting optimal landscape structure and function. First, we identified 14 native primary forest types that correspond to different topographies in the study area with data from previous studies. Then, we extracted topography data from a digital elevation model and forest inventory. Combining the topography data with the native primary forest types, we identified the forest types for restoration in each forest sub-compartment. However, some sub-compartments had multiple alternative. Based on the landscape structure analyses, the optimal arrangement of forest types for restoration in the landscape was determined. Combined landscape restoration target and potential forest types for restoration of each sub-compartment, the locations and the species for restoration were determined. This study provides a significant baseline for forest restoration and increase restoration effects.

A novel forest state assessment methodology to support conservation and forest management planning

A new forest state assessment methodology to complement existing conservation and forestry data has been developed. The aim is to provide tools for strategic planning including spatial distribution of conservation priorities. The method is point-based using a dense systematic sampling grid and provides more detailed information than vegetation maps or forest subcompartment descriptions, but requires less effort than forest inventories. Indicators include canopy composition and structure, deadwood, herbs, microhabitats, disturbances, shrubs and regeneration. The results can inform managers about the structural and compositional diversity of forest stands in the form of thematic maps and can provide the basis for analysis of habitat suitability for forest-dwelling organisms. A smartphone application has been developed to enable electronic data collection. PostGIS and Python scripts were used in the data flow. In this paper, we outline the development of the assessment protocol, and present the sampling design and the variables recorded. The main advantages of the survey methodology are also shown by case-studies based on data collected during the first field season in 2014. The protocol has been designed for low mountain forests in Hungary, but it can be modified to fit other forest types.

A Regional Forest Tree Layer Biomass Estimation Method Based on Clustering Analysis

As an area always contains varies of tree spices or forest types, therefore, when using biomass estimation model based on single tree or forest stand to estimate regional biomass, the modeling workload is big, and the existing models do not adequately reflect the factors that influence the biomass. Aiming at the problems above, this paper proposes a regional forest tree layer biomass estimation method based on clustering analysis, using the forest resources survey data of the study area as the research object, using principal component analysis to extract characteristic factors from 17 indexes, using the improved K-means algorithm to clustering the forest subcompartment, and using support vector regression algorithm to separately build the biomass estimation model based on clusters. The results show that 8 principal components can reflect over 80% information of the original data; the subcompartment of the study area can be divided into 6 classes, the coefficients of each model are ranging from 0.7 to 0.92, the average relative error absolute values of each model are ranging from 11.173% to 23.583%, this method has got a satisfactory accuracy, which can provide a new way for regional biomass estimation.

Host and site factors affecting tree mortality caused by the spruce bark beetle (Ips typographus) in mountainous conditions

To better understand the initiation and severity of tree mortality caused by the spruce bark beetle (Ips typographus (L.)) during an outbreak, we analysed the entire course of an outbreak from 1990 to 2000 in the Tatra Mountains (Western Carpathians, Central Europe). This time period represents the last complete bark beetle gradation in this area. We distinguished three outbreak phases: the incipient epidemic, epidemic and post-epidemic stages. The sampling unit was the forest subcompartment. We analysed a total of 315 forest subcompartments over more than 2000ha. We investigated the influence of 11 environmental and stand variables on two processes in different phases of the outbreak: the initiation and the severity of spruce mortality. We used factor analysis, discriminant analysis, multiple linear regressions and boosted regression trees for the statistical analyses. The results showed that the roles of host and site factors in the initiation and severity of spruce mortality caused by the spruce bark beetle differed during the outbreak according to the exploitation of available host resources. The initiation of tree mortality was primarily related to host factors, and the severity of mortality was dependent on host size and insolation.

Approach and Technical Route for Forest Resource Regeneration Based on the Forest Sub-Compartment Data of Forest Management Inventory

Approach and Technical Route for Forest Resource Regeneration Based on the Forest Sub-Compartment Data of Forest Management Inventory

Cryphonectria parasitica in Sessile Oak in Hungary

Since 1999 occurrence of chestnut blight fungus (Cryphonectria parasitica) has been observed in sessile oak in Western and South-Western regions of Hungary in young and middle aged Quercus petraea stands mixed with Castanea sativa. Incidence and impact of the disease, vegetative compatibility type diversity of the pathogen, occurrence of the natural hypovirulence in oak, conversion capacity of the local hypovirulent strains and development of the symptoms in inoculated oak trees were studied in order to investigate the conditions of the biological control based on the hypovirulence in oak. In 2003 survey plots were designated in 12 infected oak stands. The rate of infection varied up to 23.02% and the mortality rate up to 5.76%. Isolations were performed in 2004 from survey plots and in 2006 from larger areas of two forest management units. In 2004 all isolates from oak were of virulent character, while 15.38% of the isolates showed hypovirulent features in 2006. Totally 15 VC types were delimited among the 174 isolates. The VC type diversity varied between 1 to 5 types/plot or forest subcompartment. Five local hypovirulent isolates showed full conversion capacity to the selected virulent strains of different VC types in vitro. Early appearing and progressive increasing of the symptoms were observed in the oak trees inoculated with virulent strains, however more than half of the trees healed during the second year after the inoculation. Some hypovirulent inoculations caused superficial altering of the suberisation, showing the establishment of the hypovirulent fungus in the bark. Our results show favourable conditions for successful application of the preventive control by disseminating the hypovirulent strains in young oak stands.

Conserving red squirrels ( Sciurus vulgaris): mapping and forecasting habitat suitability using a Geographic Information Systems Approach

A model of habitat suitability linked to a Geographic Information System was developed for the red squirrel ( Sciurus vulgaris) in 2800 ha of Thetford Forest, East England, to assess red squirrel population numbers in relation to forest management. We defined each forest sub-compartment or parcel of land in terms of its tree species and age between 1995 and 2015, and categorised each parcel of land as low, moderate or high red squirrel suitability. Resident squirrels may live in more than one habitat patch providing the distance between patches is within the foraging range of the animals and the land between the patches does not act as a barrier to foraging movements. Moreover, squirrels require a minimum area (home range area) of suitable habitat that will provide them with sufficient food resources. To examine these two factors, we explored 120 different model scenarios using three different distances to link patches together and four different sized minimum areas, termed minimum linked areas (MLA), that would hold resident red squirrels, at five year intervals between 1995 and 2015. As an overall measure of suitability, we summed all the MLAs in the reserve for high plus moderate suitability, which we have called the total linked area (TLA), and forecast how this may change in the future. We show that TLA will increase from 39% in 1995 to 67% of the study area by 2015, demonstrating that the reserve will get better for red squirrels over this time. We also demonstrate how changes in forest management would further increase TLA to 82% by 2015. Our results demonstrate how a habitat suitability model operating at the scale of an individual forest, coupled with a GIS and based on an understanding of the species' ecology, provides an objective way of assessing the impact of forest management prescriptions on red squirrel populations.