An unprecedented number of wildfire events during 2019 throughout Brazilian Amazon has caught global attention due to its massive extension and the associated loss in the Amazonian forest- an ecosystem on which the whole world depends. Such devastating wildfire in Amazon has strongly hampered the global carbon cycle and significantly reduced forest productivity. In this study, we have quantified such loss in forest productivity in terms of Gross primary productivity (GPP) using a comparative approach from Google Earth Engine. In total 12 wildfire spots have been identified based on its fire extension over the Brazilian amazon and quantified the loss in productivity between 2018 and 2019. MODIS GPP and MODIS Burned Area satellite imageries with the revisit time of 8-days and 30-days respectively have been used for this study. Interesting and significant outcomes have been found within this study after final processing. We have observed that maximum fire events during 2019 in compared to 2018 does not hamper the natural annual trend of GPP of the Amazonian Ecosystem. However, a significant drop in forest productivity in terms of GPP has been observed. All 11 sites have been recorded with GPP loss that ranging from 18.88 gC m⁻² yr⁻¹ to 120.11 gC m⁻² yr⁻¹ except site 3. Such drastic loss in GPP supports that during 2019 fire events, all these sites acted as a carbon source rather than a carbon sink sites that were directly humped the global carbon cycle and terrestrial CO₂ fluxes. So it has been assumed that these findings will suit other Amazonian wildfire sites and also for the tropical forest ecosystem. We hope this study will provide significant contributions to the global carbon cycle, terrestrial ecosystem studies, sustainable forest management, and climate change in contemporary science.

Cable skyline systems are often used to yard felled trees in mountain forests. As they are in the difficult terrain forest stands and these operations are process of the works by temporal setting at the irregular shape site, it has been difficult to be standardized and to store results useful for the following operations. Pre-processes for the operation are inevitable such as for design of process management and for mechanism rig up of the operation and usually their simplification is expected, and always the craftsmanship of the operation staff is required. The recent development of high-definition local environmental information and the ease of public use made it easy for them to be made possible in a short period of time. Furthermore, the simulation method using CG technology makes it possible to examine various location relationship, mechanisms, etc. of real three-dimensional space by VR etc. Here I show 1) modeling the main rigging method that has been used so far in a digital three-dimensional space on a PC, 2) cable rigging can be designed quickly, one day for a yarding site, 3) validating and revising smooth yarding operation, by virtual yarding operation with keyboard/joystick control for design better setting and operation, 4) designing and creation of data system for storing the results of the operation to improve following operations, which may support timber SCM. Moreover, it can be applied to develop a new cable skyline mechanism.

Information on forest composition, and specifically the tree types and their distribution, aids in timber stock calculation and helps better understand the biodiversity in a particular region. Automatic satellite imagery analysis can significantly accelerate the process of tree type classification, which is traditionally done via ground-based observations. Although computer vision methods have proven their efficiency in remote sensing tasks, specific challenges arise in forestry applications. In this paper, we aimed to improve tree species classification based on the neural network approach. The study involved four species commonly found in the Russian boreal forests: birch, aspen, pine, and spruce. We used imagery from the Sentinel-2 satellite, which has multiple bands in the visible and infrared spectra, and spatial resolution of up to 10 meters. Additionally, the short revisit time and free access policy, it makes these images a valuable data source for the purposes of forest classification. In computer vision terms, we define the problem of tree type classification as one of semantic segmentation, and assign each pixel of the image a particular tree type. The forest inventory data contain the tree type composition, but do not describe their spatial distribution within each individual stand. Therefore, some pixels can be assigned a wrong label if we consider each stand to be homogeneously populated by its dominant species. This calls for the weakly supervised learning approach. To solve this problem, we used a deep convolutional neural network with a tailored loss function set to optimize for multiple objectives. We tested the model's transferability by creating a dataset of images for three regions of Russia (Arkhangelsk Oblast, Leningrad Oblast, and Perm Krai), with the combined area of more than one million hectares, over four years (2016-2019). In our study, we demonstrated how to modify the training strategy so it outperforms the basic per-pixel neural network approach.

In this work, we present a hybrid methodology based on the ADA methodology, applied to the simulation of pine species from northern Mexico. From algebraic transformations and certain premises, we were able to reduce the parameter space of the Weibull growth function from 3 parameters to just 1, the maximum diameter of the individual at the end of growth. From the point of view of complexity, we have a decrease in computational cost, because now we have only one parameter to estimate, and from a practical point of view, it is an easy parameter to obtain, even in the field. To present the quality of the method, we used the mean absolute percentage error and the quantile regression to visually present the quality of the fit. Then we compare this proposed methodology with the GADA versions for the Chapman-Richards and Hossfeld models. The results presented for the study area, to avoid generalizations, show that the proposed hybrid method was more accurate in the estimates.

Cultural studies on perception of cultural ecosystem services of urban green spaces are important and often recognized as such by people living in urban areas. There is lack of qualitative studies and understanding how people perceive cultural ecosystem services from different types of tree-based urban green areas. The aim of the study was to explore whether and how citizens of Zagreb perceive and use cultural ecosystem services of different types of tree-based urban green spaces. Focus groups were conducted in each city district with its residents. Interviews were recorded, transcribed and transcripts analyzed in MAXQDA software. To analyze the data without a predefined set of codes or categories the bottom up code-category-theme approach was used. Results showed that place attachment, aesthetic and recreational services were more recognized than educational and cultural identity services. Most important single attributes for place attachment were positive memories and good maintenance, while most important categories were facilities, existence of emotional ties, possibility of experiences, recreational use and access. Presence of specific tree species and presence of trees in general were the most important attributes for aesthetic services, while possibility of experiences and trees were the most important categories. People perceived various cultural ecosystem services from tree-based urban green space, even though some services more than others. Forests and parks were recognized as those providing multiple cultural ecosystem services. Other types of green spaces were also recognized as bearers of these services, albeit with fewer services and attributes attached. Findings support the importance of careful planning of urban green spaces in terms of providing a variety of green space types. The study provides a basis for later quantification of cultural ecosystem services from tree-based urban green space.

Restoration of endangered slash/longleaf pine flatwood ecosystems is of critical, regional importance to the biota of the Gulf coastal plain. One of the serious threats facing this ecosystem is the invasion of Chinese tallow (Tricdica sebifera), a community-transforming invasive tree species. We developed a conceptual model to decipher the mechanism of Chinese tallow invasion at the microscale based on community assembly theory and modeled the spatial variations of invasibility of slash pine flatwoods to Chinese tallow using a spatially-explicit point process model. The probability of Chinese tallow invasion was predicted through the polynomial functions of a set of identified filters (covariates) that were classified, respectively, as dispersal filters (distances to roads and seed sources), overstory filters (canopy closure, pine: hardwood ratio), and understory filters (grass cover, elevation) based on the roles they play in the invasion processes. To measure these filters (input for the model), 281 contiguous quadrats of 30 m² were set up with a total surveyed area of 0.86-ha. All overstory pine and hardwood species as well as tallow trees including seedlings, saplings and large trees were mapped and tree species and diameter at breast height (dbh, if present) were measured. Understory shrubs and grass/herbaceous species cover (%) and overstory canopy closure (%) were measured in each quadrat. The raster image (1-m resolution) of identified filters were interpolated based on field data or extracted from available DEM data for spatial modeling.

The identified filters vary spatially, and may facilitate or inhibit tallow invasion. Therefore the additive polynomial models of these identified filters provide a viable approach to predict the spatial variations of the probability of tallow invasion (invasibility). The full models including all filters, and the sub-models which included the dispersal filters and either of the overstory and understory filters seemed to have an adequate predictive power based on R², RSE and skewness (the scatter and qq-plots). In contrast, sub-models which included only one of the dispersal, overstory and understory filters failed to precisely predict the observed invasion outcomes. The results support the importance of reducing propagule pressure levels for effective tallow control and slowing of spread.

Forest management is becoming increasingly complex due to increasing demands in ecosystem service provisioning and future climate change impacts. For a sustainable forest management, scientifically well-founded decision support is therefore urgently required. Within the project SessFor, a decision support system for strategic planning at the forest enterprise level is being developed, based on the climate sensitive forest model SwissStandSim and initialized from forest inventory data. The system is currently applied to the forest enterprise Wagenrain (440 ha), located in the Swiss Plateau region. Indicators for biodiversity and ecosystem service provisioning (timber production, recreation value and carbon sequestration) are calculated for different management strategies and evaluated using a multi-criteria decision analysis. Preliminary results demonstrate the suitability of the system to evaluate ecosystem service provisioning under different management strategies and to identify the best management strategy, based on criteria defined by the forest manager. Furthermore, results show how the system can be used to assess developments for time-scales of 50-100 years under different climate change scenarios. In the ongoing project, the system will be applied to other case study regions, including mountain forests, which are of key importance in Switzerland and other alpine areas.

Lomatia hirsuta (Lam.) Diels is a pioneer tree species that regenerates mostly after fire, and more frequently found as a secondary species in Patagonian forests dominated by Austrocedrus chilensis and Nothofagus dombeyi. However, in the El Manso Valley, Province of Río Negro in Western Argentina, L. hirsuta forms pure stands, originated from stump shoots. The wood is very attractive for its colourful appearance and beautiful grain, suitable for fine furniture. Nevertheless, these forests are not managed for timber production, they are mostly thinned for grazing, and the wood is mainly used as firewood. The objective of this study was to evaluate the possibility to improve quality wood production in stands through silvicultural interventions in a sustainable way. Samples have been carried out in dense stands of different ages and in one less dense stand with the traditional use for pastures. We evaluated the state and quality of the trees, and their growth has been studied by means of trunk analysis. The results indicate, that there is a significant potential to improve the production of quality wood in dense stands through thinning oriented to crop trees. This should start in young stands, because in older stands, good form and sound trees are already considerably reduced. It also became apparent, that forest management is necessary to stabilize these nearly unattended forests, which in old stands are very vulnerable to damages caused by wind and wet snow. In such stands the extraction of trees could be combined with the planting of seed trees, with the expectation to improve the quality and vigour of the trees at maturity.

Reforestation with native broad-leaved tree species changes the aboveground functions that regulate the quality of litter inputs and soil-root systems, which ultimately influences on soil properties and nutrients pool. The current study characterizes the regeneration in the floor layer and topsoil at depth pf 0-10 cm in the skid trails in response to the reforestation of four tree species (FE; Fraxinus excelsior, PA; Prunus avium, AC; Acer cappadocicum, and QC; Quercus castaneifolia) after clear-cutting in the degraded forests, comparing to the undisturbed natural forest (CB-PP; Carpinus betulus - Parrotia persica). Results showed significant differences in litter layer properties among tree species, with the highest litter thickness, C, and C/N ratio under the QC and AC and the greatest litter N in CB-PP and FE. FE plantation resulted in an enhance soil bulk density (1.14 g cm⁻³), total porosity (55.85%), macroporosity (37.72%), penetration resistance (1.43 MPa), soil moisture (33.4%), and aggregate stability (51.7%) compared to other tree plantations, whereas these values under the FE plantation were still lower than those of the CB-PP stand over a 30-year period after logging operation. The lowest amount of soil C (3.34%), soil C/N ratio (14.58), and C storage (38.13 Mg ha⁻¹) were found under the FE plantation, whereas the greatest amount of soil pH (6.61), soil N (0.23%), N storage (2.64 Mg ha⁻¹), available P (15.53 mg kg⁻¹), K (235.55 mg kg⁻¹), Ca (171.92 mg kg⁻¹), and Mg (36.57 mg kg⁻¹), fulvic acid (282.7 mg/100 g) as well as humic acid (134.5 mg/100 g) were found under the FE plantation compared to the other trees plantation, but were still least than those of the values under the CB-PP over a 30-year period after soil compaction. Following the establishment of different tree plantations, the significantly greatest earthworm density (1.82 n m⁻²) and dry mass (22.57 mg m⁻²), fine root biomass (76.31 g m⁻²), soil microbial respiration (0.33 mg CO₂-C g soil⁻¹ day⁻¹), MBC (438.7 mg kg⁻¹), NH₄⁺ (16.54 mg kg⁻¹), NO₃⁻ (15.92 mg kg⁻¹), N mineralization (27.04 mg N kg soil⁻¹), and MBN (28.35 mg kg⁻¹) were found under the FE plantation, whereas the values did not return to the pre-harvest levels as observed under the CB-PP over a 30-year period. Litterfall on the soil surface by planted tree species (FE and PA in particular) considered as food resource (i.e., soil C and soil organic matter) that is a primary driver to the biological and microbial activities. Results of the current study can promote our knowledge to select suitable tree species, which leads to maintain soil quality and nutrients pool in the ecosystem restoration programs and reforestation in the degraded forest area.

Achievement of economically satisfactory effects of the work of wood chippers depends, among other things, on the organization of their work. A characteristic feature of Polish forests is the dispersion of relatively small unit operation areas in forest complexes where forest operations (cleaning, thinning or harvesting) are carried out, that results from the principles of silviculture applied in Poland. In the case of chipper operation, the important factor determining the efficiency of chips acquiring is the amount of material to be chipped at the location and the way it is stacked.

The aim of the research was to identify parameters influencing the efficiency and organization of chippers' operation. The conducted research allowed to determine the structure of the working shift time in the process of chipping logging residues. The analysis covered operation of five wood chippers, working in different conditions, for several months, 6 days a week, being owned by one company and managed by the same team of people. The data obtained from the ComboClient 3 machine operation monitoring program was compiled and analyzed using the Statistica v.13 statistical program.

Several machine states have been distinguished, including operational, ancillary and transport activities, fuel consumption was also determined. There were several cases of the course of task implementation: 1) a chipper does not finish work on a forest area on a given day, travels to machine base, and on the next day it travels back from the base to the place where the task is performed, 2) a wood chipper completes the task on a given area and on the same day it moves to the next task, 3) the chipper stays overnight on the forest area.

Thanks to the proposed approach, it was possible to indicate the impact of work organization on the efficiency of the examined machines. The average travel distance of the chippers when changing the forest area during a working day ranged from 4.74 km to 9.5 km, the chippers make trips every two days on average. The average duration of a working shift is 12.4 hours, after the shift is completed the chipper usually moves to a base located 4.2 km to 6.3 km away, while at the beginning of the work it goes to a forest area located 2.5 km to 4.0 km away. Average fuel consumption in chippers mounted on a forwarders is about 16 l/h, and for chipper on a truck 7.7 l/h.

It was found that the following actions have a decisive influence on the effectiveness of the operation of the chippers: determination of the size of individual tasks and the deplyment of successive forest areas, indication of the proper location of the machine base and the method of accessing the forest area.