Selection cutting is defined as a tool for uneven-aged silviculture. Our study used several long-term data sets to investigate the structural stability in stands treated with different kinds of partial cutting. The management goal was to create and maintain a stable all-aged diameter-distribution like the one described by Eyre and Zillgitt (1953) and Arbogast (1957). We analyzed data from stands at Argonne Experimental Forest (WI), Dukes Experimental Forest (MI), Cuyler Hill State Forest (NY), Secord Hill State Forest (NY), and Anna Huntington Wildlife Forest (NY). The stands differed in their initial age structure. Those at Dukes and NY were uneven-aged and treated with single-tree selection system. Stands at Argonne were even-aged second-growth treated with selection-like cuttings. We determined changes through time in number of trees across 2.5-cm diameter classes, shifts in the shape and scale of the three-parameter Weibull function used to describe the diameter distributions, and dynamics of associated stand attributes. Long-term results differed dramatically. Findings showed that single-tree selection cutting created and sustained stable diameter distributions and uniformity of conditions through consecutive entries in uneven-aged stands. By contrast, these characteristics varied through time in the second-growth stands that had been treated with selection-like cuttings. Analysis also showed that the Weibull shape and scale parameters for stands under selection system migrated towards those of the recommended target diameter distribution in the uneven-aged stands. These parameters diverged from the target with repeated use of selection-like cuttings in the second-growth even-aged stands.

There are several ecological issues associated with unmanaged secondary forests, or abandoned satoyama, in Japan, such as decreasing species diversity and invasion by alien species. To understand its vegetation dynamics, we investigated change in stand structure of an unmanaged secondary forest over 15-years.

Study plots were established in a secondary forest at varying distances from a late-successional lucidophyllous forest. We calculated Bray-Curtis similarity indices of the plots over space and time and compared them using nMDS (non-Metric Multidimensional Scaling). Species composition of the proximal secondary forest was more similar to the lucidophyllous forest than that of the distal secondary forest, indicating that late-successional species are spreading into the unmanaged secondary forest.

Over the 15-year study period, species composition of the distal secondary forest approached that of the lucidophyllous forest. This was due to decreasing abundance of shade-intolerant species, such as Rhododendron. Stand structure, however, changed very little because dominant canopy trees, namely Quercus serrata and Quercus variabilis, continued to grow. Although late-successional species are regenerating in the secondary forest, it may take several decades for the stand to reach late-successional structure, where evergreen broadleaved trees, namely Castanopsis cuspidata, dominate the canopy.

Ink disease and chestnut blight of European chestnut (Castanea sativa) represent the two major threats for chestnut orchards and coppice forests in Greece. However, since the application of biological control of chestnut blight by introducing hypovirulence of Cryphonectria parasitica on a nationwide scale in Greece has been successful in limiting chestnut blight, ink disease is an increasing threat as it causes considerable loss. For this reason, the occurrence of the disease was investigated and an updated distribution map of Phytophthora spp. in Greece has been created. In this study, the presence of ink disease was confirmed all over Greece and the Phytophthora species involved in the disease were recorded. Soil and tissue samples were collected and the obtained Phytophthora isolates were identified on the basis of their morphological and molecular traits. A total of seven species have been detected. P. cambivora, P. cinnamomi and P. cryptogea were recovered both from soil and tissue, while P. plurivora, P. cactorum and P. gonapodyides, P. citrophthora were isolated only from soil. Although P. cambivora is the prevailing species in chestnut orchards and natural coppice stands, the recent record of the more aggressive P. cinnamomi is now considered a potential major threat to C. sativa in Greece. The nationwide distribution of the disease and the severe loss of trees demand the implementation of appropriate control measures. The crucial role played by the irrigation methods used by the chestnut growers is pointed out as the major reason for the emergence of ink disease.

Currently, Pinus pinea, a valuable Mediterranean forest species in Catalonia, Spain, pinecone production is quantified visually before harvest with a manual count of the number of pinecones of 3^rd year in a selection of trees and then extrapolated to estimate forest productivity. To increase efficiency and objectivity of this process, we propose the use remote sensing to estimate pinecone productivity for every tree in a whole forest (complete coverage vs. subsampling). The use of unmanned aerial vehicle (UAV) flights with high spatial resolution imaging sensors is hypothesized to offer the most suitable platform with the most relevant image data collection from a mobile and aerial perspective. UAV flights and supplemental field data collections were carried out in several locations across Catalonia using sensors with different coverages of the visible (RGB) and near infrared (NIR) spectrum. Spectral analyses of pinecones, needles and woody branches using a field spectrometer indicated better spectral separation when using near-infrared sensors. The aerial perspective of the UAV was anticipated to reduce the percentage of hidden pinecones from a one-sided lateral perspective when conducting manual pinecone counts in the field. The fastRandomForest WEKA segmentation plugin in FIJI (Fiji is just ImageJ) was used to segment and quantify pinecones from the NIR UAV flights. Regression of manual image-based pinecone counts to field counts was R²=0.24; however, the comparison of manual image-based counts to automatic image-based counts reached R²=0.73. This research suggests pinecone counts were mostly limited by the perspective of the UAV, while the automatic image-based counting algorithm performed relatively well. In further field tests with RGB color images from the ground level, the WEKA fastRandomForest demonstrated an out of bag error of just 0.415%, further supporting the automatic counting machine learning algorithm capacities.

Wildfires are a significant worldwide problem. In Russia alone, they caused about 150 million euros worth of damage in 2020, therefore the development of solutions to control forest fires is particularly important. In this paper, we have proposed a Depth-To-Water index based solution to find the optimal location of fire ponds and access roads to them. Digital Depth-To-Water maps were created in a geographic information system for two datasets: in Lohusuu, Estonia and Podporozhye, Russia. Using a mixed integer programming model with spatial Depth-To-Water data, potential locations for fire ponds were derived on the basis of one fire pond of 100 m³ per forest compartment. Access routes for firefighting vehicles to ponds were generated using a mixed integer programming model, taking into account the existing road network. The results obtained in combination with the known compartments fire hazard classes allows both to reduce potential losses from wildfires and to ensure compliance with the requirements of existing Government regulations.

Fires are events that occur regularly in the Sierra de la Ventana region, affecting native and exotic herbaceous and exotic arboreal vegetation (mainly Pinus pinaster and Pinus halepensis). Although they are disturbances ecologically adapted to the environment, the advance of exotic vegetation and the perception of the population has modified their frequency and intensity. The objective was to identify the variation in forest cover due to fires in the Arroyo Ventana Basin, Province of Buenos Aires, covering the period 2010-2020. Two large fires were identified: 2013 and 2018. A land use map was developed through supervised classification of satellite images Lansat8 and Sentinel2. Likewise, satellite images were used for the dates before and after the events, processed with the QGIS Madeira 3.4.6 software. Vegetation indices Burned Area Index (IAQ), Normalized Burning Ratio (NBR) and Normalized Difference Vegetation Index (NDVI) were applied. It was obtained that the variation of forest cover does not exceed 30 ha in the studied period (minimum 140ha, maximum 170 ha), although its distribution does change, a spatial variation that corresponds to the burned areas. Abundant regeneration was observed between the years 2013 and 2017. The fires have proven to be controllers of the forest cover, maintaining a stable surface in the period studied. However, this process is a triggering factor for the germination and subsequent establishment of regeneration of Pinus sp.

Early bark beetle detection is still a challenge, as the symptoms of early infestation stages are hard to identify. Conventional foot-based detection is time consuming and the associated costs depend on the stand characteristics. A detection by gas sensor equipped drones can decrease the costs, as it does not rely on the movement speed on the ground. A novel drone-based system for early bark beetle detection by means of resin odor cues was compared to a conventional foot-based detection. The results showed that the cost efficiency of the drone system highly depends on the flight speed and the hourly costs of the pilot, while the cost efficiency of the foot-based assessment highly depends on the terrain slope and the forest floor characteristics. In general, the drone-based detection of early infestation stages showed increasing cost reductions in comparison to the conventional detection at increasing forest areas, increasing slopes and increasing understory density.

With a projected growth of the Brazilian pulp and paper industry of about 20 % over the period 2020-2025, the innovations in waste management and reutilization of side-products origination from the pulp- and paper industry may mostly contribute to a sustainable development of forest-based products by implementing the recuperation and innovative processing of side-stream products at a local level. In this study, we analyse the feasibility for the reuse of recovered cellulosic fiber fractions collected from different pulp and paper mills by considering some practical issues and evaluation of the quality for different side-stream fractions originating from rejects, deinking sludge, primary sludge and secondary sludge. The situation for the Brazilian pulp and paper industry will be used as a model, for which the potential for recovery of fibers from waste waters will be evaluated from the analysis of available data including . First, the water consumption and effluents from paper mills are reviewed together with an estimation of the fiber recovery potential from primary sludge and fine fiber rejects. Second, the specific characteristics and appearance of certain fiber fractions might imply constraints on their further processing properties. Therefore, we describe some insights in the fiber fractions that could provide highest potential for future valorization. Based on the degree of compositional homogeneity and concentration of cellulose fibers in several waste fractions, the processing of fibers from primary sludge and/or fine fiber rejects are estimated as the most economically feasible. The homogenization of the fiber fractions yield fibrillated cellulose materials with various morphologies depending on the selection of recuperated fractions. Through thorough characterization of the resulting fiber fraction, new application markets can be selected.

The charcoal production is considered a rudimentary activity nowadays even though it lasts centuries of practice. Controlling the process and homogenizing the raw material are the challenges in the process required to obtain a high-quality product. Thus, understanding the influence of different pyrolysis temperatures becomes of importance since the temperature is an essential variable in the energy quality of the charcoal. This study aimed to investigate the influence of two pyrolysis temperatures on a mix of commercial eucalypt woods. For this, pyrolysis was carried out at a heating rate of 3.33 °C.min^-1, 3 h of duration, and two final temperatures (300 °C e 450 °C). The apparent density, bulk density, moisture content, proximate analysis and heating calorific, energy density, and combustibility index of the charcoal were measured. The apparent density and ash content were the same for both pyrolysis temperatures (p-value> 0.05), with averages of 310 kg/m³ and 1.09%, respectively. The charcoal pyrolyzed at 450 °C provides the higher value of fixed carbon content (82.98%), lower volatile matter content and higher heating value. The charcoal at 300 °C showed the highest bulk density and, presented the higher energy density (3.58 GJ/m³). As it generates more heat and reaches a higher temperature peak, the higher combustibility index (0.135) is in the charcoal produced at a temperature of 450 °C. Under the conditions analyzed, pyrolysis performed at a final temperature of 450 ° C results in better energy performance of charcoal than at 300 °C.

Current criteria to define managed forest areas are still inconsistent among countries’ reports of GHG emissions from forestry to the UNFCCC. Integrated Assessment Models (IAM) used for assessing the countries’ mitigation pathways employ a proxy for managed forests for modelling purposes that differ from the countries’ criteria. This difference in the managed forest definition is one of the reasons for a gap of about 5.5 GtCO2 yr−1 between the modelled global land-use use GHG emissions and the one reported by the countries to the UNFCCC. Such inconsistency adds uncertainty to the contribution of the forest sector to climate change mitigation efforts and undermines its monitoring. Here we combined multiple data sources and developed an harmonized map of managed forests, consistent with official GHG inventories. The map is based on a number of data sources, in particular, the global forest management layer of the Nature map , information on road density, forest productivity, travel time to major cities, and ancillary data from forest use and the forest classes layers. We applied the map developed here in the Global Forest Model (G4M) operating on a 0.5x0.5 deg. regular grid for masking the managed forest area, which is consistent with the estimates of countries GHG emissions’ reports to the UNFCCC, and estimating the GHG emissions from that area. Currently, however, general criteria are applied to all countries, regardless of local forest practices and actual criteria applied in the countries. We conclude that a further development of managed forests maps, with consistent definitions at country-level, and country-specific rules for managed/unmanaged forest classification deserves further investigation. Such efforts can support the harmonization of GHG emissions estimates from models and official statistics and improve the design of mitigation policies informed by IAMs.