Forest Research Research Articles

Towards a benchmark of national training requirements for continuous cover forestry (CCF) in Sweden

Continuous cover forestry (CCF) is forest management based on ecological and biological principles. CCF particularly requires the abandonment of clearfelling practices in favour of more natural approaches of regeneration. Recently, CCF has been identified as a way to mitigate climate change, to bring about forest conservation and to meet the diverse requirements of recreation forests. EU strategies support the use of CCF and Sweden is committed to the transformation of 20% of its plantation forest land to CCF. This policy change meets the Swedish forest industry rather unprepared. CCF training is therefore urgently required and we applied marteloscope techniques to begin with establishing a benchmark of training requirements. A marteloscope is a forest research plot where all trees are measured and have clearly visible numbers on the stem surface. We carried out a first marteloscope experiment at the Svartberget experimental forest near Umeå in Northern Sweden involving 13 test persons that we asked to carry out CCF management by selecting trees that are supposed to stay behind and others that are to be taken out in order to achieve CCF objectives. We applied specialised statistics to analyse the trainees’ choices and thus to measure their current state of silvicultural knowledge and experience. The results were interpreted in the context of data previously obtained from 26 comparable marteloscope experiments in Britain. The Svartberget results were in parts similar to and sometimes even closer to theoretical expectations than the British results, but also revealed that more intensive training was required in individual-based forest management, which is an important part of CCF. A new didactic technique, the competitor-for-frame tree rule, tightening the link between evicted and residual trees has contributed to the good tree-selection performance at Svartberget.

Diversity and species composition of lichens across altitudinal range in the Batang Toru Forest, North Sumatra, Indonesia

Abstract. Pasaribu N, Atni OK, Siregar JP. 2023. Diversity and species composition of lichens across altitudinal range in the Batang Toru Forest, North Sumatra, Indonesia. Biodiversitas 24: 2171-2178. West Block of Batang Toru Forest, located in North Tapanuli Regency, North Sumatra is one of the protection forest areas which has uniqueness and high biodiversity, one of them is the lichen. The information regarding the lichen species found in the West Block of Batang Toru Forest Research Station has never been reported. Its various types and distributions are unknown. This study aimed to observe lichen at the Batang Toru Forest Research Area, which was carried out from September 2021 to March 2022. The study was carried out with the exploration method by exploring along the track. From the results of the study, there was a total of 54 species of lichen consisting of 23 families and 38 genera. Based on the types of the thallus, it was found 23 species of lichen classified as foliose, 21 crustose, 4 fruticose, 3 squamulose, and 3 filamentous. The most common lichen family found at the study site was Lobariaceae, with a total of six species. The species collected in this study were mostly found on the bark substrate. This study reveals important information about the variety of lichen species in the West Block of Batang Toru Forest, highlighting the urgent need for further research and conservation efforts to protect this unique and diverse ecosystem.

The need of ecohydrological research in tropical forests for healthy watersheds

Tropical forests play a critical role in providing clean water and maintaining healthy watersheds, yet they face numerous threats such as deforestation, land use change, and climate change. To address these challenges, there is a growing need for ecohydrological research that can inform land use planning and management strategies for healthy watersheds. Ecohydrology is an emerging science that seeks to understand the functional interactions between hydrology and biota. It quantifies and explains the relationships between hydrological processes and biotic dynamics as well as linkages among upland, riparian, and aquatic components on a watershed scale. However, most of the ecohydrological studies have been concentrated on temperate regions, and for tropical regions, such studies are lacking. This article argues that there is a high time to launch research for identifying critical ecohydrological functions and driving forces that regulate the quality and quantity of water, and their role in providing water-based ecosystem services in tropical watersheds. The article outlines the main challenges facing tropical forests and watersheds, and highlights the importance of interdisciplinary collaboration and long-term monitoring for effective ecohydrological research. It also provides examples of successful ecohydrological research projects in tropical forests, and discusses the potential benefits of investing in ecohydrological research for tropical forest conservation and watershed management. Overall, this article emphasizes the importance of ecohydrological research in tropical forests for healthy watersheds and calls for more attention and resources to be devoted to this field.

Geoecological Research and Management Principles in the Northern Caucasus’ Mountain Forests

The article provides an analysis of historical data on the organisation and state of geoecological research in the mountain forests of the North Caucasus and Russia. On the example of regional monitoring of mountain forest ecosystems, the organisation of the multi-purpose nature management within mountain watersheds is demonstrated. Based on the results of the experimental materials obtained from a long-term monitoring at complex forest-hydrological stations, as well as the results of active experiments, recommendations are given for forest management in the mountains. An example of obtaining information by field methods is shown, as well as computer modelling of forestry development in mountainous regions. The scientific principles and ecological bases of farming in the mountainous regions forests are proposed.

Mapping the Age of Subtropical Secondary Forest Using Dense Landsat Time Series Data: An Ensemble Model

Quantifying secondary forest age (SFA) is essential to evaluate the carbon processes of forest ecosystems at regional and global scales. However, the successional stages of secondary forests remain poorly understood due to low-frequency thematic maps. This study aimed to estimate SFA with higher frequency and more accuracy by using dense Landsat archives. The performances of four time-series change detection algorithms—moving average change detection (MACD), Continuous Change Detection and Classification (CCDC), LandTrendr (LT), and Vegetation Change Tracker (VCT)—for detecting forest regrowth were first evaluated. An ensemble model was then developed to determine more accurate timings for forest regrowth based on the evaluation results. Finally, after converting the forest regrowth year to the SFA, the spatiotemporal and topographical distributions of the SFA were analyzed. The proposed ensemble model was validated in Jiangxi province, China, which is located in a subtropical region and has experienced drastic forest disturbances, artificial afforestation, and natural regeneration. The results showed that: (1) the developed ensemble model effectively determined forest regrowth time with significantly decreased omission and commission rates compared to the direct use of the four single algorithms; (2) the optimal ensemble model combining the independent algorithms obtained the final SFA for Jiangxi province with the lowest omission and commission rates in the spatial domain (14.06% and 24.71%) and the highest accuracy in the temporal domain (R2 = 0.87 and root mean square error (RMSE) = 3.17 years); (3) the spatiotemporal and topographic distribution from 1 to 34 years in the 2021 SFA map was analyzed. This study demonstrated the feasibility of using change detection algorithms for estimating SFA at regional to national scales and provides a data foundation for forest ecosystem research.

Temporal Variations in Temperature and Moisture Soil Profiles in a Mediterranean Maquis Forest in Greece

Soil moisture (SM) and temperature (ST) are critical factors in forest eco-hydrological research. In this study, we investigated the inter- and intra-annual changes in SM and ST profiles in a mixed Mediterranean maquis forest stand together with soil and meteorological parameters. Hourly data from three field measurements points at four depths (−5, −20, −40 and −70 cm) for 6 years were interpolated using the kriging method to produce annual SM and ST profiles. The results indicate that air temperature highly affects the upper 5 cm of the mineral soil. In general, it increases with depth in winter at an average rate of 0.036 °C/cm and decreases in summer (0.035 °C/cm), presenting higher values compared to air temperature from April to August and lower ones during the rest of the period. Precipitation is the main factor driving SM variations up to a superficial soil depth of 40 cm. The upper soil layer (0–40 cm) infiltrates water faster and presents high SM variability, especially in monthly and seasonal (year to year) time steps. The maquis forest stands are likely to be strongly affected by climate change, therefore the results of this study could be useful in hydrological and climate change studies focused on maquis vegetation water management.

ИННОВАЦИИ В ЛЕСНОМ И ЛЕСОПРОМЫШЛЕННОМ КОМПЛЕКСЕ: АНАЛИЗ ЛИТЕРАТУРЫ В SCOPUS И WEB OF SCIENCE

Innovation is gaining more and more attention in the scientific community, and the study of innovation processes has become an advanced field of scientific and practice-oriented research. This article provides a systematic literature review of journal articles on innovation in forestry and the forestry industry. We include international, English-language, peer-reviewed scientific articles included in the scientific databases Scopus and Web of Science since the 1980s. Our search for articles that specifically mention “innovation/innovation” and “forest/timber/timber” from a social science perspective resulted in 230 studies. Our analysis provides a quantitative overview of institutional contexts, scientific fields, methods and thematic areas. Based on qualitative content analysis, we also describe the historical development of the research area, summarize the main ideas on central research topics at the firm and system level, and illustrate the state of knowledge in selected areas of innovation. In general, established concepts and approaches based on innovation research are well accepted in forest sector innovation research, although new trends could be used more progressively. The articles analyzed use a variety of quantitative and qualitative methods and are dominated by country and (sub) sectoral case studies. A greater variety of methods could enrich the knowledge base, and more cross-country and sectoral benchmarking could confirm previous findings.

Proteomics research in forest trees: A 2012-2022 update.

This review is a compilation of proteomic studies on forest tree species published in the last decade (2012-2022), mostly focused on the most investigated species, including Eucalyptus, Pinus, and Quercus. Improvements in equipment, platforms, and methods in addition to the increasing availability of genomic data have favored the biological knowledge of these species at the molecular, organismal, and community levels. Integration of proteomics with physiological, biochemical and other large-scale omics in the direction of the Systems Biology, will provide a comprehensive understanding of different biological processes, from growth and development to responses to biotic and abiotic stresses. As main issue we envisage that proteomics in long-living plants will thrive light on the plant responses and resilience to global climate change, contributing to climate mitigation strategies and molecular breeding programs. Proteomics not only will provide a molecular knowledge of the mechanisms of resilience to either biotic or abiotic stresses, but also will allow the identification on key gene products and its interaction. Proteomics research has also a translational character being applied to the characterization of the variability and biodiversity, as well as to wood and non-wood derived products, traceability, allergen and bioactive peptides identification, among others. Even thought, the full potential of proteomics is far from being fully exploited in forest tree research, with PTMs and interactomics being reserved to plant model systems. The most outstanding achievements in forest tree proteomics in the last decade as well as prospects are discussed.

Combining GS-assisted GWAS and transcriptome analysis to mine candidate genes for nitrogen utilization efficiency in Populus cathayana

BackgroundForest trees such as poplar, shrub willow, et al. are essential natural resources for sustainable and renewable energy production, and their wood can reduce dependence on fossil fuels and reduce environmental pollution. However, the productivity of forest trees is often limited by the availability of nitrogen (N), improving nitrogen use efficiency (NUE) is an important way to address it. Currently, NUE genetic resources are scarce in forest tree research, and more genetic resources are urgently needed.ResultsHere, we performed genome-wide association studies (GWAS) using the mixed linear model (MLM) to identify genetic loci regulating growth traits in Populus cathayana at two N levels, and attempted to enhance the signal strength of single nucleotide polymorphism (SNP) detection by performing genome selection (GS) assistance GWAS. The results of the two GWAS analyses identified 55 and 40 SNPs that were respectively associated with plant height (PH) and ground diameter (GD), and 92 and 69 candidate genes, including 30 overlapping genes. The prediction accuracy of the GS model (rrBLUP) for phenotype exceeds 0.9. Transcriptome analysis of 13 genotypes under two N levels showed that genes related to carbon and N metabolism, amino acid metabolism, energy metabolism, and signal transduction were differentially expressed in the xylem of P. cathayana under N treatment. Furthermore, we observed strong regional patterns in gene expression levels of P. cathayana, with significant differences between different regions. Among them, P. cathayana in Longquan region exhibited the highest response to N. Finally, through weighted gene co-expression network analysis (WGCNA), we identified a module closely related to the N metabolic process and eight hub genes.ConclusionsIntegrating the GWAS, RNA-seq and WGCNA data, we ultimately identified four key regulatory genes (PtrNAC123, PtrNAC025, Potri.002G233100, and Potri.006G236200) involved in the wood formation process, and they may affect P. cathayana growth and wood formation by regulating nitrogen metabolism. This study will provide strong evidence for N regulation mechanisms, and reliable genetic resources for growth and NUE genetic improvement in poplar.

Klasifikace vegetační stupňovitosti v České republice: review

Considering the changing climatic conditions, the Czech and Slovakian vegetation has been vertically divided into Forest Vegetation Zones (FVZs) units. Each FVZ is represented by a specific tree species, i.e., the oaks (Quercus sp.), European beech (Fagus sylvatica L.), silver fir (Abies alba Mill.), Norway spruce (Picea abies (L.) H. Karst.) and dwarf pine (Pinus mugo Turra). The FVZ concept has been applied in the Czechoslovakian forestry classification practice since the 1950s. Due to the broad time span of the studied topic, this article is divided into five chapters regarding the evolution of the FVZ concept. Its currently applied form was established primarily in the 1970s on the grounds of data gathered during two decades of forest typology research. An FVZ unit has become an upper unit of the Czech Forest Ecosystem Classification since its legislative codification in the Forest Act (289/1995) in 1995. To this day, however, the FVZ concept has not been reassessed by advanced, multi-dimensional statistical methods. This paper aims to describe key moments of the development of this concept and provide a perspective on its limitations, also in connection with current trends in ecological research. This review aims to provide a better understanding of the forest vegetation-environment relationship in the Czech Republic in relation to climate change, indirect anthropogenic environmental impact, and prediction of forest and landscape ecosystems response.

Forest Structure Measurement in Tropical Rainforest using Laser Scanning Technology

Numerous measurements can be made to extract the forest structure. Forest structure is one of the main aspects of forest management. The precise estimation of forest structure is vital for some forestry applications. Thus, this study presents a novel non-destructive approach for the measurement of forest structure using laser scanning technologies of airborne LiDAR and Terrestrial Laser Scanning (TLS). The study area was located at the forest campus of the Forest Research Institute of Malaysia (FRIM), Kepong, Selangor. The elements of forest structure that were measured: were canopy height; plant density and basal area. The field survey was conducted over 3 plots of 25 m radius circular shape with a total of 60 trees with diameter at breast height (DBH) of 10 cm and above. The tree canopy height was estimated based on canopy height model (CHM) of LiDAR data. For plant density, it was estimated based on crown delineation created from CHM. While, for TLS data, the extraction of individual trees was done using Cyclone algorithm. The forest structure measurement obtained from laser scanning technologies is proven to be reliable with the root mean square error (RMSE) of 5.415, t-test of 3.011, and p-value of 0.004 for canopy height. For basal area, the mean of RMSE, t-test and p-value was 0.22589, 0.620 and 0.324 for the overall 3 plots, respectively. The result obtained for plant density was one tree per meter². The final outputs were presented as the map of CHM, plant density and basal area map. In conclusion, laser scanning measurement improves and provides a precise technique for forest structure measurement.

Leaf morphological traits of nine major tropical trees of Shorea species (Dipterocarpaceae)

Abstract. Mufarhatun N, Susilowati A, Hilwan I, Arrofaha N, Yulita KS, Dwiyanti FG, Hidayat A, Kamiya K, Rachmat HH. 2023. Leaf morphological traits of nine major tropical trees of Shorea species (Dipterocarpaceae). Biodiversitas 24: 1704-1712. Shorea is the largest genus in the Dipterocarpaceae family and has high leaf morphological variations among its species, which causes difficulties in field identification. Therefore, information on the specific characteristics of the leaf morphology of each species is needed. This study aimed to examine and discriminate leaf morphological traits at both mature and sapling stages of nine Shorea species, namely Shorea balangeran (Korth.) Burck, S. leprosula Miq., S. mecistopteryx Ridl., S. multiflora (Burck) Symington, S. ovalis (Korth.) Blume, S. pinanga Scheff., S. platyclados Slooten ex Endert, S. selanica (Wight & Arn.) Blume, and S. stenoptera Burck. The leaves of 90 mature trees growing in the Dramaga Research Forest (DRF) and Gunung Dahu Research Forest (GDRF) as well as the leaves of 180 saplings growing in the nursery of Forest Research and Development Center (FRDC) were observed. Leaf traits, leaf color, and chlorophyll content were assessed on 3 leaves from each mature tree and 5 from each sapling collected. Furthermore, comparative analysis using F independent test in the one-way analysis variance (ANOVA), multivariate analysis using Principal Component Analysis (PCA), and Hierarchical Cluster Analysis were used in this study. The results showed that 8 of the 11 measured morphological traits were identified as the quantitative leaves morphological differentiators, namely Leaves Width (LW), Lamina Length (LL), the length between the largest Leaves Point (LP) with the base of the leaves, angle of leaves vein (SD), Petiole Length (PL), number of leaves vein (LB), breadth of the leaves (WL), and the Circumference of the Leaves (CL). In addition, the results of cluster analysis showed the nine Shorea spp. are clustered into two major groups. Group 1 consisted of species, S. stenoptera, and S. mecistopteryx, while the remaining are included in Group 2. Our findings conclude that the eight leaf morphological traits obtained from this study are useful as additional characters to distinguish the nine Shorea species in the field.

A LANDIS-II extension for simulating forest road networks

Forest roads are an important part of forest management, both in terms of cost and impact on surrounding ecosystems. Existing tools to simulate the construction of forest roads have been designed for tactical or operational planning purposes, for relatively small areas (<10 000 ha) and small-scale topographic information. Hence, no forest road simulation tool properly exists to assist forest landscape ecology and management research. Here, we present the Forest Roads Simulation (FRS) extension for the LANDIS-II model—a spatially explicit landscape simulation model of forest succession and disturbances. The FRS extension simulates forest road networks via a least-cost path algorithm accounting for landscape structure, decision inputs, and forest road types. We demonstrate the accuracy with which the FRS extension reproduces several key characteristics of existing road networks in two managed regions in Quebec, Canada: road density, road position, and fragmentation of the landscape. The FRS extension is easy to parameterize, proposing many options for researchers to simulate forest road networks at a strategic level in managed landscapes. It can tackle new research questions investigating the effects of forest roads within management strategies, such as the cost of road construction and habitat fragmentation, across large management units and long planning horizons.

Effects of Irrigation Interval and Planting Spacing on the Establishment and Growth of Faidherbia albida (Del.) A. Chev. Transplants in Arid Land Soils

The study aimed to assess the establishment of Faidherbiaalbida transplants under the effect of irrigation intervals and plantingspacing in the field conditions. It consisted of three irrigation intervals of5, 10 and 15 days and three planting spacings of 1x1 m, 1x2 m, and 2x3m; and it was conducted in the premises of the Forest Research Center,Khartoum, during May 2008 to June 2009. The results showed that thetemporal growth rate of F. albida shoot heights was greater in winter(November-February), but it was seriously slowed during the summerperiod (March-June). The shoot height, diameter and biomass growth ofF. albida increased with decreasing irrigation intervals; the growth ofthese parameters was highest in 5 days interval and lowest in 15 daysinterval. Planting spacings had no direct definite effect on F. albidaseedlings’ growth parameters. Even though, in the longer irrigationintervals, transplants’ growth tented to be greater in the wider spacing.Root biomass development seemed to be higher in the longer irrigationinterval regimes. There were no significant differences in the foliarnutrient content of the transplants between the different irrigationintervals. The values of mineral elements measured in this study areindicative of moderate nutrient supply for the F. albida transplants

A Dynamic Effective Class Balanced Approach for Remote Sensing Imagery Semantic Segmentation of Imbalanced Data

The wide application and rapid development of satellite remote sensing technology have put higher requirements on remote sensing image segmentation methods. Because of its characteristics of large image size, large data volume, and complex segmentation background, not only are the traditional image segmentation methods difficult to apply effectively, but the image segmentation methods based on deep learning are faced with the problem of extremely unbalanced data between categories. In order to solve this problem, first of all, according to the existing effective sample theory, the effective sample calculation method in the context of semantic segmentation is firstly proposed in the highly unbalanced dataset. Then, a dynamic weighting method based on the effective sample concept is proposed, which can be applied to the semantic segmentation of remote sensing images. Finally, the applicability of this method to different loss functions and different network structures is verified on the self-built Landsat8-OLI remote sensing image-based tri-classified forest fire burning area dataset and the LoveDA dataset, which is for land-cover semantic segmentation. It has been concluded that this weighting algorithm can enhance the minimal-class segmentation accuracy while ensuring that the overall segmentation performance in multi-class segmentation tasks is verified in two different semantic segmentation tasks, including the land use and land cover (LULC) and the forest fire burning area segmentation In addition, this proposed method significantly improves the recall of forest fire burning area segmentation by as much as about 30%, which is of great reference value for forest fire research based on remote sensing images.

Considering random effects and sampling strategies improves individual compatible biomass models for mixed plantations of Larix olgensis and Fraxinus mandshurica in northeastern China

Mixed-species plantations, which are more resilient and productive than pure plantations, have received increasing attention and have gradually become a focus of forest research. Therefore, it has become imperative to develop models to quantitatively describe specific stand types. In this study, biomass models were developed using 105 destructively sampled Changbai larch (Larix olgensis) and Manchurian ash (Fraxinus mandshurica) trees from several mixed-species plantations in northeastern China. In the case that the influence of stand variables and climate factors on tree-level biomass was not significant, seemingly unrelated regression (SUR) models that included tree height (H), crown length (CL) and plot-level random effects were developed to predict tree-level components and total biomass. The results showed that the introduction of plot-level random effects to create seemingly unrelated mixed-effects (SURM) models improved the model fitting, with the determination coefficient increasing by 0.76%∼17.35% (Changbai larch) and 0.60%∼8.15% (Manchurian ash) for all components. Among the developed models, the plot-level SURM model achieved better mean absolute percentage error (MAPE) values of all components (7.50%∼22.12% for Changbai larch and 7.52%∼39.94% for Manchurian ash) according to leave-one-out cross-validation (LOOCV), with significantly lower values than those of SUR models. Two calibration strategies and various numbers of trees (0, 2, 4, 6 and 7) were used to calibrate the random effects model. Model performance improved as the number of trees used for calibration increased, but gains in performance then decreased gradually. When wood and bark biomass were used for calibration, the prediction accuracy of other components (branches, foliage and roots) tended to be uncertain. Overall, it is recommended to use an SURM model with diameter at breast height (DBH) based on more than four local trees and an SURM with DBH, H and CL based on two local trees for random effect calibration for measurements of all biomass components in mixed-species plantations of Changbai larch and Manchurian ash.

Erratum: Below average midsummer to early autumn precipitation evolved into the main driver of sudden Scots pine vitality decline in the Swiss Rhône valley

An erratum on: Hunziker S, Begert M, Scherrer SC, Rigling A and Gessler A (2022) Below Average Midsummer to Early Autumn Precipitation Evolved Into the Main Driver of Sudden Scots Pine Vitality Decline in the Swiss Rhône Valley. Front. For. Glob. Change 5:874100. doi: 10.3389/ffgc.2022.874100 An omission to the funding section of the original article was made in error. The following sentence has been added: "Open access funding provided by WSL - Swiss Federal Institute For Forest, Snow And Landscape Research".The original version of this article has been updated.

Morphological Assessment of Annatto (Bixa orellana L.) Fruit and Seed for the Development of Mechanical Seed Separator

Background: The development of post-harvest equipment or machinery is vital for agricultural productivity. Bixin, a natural colourant derived from annatto seeds, is still separated manually, which may result in pigment loss. The engineering properties of annatto fruits and seeds must be analyzed in this note for the development of a mechanical seed separator. Methods: The fruits were collected from Forest College and Research Institute, TNAU, Mettupalayam, Tamil Nadu. Engineering properties such as physical, gravimetric and frictional properties, colour and bixin content were determined for two dried annatto fruit and seed varieties (A1 and A2). The Z-test and t-test (p less than 0.05) were used to statistically analyze the data. Result: The morphological characteristics of annatto fruits A1 and A2 differed noticeably and significantly. The surface area and volume of the A1 fruit were higher. The fruit and seed were merely spherical and conical. The lowest static friction was observed for stainless steel in both fruit and seeds. The mean bixin content of the A1 and A2 seeds was 1.5±0.4% and 1.84±0.57%, respectively. These engineering properties will be used to design a mechanical separator without much loss of pigment.

Using a digital elevation model to place overland flow fields and uncleaned ditch sections for water protection in peatland forest management

Peatland forest management is an important source of human-induced additional nitrogen, phosphorus, and organic carbon loads to surface waters in Finland. Ditch network maintenance (DNM) is typically used to ensure sufficient soil drainage for profitable timber production on peatland sites, but nutrient mobilization, particularly of phosphorus, and suspended sediment loads from ditches can cause harmful ecological effects on the quality of water courses. Various water protection structures have been developed to capture the loads released after treatments and to decrease the management impacts in forestry. Overland flow fields are efficient mechanisms for water purification, but they are rarely used in practice due to difficulties in finding suitable locations. In addition, leaving breaks between cleaned ditch sections is recommended wherever possible, as uncleaned sections decrease flow velocity and enhance sediment deposition from runoff water. To plan the most adequate protection methods in DNM, new GIS-based tools are needed to propose e.g. appropriate locations for water protection structures. We developed a spatial analysis to suggest locations for overland flow fields and uncleaned ditch sections within the catchment of lake Kovesjärvi (Parkano, Western Finland). Airborne lidar data consisting of 5 pulses m−2 enabled detailed terrain analysis and finding strictly specified terrain properties that satisfied the conditions of the water protection structures. Half of the field-reviewed overland flow fields were evaluated as good suggestions by forest management professionals and researchers. The model for uncleaned ditch sections worked well on the relatively flat study area, as 77% of the field-reviewed suggestions were rated good by expert opinions. Overall, the approach was evaluated to be useful in peatland forest management. Model parameters can be modified for various topographies, but more studies are needed prior to wider use of the model.

The use of remote sensing data sources and GIS in fire protection planning in biebrza national Park, with special attention to non-forest ecosystems

ABSTRACT In the spring of 2020, a large-scale fire destroyed 5,526 hectares of wetlands in Biebrza National Park. It was decided to modernize the park’s fire protection system. It proved necessary to develop rules for fire protection in large natural areas where non-forest communities predominate. A team of experts from the Forest Research Institute, the Fire Department, and the Biebrza National Park developed methods for fire protection in the park based on open, publicly available remote sensing data sources. The following methods were developed or modified and adapted to the conditions of the park: determination of fire danger, prediction of fire danger, modeling of fire development, determination of the network of fire access roads, determination of water supply points, including water withdrawal points for helicopters, detection of fires, functioning of the alarm and communication system, firebreaks, places of concentration of forces and resources, equipment for fire fighting, and taking preventive measures. The developed principles of fire protection in the Biebrza National Park, based on open remote sensing data and the technology of GIS, will enable the creation and operation of a system that will reduce the probability of fires in the future.