Category Of Trees Research Articles

Chromosome-scale genomes of five Hongmu species in Leguminosae

The Legume family (Leguminosae or Fabaceae), is one of the largest and economically important flowering plants. Heartwood, the core of a tree trunk or branch, is a valuable and renewable resource employed for centuries in constructing sturdy and sustainable structures. Hongmu refers to a category of precious timber trees in China, encompassing 29 woody species, primarily from the legume genus. Due to the lack of genome data, detailed studies on their economic and ecological importance are limited. Therefore, this study generates chromosome-scale assemblies of five Hongmu species in Leguminosae: Pterocarpus santalinus, Pterocarpus macrocarpus, Dalbergia cochinchinensis, Dalbergia cultrata, and Senna siamea, using a combination of short-reads, long-read nanopore, and Hi-C data. We obtained 623.86 Mb, 634.58 Mb, 700.60 Mb, 645.98 Mb, and 437.29 Mb of pseudochromosome level assemblies with the scaffold N50 lengths of 63.1 Mb, 63.7 Mb, 70.4 Mb, 61.1 Mb and 32.2 Mb for P. santalinus, P. macrocarpus, D. cochinchinensis, D. cultrata and S. siamea, respectively. These genome data will serve as a valuable resource for studying crucial traits, like wood quality, disease resistance, and environmental adaptation in Hongmu.

Comparison of growth of northern red oak (Quercus rubra L.) and durmast oak (Quercus petraea [Mattusch.] Liebl.) under similar growth conditions

Abstract The impacts of climate change on forest stands are manifested in different ways and intensity. Changes in the species composition of forest stands due to the different tolerance of forest species to the effects of climate change are one of the consequences too. In this context, introduced tree species are often mentioned as a possible replacement for dying autochthonous species. Of the deciduous species, it is mainly northern red oak. The aim of this paper is to compare selected quantitative (number of trees, basal area, merchantable volume, basal area increment and volume increment) and qualitative (crop trees) characteristics in one stand of the northern red oak at the age of 54 years and in two stands of durmast oak (age 57 and 58 years) in comparable site conditions. Achieved results showed higher values in all investigated quantitative parameters in the northern red oak stand compared to durmast oak stands. The merchantable volume in the northern red oak stand was 473 m3 per hectare in the tended subplots and 742 m3 ha–1 in the control ones. On the subplots with durmast oak, it was only from 228 to 289 m3 ha–1 in the subplots with thinning and 226 to 357 m3 ha–1 in the control areas. The same results were obtained for the category of crop trees. It means 230 m3 ha–1 for the northern red oak and 28 to 121 m3 ha–1 for durmast oak. The well-known fact about the higher quantitative production of the northern red oak compared to durmast oak was confirmed.

Accurate delineation of individual tree crowns in tropical forests from aerial RGB imagery using Mask R‐CNN

AbstractTropical forests are a major component of the global carbon cycle and home to two‐thirds of terrestrial species. Upper‐canopy trees store the majority of forest carbon and can be vulnerable to drought events and storms. Monitoring their growth and mortality is essential to understanding forest resilience to climate change, but in the context of forest carbon storage, large trees are underrepresented in traditional field surveys, so estimates are poorly constrained. Aerial photographs provide spectral and textural information to discriminate between tree crowns in diverse, complex tropical canopies, potentially opening the door to landscape monitoring of large trees. Here we describe a new deep convolutional neural network method, Detectree2, which builds on the Mask R‐CNN computer vision framework to recognize the irregular edges of individual tree crowns from airborne RGB imagery. We trained and evaluated this model with 3797 manually delineated tree crowns at three sites in Malaysian Borneo and one site in French Guiana. As an example application, we combined the delineations with repeat lidar surveys (taken between 3 and 6 years apart) of the four sites to estimate the growth and mortality of upper‐canopy trees. Detectree2 delineated 65 000 upper‐canopy trees across 14 km2 of aerial images. The skill of the automatic method in delineating unseen test trees was good (F1 score = 0.64) and for the tallest category of trees was excellent (F1 score = 0.74). As predicted from previous field studies, we found that growth rate declined with tree height and tall trees had higher mortality rates than intermediate‐size trees. Our approach demonstrates that deep learning methods can automatically segment trees in widely accessible RGB imagery. This tool (provided as an open‐source Python package) has many potential applications in forest ecology and conservation, from estimating carbon stocks to monitoring forest phenology and restoration.Python package available to install at https://github.com/PatBall1/Detectree2.

Palm live aboveground biomass in the riparian zones of a forest in Central Amazonia

AbstractAboveground biomass estimates in the Amazon region remain uncertain, partly due to extrapolations based mainly on samples collected in upland terrains of terra‐firme forests. Most biomass estimates were focused on dicotyledonous trees or included other plant groups as a category of trees. Palms dominate areas that represent 20% of the Brazilian Amazon. However, their contribution to biomass estimates and the variation within riparian zones remain poorly documented. We estimated the biomass of palms larger than 1–cm diameter at breast height (1.3 m aboveground) in riparian plots (n = 40); investigated the potential bias caused by the use of dicotyledonous‐ or family‐ rather than species‐level equations for biomass estimation; compared palm biomass between riparian and non‐riparian plots (n = 72); and evaluated the effects of soil, topography, and stream characteristics in riparian plots on palm biomass. Mean palm biomass in riparian zones estimated with species‐level equations (27.50 ± 12.94 Mg/ha, range: 3.32–63.27 Mg/ha) was three times greater than biomass estimated with a family‐level equation (9.04 ± 4.29 Mg/ha, range: 1.51–21.25 Mg/ha) and was greater than mean biomass estimated with a pantropical equation (20.46 ± 9.29 Mg/ha, range: 3.67–47.99 Mg/ha). Mean palm biomass in riparian zones was four times greater than in non‐riparian zones. Palm biomass was high in flatter areas with poorly drained soils, but lower around streams with higher discharge. Inclusion of palms can contribute to reducing the uncertainties in biomass estimates in Amazonian forests. Recognition of the importance of riparian zones may improve conservation policies.Abstract in Portuguese is available with online material.

Biodiversity dynamics in primary mid-taiga spruce forests after total windthrow in the Vodlozersky National Park, Russia

In windthrow-affected areas, the research of biota is of high relevance taking into account the lack of knowledge about the dynamics of their flora, soil properties, and tree stand regeneration. An important task is to study the mechanisms of the natural dynamics of plant communities after major disturbances in large boreal forests. This paper was aimed to investigate the effects of a total windthrow event on the dynamics of biodiversity in pristine mid-boreal spruce (Picea abies) forests. The study was carried out in the Vodlozersky National Park (Northwest Russia: Arkhangelsk Region and Republic of Karelia), situated in the northern and middle taiga subzones. A series of permanent sample plots was established in an area affected by massive windthrow in 2000. The windthrow consequences of the forest communities have been studied, starting from the year of the event (2000) at 2–5-year intervals. A soil survey has been conducted in 2016. Windthrown trees, situated in the sample plots, were counted by species and diameter classes. Natural regeneration was estimated in subplots with a division to height cohorts and vitality status. Geobotanical relevé sampling of the ground vegetation has been conducted in 1 × 1-m permanent plots. Aphyllophoroid fungi (Basidiomycota) were counted by fruit bodies. Main soil pits and partial pits were dug. The morphological description of soils was produced in both undisturbed and disturbed sites in the study area. Obtained data, covering 20 years of surveys of various components of the forest plant communities (tree stand, advance regeneration, ground vegetation, wood-destroying fungi, soils), were analysed. We found that 16–20 years after the windthrow event the species and age structure of the tree stand has been considerably changed due to the forest stand rejuvenation. Post-windthrow regeneration of coniferous species in the true-moss group of forests has been successfully going on. By the end of the second decade after the windthrow event, cowberry spruce forests contained 4300 individuals/0.01 km2 of viable spruce regeneration, including 1500 individuals/0.01 km2 belonging to the large size category of spruce trees. In the bilberry-Sphagnum-type forest, spruce regeneration amounted to 8700 individuals/0.01 km2, including 2200 individuals/0.01 km2 belonging to the large size category of spruce trees. This amount is sufficient to ensure the development of spruce-dominated communities in the future. Since the forest ecosystems were recovering after the windthrow, the biodiversity of changed, that was reflected in an increase in the species composition of the ground vegetation and fungal communities. Over the study period (2001–2021), surveys of the sample plots demonstrated 83 aphyllophoroid fungi species, including five species included in the Red Data Book of the Republic of Karelia, as well as 22 taxa, considered old-growth forest indicator- and specialist species. The number of wood-destroying fungi species was the highest in the period from the 12th to the 19th post-windthrow years. The changes in soil properties on windthrow-affected sites were more explicit in the upper horizons: soil acidity decreased; both potassium and carbon content increased; nitrogen distribution across horizons became more even. An increase in the carbon-nitrogen ratio was detected in the Е and BF horizons. The obtained data can be used for predicting the regeneration of pristine mid-boreal spruce forests affected by catastrophic disturbances.

Exploration of the Diversity of Trees and Its Implementation in the Plant Morphology Course

The campus as an educational facility is always designed to create comfort that can support the quality of learning in it so the concept of green open space has long been part of the development of the campus environment. This study aims to determine tree species on the FKIP Universitas Cenderawasih (UNCEN) Abepura Campus and their implementation in learning plant morphology in the Biology Education Study Program. This research uses an exploratory method. The results of research on the Uncen Abepura FKIP Campus environment found 13 species with 10 families in the category of trees with a diameter of 20 cm and above. These trees are scattered in various environments on the FKIP UNCEN Abepura Campus. The Arecaceae family consists of two tree species, namely Cocos nucifera L and Livistona saribus (Lour.) Marr. The Cupressaceae family consists of one type of tree, namely Cryptomeria japonica. The Sapindaceae family consists of two types of trees, namely Filicium decipiens (Wight & Arn.) and Pometia pinnata. The Fabaceae family consists of two tree species, Albizia saman (Jacq.) Merr, and Tamarindus indica L. The Moraceae family consists of one tree species, namely Ficus benjamina. The Lecythidaceae family consists of one tree species, namely Barringtonia asiatica (L.) Kurz. The Combretaceae family consists of one type of tree, namely Terminalia catappa L. The Anacardiaceae family consists of one type of tree, namely Mangifera indica L. The Oxalidaceae family consists of one type of tree, namely Averrhoa carambola L. The Clusiaceae family consists of one type of tree, namely Calophyllum inophyllum L. Implementation of This research is in the form of learning media in the form of a plant morphology practicum guide

A Detection Method for Individual Infected Pine Trees with Pine Wilt Disease Based on Deep Learning

Pine wilt disease (PWD) can cause destructive death in many species of pine trees within a short period. The recognition of infected pine trees in unmanned aerial vehicle (UAV) forest images is a key technology for automatic monitoring and early warning of pests. This paper collected UAV visible and multispectral images of Korean pines (Pinus koraiensis) and Chinese pines (P. tabulaeformis) infected by PWD and divided the PWD infection into early, middle, and late stages. With the open-source annotation tool, LabelImg, we labeled the category of infected pine trees at each stage. After coordinate-correction preprocessing of the ground truth, the Korean pine and Chinese pine datasets were established. As a means of detecting infected pine trees of PWD and determining different infection stages, a multi-band image-fusion infected pine tree detector (MFTD) based on deep learning was proposed. Firstly, the Halfway Fusion mode was adopted to fuse the network based on four YOLOv5 variants. Simultaneously, the Backbone network was initially designed as a dual branching network that includes visible and multispectral subnets. Moreover, the features of visible and multispectral images were extracted. To fully utilize the features of visible and multispectral images, a multi-band feature fusion transformer (MFFT) with a multi-head attention mechanism and a feed-forward network was constructed to enhance the information correlation between visible and multispectral feature maps. Finally, following the MFFT module, the two feature maps were fused and input into Neck and Head to predict the categories and positions of infected pine trees. The best-performing MFTD model achieved the highest detection accuracy with mean average precision values (mAP@50) of 88.5% and 86.8% on Korean pine and Chinese pine datasets, respectively, which improved by 8.6% and 10.8% compared to the original YOLOv5 models trained only with visible images. In addition, the average precision values (AP@50) are 87.2%, 93.5%, and 84.8% for early, middle, and late stages on the KP dataset and 81.2%, 92.9%, and 86.2% on the CP dataset. Furthermore, the largest improvement is observed in the early stage with 14.3% and 11.6%, respectively. The results show that MFTD can accurately detect the infected pine trees, especially those at the early stage, and improve the early warning ability of PWD.

Modelling and evaluation of land use changes through satellite images in a multifunctional catchment: Social, economic and environmental implications

Floods are recurrent phenomena with significant environmental and socio-economic impacts. The risk of flooding increases when land use changes. The objective of this research is to detect land cover changes via Sentinel-2 images in the Umia Basin (Galicia, NW Spain) in 2016–2021 and to analyse the associated flood risk. This study focuses on how forest use and nature-based solutions (NBS) can reduce the risk and hazard of flooding in cities and crops in the high-risk area. A flood simulation was performed with the land use obtained from Sentinel-2 (Observed) and three more simulations were performed changing the location of afforestation and NBS, i.e. “S-Upstream”, “S-Downstream” and “S-Total”. Finally, the environmental, economic and social impacts of the scenarios designed and estimated are analysed and discussed. Land cover change was successfully monitored with Sentinel-2 imagery. The catchment area showed noteworthy changes in land use, most notably for the category of trees, which covered 6700 ha in 2016 and 10,911 ha in 2021. However riparian vegetation decreased by almost 11%. For the flood hazard simulations, an average reduction in peak discharge was obtained for all three scenarios (9.3% for S-Up; 8.6% for S-Down and 13% for S-Total). From the economic perspective, all three scenarios show a positive net present value for the period studied. However, S-Down is the scenario with the lowest benefits (€15,476,487), while S-Up and S-Total show better values at €29,580,643 and €65,158,130 respectively. However, investment cost is much higher for the S-Total scenario, and upstream actions affect the whole catchment, so S-Up is the best decision. This study concludes that the information provided by satellites is a large-scale analysis tool for small heterogeneous plots that facilitates the comprehensive analysis of a territory. This information can be incorporated into flood analysis models, facilitating simulation through the use of NBS. It has been proven that the use of reforestation upstream only is almost as beneficial as reforestation in the entire catchment and is economically more viable. This confirms that the methodology used reduces flood hazard, despite the territorial complexity, facilitating decision making on the use of NBS.

Detecting pine wilt disease at the pixel level from high spatial and spectral resolution UAV-borne imagery in complex forest landscapes using deep one-class classification

Pine wilt disease (PWD) poses a serious threat to the worldwide pine forest resources. Unmanned aerial vehicle (UAV) remote sensing has been widely used for PWD control, due to its flexibility and efficiency. Although pixel-level detection can obtain fine detection boundaries, there have been few related works in complex scenes because of the difficulty of setting a preset category system and the poor generalization. A preset category system establishes which categories are to be labeled, and is necessary for traditional pixel-level detection. However, the poor generalization leads to an obvious accuracy drop when detecting PWD in new scenes. In the proposed approach, to address the first issue, one-class classification (OCC) is introduced to detect diseased pixels, focusing only on the category of diseased pine trees. However, the numerous objects but low PWD pixel proportion makes the model optimization unbalanced, for which balanced unbiased detection risk estimation is proposed. To address the second issue, a novel model consisting of three-dimensional (3D) convolutional layers and transformer blocks is proposed to extract more robust features. A novel PWD detection framework based on deep OCC is finally proposed to achieve fine pixel-level PWD detection results. PWD detection experiments were conducted on eight UAV H2 (high spatial and spectral resolution) image strips. In total, 300 PWD samples from strip 1 (accounting for roughly 0.009 % of the total pixels) and 400 unlabeled pixels formed the training set. The test experiments were conducted in the remaining seven strips to validate the model generalization. Satisfactory quantitative results (F1-score greater than 0.9) were obtained for all the test strips. The results indicate that the proposed method has a powerful ability to detect PWD in pine trees, even when the PWD proportion is low, and shows better model generalization than the traditional pixel-level detection methods.

Bird Species Based on Tree Height Perched in the Liwa Botanical Garden, West Lampung Regency

Birds are one of the most diverse animals in the world, especially in Indonesia. Liwa Botanical Garden located in Pekon Kubu Perahu, Balik Bukit District, West Lampung Regency, is a conservation area with the theme of conservation and development of ornamental plants, representing the flora of Southern Sumatra. This research is a continuation of the collaboration between the Department of Biology and Balitbang UPTD Liwa Botanical Garden, West Lampung Regency. The presence of birds in the Liwa Botanical Garden is also a bioindicator of biodiversity for the environment in this area. By maintaining the presence of birds in the Liwa Botanical Garden means protecting their habitat and existing plants. The purpose of this study was to determine the species of birds based on the height of the perched trees in the Liwa Botanical Garden and the abundance of their species. The method used in this research is the point count with the observation time for 9 days in the morning and evening at the height of the tree in 3 different observation stations. Birds on KRL are mostly found on perches at an altitude of 2 - 7 meters, in the category of shrubs and trees, there are 19 out of 25 bird species found. The highest Relative Abundance Index (IKR) was Collocalia esculenta at 39.91% and the lowest IKR value was 7 bird species, each with 0.14% value. The conservation status of the 25 bird species based on IUCN is Least Concern (LC) and based on CITES there is one species that is included in Appendix II, namely Ictinaetus malayensis while based on the Regulation of the Minister of Environment and Forestry of the Republic of Indonesia No. P.20 / MENLHK / SETJEN / KUM.1 / 6/2018 there is one bird species that is included in the protection, namely species Ictinaetus malayensis

Statistical Analysis and Machine Learning Used in the Case of Two Behavioral Tests Applied in Zebrafish Exposed to Mycotoxins

Machine learning is a branch of artificial intelligence that allows computer systems to learn directly from examples, data, and experience. Statistical modeling is more about finding connections between variables and consequently the impact of these relationships, while also catering for prediction. It should be clear that these two methodologies are different in terms of their purpose, despite the fact that they use similar means to get there. The evaluation of the machine learning algorithm uses a set of tests to validate its accuracy. Although, for a statistical model, the analysis of regression parameters by confidence intervals, significance tests and other tests can be used to assess the legitimacy of the model. To demonstrate the applications and usefulness of this theory, an experimental study was conducted on zebrafish exposed to mycotoxin. Methods: Patulin (70 µg/L) and kojic acid (100 mg/L, 204 mg/L, and 284 mg/L) were administered by immersion to zebrafish once daily for a period of 7 days before the behavior testing. The following behavioral tests were performed: a novel tank test (NTT) (to assess the explorative behavior and anxiety); and a Y-maze test (which measures the spontaneous explorative behavior). Behavioral tests were performed on separate days. For the behavior tests, the statistical analysis was performed using ANOVA variation analysis (two-way ANOVA). All results are expressed as the mean ± standard error of the mean. The values of the general index F for which p < 0.05 were considered statistically significant. Results: Y-maze—patulin exposure led to an intensification of the locomotor activity and an increased traveled distance and number of arm entries. By increasing the spontaneous alternation between the aquarium’s arms, patulin has shown a stimulating effect on spatial memory. In the case of zebrafish exposed to 100 mg/L kojic acid, the traveled distance was shorter by 27% than the distance attained by those in the control group. The higher doses of kojic acid (204 mg/L and 284 mg/L) led to an increased locomotor activity, distance traveled, number of arm entries, and the spontaneous alternation. The increase in spontaneous alternation demonstrates that 204 mg/L and 284 mg/L kojic acid doses had a stimulating effect on spatial memory. Novel tank test—compared to the control group, the traveled distance of the patulin-exposed fish is slightly reduced. Compared to the control group, the traveled distance of the kojic acid-exposed fish is reduced, due to a shorter mobile time (by 25–27% in the case of fish exposed to 204 mg/L and 284 mg/L kojic acid). Patulin and kojic acid exhibit toxic effects on zebrafish liver, kidney, and myocardium and leads to severe alteration. We continued the analysis by trying some machine learning algorithms on the classification problems in the case of the two behavioral tests MAZE and NTT, after which we concluded that the results were better in the case of the NTT test relative to the MAZE test and that the use of decision tree algorithms leads to amazing results, knowing that their hierarchical structure allows them to learn signals from both classes. Conclusions: The groups exposed to patulin and kojic acid show histological changes in the liver, kidneys, and myocardial muscle tissue. The novel tank test, which assesses exploratory behavior, has been shown to be conclusive in the behavioral analysis of fish that have been given toxins, demonstrating that the intoxicated fish had a decreased explorative behavior and increased anxiety. We were able to detect a machine learning algorithm in the category of decision trees, which can be trained to classify the behavior of fish that were given a toxin in the category of those used in the experiment, only by analyzing the characteristic features of the NTT Behavior Test.

Impact of different factors degrading cork oak stands in the Mediterranean region: A case study from Algeria

In recent years, the cork oak forests that characterise the Mediterranean region have been exposed to various factors that result in their degradation. These cork oak trees, due to increasingly accentuated anthropogenic activity, undergo withering at different scales.The objective of the study is to assess the impact of various factors that degrade cork oak forests in the Mediterranean region located in northeastern Algeria, and this was achieved by prospecting 22 sampling locations. This allowed the creation of a database containing 745 trees that were observed and 27 measured variables. Different readings were then taken into consideration based on measurements and sometimes on ratings. The impact of several biotic and abiotic factors, which affect and damage the health of cork oak, was identified. These factors include in particular the infestations by xylomycetophagous insects such as Platypus cylindrus and Xyleborus sp., which can potentially infest the cork oak trees that we observed one year after bark harvesting. On the other hand, the stationary descriptors such as altitude, slope, exposure, etc., are important for the dendrometric and exploitation characteristics, but their unfavourable values do not necessarily lead to tree mortality; for example, medium to low slopes, associated with average altitudes of 600 m a.s.l., may ensure the healthiest trees like in our case study. Finally, we were able to find that certain decline factors may affect a particular category of trees, either because they are older, taller or have a large girth, or because they are subject to inadequate debarking.

Analysis of the Influence of the Parameters of the Object of Labor on the Geometric Characteristics of the Levers of the Skidder

The following logging technologies are known today: logging in the form of trees, whips, assortments and wood chips. The most common are logging in the form of whips and assortments. When logging in the form of whips or trees, a skidder is used, which carries out transportation of felled whips or trees to a loading dock. Blockless skidding machines equipped with technological equipment in the form of a manipulator with a gripper and a conic clamping device are widely used in the Russian forest industry. In the process of moving trees into a conical clamping device, as well as in the process of skidding, interaction forces arise between the grip and the tree, which must be taken into account when designing technological equipment for skidding machines. Due to the large variety of trees, it is also necessary to take into account the mass and geometric characteristics of trees. The article publishes the methodology and results of the study of the influence of breed and category of trees on the geometric characteristics of the capture skidder.

Karakteristik ekologi, kondisi kesehatan dan tingkat kerawanan degradasi mangrove saat penginisiasian KKPD Rupat Utara 2018

The study of ecological characteristics, health conditions and the level of vulnerability of mangrove degradation when initiating North Rupat as a Regional Aquatic Conservation Area (KKPD) was conducted in July 2018 with the aim of future baseline data and comparison. Data collection on the condition of mangrove vegetation is carried out by making line transects and plots drawn from the reference point (outermost mangrove stands) in a direction perpendicular to the coastline to the mainland. The results of the study showed that 12 identified species. The diversity index and dominance are relatively low (H’ ≤ 2.0 and 0 < C ≤ 0.5), while the uniformity is classified as stable (0.75 < E ≤ 1). For the density of mangroves the highest category of trees is at Station 4 (2525 ind/ha ± 638.15), while the density of saplings and seedlings at Station 1 (2800 ind/ha ± 873.48 and 50000 ind/ha ± 17638.34), where Xylocarpus granatum is the dominant species in the tree and seedling category (Importance Value Index/IVI 191.74% and 240.80%), while Avicennia alba was for the saplings category (IVI 216.01%). In the main land part of the North Rupat KKPD area, the mangroves' health condition was increasingly threatened by destruction compared to the small islands around it. However, overall the level of vulnerability of mangrove degradation in the initiating area of North Rupat KKPD is still relatively low.

Hilbert series in the category of trees with contractions

We consider Hilbert series associated to modules over various categories of trees. Using the technology of Sam and Snowden (J Am Math Soc 30(1): 159–203, 2017) we show that these Hilbert series must be algebraic. We then apply these technical theorems to prove facts about certain natural generating functions associated to trees.

Rigidification of dendroidal infinity-operads

We give an explicit description of the rigidification of an $\infty$-operad as a simplicial operad. This description is based on the notion of dendroidal necklace, extending work of Dugger and Spivak from the categorical context to the operadic context, although with a different framework, which relates constructions involving necklaces to a standard factorization of maps in the category of trees.

Vegetation analysis of karst in Padjadjaran University Campus area Cintaratu, Pangandaran, West Java

Abstract. Nasrudin A, Parikesit. 2020. Vegetation analysis of karst in Padjadjaran University Campus Area Cintaratu, Pangandaran, West Java. Pros Sem Nas Masy Biodiv Indon 6: 468-475. The research carried out was an analysis of karst vegetation in the category of seedlings, saplings, poles, and trees in the campus area of Padjadjaran University Cintaratu, Pangandaran, West Java. This study aimed to determine the species composition and vegetation structure and plant species diversity in the campus area of Padjadjaran University Cintaratu, Pangandaran. The research method used was a squared line method, with a measurement plot of 20 m x 20 m for category data of trees, 10 m x 10 m plot size for poles, 5 m x 5 m plot for saplings, and sample plots measuring sized 2 m x 2 m for data of seedlings. The physical data that measured were temperature, humidity, soil pH, and soil moisture. Data analysis was carried out by using vegetation analysis method to calculate frequency, density, dominance, relative frequency, relative density, relative dominance, Important Value Index (INP), Shannon-Wienner diversity index (H'), and evenness index (E). The results showed there were 32 types of plants from 16 families, namely 14 types in seedlings, 15 types of saplings, 24 types of poles, and 6 types of trees. The highest Important Value Index in the research transect was coconut (Cocos nucifera) by 188.2% in the tree category, the pole category of albasiah (Albizia chinensis) by 58.9%, the sapling category of albizia (Albizia chinensis) by 87.07%, and the seedling category of Ficus septica by 83.95%.

ТЕПЛОТВОРНАЯ СПОСОБНОСТЬ ПОСТПИРОГЕННОЙ ДРЕВЕСИНЫ СОСНЫ

The forests of the North are characterized by frequent exposure to ground fires. The study of wood qualities at the burnt areas for its rational use is relevant. The aim of the study was to study the calorific value of Scots pine after a ground fire. The studies were conducted in the Permilovsk, Unsk and Obozersk forest districts of the Arkhangelsk region from 2016-2018. The fire duration in the studied areas was 3-8 years. The calorific value of pine wood in an absolutely dry state was determined using an ABK-1V automated bomb calorimeter. The calorific value of pine wood of post-pyrogenic stands averages from 21,389 J/g to 22,452 J/g. In post-pyrogenic stands, the calorific value of pine soundwood is significantly higher (1331 J/g) compared to sapwood. In pine trees that have dried up after a ground fire and in viable trees that are susceptible to 1-2 stages of decay, the calorific value of wood is at the level of healthy trees. It is 21,182 — 22,590 J/g and 21,521 — 22,394 J/g, respectively. However, sapwood for this category of trees has lower values of 19,648 — 19,873 J/g. The average calorific value of pine wood in plantations not damaged by fires is lower by 658 — 1,721 J/g in comparison with post-pyrogenic ones. For the first time, data on the calorific value of post-pyrogenic wood of trees of different status categories were obtained for the north of the Arkhangelsk region. The calorific value of post-pyrogenic pine wood of different categories of state is characterized by increased values. It allows it to be used as raw material for biofuel.

Above-ground carbon stock at Kamojang Regions, West Java, Indonesia

Abstract. Kuncoro DD, Husodo T, Kusmoro J, Hendrawan R, Suroso, Afriyanti F, Megantara EN. 2020. Above-ground carbon stock at Kamojang Regions, West Java, Indonesia. Biodiversitas 21: 1749-1754. Kamojang is one of the regions that have the potential for carbon dioxide (CO2) sequestration and carbon storage for the southern side of West Java Province, Indonesia. The existence of vegetation as a provider of ecological services in the form of carbon dioxide (CO2) absorption and carbon storage certainly has a very important role, either in living conditions (biomass) or dead conditions (necromass). The aims of this study are to determine the total amount of above-ground carbon stock and determine the type of land-use that has the greatest carbon storage potential in the Kamojang region. Data collection in this research combines destructive and non-destructive methods. The measurement of biomass was carried out by the non-destructive sampling method for the category of sapling, poles, trees and necromass and the destructive sampling method for the category of undergrowth and litter. The results showed total above-ground carbon stored in Kamojang area is 4,995.75 t C with the largest potential value of carbon stock in the pine production forest of 163.79 t C/ha.

Influence of low fire on condition of pine plants

Fires have caused significant damage since ancient times, and over time the area and damage has increased. Pine plantations in the southern and eastern regions of Ukraine are particularly affected by this natural phenomenon. The damage caused by the fire interrupts the course of natural successions and prolongs the period of climax. In order to assess the impact of persistent grassroots fire on the complex of forestry and taxation indices of plantations, the taxation structure of pine plantations and the impact on phytocenoses, a methodical analysis of plantations in the Skripayivsky forestry of the state enterprise «Skripayevsky Educational Research Forestry» was made. The data of forest fires over the last 30 years have been analyzed and the reconnaissance works have been carried out, the characteristic test areas have been selected and monitored over the three years. As a result of the work, the relationship between the height of the slope and the intensity of drying was observed. It has been observed that the mass drying of trees does not occur in the first year, but within three years. Also noted was a certain category of trees that appeared to be more resistant to the negative effects of fire, characterized by the following characteristics: thick, dense, high raised bark, well cleared of branches of tree trunks, diameter above average, high raised crown. This factor should be taken into account when creating forest crops (use quality planting material and the introduction of deciduous trees), carrying out further planting care (timely care of forest crops and the required intensity) and carrying out fire prevention measures (raising crowns, mineralization and mineralization breaks). Based on these observations, it is possible to predict the state of planting after a fire, depending on the intensity of the fire (altitude and the degree of burning of the litter) and take into account when conducting forestry activities.