Biomass and mortmass of woody vegetation in metal-contaminated areas (Southern Urals, Russia)

Since the mid-2000s, long-term monitoring of various components of natural ecosystems under conditions of industrial pollution has been carried out in the Southern Urals. As a part of these monitoring programmes, the data on various components of biota in different biotopes, collected with different methods and in different time intervals, continue to be gathered. In addition, data collected through these monitoring programmes can also be used to study the local biodiversity of non-polluted areas. In 2012, in the vicinity of the Karabash Copper Smelter, a study of communities of small mammals was carried out, considering the heterogeneity of their habitats. Within the framework of this project, we presented a detailed description of the state of woody vegetation in the study area. The dataset (available from the GBIF network at https://www.gbif.org/dataset/61384edd-2d0a-437b-8cf0-ff4d2dfcc0da) includes the results of an assessment of the woody vegetation biomass at seven habitats (pine, birch and floodplain forests, reed swamp, sparse birch stand, marshy meadow and dump of household waste) of areas with different levels of industrial pollution in the vicinities of the Karabash, the Southern Urals. Karabash Copper Smelter (KCS) is one of Russia’s most significant point polluters; the main components of its emissions are heavy metals, dust and sulphur dioxide. Parameters of woody vegetation (diameter at breast height, diameter at root collar level and biomass) were estimated for seven forest elements (forest stand, subcanopy (undergrowth and underwood), half-dead tree of a forest stand and four types of coarse woody debris (downed bole, fragment of downed bole, standing dead tree and stump)) at 41 sampling plots (20 at unpolluted and 21 at polluted areas) and 165 subplots (81 and 84, respectively). The dataset includes 411 sampling events (estimation events of the forest elements at sampling plots and subplots), corresponding to 5786 occurrences (estimations of the woody vegetation components) observed during July 2012. For most woody vegetation components (72%), an estimate of the above-ground phytomass is given. For each sampling event, information on the presence or absence of woody vegetation species at the considered habitats is provided (a total of 1479 occurrences with status "absent"). The dataset can be used for environmental monitoring, sustainable forest management, modelling forest productivity considering global changes, studying the structure and biodiversity of forest cover and assessing forests’ carbon-sequestration capacity. In addition, the dataset provides information about different forest ecosystems under the influence of strong industrial pollution.

Comparison of optical coherence tomography angiography features in type 1 versus type 2 choroidal neovascular membranes secondary to age-related macular degeneration

Background: Optical coherence tomography angiography (OCTA) is an advanced imaging modality that provides high resolution images at the level of different retinal layers. This study aime to evaluate choroidal neovascular membranes (CNVMs) secondary to age-related macular degeneration (AMD) quantitatively and qualitatively, according to their classification, morphological features, and flow areas, using OCTA. Methods: In this descriptive, comparative, cross-sectional study, CNVMs were divided into 2 groups according to their classification as type 1 or type 2 neovascularization. Mixed CNVMs were excluded from the study. The size (mm2) and the flow area (mm2) of the CNVMs were calculated via OCTA and the presence of the perivascular halo and loop anastomoses were analyzed. The morphological appearance of the CNVMs were classified as: medusa, sea-fan, lacy-wheel, glomerular, dead tree, and mature vascular networks. Results: Of the 85 eyes assessed for eligibility, 45 eyes of 34 individuals with CNVM were enrolled in this retrospective study. Twenty-eight eyes had type 1 and 17 eyes had type 2 CNVMs. The mean size and flow area were greater in type 1 than in type 2 CNVMs (mean ± standard deviation [SD], 6.69 ± 4.54 and 3.61 ± 3.56 mm2 versus 3.04 ± 1.98 and 1.77 ± 1.62 mm2; P = 0.044 and 0.046, respectively). Among the 22 eyes with type 1 CNVMs and the 9 eyes with type 2 CNVMs, 31 eyes had exudative membranes. Among the eyes with exudative CNVMs, 22 eyes had a perivascular halo and 22 eyes had loop anastomoses; this was significantly more than in the non-exudative eyes (P = 0.042 and 0.041, respectively). The lacy-wheel (38.7%) and dead tree (71.4%) patterns were the most frequent morphological appearance of the CNVMs in the exudative and non-exudative membranes, respectively. Conclusions: OCTA provides objective documantation about CNVMs. A perivascular dark halo around CNVMs could be a criterion to define exudative membranes activity. How to cite this article: Goker YS, Demir G. Comparison of optical coherence tomography angiography features in type 1 versus type 2 choroidal neovascular membranes secondary to age-related macular degeneration. Med Hypothesis Discov Innov Ophthalmol. 2021 Summer; 10(2): 25-31. https://doi.org/10.51329/mehdiophthal1423

PENDUGAAN STOK KARBON PADA POLA TANAM AGROFORESTRI SEDERHANA DAN AGROFORESTRI KOMPLEKS DI KPH BATUTEGI, KABUPATEN TANGGAMUS

Global warming is a natural phenomenon that is currently taking place. Natural phenomena occur as a result of changing ecosystem balance. This can be minimized by adding vegetation which acts as an absorber of CO2 to convert CO2 into glucose and oxygen through the process of photosynthesis. Each type of vegetation has the potential to absorb different carbon, so this can be circumvented by using the right cropping pattern. Therefore, information about the potential for carbon stored in complex and simple agroforestry cropping patterns in KPH Batutegi is important. The purpose of this study was to analyze carbon stocks in agroforestry cropping patterns and to compare carbon stocks in simple and complex agroforestry cropping patterns in KPH Batutegi. Source of living tree biomass, dead tree biomass, understorey biomass, and litter biomass. The results showed that the carbon stored in complex agroforestry cropping patterns fell into the good category according to the Intergovermental Panel on Climate Change (IPCC). However, the stored carbon in complex agroforestry cropping patterns is greater than the stored carbon in simple agroforestry cropping patterns, namely 765.61 tonC/ha and 356.21 tonC/ha.

BURSAPHELENCHUS SPECIES (NEMATODA: APHELENCHIDA) ASSOCIATED WITH AN OLIVE TREE IN CENTRAL ITALY

Olive cultivation is of great economic, ecological, and cultural interest in Italy, as well as in the rest of the Mediterranean basin. Among the pests of olive trees, several groups of insects, mites, and nematodes have been reported. Phytoparasitic nematodes especially of the genera Meloidogyne, Pratylenchus, Helicotylenchus, Xiphinema, Tylenchulus, Rotylenchulus, and Heterodera have usually been extracted from roots and soil around trees. On the other hand, no information is available concerning nematodes directly associated with the wood. At the end of September 2018, in a high-density cultivated olive grove in Tuscany (central Italy), several olive trees with decline symptoms were observed. Three Bursaphelenchus species, B. fungivorus, B. minutus, and B. sexdentati were extracted from the wood of one dead tree. Even though these species had already been reported in Italy, these findings were the first ones recorded in olive wood. Moreover, another undescribed Bursaphelenchusspecies was found associated with the bark beetle Hylesinus fraxini collected from olive trunks and branches. Further research is needed to investigate the role of insects and Bursaphelenchus spp. in the decline processes of olive trees.

Detection and Location of Dead Trees with Pine Wilt Disease Based on Deep Learning and UAV Remote Sensing

Pine wilt disease causes huge economic losses to pine wood forestry because of its destructiveness and rapid spread. This paper proposes a detection and location method of pine wood nematode disease at a large scale adopting UAV (Unmanned Aerial Vehicle) remote sensing and artificial intelligence technology. The UAV remote sensing images were enhanced by computer vision tools. A Faster-RCNN (Faster Region Convolutional Neural Networks) deep learning framework based on a RPN (Region Proposal Network) network and the ResNet residual neural network were used to train the pine wilt diseased dead tree detection model. The loss function and the anchors in the RPN of the convolutional neural network were optimized. Finally, the location of pine wood nematode dead tree was conducted, which generated the geographic information on the detection results. The results show that ResNet101 performed better than VGG16 (Visual Geometry Group 16) convolutional neural network. The detection accuracy was improved and reached to about 90% after a series of optimizations to the network, meaning that the optimization methods proposed in this paper are feasible to pine wood nematode dead tree detection.

INVENTARISASI JAMUR MAKROSKOPIS DI HUTAN BUKIT DANAU DESA PENIRAMAN KECAMATAN SUNGAI PINYUH KABUPATEN MEMPAWAH

Macroscopic mushrooms are one of the important biodiversity in the ecosystem of forests and human life. Research related to macroscopic mushrooms in West Kalimantan has already been done, but have never done in some areas, which is in the forest of Bukit Danau Peniraman Village of Mempawah regency. This research aims to determine the types of macroscopic mushrooms that exist in the forest of Bukit Danau Peniraman Village of Sungai Pinyuh district, Mempawah regency. Sampling of fungi using exploration methods by exploring the forest according to the transect pathway. The results showed that there were 20 types of macroscopic mushrooms consisting of 5 orders, 13 families, and 17 generas. Fungi that most commonly found came from an order of Polyporales and the fewest orders are the order ofDacrymycetales, the order of Hymenochaetales, and the order of Xylariales. Macroscopic mushrooms found in the forest of Bukit Danau Peniraman Village of Sungai Pinyuh district, Mempawah regency, fungi most commonly grew at substrate of dead tree.