Classification Of Species Research Articles

Viral metagenomics combined with non-targeted serum metabolomics reveals the role of enteroviruses in a mouse model of coronary heart disease

BackgroundCoronary heart disease (CHD) is a common cardiovascular disease that is associated with altered gut microbiota. Enteroviruses, an essential component of the gut microbiome, may play an important role in disease progression. However, the relationship between enteroviruses and CHD remains unclear. The development of high-throughput sequencing technologies has facilitated research on the interconnections between viruses and disease-related metabolites.Methods and resultsMice were fed a high-fat diet (CHD group) or chow diet (Sham group) for 12 weeks, and ligation of the left anterior descending coronary artery was performed at the end of week 8. After 4 weeks, all animals were euthanised. Subsequently, the animals were evaluated for basic haemato-biochemical parameters and cardiac function, and aorta staining was performed. Based on enteroviral metagenomics and serum UPLC–MS/MS metabolomics analyses, we evaluated the association between enteroviral groups and serum metabolites of CHD mouse model. A high-fat diet and coronary ligation enabled the establishment of the CHD mouse model. Notably, the enterovirus spectrum of the sham group was significantly different from that of the CHD group, with 24 viral communities of different family and species classification, such as Tsarbombavirus, Mingyongvirus, Claudivirus, and Firehammervirus, exhibiting significant differences. In addition, 731 Differential metabolites were detected in the serum of both groups of mice. Correlation network analysis revealed a close relationship between various metabolites related to lipid metabolism and different viruses, including Tsarbombavirus, Mingyongvirus, Claudivirus, and Firehammervirus.ConclusionsAn animal model of CHD, characterised by lipid disturbance and myocardial ischaemia, was established using a high-fat diet and ligation of the left anterior descending branch of the coronary artery. Tsarbombavirus, Firehammervirus, Mingyongvirus, and Claudivirus were associated with metabolites in the lipid metabolism pathway. The results indicate that Tsarbombavirus may be the main genus interacting with CHD-related metabolites in mice. Conclusively, the findings of our study provide novel insights into the potential relationship enterovirus groups and metabolites associated with CHD.

Comparison of Algorithms and Optimal Feature Combinations for Identifying Forest Type in Subtropical Forests Using GF-2 and UAV Multispectral Images

The composition and spatial distribution of tree species are pivotal for biodiversity conservation, ecosystem productivity, and carbon sequestration. However, the accurate classification of tree species in subtropical forests remains a formidable challenge due to their complex canopy structures and dense vegetation. This study addresses these challenges within the Jiangxi Lushan National Nature Reserve by leveraging high-resolution GF-2 remote sensing imagery and UAV multispectral images collected in 2018 and 2022. We extracted spectral, texture, vegetation indices, geometric, and topographic features to devise 12 classification schemes. Utilizing an object-oriented approach, we employed three machine learning algorithms—Random Forest (RF), k-Nearest Neighbor (KNN), and Classification and Regression Tree (CART)—to identify 12 forest types in these regions. Our findings indicate that all three algorithms were effective in identifying forest type in subtropical forests, and the optimal overall accuracy (OA) was more than 72%; RF outperformed KNN and CART; S12 based on feature selection was the optimal feature combination scheme; and the combination of RF and Scheme S12 (S12) yielded the highest classification accuracy, with OA and Kappa coefficients for 2018-RF-S12 of 90.33% and 0.82 and OA and Kappa coefficients for 2022-RF-S12 of 89.59% and 0.81. This study underscores the utility of combining multiple feature types and feature selection for enhanced forest type recognition, noting that topographic features significantly improved accuracy, whereas geometric features detracted from it. Altitude emerged as the most influential characteristic, alongside significant variables such as the Normalized Difference Greenness Index (NDVI) and the mean value of reflectance in the blue band of the GF-2 image (Mean_B). Species such as Masson pine, shrub, and moso bamboo were accurately classified, with the optimal F1-Scores surpassing 89.50%. Notably, a shift from single-species to mixed-species stands was observed over the study period, enhancing ecological diversity and stability. These results highlight the effectiveness of GF-2 imagery for refined, large-scale forest-type identification and dynamic diversity monitoring in complex subtropical forests.

Identification and Full-Length Sequence Analysis of a Novel Recombinant Goat Astrovirus Genotype in Guangxi, China.

Astroviruses are single-stranded, positive-sense RNA viruses capable of infecting humans as well as a wide range of mammalian and avian species, with a length of approximately 6.6-7.7 kb. In this study, 139 goat fecal samples collected from the Guangxi province were used for the RT-PCR detection, and two of these were positive for goat astrovirus, with a positivity rate of 1.44% (2/139). The complete genome sequence of an astrovirus strain and the partial genome sequence of a strain astrovirus, named GX WZ 2023 and GX HC 2023, were amplified and sequenced, and their sequence lengths were 6284 nt and 6213 nt, respectively. Among them, the capsid protein of goat astrovirus GX HC 2023 showed the highest amino acid identity of 95.9% with ovine astrovirus GX, which belonged to the MAstV-2 genotype. However, the closest relative of the GX WZ 2023 strain was found to be the caprine astrovirus Sichuan, with a nucleotide sequence identity of 76.8%. The ORF1ab nonstructural protein of this strain showed the highest amino acid identities of 89.2 and 95.8% with the ovine astrovirus S5.1 and caprine astrovirus G5.1 strains, respectively. However, its ORF2 capsid protein has 68.4% amino acid identity with the bovine astrovirus (BAstV) 16 2021 CHN strain and only 21.9-64% amino acid identity with all available strains of goat astrovirus. The GX WZ 2023 strain was recombined with the Chinese (BAstV 16 2021 CHN) and Japanese bovine strains (BAstV JPN 2015) in the ORF2 region. Therefore, the goat astrovirus GX WZ 2023 is proposed as a new member of the family goat astroviridae based on the species classification criteria of the International Committee on Taxonomy of Viruses. These findings enhance our understanding of the prevalence and genetic evolution of goat astrovirus and provide a scientific basis for future studies of these viruses in other animals.

Mapping tree species of wetlands using multispectral images of UAVs and machine learning: A case study of the Dong Rui Commune

Wetlands provide resources, regulate the environment, and stabilize shorelines; however, they are among the most vulnerable ecosystems in the world. The classification of mangrove species allows the determination of the habitat of each species, thereby serving as a basis for determining protection solutions and planning plans for mangrove conservation and restoration according to each environmental condition. We used Phantom 4 multispectral unmanned aerial vehicles (UAVs) to collect data from wetland areas in the Dong Rui Commune, which is one of the most diverse and valuable wetland ecosystems in northern Vietnam. A tree-species classification map was constructed through a combination of the object-based image analysis method and spectral reflectance values of each plant species, and the characteristic distributions of mangrove plants, including Bruguiera gymnorrhiza, Rhizophora stylosa, and Kandelia obovata, were determined with an overall accuracy of 91.11 % and a kappa coefficient (K) of 0.87. The overall accuracy for Rhizophora stylosa was the highest (94.23 %), followed by Kandelia obovata (93.61 %) and Bruguiera gymnorrhiza (85.50 %). An experiment was conducted to map plant taxonomy in the same area based only on a graph of spectral reflectance values at five single-spectral bands, and normalized difference vegetation index values were constructed, resulting in an overall accuracy of 78.22 % and a K of 0.67. The constructed map is useful for classifying, monitoring, and evaluating the structure of each group of mangroves, thereby serving as a basis for determining the distribution of each mangrove species according to natural conditions and contributing to the formulation of policies for afforestation and mangrove conservation in Dong Rui commune.

Gut microbiota affects the activation of STING pathway and thus participates in the progression of colorectal cancer

BackgroundMore and more studies showed that gut microbiota was closely related to the development of colorectal cancer (CRC). However, the specific pathway of gut microbiota regulating CRC development is still unknown.MethodsWe collected fecal samples from 14 CRC patients and 20 normal volunteers for 16 S sequencing analysis. At the same time, 14 CRC patients’ tumors and their adjacent tissues were collected for the detection of STING pathway related protein level. Mice were injected with azoxymethane (AOM) to establish an animal model of CRC, and antibiotics were given at the same time to evaluate the influence of gut microbiota on STING pathway and whether it was involved in regulating the tumor development of CRC mice.ResultsThe sequencing results showed that compared with the normal group, the gut microbiota gut microbiota of CRC patients changed significantly at different species classification levels. At the level of genus, Akkermansia, Ligilactobacillus and Subdoligranulum increased the most in CRC patients, while Bacteroides and Dialister decreased sharply. The expression of STING-related protein was significantly down-regulated in CRC tumor tissues. Antibiotic treatment of CRC mice can promote the development of tumor and inhibit the activation of STING pathway.ConclusionGut microbiota participates in CRC progress by mediating STING pathway activation.

OMSACC-SGRAN: an implementation of hybrid Optimized Multi-Scale Atrous Convoluted CNN with Self Guided Residual Attention Network for fish species classification

OMSACC-SGRAN: an implementation of hybrid Optimized Multi-Scale Atrous Convoluted CNN with Self Guided Residual Attention Network for fish species classification

Development of an Image Recognition System Based on Neural Networks for the Classification of Plant Species in the Amazon Rainforest, Peru, 2024

Introduction: The recognition and classification of plant species in the Amazon Rainforest is crucial for biodiversity conservation and ecological research. This study presents the development of an image recognition system based on neural networks for the classification of plant species in the Amazon Rainforest, Peru, 2024.Objective: Create an efficient model that can identify and classify various plant species from images, thus improving current methods of cataloging and studying Amazonian flora.Methodology: The methodology includes collecting a large dataset of plant images, followed by rigorous preprocessing to normalize and augment the data. A convolutional neural network (CNN) was designed and trained using advanced machine learning techniques, and its performance was evaluated using metrics such as precision, recall and F1-score.Results: The results show that the developed model achieves an accuracy of 92%, surpassing traditional methods and some previous models in the literature. This high precision suggests that the system can be a valuable tool for researchers and conservationists in the Amazon Rainforest.Conclusion: This study demonstrates the effectiveness of neural networks in the classification of plant species and highlights their potential to contribute significantly to the conservation and study of biodiversity in the Amazon region.

Temporal Transferability of Tree Species Classification in Temperate Forests with Sentinel-2 Time Series

Detailed information on forest tree species is crucial to inform management and policy and support environmental and ecological research. Sentinel-2 imagery is useful for obtaining spatially explicit and frequent information on forest tree species due to its suitable spatial, spectral, and temporal resolutions. However, classification workflows often do not generalise well to time periods that are not seen by the model during the calibration phase. This study investigates the temporal transferability of dominant tree species classification. To this end, the Random Forest, Support Vector Machine, and Multilayer Perceptron algorithms were used to classify five tree species in Flanders (Belgium) with regularly spaced Sentinel-2 time series from 2018 to 2022. Cross-year single-year input scenarios were compared with same-year single-year input scenarios to quantify the temporal transferability of the five evaluated years. This resulted in a decrease in overall accuracy between 2.30 and 14.92 percentage points depending on the algorithm and evaluated year. Moreover, our results indicate that the cross-year classification performance could be improved by using multi-year training data, reducing the drop in overall accuracy. In some cases, gains in overall accuracy were even observed. This study highlights the importance of including interannual spectral variability during the training stage of tree species classification models to improve their ability to generalise in time.

Assembly and comparative analysis of the complete mitochondrial genome of Vaccinium carlesii Dunn

Vaccinium L. is an important fruit tree with nutritional, medicinal, and ornamental values. However, the mitochondrial (mt) genome of Vaccinium L. remains largely unexplored. Vaccinium carlesii Dunn is an endemic wild resource in China, which is crucial for blueberry breeding. The V. carlesii mt genomes were sequenced using Illumina and Nanopore, which total length was 636,904 bp with 37 protein coding genes, 20 tRNA genes, and three rRNA genes. We found four pairs of long repeat fragments homologous recombination mediated the generation of substructures in the V. carlesii mt genome. We predicted 383 RNA editing sites, all converting cytosine (C) to uracil (U). According to the phylogenetic analysis, V. carlesii and V. macrocarpon of the Ericaceae exhibited the closest genetic relationship. This study provides a theoretical basis for understanding the evolution of higher plants, species classification and identification, and will also be useful for further utilization of Vaccinium germplasm resources.

Attributive analysis of the anthropophytes fraction as part of the urban flora of Kyiv urban area (the degree of naturalization, invasive status, threat assessment for local ecosystems and biotic diversity)

International ecological scientific community pays special attention to urbanized territories as separate locations of alien invasive species of biota. The results of the attributive analysis of the structure of the alien fraction of KUA flora according to three current European categories are presented. The basis of the analysis is the final list of alien vascular plants of KUA flora, which contains 718 species. 166 taxa of alien vascular plants that immigrated to KUA from 2003 to 2023 were added to the list. It was found that the degree of naturalization of immigrant species is dominated by casual alien species, which make up 59.0% of the taxonomic composition of the fraction. Species that are elements of man-make environments reach 35.5%. At the same time, alien species that grow and persist for a long time in natural habitats, including protected areas, do not exceed 5.0%. According to the categories of invasive activity, there are species that are naturalized and do not show a tendency to invasions — 32.0%. The most dangerous among invasive plants are transformer species, represented by 2.5%, actual invasive species — 4.0%, potentially invasive species — 2.0%. Based on the «Classification of alien species according to their impact on the environment», adapted by the IUCN: the massive impact is 1.5% of the total number and 4.0% of the number of naturalized ones; accordingly, the major impact — 2.2% (5.4%); the moderate impact — 5.2% (11.2%); the minor impact — 28.1% (68.6%); the minimal impact — 4.2% (10.8%). Based on the results of screening the negative effects of invasive species on the environment, examples of threats are given. This is competition for natural resources, displacement of native plant species; penetration into forests of plants whose climamorphotypes are absent in local forest ecosystems (tree vines), etc. Threatening cases of spontaneous hybridization of immigrant species with local species and with each other have been identified (repeated occurrences in the genera Bidens L., Populus L., Reynoutria Houtt., etc.). The need for an experimental study of the chemical and physical negative effects of invasive plants on local species of biota and human health is indicated. It is noted that the flora of KUA, on the background of the flora of Europe, is currently uniformly affected by phytoinvasions as an urbanized spatial unit of Ukraine.

Identification of dominant tree species based on Resource-1 02D hyperspectral image data

Fine-grained classification of tree species by using high-spectral image data has garnered considerable attention from scholars. In this study, through field measurements from Maguan County, Wenshan Prefecture, Yunnan Province, China, high-spectral image data from the Chinese Resource-1 02D satellite were used as the data source. Various analyses were conducted on the original image’s spectral curve, the spectral curve after envelope removal, the spectral curve after first-order differential transformation, and the spectral curve after second-order differential transformation. A spectral angle mapping classification method was employed to classify and identify four dominant tree species in Maguan County, and the accuracy of the classification results was validated using a confusion matrix. Results indicate that the highest accuracy in tree species classification was achieved when first-order differential transformation and envelope removal were used for the spectral curve; the overall accuracy exceeded 95%, and the kappa value was approximately 0.95. The classification results for the spectral curve after second-order differential transformation were the lowest, with an overall accuracy of 81.69% and a kappa value of 0.76. This research demonstrates that applying first-order differential transformation or envelope removal in combination with spectral angle mapping classification considerably reduces data processing time and improves tree species classification accuracy.

Factors Influencing Endangered Marine Species in the Mediterranean Sea: An Analysis Based on IUCN Red List Criteria Using Statistical and Soft Computing Methodologies

The Mediterranean Sea is the second largest biodiversity hotspot on earth, with over 700 identified fish species is facing numerous threats. Of more than 6000 taxa assessed for the IUCN Red List, a minimum of 20% are threatened with extinction. A total of eight key factors that affect vulnerability of marine fish species in the Mediterranean Sea were identified using the scientific literature and expert-reviewed validated databases. A database of 157 teleost fish species with threat status ranging from least concern to critically endangered was compiled. Nominal logistic curves identified the factor thresholds on species vulnerability, namely, age at maturity, longevity, and asymptotic length at 8.45 years, 36 years, and 221 cm, respectively. A second-degree stepwise regression model identified four significant factors affecting the threat category of Mediterranean fish species, namely, overfishing, by-catch, pollution, and age at maturity according to their significance. Predictive analysis using supervised machine learning algorithms was further employed to predict the vulnerability of Mediterranean marine fish species, resulting in the development of a framework with classification accuracy of 87.3% and 86.6% for Support Vector Machine (SVM) and Gradient Boosting machine learning algorithms, respectively, with the ability to assess the degree of variability using limited information.

Rapid Classification and Differentiation of Sepsis-Related Pathogens Using FT-IR Spectroscopy.

Sepsis is a life-threatening condition arising from a dysregulated host immune response to infection, leading to a substantial global health burden. The accurate identification of bacterial pathogens in sepsis is essential for guiding effective antimicrobial therapy and optimising patient outcomes. Traditional culture-based bacterial typing methods present inherent limitations, necessitating the exploration of alternative diagnostic approaches. This study reports the successful application of Fourier-transform infrared (FT-IR) spectroscopy in combination with chemometrics as a potent tool for the classification and discrimination of microbial species and strains, primarily sourced from individuals with invasive infections. These samples were obtained from various children with suspected sepsis infections with bacteria and fungi originating at different sites. We conducted a comprehensive analysis utilising 212 isolates from 14 distinct genera, comprising 202 bacterial and 10 fungal isolates. With the spectral analysis taking several weeks, we present the incorporation of quality control samples to mitigate potential variations that may arise between different sample plates, especially when dealing with a large sample size. The results demonstrated a remarkable consistency in clustering patterns among 14 genera when subjected to principal component analysis (PCA). Particularly, Candida, a fungal genus, was distinctly recovered away from bacterial samples. Principal component discriminant function analysis (PC-DFA) allowed for distinct discrimination between different bacterial groups, particularly Gram-negative and Gram-positive bacteria. Clear differentiation was also observed between coagulase-negative staphylococci (CNS) and Staphylococcus aureus isolates, while methicillin-resistant S. aureus (MRSA) was also separated from methicillin-susceptible S. aureus (MSSA) isolates. Furthermore, highly accurate discrimination was achieved between Enterococcus and vancomycin-resistant enterococci isolates with 98.4% accuracy using partial least squares-discriminant analysis. The study also demonstrates the specificity of FT-IR, as it effectively discriminates between individual isolates of Streptococcus and Candida at their respective species levels. The findings of this study establish a strong groundwork for the broader implementation of FT-IR and chemometrics in clinical and microbiological applications. The potential of these techniques for enhanced microbial classification holds significant promise in the diagnosis and management of invasive bacterial infections, thereby contributing to improved patient outcomes.

Remote Sensing Classification and Mapping of Forest Dominant Tree Species in the Three Gorges Reservoir Area of China Based on Sample Migration and Machine Learning

Remote Sensing Classification and Mapping of Forest Dominant Tree Species in the Three Gorges Reservoir Area of China Based on Sample Migration and Machine Learning

Data homogeneity impact in tree species classification based on Sentinel-2 multitemporal data case study in central Sweden

ABSTRACT Spatial information on forest composition is invaluable for achieving scientific, ecological, and management objectives and for monitoring multiple changes in forest ecosystems. The increased flow of optical satellite data provides new opportunities to improve tree species mapping. However, the accuracy of such maps is affected by training data, and in particular on the homogeneity of individual classes. Thus, we evaluated the effect of data homogeneity in tree species classification. We performed tree species classification by considering different ways to partition data into tree species classes. The class sets considered were (i) only mixed coniferous and mixed deciduous forest classes, (ii) single-species classes, (iii) single-species, mixed coniferous and mixed deciduous classes, and (iv) single-species, mixed coniferous and mixed deciduous classes and a true mixed class. Using data from the Swedish National Forest Inventory, we varied the threshold that defined dominating species. Tree species were classified for a study area in central Sweden using Sentinel-2 data and two classification approaches: Bayesian inference and random forest (RF). Images were selected by class separability and the most informative images based on variable selection with RF. The most informative images tended to be selected by both methods. However, in forests with tree species of similar spectral behaviour, image selection on the basis of class separability was found to be more reliable. More accurate classification results were achieved as the number of classes decreased and the threshold of plot purity increased. The Bayesian classification approach of only mixed coniferous and mixed deciduous classes gave the highest OA, always greater than 90%. When discriminating between pure plots of Birch (Betula spp.), Spruce (Picea abies), Scots pine (Pinus sylvestris) and Lodgepole pine (Pinus contorta), the best OA values were 84% for Bayesian and 80% for RF. In more complicated scenarios, RF resulted in higher overall accuracies (OA).

Mitochondrial Genome Characteristics Reveal Evolution of Acanthopsetta nadeshnyi (Jordan and Starks, 1904) and Phylogenetic Relationships.

In the present study, the mitochondrial genomic characteristics of Acanthopsetta nadeshnyi have been reported and have depicted the phylogenetic relationship among Pleuronectidae. Combined with a comparative analysis of 13 PCGs, the TN93 model was used to review the neutral evolution and habitat evolution catalysis of the mitogenome to verify the distancing and purification selectivity of the mitogenome in Pleuronectidae. At the same time, a species differentiation and classification model based on mitogenome analysis data was established. This study is expected to provide a new perspective on the phylogenetic relationship and taxonomic status of A. nadeshnyi and lay a foundation for further exploration of environmental and biological evolutionary mechanisms.

Assemble and comparative analysis of the mitochondrial genome of Rhododendron delavayi: Insights into phylogenetic relationships and genomic variations

Rhododendron delavayi, a notable ornamental plant primarily found in regions of China like Yunnan and Guizhou provinces, holds substantial horticultural value. To elucidate the systematic phylogenetic relationships and organelle genomic differences within R. delavayi and related Rhododendron species, we conducted sequencing and assembly of the complete mitochondrial genome of R. delavayi. The full-length mitochondrial genome of it was a singular circular molecule spanning 1,009,263 bp, comprising 53 protein-coding genes, including 18 transfer RNA (tRNA) genes, 3 ribosomal RNA (rRNA) genes, and 32 protein-coding genes. A total of 1,182 simple sequence repeats (SSRs) loci were identified in the R. delavayi mitochondrial genome, primarily consisting of single nucleotide, dinucleotide, and trinucleotide repeats. Nucleotide diversity analysis highlighted five genes (atp6, atp9, cox2, nad1, and rpl10) with the highest diversity within the mitochondrial genomes of Rhododendron genus. Comparative analysis of the mitochondrial genome of R. delavayi with those of four other Rhododendron species indicated complex rearrangements in 21 genes, including rps4, nad6, rps3, atp6, cob, atp9, nad7, among others. The mitochondrial phylogenetic tree revealed a close relationship between R. delavayi and R. decorum, forming a sister clade to R. × pulchrum and R. simsii. Furthermore, 126 plastid-to-mitochondrial gene transfers in R. delavayi were identified, ranging from 30 bp to 19,385 bp. These fragments collectively constituted 47.54 % and 9.52 % of the chloroplast and mitochondrial genomes (202,169 bp), respectively. Complex mitochondrial-to-mitochondrial transfers were also observed, with 843 identified fragments totaling 312,036 bp (30.92 % of the mitochondrial genome). Segments exceeding 10 kb may mediate homologous recombination within the mitochondrial molecules. Remarkably, our study underscores that the mitochondrial genome of R. delavayi was the largest reported within the Rhododendron genus to date. The intricate rearrangements observed in the mitochondrial genomes of Rhododendron species, alone with the identification of five potential molecular marker sites, provided valuable insights for species classification and parentage identification within the Rhododendron genus.

Description of Aphelenchoides yixingensis n. sp. (Tylenchina: Aphelenchoididae) found in Pinus massoniana from China, and proposal for genus Ptychaphelenchus as a synonym of Aphelenchoides

Summary Aphelenchoides yixingensis n. sp. found in Chinese red pine (Pinus massoniana) in Yixing city, Jiangsu Province, P.R. China, is described. It is characterised by a very slim body (a = 50.8 (41.3-63.8) and 49.3 (42.3-55.1) for males and females, respectively), three (occasionally five) lateral lines in the lateral field, a short stylet (9-12 μm), the excretory pore located at the level of nerve ring, the vagina is not sclerotised and the vulva has slightly protruding lips and lacks a flap, the post-uterine sac is well developed and forms ca 29.0% (24.1-34.1%) of the vulva to anus distance. The spicules are smoothly arcuate, the apex and rostrum rounded and short, and the dorsal limb is 20.5 (16.9-22.2) μm long, the distal end bluntly rounded. Spicule sheath-like structure is present, triangular and outstretched when heat-killed in some individuals. The male tail bears three pairs (2 + 2 + 2) of caudal papillae. The tail of both sexes is sub-cylindrical, the terminus bearing a bluntly pointed mucron with tiny nodular protuberances, mainly at the distal part. The new species belongs to the Group 2 category of Aphelenchoides species sensu Shahina and is defined as A2-B1-C1-D1-E2-F2 according to the categorisation codes of OEPP/EPPO. Phylogenetic analysis based on 18S and 28S D2-D3 of rDNA, along with ITS and mtCOI, confirmed its status as a new species. A proposal for genus Ptychaphelenchus as a synonym of Aphelenchoides is also discussed.

Integrative studies of Microtus hartingi and Microtus guentheri (Cricetidae, Arvicolinae) and taxonomic problem of Microtus elbeyli

In this study, Taxonomic differences between Microtus guentheri and Microtus hartingi, which are similar in terms of external morphological features, were determined using linear morphometric, geometric morphometric, karyological and molecular analyses methods. Through classical morphometric (mean values) and geometric morphometric analyses of craniodental and mandible characters, influenced by various genetic, developmental, and functional processes, it was found that M. hartingi and M. guentheri exhibited notable differences in both mean linear measurements and shape. The Jackknife in classical morphometric analyses of samples, which underwent molecular and karyological species diagnoses, was higher than 88 % for each character. In geometric morphometric analyses, the Procrustes distance for shape follows the order Ventral < Dorsal < Mandible < M3<M2<M1. Based on cross-validation, the accurate classification rate is between 73 and 100 %. In both mean linear measurements and centroid size, M. hartingi specimens exhibited significantly larger mandibles and craniodentals compared to individuals of M. guentheri. According to PLS results, there was a significant relationship between the shape of M1, M2 and M3 and environmental variables, while the relationship between their size and environmental variables was not significant. However, neither the shape nor the size of the other parts had an sufficient relationship with environmental variables. Both species exhibited karyological similarity with a chromosome number of 2n = 54, but display polymorphism in chromosome arm number. There were differences in the C-banding of autosomal chromosomes and X chromosome. The classification of species in classical and geometric morphometric analyses, diverges from the outcomes of karyological and molecular assessments. In both species, the intraspecific genetic distance remained below 1.35 %. The cyt-b exhibits significant differentiation between the two species (K2P = 6.55 %). The divergence time for M. guentheri from the clade containing M. hartingi + M. qazvinensis + Microtus dogramacii was estimated to be 0.73 million years ago. Since no sample of Microtus elbeyli with karyological and cyt-b characteristics was found in the samples taken from the type locality, the taxonomic status of M. elbeyli remains unclear.

Epigeic spider and ground beetles (Carabid) communities of semi-natural and natural habitats in agricultural landscape in Slovakia

Abstract We studied the spatial structure of spiders and beetles in 4 types of habitats in the Poloniny National Park. Between the years 2020 and 2021, we recorded 1,597 beetle specimens and 3,765 spider specimens using the pitfall trap method. The most represented beetles were Poecilus versicolor (53.4%), Nebria brevicollis (10.3%), Staphylinus caesareus (4.4%) and Amara familiaris (4.1%). Among the spiders, there were species Pardosa pullata (21.81%), Pachygnatha degeeri (14.21%), Xerolycosa nemoralis (10.28%), Pardosa palustris (7.86%), Trochosa ruricola (6.24%) and Alopecosa pulverulenta (4.38%). We confirmed the occurrence of two European important species of beetles (Carabus zawadzkii, Carabus variolosus) and 3 species of spiders belonging to the vulnerable species according to the IUCN threat status (Gongylidiellum vivum, Palliduphantes milleri and Xysticus lineatus). We also found the spider Micaria micans, which is new to the Slovak fauna and information about its distribution and habitat preferences in Slovakia is presented. Using multivariate analyzes (CCA, RDA) and classification species into bioindicative groups, we found a greater connection of adaptable and eurytopic species of ground beetles to the mesophilic meadow and of spiders to the habitat Nardetum pasture. Based on bioindicative groups of species (adaptable, eurytopic and relict), we found only a small difference in percentile points between spiders and beetles.