Classification Of Plant Communities Research Articles

Classification of plant communities in the Caspian Hyrcanian English yew (Taxus baccata L.) forests using environmental factors: testing the modified TWINSPAN method

Classification of plant communities in the Caspian Hyrcanian English yew (Taxus baccata L.) forests using environmental factors: testing the modified TWINSPAN method

Studying the vegetation impact of terrestrial ecosystems on reducing the carbon footprint in in the territory of the Russian Federation

Plant communities of terrestrial ecosystems of the Russian Federation are studied in terms of their ability to reduce the carbon footprint as a result of carbon dioxide sequestration. The classification of typical plant communities and the division of the territory depending on the climatic and regional characteristics is given, with further provision of values of the specific absorption capacity of growing plant communities according to the division presented. To assess the biomass of vegetation, as well as its dynamics of change, an analysis of the remote sensing method was carried out as the most preferred method for determining biomass in real time. The characteristics of currently used remote sensing systems, including IKONOS, Quickbird, Worldview, ZY-3, SPOT, Sentinel, Landsat and MODIS are given. The main indicators used for the indexation assessment of vegetation biomass are listed, with subsequent prediction based on them of the efficiency of carbon dioxide uptake by plant communities.

A life dedicated to the classification of neotropical plant communities: a tribute to Antoine M. Cleef

A life dedicated to the classification of neotropical plant communities: a tribute to Antoine M. Cleef

Classification of plant communities in the Caspian Hyrcanian English yew (Taxus baccata L.) forests using environmental factors: testing the modified TWINSPAN method

The purpose of this research is to evaluate the quality of the modified and classical TWINSPAN classification based on the environmental factors to identify the plant communities of Taxus baccata L. forests of Golestan Province. Fifty 400-m2 plots were systematically selected along an elevation gradient in the Taxus baccata forests. In each plot, soil was sampled using a composite sample taken to a depth of 20 cm. All vascular species were recorded on each plot according to the Braun-Blanquet’s method. In total, 56 plant species belonging to 48 genera and 34 families were recorded in spring 2018. The comparison of the results of modified and classical TWINSPAN showed that the modified TWINSPAN did not change the classification logic, but introduced more flexibility in the hierarchy of the division. It was also found that the compliance rate of the results provided by the classical TWINSPAN method was lower than the modified method. Using modified TWINSPAN, Detrended correspondence analysis (DCA), and Redundancy analysis (RDA), we determined four floristic groups in the Taxus baccata habitat. The first (Carpinus betulus) and second (Taxus baccata) groups were located at low altitudes and soil contents in silt and clay were higher than in the other groups. In contrast, the third (Quercus castaneifolia) and the fourth (Juniperus communis) groups were located next to each other at higher altitudes and southwestern aspects, on steeper slopes and soils exhibited a high pH and a high sand content. We found close relationships between the distribution of vegetation groups of Taxus baccata habitat with edaphic and physiographic factors using RDA method. To conclude, the modified TWINSPAN offers a more efficient and flexible method to identify vegetation communities. This is a first step to implement future management and ecological restoration measures in habitats of high ecological value such as yew forests.

Genus-Physiognomy-Ecosystem (GPE) System for Satellite-Based Classification of Plant Communities

Vegetation mapping and monitoring is important as the composition and distribution of vegetation has been greatly influenced by land use change and the interaction of land use change and climate change. The purpose of vegetation mapping is to discover the extent and distribution of plant communities within a geographical area of interest. The paper introduces the Genus-Physiognomy-Ecosystem (GPE) system for the organization of plant communities from the perspective of satellite remote sensing. It was conceived for broadscale operational vegetation mapping by organizing plant communities according to shared genus and physiognomy/ecosystem inferences, and it offers an intermediate level between the physiognomy/ecosystem and dominant species for the organization of plant communities. A machine learning and cross-validation approach was employed by utilizing multi-temporal Landsat 8 satellite images on a regional scale for the classification of plant communities at three hierarchical levels: (i) physiognomy, (ii) GPE, and (iii) dominant species. The classification at the dominant species level showed many misclassifications and undermined its application for broadscale operational mapping, whereas the GPE system was able to lessen the complexities associated with the dominant species level classification while still being capable of distinguishing a wider variety of plant communities. The GPE system therefore provides an easy-to-understand approach for the operational mapping of plant communities, particularly on a broad scale.

Vegetation ecology with anthropic drivers and consequences

Current research on vegetation makes a difference in people’s lives. Plant community classification is a backbone of land management, plant communities are changing in response to anthropogenic drivers, and the processes of change have impacts on ecosystem services. In the following progress report, we summarize the status of classification and recent research on vegetation responses to pollution, especially nitrogen deposition, invasive species, climate change, and land use and direct exploitation. Two areas with human feedbacks are underscored: fire ecology and urban ecology. Prominent questions at the current research frontier are highlighted with attention to new perspectives.

Classification of forest communities (co-)dominated by Taxus baccata in the Hyrcanian forests (northern Iran) and their comparison with southern Europe

English yew (Taxus baccata) is one of the few gymnospermous species present in the Hyrcanian forests, and it is listed as a rare and endangered species prone to extinction in Iran. This study aims to determine the ecological capability of Taxus baccata in the Hyrcanian region by identifying the diversity of plant communities dominated by this species, and to compare their floristic composition with the Taxus communities of southern Europe (Sicily, Corsica, Sardinia). We collected 408 releves in the central and eastern part of the Hyrcanian forests. The classification of plant communities was performed using TWINSPAN. Phi-coefficient index, constancy ratio, and the ratio of average cover were used to determine diagnostic species in each vegetation unit. The expert system language of the JUICE program was applied to create formal definitions for syntaxa. The relationship between species and environmental factors were investigated with DCA. The environmental differences among the syntaxa were also tested with one-way ANOVA. Sums of constancy and average species cover of the diagnostic species of classes according to the EuroVegChecklist were computed. We distinguished five associations within three alliances. Of these, two associations and one alliance are new for science. Annual precipitation, elevation and annual temperature which are affected by elevational as well as longitudinal gradients were found to be important factors affecting the diversity of Hyrcanian Taxus communities. The constancy sum of diagnostic species was the highest for the class Carpino-Fagetea sylvaticae in all Hyrcanian and European units except for one Taxus community in Sardinia. We conclude that the Hyrcanian and southern European Taxus communities are similar in their floristically and ecological properties. Yew communities in the central Hyrcanian forests are associated with humid temperate diagnostic species, while semi-humid temperate plants are frequent in the eastern Hyrcanian forests, similar to the yew communities in southern Europe.

Wykorzystanie zdjęć fitosocjologicznych w najnowszych badaniach środowiska przyrodniczego = The use of phytosociological relevés in recent studies of the natural environment

The aim of this work was to review the latest literature in terms of the use of phytosociological relevés (vegetation plots) in research on the natural environment. The systematic review included 321 articles published in 2010‑2021 in the most renowned journals (indexed in the Web of Science Core Collection with a score ≥100 according to the 2021 list of journals of the Poland’s Ministry of Education and Science). The research questions were: in which fields of science and practice, for what purposes and on what spatial scales the phytosociological relevés are currently used. After initial review, the articles were divided into 10 thematic groups: 1) classification of plant communities, 2) methodological studies, 3) relationship between vegetation and other elements of the environment, 4) occurrence of invasive plant species, 5) indicative role of vegetation, 6) plant communities as habitats for animals, 7) human footprint on vegetation, 8) long-term vegetation changes, 9) combining phytosociological methods with remote sensing methods, 10) social studies. The results showed that phytosociological relevés, as the method to investigate vegetation developed in the first decades of the 20th century, are still widely used in many regions of the world. The most numerous thematic group comprised articles that show how habitat conditions impact the distribution and diversity of plant species and their communities, while the least numerous – studies combining natural and social research. The vast majority of research was dedicated to environmental problems, although social and economic aspects were also present. These were both theoretical and methodological works, as well as detailed studies, which resulted in the formation of recommendations and practical guidelines for nature protection or spatial planning. Recently, relevés have been rarely used solely to distinguish and characterise plant communities, as originally intended by those who invented this method. However, thanks to modern statistical and computer tools, more and more attempts are being made to create automatic classifications with the use of artificial intelligence, e.g. neural networks. The geographic scope was usually restricted to one country (local and regional – 241 articles) or to two or more bordering countries (47). Continental (19) and global (7) studies are less common and studies within Europe prevail. It is because the discussed method was developed and is best known in Europe (Franco-Swiss Phytosociological School), and its dissemination throughout the world is only an evidence of its universality and efficiency. The recent larger-scale studies became possible mainly due to the development of transnational vegetation databases, e.g. the widely utilised European Vegetation Database – EVA.

北疆盐碱地植物群落空间分布及物种多样性

为探究盐碱地植物群落空间分布特征及群落间物种多样性的关系，根据对北疆盐碱地植物群落84个样点调查的数据，以各物种多度为指标，采用双向指示种分析方法（TWINSPAN）、除趋势对应分析法（DCA）、典范对应分析法（CCA）进行数量分类并分析群落分布与环境因子间关系和群落物种多样性及相似性变化特征。结果表明，TWINSPAN数量等级分类将84个样点的植物划分为11种类型。各群丛类型的物种多样性特征表现为群丛Ⅲ的多样性最大，群丛X多样性最小，且群丛Ⅲ多样性显著高于群丛X （P<0.05），群丛VⅡ均匀度最大，群丛X均匀度最小，且群丛Ⅲ均匀度显著高于群丛X（P<0.05），群丛I的丰富度最大，群丛X丰富度最小，且群丛I丰富度显著高于群丛X（P<0.05），在所有群丛中群丛Ⅲ所含有的植物种类最多，有26种；相似性特征为群丛V和群丛VⅡ的相似性最大，群丛V和群丛VⅡ物种间的竞争较小，群丛稳定性高；CCA排序结果表明，北疆盐碱地植物群落分布与海拔高度、多年平均温度、土壤酸碱度等因素有关，其中影响最大的是海拔高度，其次为多年平均温度、降水量、蒸发量和土壤电导率，地形因子坡度对各群丛分布影响不大；北疆盐碱地植物群落数量分类及物种多样性变化的分析对于揭示北疆盐碱地植物群落空间分布特征和新疆盐碱地植物种质资源调查及其保护具有重要的意义。;In order to explore the relationship between the spatial distribution characteristics of plant communities in saline-alkali soils and the species diversity between communities, based on the data from 84 sample surveys of saline plant communities in saline-alkali land in northern Xinjiang, using the abundance of each species as an indicator, a two-way indicator species analysis method (TWINSPAN). In addition to trend correspondence analysis (DCA) and canonical correspondence analysis (CCA), the quantitative classification and analysis of the relationship between community distribution and environmental factors, community species diversity and similarity change characteristics. The results showed that TWINSPAN quantitative classification can divide 84 plants into 11 types. The species diversity characteristics of each cluster type showed that cluster Ⅲ had the largest diversity, cluster X had the smallest diversity, and cluster Ⅲ had a significantly higher diversity than cluster X (P<0.05), cluster VⅡ had the highest uniformity, and the uniformity of cluster X was the smallest, and the uniformity of cluster Ⅲ was significantly higher than that of cluster cluster X (P<0.05), the richness of cluster cluster I was the largest, the richness of cluster cluster X was the smallest, and the richness of cluster cluster I was significantly higher than that of cluster cluster X (P<0.05), among all clusters, cluster Ⅲ contains the most species of halophytes, with 26 species; the similarity feature was that cluster V and cluster VⅡ are the most similar, and the competition between cluster V and cluster VⅡ species was relatively high small, high cluster stability. The CCA ranking results showed that the distribution of halophyte clusters in saline-alkali land in northern Xinjiang was related to altitude, average temperature, soil pH, etc. Among them, the highest impact was altitude, followed by average temperature, precipitation, evaporation, soil conductivity, and terrain factor slope has little effect on the distribution of each group. The analysis of the number classification and species diversity changes of saline-alkali soil plant communities in northern Xinjiang reveals the spatial distribution characteristics of plant communities in saline-alkali soil in northern Xinjiang: It was of great significance for the investigation and protection of plant germplasm resources in the saline-alkali soils in Xinjiang.

Mapping Wetland Plant Communities Using Unmanned Aerial Vehicle Hyperspectral Imagery by Comparing Object/Pixel-Based Classifications Combining Multiple Machine-Learning Algorithms

Understanding the spatial patterns of plant communities is important for sustainable wetland ecosystem management and biodiversity conservation. With the rapid development of unmanned aerial vehicle (UAV) technology, UAV-borne hyperspectral data with high spatial resolution have become ideal for accurate classification of wetland plant communities. In this article, four dominant plant communities (Phragmites australis, Typha orientalis, Suaeda glauca, and Scirpus triqueter) and two unvegetated cover types (water and bare land) in the Momoge Ramsar wetland site were classified. This was achieved using UAV hyperspectral images and three object- and pixel-based machine-learning classification algorithms [random forest (RF), convolutional neural network (CNN), and support vector machine (SVM)]. First, spectral derivative analysis, logarithmic analysis, and continuum removal analysis identified the wavelength at which the greatest difference in reflectance occurs. Second, dimensionality reduction of hyperspectral images was conducted using principal component analysis. Subsequently, an optimal feature combination for community mapping was formed based on data transformation (spectral features, vegetation indices, and principal components). Image objects were obtained by segmenting the optimum object feature subsets. Finally, distribution maps of communities were produced by using three machine-learning classification algorithms. Our results reveal that object-based image analysis outperforms pixel-based methods, with overall accuracies (OAs) of 80.29-87.75%; RF has the highest OA of 87.75% (Kappa = 0.864), followed consecutively by CNN (OA = 83.31%, Kappa = 0.829) and SVM (OA = 80.29%, Kappa = 0.813). Phragmites australis dominates the plant community (55.9%) at the study area, followed by Typha orientalis (16.2%), Suaeda glauca (16.2%), and Scirpus triqueter (4.6%). The results highlight the importance of spectral transformation features in red-edge regions. The mapping results will help establish basic information for subsequent studies involving habitat suitability assessment at this study site.

Научное совещание «Теоретические вопросы классификации растительных сообществ России» (Ялта, 1–3 ноября 2021 г.)

Thirty years after the publication of the USSR vegetation syntaxa prodromus (Korotkov et al., 1991), the active work on the preparation of the Prodromus of the Russian Federation vegetation (Plugatar et al., 2020) has started. 29 contributions (incl. 5 via Skype), were represented at the Workshop “Theoretical problems of the classification of plant communities of Russia”, that took place in Yalta, Republic of Crimea, on November 1–3, 2021. Twenty six scientists (Fig. 1, 2) from St. Petersburg, Moscow, Novosibirsk, Ufa, Vladivostok, Yakutsk, Syktyvkar, Bryansk, Rostov on Don, Khanty-Mansiysk, Ekaterinburg, Nalchik, Kursk, Yalta) participated this meeting. The reviews of syntaxonomic systems of forests, steppes, meadows, and aquatic, halophytic, synantropic, alpine, arctic, petrophytic, see-shore vegetation and wetlands were represented. The problems, that have appeared after beginning the syntaxa checklists development, such as the validation of units, the dubiousness of some accepted syntaxonomic decisions, poor syntaxonomic knowledge of some regions were discussed. The directors of three Botanical Gardens (from Yalta, Novosibirsk and Vladivostok) of the Russian Academy of Sciences signed documents (Fig. 3) on the starting of a scientific consortium «National Network of Botanical Gardens of the Russian Federation», focused on joint fundamental researches in the vegetation science, ecology, bioclimatology and biogeography; on the development of the National classification of vegetation and National typology of habitats as a scientific basis for assessing the carbon balance, rational use of natural resources and vegetation conservation in the country. Resolution of the Workshop emphasizes the necessity to consider the development of the Russian national vegetation classification as a priority task for phytosociologists in Russian Federation for the next five years.

Трансформация галофитной растительности Сердобского солонца (Сердобский район, Пензенская область)

Halophytic vegetation is very rare in the forest-steppe zone. It was studied in the tract Serdobsky solonetsin the vicinity of Serdobsk (Serdobsky district, Penza region). The studies were conducted in the years 2009–2018, using the technique of geobotanical profiling. 80 trial areas were laid (35 in 2009 and 45 in 2008). Ecological and phytocenotic classification of plant communities is performed on the dominant principle. Comparison of two descriptions of vegetation with an interval of 10 years allows us to trace the transformation of halophytic vegetation after intensive anthropogenic impact (grazing and partial plowing) in different environmental conditions. The flora of Serdobsky solonets consists of 179 species of vascular plants, of which 13 species are included in the Red book of the Penza region (2013). The share of halophytic vegetation on the territory of Serdobsky solonetshas changed over 10 years: from 97.0 % to 63.8 %. Moreover, halophyte meadows occupied 67.0 % and halophyte steppes 30.0 % of the area in 2009. Now (2018) halophytic steppes make up 30.8 %, and halophytic meadows 33.0 %.The main stages of demutation of halophytic steppe and meadow vegetation were identified in various environmental conditions (meadows and steppes). The same stages of demutation were identified earlier for the South-Eastern Solonets (Neverskinsky district of the Penza region). However, a special stage of annual saline grasslands has been identified.This place requires protection due to the high level of floral and phytocenotic diversity. We offer to organize here a natural monument called “Serdobsky solonets”.

Woody Species Diversity and Vegetation Structure of Wurg Forest, Southwest Ethiopia

This study was aimed to determine woody species composition, diversity, and vegetation structure and to investigate major threats to Wurg forest, southwest Ethiopia. In order to collect vegetation data, 64 (400 m2) sample plots from eight transect lines were employed. The distances between transect lines and plots were 400 m and 200 m, respectively. DBH of woody species &gt;2.5 cm and the height &gt;2 m were measured and recorded. Voucher specimens were brought to the Ethiopian Biodiversity Institute for identification and deposited there. R program version 12.5.2 software and Microsoft Excel spreadsheet were used to analyze plant community classification and structural analysis, respectively. A total of 76 woody species representing 40 families were recorded. Rubiaceae was the dominant family followed by Asteraceae. The average Shannon–Wiener diversity index (H′) and the average evenness values of Wurg forest were 3.38 and 0.90, respectively. Four plant community types were identified by using the presence/absence values of each species. The total density of woody species with DBH &gt; 2.5 cm was 1745.3 ha−1. The DBH and height class distributions showed an inverted J-shaped pattern, which indicates a good regeneration potential of the forest. The most frequently observed species (92%) was Syzygium guineense, which contributed 46% of the total basal area. The composition of seedling, sapling, and adult trees/shrubs species was 4966.07 ha−1, 3125.78 ha−1, and 1745.27 ha−1, respectively. However, the major threat to the forest was selective cutting of some woody species for various purposes. Therefore, raising local community awareness on conservation and sustainable use of the forest and exploring various alternatives for local communities’ livelihood and promoting private and community plantations are recommendable.

Концепция классификации растительности России как отражение современных задач фитоценологии

Концепция классификации растительности России как отражение современных задач фитоценологии

In memoriam: Vladislav Ivanovich Vasilevich (1935–2020)

Russian Botanical Society, Komarov Botanical Institute of the Russian Academy of Sciences, and all Russian geobotany have suffered a huge irreparable loss. On May 2 2020 after a serious illness the greatest geobotanist of Russia, Doctor of Biology, Professor Vladislav Ivanovich Vasilevich left us. V. I. Vasilevich was born in 1935 in the town of Vyatskie Polyany, Kirov Region, in the family of a school teacher. After graduating fr om high school, in 1953 he entered the Leningrad State University, wh ere he specialized in the Department of Geobotany under the supervision by Professor A. P. Shennikov. After graduating from the University and post-graduate studies, in 1960 he was enrolled in the Laboratory of Experimental Geobotany of the Komarov Botanical Institute. All his scientific life was completely connected with the Institute. V. I. Vasilevich went from a junior researcher of the Laboratory of Experimental Geobotany to the ­Institute Deputy Director of the for scientific work. He was the Head of the Laboratory of the Forest Zone Vegetation, the Head of the Department of Geobotany, and the Chief Researcher of the Laboratory of Geobo­tany. For many years, he was a member of the Scienti­fic and Dissertation Councils of the Komarov Botanical Institute. He was the organizer and the leader of many geobotanical expeditions. The geography of his field research was truly diverse. Vladislav Ivanovich brilliantly knew not only the vegetation of the North-West of Russia, but also of many other regions of USSR (Kazakhstan, Taymyr, the Middle Urals, the Western Caspian, etc.). In the person of Vladislav Vasilevich, Russian vegetation science has lost an outstanding scientist, the greatest specialist in theoretical phytocoenology, vegetation classification, and the study of biodiversity (Vasilevich, 1971, 1985, 2010, etc.). He proposed the quantitative method of dominant-determinant classification (the “dominant-floristic method”) based on the analysis of the uniformity of distribution of species with similar ecology in a certain groups of plant communities (Vasilevich, 1995). Using this method, V. I. Vasilevich and his colleagues developed a detailed classification of plant communities of the North-West of Russia that has resulted in numerous publications (Vasilevich, 2000; Vasilevich, Bibikova, 2003, 2011; etc.) He had published about 300 scientific papers and two monographs “Statistical methods in geobotany” (Vasilevich, 1969) and “Essays on theoretical phytocoenology” (Vasilevich, 1983), that had a huge impact on the development of vegetation science in Russia. He was an editor of many proceedings of scientific papers and collective monographs. In 1994, he was awarded the title “Honored scientist of the Russian Federation”. He was awarded the medal of the Order “For Merits to the Motherland”. Vladislav Ivanovich greatly contributed to the training of young scientists: 5 doctoral and 15 PhD theses were defended under his supervision. For many years, he gave lectures at the Department of geobotany of Saint Petersburg University in the specialities “Biometrics”, “Vegetation classification”, “Geobotanical subdivision”, “Vegetation of the North-West of Russia”, “Special chapters in geobotany”. He led the course “Phytocoenology” for graduate students of the Komarov Botanical Institute. Numerous students of him work in various regions of Russia and abroad. Vladislav Ivanovich devoted a lot of time and efforts to the work in the Russian Botanical Society (RBO). He was a Scientific Secretary, a Member of the Presidium, and a Vice-President of the RBO, Chairman of the Section of Geobotany of the RBO, a member of the Organizing Committees of the XII International Botanical Congress and Delegates’ Congresses of the RBO. The memory of Vladislav Ivanovich Vasilevich — an outstanding geobotanist, theoretician, teacher, and organizer of science — will always remain in our hearts.

Как погрешности при описании растительности в поле и обработке данных влияют на результаты классификации (на примере арктических сообществ)

Как погрешности при описании растительности в поле и обработке данных влияют на результаты классификации (на примере арктических сообществ)

Floristic composition and vegetation community analysis of Gesha and Sayilem Forest in Kaffa Zone south western Ethiopia

Abstract. Addi A, Soromessa T, Bareke T. 2020. Plant diversity and community analysis of Gesha and Sayilem Forest in Kaffa Zone, southwestern Ethiopia. Biodiversitas 21: 2878-2888. The study was conducted at Gesha and Sayilem districts of the Kaffa Zone with the objective of identifying the floristic compositions, plant community types, and associated environmental factors of the forest. Stratified random sampling technique was used. A total of 90 plots were used to collect vegetation data. The plant community classification was performed using agglomerative Hierarchical cluster analysis Ward’s linkage method was applied in R-software. Species diversity and evenness were evaluated using the Shannon diversity and evenness indices respectively. The study revealed that the study area composed of 300 species that belong to 239 genera in 96 families. Asteraceae was the most abundant family followed by Fabaceae, Acanthaceae, Poaceae, Rubiaceae, and Euphorbiaceae accounting 37%, 15%, 14%, 13%, 12%, and 9% respectively. Five plant community types were identified and these were Ilex mitis-Syzygium guineense, Pouteria adolfi-friedericii-Schefflera abyssinica, Millettia ferruginea-Sapium ellipticum, Arundinaria alpina and Schefflera volkensii-Masea-lanceolata community types. Among the community types, Pouteria adolfi-friedericii-Syzygium guineense community was the most diverse whereas Arundinaria alpina community was the least diverse community. Canonical Correspondence of vegetation data analysis indicated that altitude, disturbance, slope, phosphorus, and the electrical conductivity were the environmental factors that significantly influence the plant communities. The high dependency of local communities on the forest resources is affecting the plant biodiversity. Thus, conservation of the forest through the introduction of sustainable forest management interventions including participatory forest management seems an appropriate action.

Community structure and species composition in a subtropical evergreen broad-leaved forest in Wuchaoshan, Hangzhou, Zhejiang Province, China

The numerical classification and ordination of plant communities can reveal the relationship between plant distribution and environment, with implications on vegetation restoration and forest management. Community types were classified using a clustering method based on 45 forest dynamic plots with each area of 0.04 hm2 in Wuchaoshan, Hangzhou, Zhejiang Province, China. The ordination of plant community and the relationship between communities and edaphic variables (soil nutrient availability and topography) were explored using redundancy analysis. Results showed there were three community types in the study area, including Schima superba community type, Quercus fabri-Symplocos anomala community type, and Cyclobalanopsis glauca community type. Stem density and basal area of trees were not significantly different among those community types. Species richness in the C. glauca community was higher than that in S. superba community, but not significantly different from the Q. fabri-S. anomala community. Results from the redundancy analysis showed that community distribution was significantly related to edaphic factors. Topographic and soil factors accounted for 46.4% of the total variation in community distribution while total soil phosphorus, available phosphorus, available potassium, elevation, slope, aspect, and canopy openness had significant effects on community composition. Total soil phosphorus, available potassium, and altitude were the main factors influencing community distribution in Wuchaoshan. 53.6% of the total variation in community distribution were not explained, perhaps due to anthropogenic disturbance.

Effect of environmental gradients on diversity and plant community distribution in remnant dry Afromontane forest of Mount Duro, Nagelle Arsi, Ethiopia

Abstract For forest ecosystem management to be effective, explicit understanding of the species diversity-environmental relationship along elevation gradient is crucial. This study aimed at identifying and describing plant communities and also documenting their species diversity. Evaluation of relationships between selected environmental variables and species diversity was another objective of this study. Systematic sampling techniques were used to collect vegetation data in a total of forty two sample plots (size=20×20 m). Within main plots, four sub-plots of 5×5 m were established at four corners and – one sub-plot of the same size in the center. These plots were used for shrub and herb diversity assessment. Within each sample plot, all plant species were documented and their scientific names were identified. Environmental variables, such as: elevation, aspect and slope, were also recorded for each main plot. Species diversity was determined using Shannon-Wiener diversity index and evenness in R statistical software. Agglomerative hierarchical clustering method was used for plant community classification. The total of 44 plant species belonging to 30 families was documented. Four plant community types were identified with different diversity, evenness and species richness. These plant communities were: Afrocurpus falcatus-Ficus sur, Maesa lanceolata-Bersama abyssinica, Vernonia myriantha-Urera hypselodendron and Croton machrostachus-Tecleanobilis occurring at average elevation of 2521, 2429, 2329, and 2364 m asl, respectively. Maesa lanceolata-Bersama abyssinica community type exhibited the highest species diversity and evenness followed by Croton machrostachus-Teclea nobilis community type showing the fact that median elevation ranges were rich in species. Elevation and slope gradient explained significant variation in species richness in the studied forest. For effective conservation of biodiversity and sustainable management of the forest ecosystem, further research on the impacts of anthropogenic disturbances and soil properties is recommended as a result of this study.

Deep learning-based rapid recognition of oasis-desert ecotone plant communities using UAV low-altitude remote-sensing data

The oasis-desert ecotone plant community is a protective barrier for an oasis. With the continuous expansion of oasis ecosystems and gradual increases in the intensity of human activities, the degradation of plant communities in oasis-desert ecotones has become increasingly prominent. Timely and accurate detection of such degradation is a prerequisite for vegetation restoration. Currently, vegetation information extraction has been primarily based on an analysis of spectral features; however, the vegetation coverage area and the soil background are easily confused. In addition, conventional supervised classification methods have a strong dependence on the training samples, and this technique can fail due to the complicated image processing procedure, relatively lower recognition ability, and optimal threshold determination for a multi-temporal image. In this study, the aim was to accurately extract the plant community features, distribution area, and the image background using two automatic recognition algorithm models known as the convolution neural network (CNN)-based VGG16 and VGG19 models. These models were used to investigate an oasis-desert ecotone in an arid area using an unmanned aerial vehicle (UAV) remote-sensing image. Additionally, the impacts of a change in the training sample size on the automatic classification accuracy of the models were evaluated. The results showed that the size of the training samples has a significant impact on the classification accuracy, and with an increase in the sample sizes, the generalization ability of the models gradually improved. The modeling accuracy of the VGG16 and VGG19 increased from 88.25% and 95.25% to 88.50% and 96.73%, respectively. The classification accuracy of the VGG16 model varied from 79.6 to 93.8%, and the classification accuracy of VGG19 model varied from 82.3 to 95.6%. The size of the training samples was 300, so both models presented the best classification results. Compared with the conventional supervised classification methods, the deep learning algorithm-based models yielded significantly higher classification accuracies. These models can provide technical support for the realization of the unsupervised automatic classification of oasis-desert ecotone plant communities in arid areas.