<i>Waldsteinia</i> within <i>Geum</i> s.l. (Rosaceae): Main Aspects of Phylogeny and Speciation History

Waldsteinia is a small plant genus inhabiting the temperate regions of the Northern Hemisphere. According to the latest revisions, Waldsteinia is included in Geum. We have obtained a phylogenetic reconstruction based on the nuclear (ITS) and plastid (trnL-trnF) DNA to understand the phylogenetic structure of Waldsteinia and its relationships with other taxa of Geum s.l. Phylogenetic analysis based on the joint ITS + trnL-trnF dataset demonstrated Waldsteinia monophyly. The phylogenetic relationships of Waldsteinia species were better explained by their geographical distribution than their morphology. Hence, Euro-Siberian, Northeast Asian, and North American phylogeographic groups were distinguished, with East Asia having been suggested as the place of Waldsteinia origin. Considering the incongruence in W. geoides (a type species) position on the plastid and nuclear DNA trees, together with the discrepancy between the species morphology and its location on the plastid DNA tree, a hybrid origin was suggested for this species. Despite the fact that the position of W. maximowicziana is still not fully resolved, we support the point of view that claims it should be separated from the W. ternata aggregate (traditionally including W. trifolia, W. ternata s.str., and W. maximowicziana) and considered a separate species. The American W. doniana, W. fragarioides, and W. lobata belong to a single maternal lineage, but the observed genetic differences are too small to serve as a convincing argument for species segregation, so their relationships still remain unresolved

Environmental determinants of lake macrophyte communities in Baikal Siberia

We investigated whether environmental filtering or dispersal-related factors mostly drive helophyte and hydrophyte species richness and community composition in 93 lakes situated in Baikal Siberia. Using partial linear regression and partial redundancy analysis, we studied (1) what are the relative roles of environmental variables, dispersal variables, spatial processes and region identity (i.e., river basins) in explaining variation in the species richness and species composition of helophytes and hydrophytes across 93 Siberian lakes, and (2) what are the differences in the most important explanatory variables driving community variation in helophytes versus hydrophytes? We found that, for both species richness and species composition, environmental variables clearly explained most variation for both plant groups, followed by region identity and dispersal-related variables. Spatial variables were significant only for the species composition of hydrophytes. Nutrient-salinity index, a proxy for habitat trophic-salinity status, was by far the most significant environmental determinant of helophytes and hydrophytes. Our results indicate that environmental factors explained the most variation in both species richness and species composition of helophytes and hydrophytes. Nevertheless, dispersal-related variables (i.e. spatial and dispersal) were also influential but less important than environmental factors. Furthermore, the dispersal-related variables were more important for hydrophytes than for helophytes. Most brackish permanent lakes were mostly located in the steppe biomes of southern Transbaikalia. This characteristic along with the oldest age, the largest distances to both river and settlements and the lowest temperatures in the study region distinguished them from freshwater, drained and more nutrient-rich floodplain lakes

Mapping Asia Plants: Historical outline and review of sources on floristic diversity in North Asia (Asian Russia)

North Asia - the Asian part of Russia - is a vast territory that occupies 1/3 of Asia, or about 13 100 000 sq. km. Floristic exploration of North Asia was bolstered in the first half of the 18th century when the emperor Peter I the Great founded the Academy of Sciences (currently, the Russian Academy of Sciences). The first complete flora of the Russian Empire was published in the middle of the 19th century by C.F. von Ledebour, and a wealth of North Asian floristic data had accumulated by the beginning of the 20th century. Under the guidance of the Botanical Institute in Leningrad (St. Petersburg), the Flora of the USSR (1944-1964) was initiated to consolidate this vast body of floristic knowledge. Following this Flora, two modern interregional compendia (Vascular Plants of the Soviet Far East and Flora of Siberia) were published in the 1980s and 1990s, which serve as the taxonomic foundation for the newest regional floras and checklists of the last twenty years. According to our statistics, which are expansive but not comprehensive, there are at least 300 books devoted to the flora of different regions of North Asia. The newest Checklist of the Flora of Asian Russia published in 2012 listed 6961 species and subspecies of vascular plants. Here, we provide a short review of the main references on vascular flora within all 27 administrative regions of North Asia. (C) 2020 The Authors. Published by Elsevier B.V

Improved Wetland Classification Using Eight-Band High Resolution Satellite Imagery and a Hybrid Approach

Although remote sensing technology has long been used in wetland inventory and monitoring, the accuracy and detail level of wetland maps derived with moderate resolution imagery and traditional techniques have been limited and often unsatisfactory. We explored and evaluated the utility of a newly launched high-resolution, eight-band satellite system (Worldview-2; WV2) for identifying and classifying freshwater deltaic wetland vegetation and aquatic habitats in the Selenga River Delta of Lake Baikal, Russia, using a hybrid approach and a novel application of Indicator Species Analysis (ISA). We achieved an overall classification accuracy of 86.5% (Kappa coefficient: 0.85) for 22 classes of aquatic and wetland habitats and found that additional metrics, such as the Normalized Difference Vegetation Index and image texture, were valuable for improving the overall classification accuracy and particularly for discriminating among certain habitat classes. Our analysis demonstrated that including WV2’s four spectral bands from parts of the spectrum less commonly used in remote sensing analyses, along with the more traditional bandwidths, contributed to the increase in the overall classification accuracy by ~4% overall, but with considerable increases in our ability to discriminate certain communities. The coastal band improved differentiating open water and aquatic (i.e., vegetated) habitats, and the yellow, red-edge, and near-infrared 2 bands improved discrimination among different vegetated aquatic and terrestrial habitats. The use of ISA provided statistical rigor in developing associations between spectral classes and field-based data. Our analyses demonstrated the utility of a hybrid approach and the benefit of additional bands and metrics in providing the first spatially explicit mapping of a large and heterogeneous wetland system

Comparing Pixel- and Object-Based Approaches in Effectively Classifying Wetland-Dominated Landscapes

Wetland ecosystems straddle both terrestrial and aquatic habitats, performing many ecological functions directly and indirectly benefitting humans. However, global wetland losses are substantial. Satellite remote sensing and classification informs wise wetland management and monitoring. Both pixel- and object-based classification approaches using parametric and non-parametric algorithms may be effectively used in describing wetland structure and habitat, but which approach should one select? We conducted both pixel- and object-based image analyses (OBIA) using parametric (Iterative Self-Organizing Data Analysis Technique, ISODATA, and maximum likelihood, ML) and non-parametric (random forest, RF) approaches in the Barguzin Valley, a large wetland (~500 km2) in the Lake Baikal, Russia, drainage basin. Four Quickbird multispectral bands plus various spatial and spectral metrics (e.g., texture, Non-Differentiated Vegetation Index, slope, aspect, etc.) were analyzed using field-based regions of interest sampled to characterize an initial 18 ISODATA-based classes. Parsimoniously using a three-layer stack (Quickbird band 3, water ratio index (WRI), and mean texture) in the analyses resulted in the highest accuracy, 87.9% with pixel-based RF, followed by OBIA RF (segmentation scale 5, 84.6% overall accuracy), followed by pixel-based ML (83.9% overall accuracy). Increasing the predictors from three to five by adding Quickbird bands 2 and 4 decreased the pixel-based overall accuracy while increasing the OBIA RF accuracy to 90.4%. However, McNemar’s chi-square test confirmed no statistically significant difference in overall accuracy among the classifiers (pixel-based ML, RF, or object-based RF) for either the three- or five-layer analyses. Although potentially useful in some circumstances, the OBIA approach requires substantial resources and user input (such as segmentation scale selection—which was found to substantially affect overall accuracy). Hence, we conclude that pixel-based RF approaches are likely satisfactory for classifying wetland-dominated landscapes

Diversity and distribution of Oxytropis DC. (Fabaceae) species in Asian Russia

The dataset providing information on the geographic distribution of Oxytropis species on the territory of Asian Russia is discussed. The data were extracted from different sources including prominent floras and check-lists, Red Data books, published research on congeneric species and authors’ field observations and mainly cover less-studied, remote regions of Russia. The dataset should be of value to applied, basic and theoretical plant biologists and ecologists interested in the Oxytropis species.The dataset includes 5172 distribution records for 143 species and 15 subspecies of genus Oxytropis DC. (Fabaceae Lindl.) in Asian Russia. The dataset fills gaps in the distribution of locoweeds in the study area and contains precise coordinates for many of rare and endemic species

The Influence of Region of Interest Heterogeneity on Classification Accuracy in Wetland Systems

Classifying and mapping natural systems such as wetlands using remote sensing frequently relies on data derived from regions of interest (ROIs), often acquired during field campaigns. ROIs tend to be heterogeneous in complex systems with a variety of land cover classes. However, traditional supervised image classification is predicated on pure single-class observations to train a classifier. This ultimately encourages end-users to create single-class ROIs, nudging ROIs away from field-based points or gerrymandering the ROI, which may produce ROIs unrepresentative of the landscape and potentially insert error into the classification. In this study, we explored WorldView-2 images and 228 field-based data points to define ROIs of varying heterogeneity levels in terms of class membership to classify and map 22 discrete classes in a large and complex wetland system. The goal was to include rather than avoid ROI heterogeneity and assess its impact on classification accuracy. Parametric and nonparametric classifiers were tested with ROI heterogeneity that varied from 7% to 100%. Heterogeneity was governed by ROI area, which we increased from the field-sampling frame of ~100 m2 nearly 19-fold to ~2124 m2. In general, overall accuracy (OA) tended downwards with increasing heterogeneity but stayed relatively high until extreme heterogeneity levels were reached. Moreover, the differences in OA were not statistically significant across several small-to-large heterogeneity levels. Per-class user&rsquo;s and producer&rsquo;s accuracies behaved similarly. Our findings suggest that ROI heterogeneity did not harm classification accuracy unless heterogeneity became extreme, and thus there are substantial practical advantages to accommodating heterogeneous ROIs in image classification. Rather than attempting to avoid ROI heterogeneity by gerrymandering, classification in wetland environments, as well as analyses of other complex environments, should embrace ROI heterogeneity

Out of the Qinghai-Tibet plateau: Genomic biogeography of the alpine monospecific genus Megadenia (Biscutelleae, Brassicaceae)

Numerous high-elevation alpine plants of the Qinghai-Tibet Plateau (QTP) also have disjunct distribution in adjacent low-altitude mountains. The out-of-QTP versus into-the-QTP hypothesis of alpine plants provide strong evidence for the highly disputed assumption of the massive ice sheet developed in the central plateau during the Last Glacial Maximum (LGM). In this study, we sequenced the genomes of most known populations of Megadenia, a monospecific alpine genus of Brassicaceae distributed primarily in the QTP, though rarely found in adjacent low-elevation mountains of north China and Russia (NC-R). All sequenced samples clustered into four geographic genetic groups: one pair was in the QTP and another was in NC-R. The latter pair is nested within the former, and these findings support the out-of-QTP hypothesis. Dating the four genetic groups and niche distribution suggested that Megadenia migrated out of the QTP to adjacent regions during the LGM. The NC-R group showed a decrease in the effective population sizes. In addition, the genes with high genetic divergences in the QTP group were mainly involved in habitat adaptations during low-altitude colonization. These findings reject the hypothesis of development massive ice sheets, and support glacial survival of alpine plants within, as well as further migration out of, the QTP