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

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’s and producer’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

Paper Mapping Asia plants: Current status on floristic information in Southwest Asia

Mapping Asia Plants (MAP) is a comprehensive project that aims to build a detailed infrastructure for integrating Asian plant distribution data a global-scale array of knowledge for plant biodiversity conservation. Here, we provide a brief historical review of botanical research in Southwest Asia an understudied botanical region with high conservation priority. Nineteen countries were included in this study (from west to east): Turkey, Cyprus, Palestine, Israel, Jordan, Saudi Arabia, Lebanon, Syria, Iraq, Georgia, Yemen, Armenia, Iran, Azerbaijan, Kuwait, Bahrain, Qatar, United Arab Emirates, and Oman. We reviewed 132 resources comprising 125 Floras and Checklists, of which we describe in some detail at least one of the most important Floras or Checklists for each country. Complete and published national Floras exist for 13 countries; three countries (Jordan, Israel and Bahrain) do not have a Flora but have annotated Checklists, and national Floras are at different stages of completion for Iran, Iraq and Georgia. Where present, online resources are also given for references. We found major gaps in species concepts and taxonomic classification systems, and that many up-to-date Flora revisions remained unresolved, i.e. taxon ranks and species concepts varied among different countries, different systems were adopted or followed in the taxonomic treatments in the Floras and Checklists, and some of the current Floras are out of date. Floras are the first necessary step for many fields, including evolutionary biology, ecology, biogeography, and systematics, as well as environmental research and conservation of biodiversity at national and international levels. Here, we provide the progress updates on the main published floristic works of Southwest Asia, which continue to serve as references for the Flora of Southwest Asia, and will be the foundation of the MAP project. (C) 2020 The Author(s). Published by Elsevier B.V

sPlotOpen - An environmentally balanced, open-access, global dataset of vegetation plots

Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called 'sPlot', compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01-40,000 m(2). Time period and grain 1888-2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot-level records. Software format Three main matrices (.csv), relationally linked

sPlot:a new tool for global vegetation analyses

Abstract Aims: Vegetation‐plot records provide information on the presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community‐weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale