Search

Because of human-induced habitat deterioration and climate change, a large number of species are threatened and even endangered. Batrachium pekinense Liang Liu, a perennial aquatic plant endemic to Beijing, was synonymized as a widely distributed species in Northern China, B. bungei Steudel, but it was later listed in the national key protected wild plants in China. Taxonomic uncertainty should be clarified especially when related species may be allocated with a limited conservation budget. In this study, we reappraised the identity of B. pekinense based on results from molecular phylogenetic analysis and 15-year field observations. Our result shows that 77% of the 65 individuals collected from various sites share identical sequences in both the nuclear ribosomal ITS and the plastid psbA-trnH markers, all samples of the two species consist of one monophyletic clade with strong support, and continuous morphological variations on the key distinguishing character, the leaf shape, are observed in the field. Integrative evidence from both our and the others' studies supports the same identity for B. pekinense and B. bungei. Hence, we suggest excluding B. pekinense from the list of national key protected wild plants of China in its next update and advocate the integrative evidence-based taxonomy and systematics for biodiversity conservation and management. [ABSTRACT FROM AUTHOR]

Urban functional zones are important space carriers for urban economic and social function. The accurate and rapid identification of urban functional zones is of great significance to urban planning and resource allocation. However, the factors considered in the existing functional zone identification methods are not comprehensive enough, and the recognition of functional zones stops at their categories. This paper proposes a framework that combines multisource heterogeneous data to identify the categories of functional zones and draw the portraits of functional zones. The framework comprehensively describes the features of functional zones from four aspects: building-level metrics, landscape metrics, semantic metrics, and human activity metrics, and uses a combination of ensemble learning and active learning to balance the identification accuracy of functional zones and the labeling cost during large-scale generalization. Furthermore, sentiment analysis, word cloud analysis, and land cover proportion maps are added to the portraits of typical functional zones to make the image of functional zones vivid. The experiment carried out within the Fifth Ring Road, Haidian District, Beijing, shows that the overall accuracy of the method reached 82.37% and the portraits of the four typical functional zones are clear. The method in this paper has good repeatability and generalization, which is helpful to carry out quantitative and objective research on urban functional zones. [ABSTRACT FROM AUTHOR]