In this study, we sequenced both two mitochondrial genes (COI and 16S rRNA) and nuclear genes (28S rRNA and elongation factor‐1α) from 71 species of Odonata that represent 7 superfamilies in 3 suborders. Phylogenetic testing for each two concatenated gene sequences based on function (ribosomal vs protein‐coding genes) and origin (mitochondrial vs nuclear genes) proved limited resolution. Thus, four concatenated sequences were utilized to test the previous phylogenetic hypotheses of higher taxa of Odonata via Bayesian inference (BI) and maximum likelihood (ML) algorithms, along with the data partition by the BI method. As a result, three slightly different topologies were obtained, but the BI tree without partition was slightly better supported by the topological test. This topology supported the suborders Anisoptera and Zygoptera each being a monophyly, and the close relationship of Anisozygoptera to Anisoptera. All the families represented by multiple taxa in both Anisoptera and Zygoptera were consistently revealed to each be a monophyly with the highest nodal support. Unlike consistent and robust familial relationships in Zygoptera those of Anisoptera were partially unresolved, presenting the following relationships: ((((Libellulidae + Corduliidae) + Macromiidae) + Gomphidae + Aeshnidae) + Anisozygoptera) + (((Coenagrionidae + Platycnemdidae) + Calopterygidae) + Lestidae). The subfamily Sympetrinae, represented by three genera in the anisopteran family Libellulidae, was not monophyletic, dividing Crocothemis and Deielia in one group together with other subfamilies and Sympetrum in another independent group.
Background Citizen science is becoming a mainstream approach of baseline data collection to monitor biodiversity and climate change. Dragonflies (Odonata) have been ranked as the highest priority group in biodiversity monitoring for global warming. Ischnura senegalensis Rambur has been designated a biological indicator of climate change and is being monitored by the citizen science project “Korean Biodiversity Observation Network.” This study has been performed to understand changes in the distribution range of I. senegalensis in response to climate change using citizen science data in South Korea. Results We constructed a dataset of 397 distribution records for I. senegalensis, ranging from 1980 to 2020. The number of records sharply increased over time and space, and in particular, citizen science monitoring data accounted for the greatest proportion (58.7%) and covered the widest geographical range. This species was only distributed in the southern provinces until 2010 but was recorded in the higher latitudes such as Gangwon-do, Incheon, Seoul, and Gyeonggi-do (max. Paju-si, 37.70° latitude) by 2020. A species distribution model showed that the annual mean temperature (Bio1; 63.2%) and the maximum temperature of the warmest month (Bio5; 16.7%) were the most critical factors influencing its distribution. Future climate change scenarios have predicted an increase in suitable habitats for this species. Conclusions This study is the first to show the northward expansion in the distribution range of I. senegalensis in response to climate warming in South Korea over the past 40 years. In particular, citizen science was crucial in supplying critical baseline data to detect the distribution change toward higher latitudes. Our results provide new insights on the value of citizen science as a tool for detecting the impact of climate change on ecosystems in South Korea.
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