It takes two to tango – Phylogeography, taxonomy and hybridization in grass snakes and dice snakes (Serpentes: Natricidae: Natrix natrix, N. tessellata)

Using two mitochondrial DNA fragments and 13 microsatellite loci, we examined the phylogeographic structure and taxonomy of two codistributed snake species (Natrix natrix, N. tessellata) in their eastern distribution area, with a focus on Turkey. We found evidence for frequent interspecific hybridization, previously thought to be extremely rare, and for backcrosses. This underscores that closely related sympatric species should be studied together because otherwise the signal of hybridization will be missed. Furthermore, the phylogeographic patterns of the two species show many parallels, suggestive of a shared biogeographic history. In general, the phylogeographies follow the paradigm of southern richness to northern purity, but the dice snake has some additional lineages in the south and east in regions where grass snakes do not occur. For both species, the Balkan Peninsula and the Caucasus region served as glacial refugia, with several mitochondrial lineages occurring in close proximity. Our results show that the mitochondrial divergences in both species match nuclear genomic differentiation. Yet, in the former glacial refugia of grass snakes there are fewer nuclear clusters than mitochondrial lineages, suggesting that Holocene range expansions transformed the glacial hotspots in melting pots where only the mitochondrial lineages persisted, bearing witness of former diversity. On the other hand, the deep mitochondrial divergences in N. tessellata across its entire range indicate that more than one species could be involved, even though lacking microsatellite data outside of Turkey prevent firm conclusions. On the contrary, our microsatellite and mitochondrial data corroborate that N. megalocephala is invalid and not differentiated from sympatric populations of N. natrix. For Cypriot grass snakes, our analyses yielded conflicting results. A critical assessment of the available evidence suggests that N. natrix is a genetically impoverished recent invader on Cyprus and taxonomically not distinct from a subspecies also occurring in western Anatolia and the southern Balkans. Based on combined mitochondrial and nuclear genomic evidence we propose that for grass snakes the following subspecies should be recognized in our study region: (1) Natrix natrix vulgaris Laurenti, 1768, southeastern Central Europe and northern Balkans; (2) Natrix natrix moreoticus (Bedriaga, 1882), southern Balkans, western Anatolia, and Cyprus; and (3) Natrix natrix scutata (Pallas, 1771), eastern Anatolia, Caucasus region, Iran, northeastern distribution range (from eastern Poland and Finland to Kazakhstan and the Lake Baikal region). Thus, Natrix natrix cypriaca (Hecht, 1930) becomes a junior synonym of N. n. moreoticus and Natrix natrix persa (Pallas, 1814) becomes a junior synonym of N. n. scutata. Due to insufficient material, we could not resolve the status of Natrix natrix syriaca (Hecht, 1930) from the Gulf of İskenderun, southeastern Turkey.

The distribution and biogeography of slow worms (Anguis, Squamata) across the Western Palearctic, with an emphasis on secondary contact zones

The slow-worm lizards (Anguis) comprise five species occurring throughout most of the Western Palearctic. Although these species are relatively uniform morphologically – with the exception of A. cephallonica, which exhibits a quite unique morphology – they are genetically deeply divergent. Here, we provide detailed distribution maps for each species and discuss their biogeography and conservation based on updated genetic data and a robust distribution database. We pay particular attention to the so called ‘grey zone’, which typically represents secondary contact zones and in some cases confirmed or presumed hybrid zones. Four of the five species live in parapatry, while only two species, A. cephallonica and A. graeca from the southern Balkans occur in partial sympatry. Further research should focus on the eco-evolutionary interactions between species in contact, including their hybridization rates, to reveal deeper details of the slow-worm evolutionary and natural history.

A Personalized Machine-Learning-Enabled Method for Efficient Research in Ethnopharmacology. The Case of the Southern Balkans and the Coastal Zone of Asia Minor

Ethnopharmacology experts face several challenges when identifying and retrieving documents and resources related to their scientific focus. The volume of sources that need to be monitored, the variety of formats utilized, and the different quality of language use across sources present some of what we call “big data” challenges in the analysis of this data. This study aims to understand if and how experts can be supported effectively through intelligent tools in the task of ethnopharmacological literature research. To this end, we utilize a real case study of ethnopharmacology research aimed at the southern Balkans and the coastal zone of Asia Minor. Thus, we propose a methodology for more efficient research in ethnopharmacology. Our work follows an “expert–apprentice” paradigm in an automatic URL extraction process, through crawling, where the apprentice is a machine learning (ML) algorithm, utilizing a combination of active learning (AL) and reinforcement learning (RL), and the expert is the human researcher. ML-powered research improved the effectiveness and efficiency of the domain expert by 3.1 and 5.14 times, respectively, fetching a total number of 420 relevant ethnopharmacological documents in only 7 h versus an estimated 36 h of human-expert effort. Therefore, utilizing artificial intelligence (AI) tools to support the researcher can boost the efficiency and effectiveness of the identification and retrieval of appropriate documents.

A Personalized Machine-Learning-enabled Method for Efficient Research in Ethnopharmacology. The case of Southern Balkans and Coastal zone of Asia Minor

Ethnopharmacology experts face several challenges when identifying and retrieving documents and resources related to their scientific focus. The volume of sources that need to be monitored, the variety of formats utilized, the different quality of language use across sources, present some of what we call “big data” challenges in the analysis of this data. This study aims to understand if and how experts can be supported effectively through intelligent tools in the task of ethnopharmacological literature research. To this end, we utilize a real case study of ethnopharmacology research, aimed at the Southern Balkans and Coastal zone of Asia Minor. Thus, we propose a methodology for more efficient research in ethnopharmacology. Our work follows an “Expert-Apprentice” paradigm in an automatic URL extraction process, through crawling, where the apprentice is a Machine Learning (ML) algorithm, utilizing a combination of Active Learning (AL) and Reinforcement Learning (RL), and the Expert is the human researcher. ML-powered research improved 3.1 times the effectiveness and 5.14 times the efficiency of the domain expert, fetching a total number of 420 relevant ethnopharmacological documents in only 7 hours versus an estimated 36-hour human-expert effort. Therefore, utilizing Artificial Intelligence (AI) tools to support the researcher can boost the efficiency and effectiveness of the identification and retrieval of appropriate documents.

Inventing a Prosthetic Bourgeoisie: Romania and the Aromanians, 1848–1906

The present article focuses on the period between 1848 and 1906—between the politicized “discovery” of Balkan Aromanians as a kinfolk by Romanian nation-state builders and the aftermath of the community’s recognition by the Ottoman government. Examining how Romania imagined its own entanglement in the Macedonian Question, the article aims to raise the broader question of how a nation-state imagined the agency of kinfolk beyond its borders and, as part of a geographically distributed national division of labor, ascribed a specific task to one part of its ethnic body. In Romania’s case, this had a double thrust. One, Aromanians were imagined as the natural bourgeoisie of the southern Balkans, a people superior in their origins, culture, and mores to other ethnic groups—and a natural vanguard for Romania’s economic interests in the region. Two, they were imagined as a vanguard for catalyzing the internal development of a native merchant class in Romania proper, which was understood as a primary agent for economic and social progress but perceived to be problematically absent. Thus, this study hones in on the process of ascribing the status of a “prosthetic bourgeoisie” to the Aromanians, and its insistent discursive recurrence.

A Personalized Machine-Learning-enabled Method for Efficient Research in Ethnopharmacology. The case of Southern Balkans and Coastal zone of Asia Minor

An ethnopharmacology expert faces several challenges when identifying and retrieving documents and resources related to their scientific focus. The volume of sources that need to be monitored, the variety of formats utilized, the different quality of language use across sources, present some of what we call “big data” challenges in the analysis of this data. This study aims to understand if and how the expert can be supported effectively through intelligent tools for the ethnopharmacological research in the Southern Balkans and Coastal zone of Asia Minor. Our work follows an “Expert-Apprentice” paradigm in a crawling process, where the apprentice is a Machine Learning (ML) algorithm, utilizing a combination of Active Learning (AL) and Reinforcement Learning (RL), and the Expert is the human researcher. ML-powered research improved 3.1 times the effectiveness and 5.14 times the efficiency of the domain expert, fetching a total number of 420 relevant ethnopharmacological documents in only 7 hours versus an estimated 36-hour human-expert effort. Therefore, utilizing Artificial Intelligence (AI) tools to support the researcher can boost the efficiency and effectiveness of the identification and retrieval of appropriate documents.

Late Paleogene herpetofaunas from the crossroads between two continents – new amphibian and reptile remains from the Oligocene of southern Balkans and Anatolia

We describe here new amphibian and reptile remains from three Oligocene localities of Turkey. Two of the localities (Kavakdere and Kocayarma) are situated in southeastern Europe and the other one (Kargi 2) in Anatolia, both areas where Oligocene herpetofauna is practically almost unknown. The material consists of albanerpetontids, pelobatid anurans, turtles, crocodylians, lacertids, scinciformatans, anguines, and “tropidophiids”. Albanerpetontids are for the first time identified in southeastern Europe, with the material being reminiscent of the younger species Albanerpeton inexpectatum Estes & Hoffstetter, 1976; the material potentially represents the oldest record of that species. Pelobatids, scinciformatans, and “tropidophiids” represent the oldest occurrences of these clades in the northeastern Mediterranean. The anguine genus Ophisaurus Daudin, 1803 is identified for the first time in the Paleogene of Eastern Europe. The “tropidophiids” are referred to two genera, Falseryx Szyndlar & Rage, 2003 and tentatively also to Platyspondylia Rage, 1974, with the latter having been so far exclusively known from western and central Europe. The role of a potential southern dispersal route of taxa among Asia and Europe, involving the area of southern Balkans and Anatolia, similarly to what has been recently demonstrated for mammals, is highlighted also for amphibians and reptiles.