The ‘smooth newt’, the taxon traditionally referred to asLissotriton vulgaris, consists of multiple morphologically distinct taxa. Given the uncertainty concerning the validity and rank of these taxa,L. vulgarissensu lato has often been treated as a single, polytypic species. A recent study, driven by genetic data, proposed to recognize five species,L. graecus,L. kosswigi,L. lantzi,L. schmidtleriand a more restrictedL. vulgaris. The Carpathian newtL. montandoniwas confirmed to be a closely related sister species. We propose to refer to this collective of sixLissotritonspecies as the smooth newt orLissotriton vulgarisspecies complex. Guided by comprehensive genomic data from throughout the range of the smooth newt species complex we 1) delineate the distribution ranges, 2) provide a distribution database, and 3) produce distribution maps according to the format of the New Atlas of Amphibians and Reptiles of Europe, for the six constituent species. This allows us to 4) highlight regions where more research is needed to determine the position of contact zones.
In the light of the “Biological Diversity” concept, habitats are cardinal pieces for biodiversity quantitative estimation at a local and global scale. In Europe EUNIS (European Nature Information System) is a system tool for habitat identification and assessment. Earth Observation (EO) data, which are acquired by satellite sensors, offer new opportunities for environmental sciences and they are revolutionizing the methodologies applied. These are providing unprecedented insights for habitat monitoring and for evaluating the Sustainable Development Goals (SDGs) indicators. This paper shows the results of a novel approach for a spatially explicit habitat mapping in Italy at a national scale, using a supervised machine learning model (SMLM), through the combination of vegetation plot database (as response variable), and both spectral and environmental predictors. The procedure integrates forest habitat data in Italy from the European Vegetation Archive (EVA), with Sentinel-2 imagery processing (vegetation indices time series, spectral indices, and single bands spectral signals) and environmental data variables (i.e., climatic and topographic), to parameterize a Random Forest (RF) classifier. The obtained results classify 24 forest habitats according to the EUNIS III level: 12 broadleaved deciduous (T1), 4 broadleaved evergreen (T2) and eight needleleaved forest habitats (T3), and achieved an overall accuracy of 87% at the EUNIS II level classes (T1, T2, T3), and an overall accuracy of 76.14% at the EUNIS III level. The highest overall accuracy value was obtained for the broadleaved evergreen forest equal to 91%, followed by 76% and 68% for needleleaved and broadleaved deciduous habitat forests, respectively. The results of the proposed methodology open the way to increase the EUNIS habitat categories to be mapped together with their geographical extent, and to test different semi-supervised machine learning algorithms and ensemble modelling methods.
Genetic diversity feeds the evolutionary process and allows populations to adapt to environmental changes. However, we still lack a thorough understanding of why hotspots of genetic diversity are so 'hot'. Here, we analysed the relative contribution of bioclimatic stability and genetic admixture between divergent lineages in shaping spatial patterns of genetic diversity in the common toad Bufo bufo along the Italian peninsula. We combined population genetic, phylogeographic and species distribution modelling (SDM) approaches to map ancestral areas, glacial refugia, and secondary contact zones. We consistently identified three phylogeographic lineages, distributed in northern, central and southern Italy. These lineages expanded from their ancestral areas and established secondary contact zones, before the last interglacial. SDM identified widespread glacial refugia in peninsular Italy, sometimes located under the present-day sea-level. Generalized linear models indicated genetic admixture as the only significant predictor of the levels of population genetic diversity. Our results show that glacial refugia contributed to preserving both levels and patterns of genetic diversity across glacial-interglacial cycles, but not to their formation, and highlight a general principle emerging in Mediterranean species: higher levels of genetic diversity mark populations with substantial contributions from multiple genetic lineages, irrespective of the location of glacial refugia.
Unprecedented rates of biodiversity loss rise the urgency for preserving species ability to cope with ongoing global changes. An approach in this direction is to target intra-specific hotspots of genetic diversity as conservation priorities. However, these hotspots are often identified by sampling at a spatial resolution too coarse to be useful in practical management of threatened species, hindering the long-appealed dialog between conservation stakeholders and conservation genetic researchers. Here, we investigated the spatial and temporal variation in species presence, genetic diversity, as well as potential risk factors, within a previously identified hotspot of genetic diversity for the endangered Apennine yellow bellied toad Bombina pachypus. Our results show that this hotspot is neither a geographically homogeneous nor a temporally stable unit. Over a time-window spanning 10-40 years since previous assessments, B. pachypus populations declined in large portions of its hotspot, and their genetic diversity levels decreased. Considering the demographic trend, genetic and epidemiological data, and models of current and future climatic suitability, populations at the extreme south of the hotspot area still qualify for urgent in-situ conservation actions, whereas northern populations would be better managed through a mix of in-situ and ex-situ actions. Our results emphasize that identifying hotspot of genetic diversity, albeit essential step, does not suffice to warrant on-ground conservation of threatened species. Hotspots should be analysed at finer geographic and temporal scales, to provide conservation stakeholders with key knowledge to best define conservation priorities, and to optimize resource allocation to alternative management practices.
Unprecedented rates of biodiversity loss raise the urgency for preserving species ability to cope with ongoing global changes. An approach in this direction is to target intra-specific hotspots of genetic diversity as conservation priorities. However, these hotspots are often identified by sampling at a spatial resolution too coarse to be useful in practical management of threatened species, hindering the long-appealed dialog between conservation stakeholders and conservation genetic researchers. Here, we investigated the spatial and temporal variation in species presence, genetic diversity, as well as potential risk factors, within a previously identified hotspot of genetic diversity for the endangered Apennine yellow-bellied toad Bombina pachypus. Our results show that this hotspot is neither a geographically homogeneous nor a temporally stable unit. Over a time-window spanning 10-40 years since previous assessments, B. pachypus populations declined in large portions of their hotspot, and their genetic diversity levels decreased. Considering the demographic trend, genetic and epidemiological data, and models of current and future climatic suitability, populations at the extreme south of the hotspot area still qualify for urgent in-situ conservation actions, whereas northern populations would be better managed through a mix of in-situ and ex-situ actions. Our results emphasize that identifying hotspots of genetic diversity, albeit an essential step, does not suffice to warrant on-ground conservation of threatened species. Hotspots should be analyzed at finer geographic and temporal scales, to provide conservation stakeholders with key knowledge to best define conservation priorities, and to optimize resource allocation to alternative management practices.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.