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Marine biological invasions have increased with the development of global trading, causing the homogenization of communities and the decline of biodiversity. A main vector is ballast water exchange from shipping. This study evaluates the use of ecological niche modelling (ENM) to predict the spread of 18 non-indigenous species (NIS) along shipping routes and their potential habitat suitability (hot/cold spots) in the Baltic Sea and Northeast Atlantic. Results show that, contrary to current risk assessment methods, temperature and sea ice concentration determine habitat suitability for 61% of species, rather than salinity (11%). We show high habitat suitability for NIS in the Skagerrak and Kattegat, a transitional area for NIS entering or leaving the Baltic Sea. As many cases of NIS introduction in the marine environment are associated with shipping pathways, we explore how ENM can be used to provide valuable information on the potential spread of NIS for ballast water risk assessment.
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http://dx.doi.org/10.1016/j.marpolbul.2015.04.033 | DOI Listing |
Med Vet Entomol
September 2025
Entomology Research Unit, Department of Zoology, The University of Burdwan, Burdwan, India.
The biting midges, Culicoides peregrinus Kieffer and Culicoides oxystoma Kieffer (Diptera: Ceratopogonidae) are the most significant vector species of bluetongue virus (BTV) in the Oriental region, including India. Rearing of these vector species was cumbersome; previous researchers supplemented the rearing substrates primarily with cattle dung (the habitat), yeast and nutrient broth. Other investigations reiterated that an enriched milieu of live bacteria is required for the oviposition and developmental progression of the immatures as they failed to develop in sterile medium.
View Article and Find Full Text PDFUnderstanding the spatial distribution of rare species is fundamental to biodiversity conservation. The black-necked crane (), a flagship species of alpine wetlands and a first-class nationally protected species in China, serves as an important indicator for ecosystem health. Based on the had data and ecological environment data, this study used the Maximum Entropy model (MaxEnt) and Random Forest model (RF) to predict the suitable distribution area of the black-necked crane.
View Article and Find Full Text PDFInt Urol Nephrol
September 2025
Division of Nursing, Singapore General Hospital, Singapore, Singapore.
Objective: To explore healthcare professionals' perceptions on the implementation of home hemodialysis and self-assisted hemodialysis in Singapore and to identify the perceived barriers, facilitators, and actionable strategies for increasing uptake.
Methods: This is a qualitative explorative study based on semi-structured face-to-face interviews conducted with a multidisciplinary group of 12 healthcare professionals at an acute teaching hospital in Singapore. Thematic analysis was used for data analysis.
Mar Life Sci Technol
August 2025
Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101 China.
Unlabelled: Biological invasions represent one of the main anthropogenic drivers of global change with a substantial impact on biodiversity. Traditional studies predict invasion risk based on the correlation between species' distribution and environmental factors, with little attention to the potential contribution of physiological factors. In this study, we incorporated temperature-dependent sex determination (TSD) and sex-ratio data into species distribution models (SDMs) to assess the current and future suitable habitats for the world's worst invasive reptile species, the pond slider turtle ().
View Article and Find Full Text PDFEcol Evol
September 2025
Laboratory of Wildlife Biology and Medicine, Department of Environmental Veterinary Science, Graduate School of Veterinary Medicine Hokkaido University Sapporo Japan.
The king cobra (), the world's largest venomous snake, is a vulnerable species with an expanding distribution in Nepal. This study modeled its current climatically suitable habitat and predicted future changes (2050 and 2070) under the SSP2-4.5 climate change scenario.
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