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Reviews in Fish Biology and Fisheries · 2026 · Vol. 36 · Issue 1 · Springer
Parasites play a critical yet understudied role in Arctic ecosystems, particularly within key subsistence species such as Arctic char ( Salvelinus alpinus ). As the Arctic undergoes rapid climate-driven change, establishing baseline parasite biodiversity is essential for monitoring ecological shifts and anticipating emerging health and conservation concerns. This study provides the most comprehensive assessment to date of Arct...
Reviews in Fish Biology and Fisheries · 2026 · Vol. 36 · Issue 1 · Springer
Research on cephalopod early ontogeny has significantly advanced in recent decades, including embryo organogenesis and neurogenesis and early behavioural adaptations, particularly in commercially important and coastal species. Within this context, here we compiled current knowledge on the collection, handling and care under experimental conditions and monitoring in the field of cephalopod eggs and egg masses. It covers field o...
Regional Environmental Change · 2026 · Vol. 26 · Issue 3 · Springer
With heatwaves set to increase in frequency, intensity and duration, a policy shift is needed to build climate resilience on national and local levels. In London, a new strategy has been introduced to build urban heat resilience with the ‘Cool Spaces’ scheme. Cool spaces are free, public, indoor areas where people can escape hot weather and reduce heat-related health risks. Despite the scheme’s potential, it is unclear what ty...
Journal of Fish Diseases · 2026 · Wiley
Poikilothermic organisms like fish are key economic drivers in aquaculture and the ornamental fish trade. Climate change impacts the health of fish because poikilothermic hosts experience the same temperature as their environment, making temperature a critical determinant of parasite infection dynamics. Pseudocapillaria tomentosa , a capillarid nematode infecting approximately 20% of zebrafish research facilities, provides an...
Bulletin of Volcanology · 2026 · Vol. 88 · Issue 7 · Springer
The Best-Fit Assessment for Numerical Models (BAM) is a Python-based, open-source, modular, and versatile statistical tool designed to primarily evaluate the performance of numerical models in volcanology. BAM was developed to assess models that simulate the transport and deposition of volcanic mass flows, namely pyroclastic density currents, lava flows, lahars, and debris avalanches. BAM makes use of matrix arrays in the form...