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Resurrecting habitat fragmentation as a process over timeNARA Subscribed
Landscape experiments unlock relationships among habitat loss, fragmentation, and patch‐size effectsNARA Subscribed
Habitat loss is often considered the greatest near‐term threat to biodiversity, while the impact of habitat fragmentation remains intensely debated. A key issue of this debate centers on the problem of scale–landscape or patch–at which to assess the consequences of fragmentation. Yet patterns are often confounded across scales, and experimental designs that could solve this scaling problem remain scarce. We conducted two field...
A pheromone bouquet controls the reproductive behaviour of the male shore crab, Carcinus maenasNARA Subscribed
The reproduction of many brachyuran crustaceans involves the formation of mating pairs often around the time of the female moult with attraction of a sexual partner and mating behaviour controlled by sex pheromones. In shore crabs, Carcinus maenas , females produce sex pheromones that are released in the urine. High Performance Liquid Chromatography analysis (HPLC) of female urine shows that the pheromone, identified as the nu...
The role of changing pH on olfactory success of predator–prey interactions in green shore crabs, Carcinus maenasNARA Subscribed
Arguably climate change is one of the biggest challenges faced by many organisms. One of the more significant of these is the decreasing pH level of the ocean, a consequence of the increasing amount of atmospheric CO 2 being absorbed. With the current open ocean pH level of 8.15 projected to fall to just over 7.6 in 2100, the impacts could be devastating for marine species reliant upon olfaction to survive. Here, we show that...
Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severityNARA Subscribed
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the pr...
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