Climate change affects plants in natural and agricultural ecosystems throughout the world but little work has been done on the effects of climate change on plant disease epidemics. To illustrate such effects, a weather-based disease forecasting model was combined with a climate change model predicting UK temperature and rainfall under high-and low-carbon emissions for the 2020s and 2050s. Multi-site data collected over a 15-year period were used to develop and validate a weather-based model forecasting severity of phoma stem canker epidemics on oilseed rape across the UK. This was combined with climate change scenarios to predict that epidemics will not only increase in severity but also spread northwards by the 2020s. These results provide a stimulus to develop models to predict the effects of climate change on other plant diseases, especially in delicately balanced agricultural or natural ecosystems. Such predictions can be used to guide policy and practice in adapting to effects of climate change on food security and wildlife.

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The rhythm of life on earth is shaped by seasonal changes in the environment. Plants and animals show profound annual cycles in physiology, health, morphology, behaviour and demography in response to environmental cues. Seasonal biology impacts ecosystems and agriculture, with consequences for humans and biodiversity. Human populations show robust annual rhythms in health and well-being, and the birth month can have lasting effects that persist throughout life. This review emphasizes the need for a better understanding of seasonal biology against the backdrop of its rapidly progressing disruption through climate change, human lifestyles and other anthropogenic impact. Climate change is modifying annual rhythms to which numerous organisms have adapted, with potential consequences for industries relating to health, ecosystems and food security. Disconcertingly, human lifestyles under artificial conditions of eternal summer provide the most extreme example for disconnect from natural seasons, making humans vulnerable to increased morbidity and mortality. In this review, we introduce scenarios of seasonal disruption, highlight key aspects of seasonal biology and summarize from biomedical, anthropological, veterinary, agricultural and environmental perspectives the recent evidence for seasonal desynchronization between environmental factors and internal rhythms. Because annual rhythms are pervasive across biological systems, they provide a common framework for trans-disciplinary research.

We derive the distance and structure of the Perseus molecular cloud by combining trigonometric parallaxes from Very Long Baseline Array (VLBA) observations, taken as part of the GOBELINS survey, and Gaia Data Release 2. Based on our VLBA astrometry, we obtain a distance of 321 ± 10 pc for IC 348. This is fully consistent with the mean distance of 320 ± 26 measured by Gaia. The VLBA observations toward NGC 1333 are insufficient to claim a successful distance measurement to this cluster. Gaia parallaxes, on the other hand, yield a mean distance of 293 ± 22 pc. Hence, the distance along the line of sight between the eastern and western edges of the cloud is ∼30 pc, which is significantly smaller than previously inferred. We use Gaia proper motions and published radial velocities to derive the spatial velocities of a selected sample of stars. The average velocity vectors with respect to the LSR are (u, v, w) = (−6.1±1.6, 6.8±1.1, −0.9±1.2) and (−6.4±1.0, 2.1±1.4, −2.4±1.0) km s −1 for IC 348 and NGC 1333, respectively. Finally, our analysis of the kinematics of the stars has shown that there is no clear evidence of expansion, contraction, or rotational motions within the clusters.

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