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Mountain goats use steep terrain to avoid predators, but this exposes them to snow avalanches. Kevin White presents long-term research on the natural history and population ecology of mountain goats in coastal Alaska, focusing on how avalanches alter landscapes and wildlife populations. These extreme events can cause declines that take more than a generation to reverse, linking mountain-wildlife persistence to climate-related hazards. The interdisciplinary studies involve snow scientists and collaborators in Alaska, Canada and Switzerland.
Thu, Nov 5 · 20:00 UTC · Online
Sanne Evers introduces the first forecasting challenge organized by the European Ecological Forecasting Initiative. The challenge uses long-running observations from Doñana National Park in southern Spain to support short-term predictions of vegetation indices and the abundance of multiple shrub species. Forecasting these changes can inform habitat management, productivity assessments and conservation decisions under climatic and hydrological pressures. The seminar explains why Doñana’s range of habitats and monitoring infrastructure offer a useful setting for comparing predictions before new observations become available. It also discusses lessons from developing the challenge and planned next steps, with participation encouraged across ecological disciplines and levels of forecasting experience.
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After more than 4 million deaths worldwide, the ongoing vaccination to conquer the COVID-19 disease is now competing with the emergence of increasingly contagious mutations, repeatedly supplanting earlier strains. Following the near-absence of historical examples of the long-time evolution of infectious diseases under similar circumstances, models are crucial to exemplify possible scenarios. Accordingly, in the present work we systematically generalize the popular susceptible-infected-recovered model to account for mutations leading to repeatedly occurring new strains, which we coarse grain based on tools from statistical mechanics to derive a model predicting the most likely outcomes. The model predicts that mutations can induce a super exponential growth of infection numbers at early times, which self-amplify to giant infection waves which are caused by a positive feedback loop between infection numbers and mutations and lead to a simultaneous infection of the majority of the population. At later stages -- if vaccination progresses too slowly -- mutations can interrupt an ongoing decrease of infection numbers and can cause infection revivals which occur as single waves or even as whole wave trains featuring alternative periods of decreasing and increasing infection numbers. Our results might be useful for discussions regarding the importance of a release of vaccine-patents to reduce the risk of mutation-induced infection revivals but also to coordinate the release of measures following a downwards trend of infection numbers.
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Natural selection affects not only selected alleles, but also indirectly affects all genes near selected sites on the genome. An increasing body of evidence suggests that this linked selection is an important driver of evolutionary dynamics throughout the genomes of many species, implying that we need to substantially revise our basic understanding of molecular evolution. This session brings together early-career researchers working towards a quantitative understanding of the prevalence and effects of linked selection.
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