dziwne-zwierzęta-oceaniczne: Season creep

Evidence: 100 • authority: 72

In phenology, season creep refers to observed changes in the timing of the seasons, such as earlier indications of spring widely observed in temperate areas across the Northern Hemisphere. Phenological records analyzed by climate scientists have shown significant temporal trends in the observed time of seasonal events, from the end of the 20th century and continuing into the 21st century. In Europe, season creep has been associated with the arrival of spring moving up by approximately one week in a recent 30-year period. Other studies have put the rate of season creep measured by plant phenology in the range of 2–3 days per decade advancement in spring, and 0.3–1.6 days per decade delay in…

Evidence: 41 • authority: 92

Evidence: 41 • authority: 72

Phenology is the study of periodic events in biological life cycles and how these are influenced by seasonal and interannual variations in climate, as well as habitat factors (such as elevation). Examples include the date of emergence of leaves and flowers, the first flight of butterflies, the first appearance of migratory birds, the date of leaf colouring and fall in deciduous trees, the dates of egg-laying of birds and amphibia, or the timing of the developmental cycles of temperate-zone honey bee colonies. In the scientific literature on ecology, the term is used more generally to indicate the time frame for any seasonal biological phenomena, including the dates of last appearance (e.g.,…

Evidence: 36 • authority: 92

Evidence: 35 • authority: 88

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Evidence: 27 • authority: 80

Evidence: 27 • authority: 80

Evidence: 27 • authority: 80

Evidence: 27 • authority: 80

Evidence: 24 • authority: 92

Petal to the metal: The slow road to automating large-scale phenology labeling for herbarium specimens.. Premise Herbarium specimens represent critical historical records of plant phenology, yet automating annotation of reproductive structures remains challenging given the diversity of floral morphologies, specimen age and quality, and image quality. Methods Here, we present a machine learning pipeline that uses an ensemble modeling approach to detect flowers on herbarium specimens and deliver these data to the phenology research community. After testing multiple strategies for generating training data, we found that in-house expert-curated annotations were essential for producing reliable…