ArticleApplications in plant sciences2019
Testing Hopkins' Bioclimatic Law with PhenoCam data.
Article in Applications in plant sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Opportunistic plant observations reveal spatial and temporal gradients in phenology.npj biodiversity · 2024Article
- Contrasting phenology responses to climate warming across the northern extra-tropics.Fundamental research · 2022Article
- Long-term standardized forest phenology in Sweden: a climate change indicator.International journal of biometeorology · 2021Article
- Seasonal variation in the canopy color of temperate evergreen conifer forests.The New phytologist · 2021Article
- How did the characteristics of the growing season change during the past 100 years at a steep river basin in Japan?PloS one · 2021Article
- Spatiotemporal Variation ofFrontiers in plant science · 2021Article
- Peak autumn leaf colouring along latitudinal and elevational gradients in Japan evaluated with online phenological data.International journal of biometeorology · 2020Article
- Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset.Scientific data · 2019Article
- Testing Hopkins' Bioclimatic Law with PhenoCam data.Applications in plant sciences · 2019Article
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4 authors.
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Abstract
premise of the studyWe investigated the spatial and temporal patterns of vegetation phenology with phenometrics derived from PhenoCam imagery. Specifically, we evaluated the Bioclimatic Law proposed by Hopkins, which relates phenological transitions to latitude, longitude, and elevation.
methods"Green-up" and "green-down" dates-representing the start and end of the annual cycles of vegetation activity-were estimated from measures of canopy greenness calculated from digital repeat photography. We used data from 65 deciduous broadleaf (DB) forest sites, 18 evergreen needleleaf (EN) forest sites, and 21 grassland (GR) sites.
resultsDB green-up dates were well correlated with mean annual temperature and varied along spatial gradients consistent with the Bioclimatic Law. Interannual variation in DB phenology was most strongly associated with temperature anomalies during a relatively narrow window of time. EN phenology was not well correlated with either climatic factors or spatial gradients, but similar to DB phenology, interannual variation was most closely associated with temperature anomalies. For GR sites, mean annual precipitation explained most of the spatial variation in the duration of vegetation activity, whereas both temperature and precipitation anomalies explained interannual variation in phenology. DISCUSSION: PhenoCam data provide an objective and consistent means by which spatial and temporal patterns in vegetation phenology can be investigated.
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