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. ResultsDBgreen‐up dates were well correlated with mean annual temperature and varied along spatial gradients consistent with the Bioclimatic Law. Interannual variation inDBphenology was most strongly associated with temperature anomalies during a relatively narrow window of time.ENphenology was not well correlated with either climatic factors or spatial gradients, but similar toDBphenology, interannual variation was most closely associated with temperature anomalies. ForGRsites, 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. DiscussionPhenoCam data provide an objective and consistent means by which spatial and temporal patterns in vegetation phenology can be investigated.
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Decentralised Robust Inverter-based Control in Power Systems * *This work was supported by the Swedish Research Council through the LCCC Linnaeus Center, NSF CPS grant CNS 1544771, Johns Hopkins E2SHI Seed Grant, and Johns Hopkins WSE startup funds
- Award ID(s):
- 1544771
- PAR ID:
- 10111364
- Date Published:
- Journal Name:
- IFAC-PapersOnLine
- Volume:
- 50
- Issue:
- 1
- ISSN:
- 2405-8963
- Page Range / eLocation ID:
- 5548 to 5553
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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