Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by AE 60 days and in standard deviation by AE 20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground-or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS Correspondence: Michael A. White, tel. 1 1 435 797 3794, fax 1 1 435 797 187, trends could be detected for only 12% of North America and were divided between trends towards both earlier and later spring.

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While commonplace in other parts of the world, long-term and ongoing observations of the phenology of native tree species are rare in North America. We use 14 years of field survey data from the Hubbard Brook Experimental Forest to fit simple models of canopy phenology for three northern hardwood species, sugar maple (Acer saccharum), American beech (Fagus grandifolia), and yellow birch (Betula alleghaniensis). These models are then run with historical meteorological data to investigate potential climate change effects on phenology. Development and senescence are quantified using an index that ranges from 0 (dormant, no leaves) to 4 (full, green canopy). Sugar maple is the first species to leaf out in the spring, whereas American beech is the last species to drop its leaves in the fall. Across an elevational range from 250 to 825 m ASL, the onset of spring is delayed by 2.7 AE 0.4 days for every 100 m increase in elevation, which is in reasonable agreement with Hopkin's law. More than 90% of the variation in spring canopy development, and just slightly less than 90% of the variation in autumn canopy senescence, is accounted for by a logistic model based on accumulated degree-days. However, degree-day based models fit to Hubbard Brook data appear to overestimate the rate at which spring development occurs at the more southerly Harvard Forest. Autumn senescence at the Harvard Forest can be predicted with reasonable accuracy in sugar maple but not American beech. Retrospective modeling using five decades of Hubbard Brook daily mean temperature data suggests significant trends (P 0.05) towards an earlier spring (e.g. sugar maple, rate of change 5 0.18 days earlier/yr), consistent with other studies documenting measurable climate change effects on the onset of spring in both North America and Europe. Our results also suggest that green canopy duration has increased by about 10 days (e.g. sugar maple, rate of change 5 0.21 days longer/yr) over the period of study.