## 1 Introduction  
The timing of plant canopy phenological events is an important indicator of the temporal and spatial variability of ecosystem-atmosphere fluxes [1,2]. Therefore, efforts have focused on understanding the impacts of phenological transitions on carbon (C) sequestration both at the plot level and on a continental scale [3, 4, 5]. Interannual variability of net ecosystem production (NEP), the difference between gross primary production (GPP) and ecosystem respiration (\(R_{e}\)), is regulated by both biotic (e.g., GPP, stand age) and abiotic (e.g., precipitation, temperature) variables [6,7]. However, annual NEP is also dependent on the seasonal variation of other variables, such as spring temperature and growing season length (GSL) [8, 9, 10, 11, 12]. Higher spring temperatures tend to increase annual NEP in various ecosystems, likely due to the earlier onset of canopy greenness [13,14]. In contrast, autumn warming would have a negative influence on annual NEP if ecosystem respiration rates were more sensitive to temperature changes [15,16]. These results imply that seasonal changes in climate are important indicators of the annual NEP, as these changes can shift phenological transitions and consequently affect plant growth rhythm. Various phenological indicators derived from diverse datasets have been used in previous studies. Among these, carbon flux-based phenology (CFP) has recently been used widely. These phenological indicators include the onset and end of the carbon-uptake period (CUP) (_i.e._, the period of net carbon uptake from the atmosphere) [1,2,9,17, 18, 19, 20]. Spring temperature (mean values from March to May) has also been used to indicate the onset of the growing season and the annual NEP [3,13]. However, flux-based phenology is limited by the availability of flux data (_i.e._, spatial representativeness), as well as the distributions and footprints of the towers [17]. Although many flux networks, such as AmeriFlux and Fluxnet-Canada, have been established, data from these networks provide critically useful but spatially limited information for global applications. Satellite data have been utilized as an alternative for the capture of phenological transitions at regional, continental, and global scales [20]. Fitted curves for vegetation index (VI) time series are used (e.g., determining the transition dates from the local maxima and minima in the fitted function), including the enhanced vegetation index (EVI) [4,18,21], the normalized difference vegetation index (NDVI) [2,20,22], and the MERIS Terrestrial Chlorophyll Index (MTCI) [23]. The advantage of remote-sensing data is that they are uniquely spatially explicit, and are useful for evaluating and validating models and assumptions with a wider spatial coverage compared to flux measurements. Furthermore, the results presented by [PERSON] and [PERSON] [24] indicate a good general consensus among different spatial datasets of satellite-generated interannual phenology features, supporting the effectiveness of remote-sensing data for monitoring forest responses to global-scale climate variability [25]. As demonstrated by [PERSON] _et al._[4], the relative strengths and weaknesses of phenological indicators must be identified and compared. This is a necessary step for the incorporation of these indicators into ecosystem models, to better interpret annual C fluxes. Furthermore, it is vital to understand the effects of plant functional types on the relationship between C fluxes and phenologicalindicators, which is significant when scaling up these relationships. Here we present a comparison of the predictive strength of several spring phenological indicators for annual GPP and NEP in boreal regions of Canada, where climate warming has been suggested to be the greatest worldwide during the several past decades [14].