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Carbon Flux Phenology (CFP) can affect the interannual variation in Net Ecosystem Exchange (NEE) of carbon between terrestrial ecosystems and the atmosphere. In this study, we proposed a methodology to estimate CFP metrics with satellite-derived Land Surface Phenology (LSP) metrics and climate drivers for 4 biomes (i.e., deciduous broadleaf forest, evergreen needleleaf forest, grasslands and croplands), using 159 site-years of NEE and climate data from 32 AmeriFlux sites and MODIS vegetation index time-series data. LSP metrics combined with optimal climate drivers can explain the variability in Start of Carbon Uptake (SCU) by more than 70% and End of Carbon Uptake (ECU) by more than 60%. The Root Mean Square Error (RMSE) of the estimations was within 8.5 days for both SCU and ECU. The estimation performance for this methodology was primarily dependent on the optimal combination of the LSP retrieval methods, the explanatory climate drivers, the biome types, and the specific CFP metric. This methodology has a potential for allowing extrapolation of CFP metrics for biomes with a distinct and detectable seasonal cycle over large areas, based on synoptic multi-temporal optical satellite data and climate data. [ABSTRACT FROM AUTHOR]

Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem-scale CO2 exchange, in 14 models participating in the North American Carbon Program Site Synthesis. Model predictions were evaluated using long-term measurements (emphasizing the period 2000-2006) from 10 forested sites within the Ameri Flux and Fluxnet- Canada networks. In deciduous forests, almost all models consistently predicted that the growing season started earlier, and ended later, than was actually observed; biases of 2 weeks or more were typical. For these sites, most models were also unable to explain more than a small fraction of the observed interannual variability in phenological transition dates. Finally, for deciduous forests, misrepresentation of the seasonal cycle resulted in over-prediction of gross ecosystem photosynthesis by +160 ± 145 g C m−2 yr−1 during the spring transition period and +75 ± 130 g C m−2 yr−1 during the autumn transition period (13% and 8% annual productivity, respectively) compensating for the tendency of most models to under-predict the magnitude of peak summertime photosynthetic rates. Models did a better job of predicting the seasonality of CO2 exchange for evergreen forests. These results highlight the need for improved understanding of the environmental controls on vegetation phenology and incorporation of this knowledge into better phenological models. Existing models are unlikely to predict future responses of phenology to climate change accurately and therefore will misrepresent the seasonality and interannual variability of key biosphere-atmosphere feedbacks and interactions in coupled global climate models. [ABSTRACT FROM AUTHOR]

Quantifying the response of vegetation Net Primary Productivity (NPP) to phenological dynamics is critical to study climate change effects on ecosystem dynamics in the high-latitude, so investigating responses of NPP to phenological dynamics is becoming an increasing important way to identify and predict global ecosystem dynamics. In this study, we intend to quantifying the temporal trends and spatial variations of vegetation phenology and NPP across the Tibetan Plateau by calibrating and analyzing time series of the MODIS-derived normalized difference vegetation index (NDVI) during 2002–2012, and examining the mechanisms of vegetation NPP response to phenological dynamics over the plateau. Our results indicated that most of the plateau experienced a coninuous advancing trend in the beginning of vegetation growing season (BGS) and a delaying trend in the end of vegetation growing season (EGS), consequently a prolonged length of vegetation growing season (LGS). Accordingly, NPP also substantially increased in most parts of the plateau. Meanwhile, the spatial patterns of the BGS, EGS, LGS and NPP varied in accordcance with the heat and water gradient across the plateau. The response modes of the NPP to phenological shifs varied within different climatic regimes, and the spatiotemporal response patterns were primarily controlled by the local climatic and topographic conditions. Moreover, temperature and precipitation played different roles in diverse responses of NPP to phenological dynamics, implying a profound effect of climate on response mechanism of the NPP to phenological changes. [ABSTRACT FROM AUTHOR]