Date Published: November 28, 2016
Publisher: Public Library of Science
Author(s): Yang Fu, Zeyu Zheng, Haibo Shi, Rui Xiao, Wenping Yuan.
Vegetation phenology regulates many ecosystem processes and is an indicator of the biological responses to climate change. It is important to model the timing of leaf senescence accurately, since the canopy duration and carbon assimilation are strongly determined by the timings of leaf senescence. However, the existing phenology models are unlikely to accurately predict the end of the growing season (EGS) on large scales, resulting in the misrepresentation of the seasonality and interannual variability of biosphere–atmosphere feedbacks and interactions in coupled global climate models. In this paper, we presented a novel large-scale temperature dominated model integrated with the physiological adaptation of plants to the local temperature to assess the spatial pattern and interannual variability of the EGS. Our model was validated in all temperate vegetation types over the Northern Hemisphere. The results indicated that our model showed better performance in representing the spatial and interannual variability of leaf senescence, compared with the original phenology model in the Integrated Biosphere Simulator (IBIS). Our model explained approximately 63% of the EGS variations, whereas the original model explained much lower variations (coefficient of determination R2 = 0.01–0.18). In addition, the differences between the EGS reproduced by our model and the MODIS EGS at 71.3% of the pixels were within 10 days. For the original model, it is only 26.1%. We also found that the temperature threshold (TcritTm) of grassland was lower than that of woody species in the same latitudinal zone.
Vegetation phenology plays a crucial role in regulating the exchanges of carbon, water and energy between the terrestrial ecosystems and the atmosphere[1–3]. Previous studies have revealed that the canopy duration and carbon assimilation are strongly determined by the timings of leaf senescence[4–6], which exhibits an increasingly delaying trend and has been related to a longer carbon uptake period in the context of global warming [7–9]. Therefore, it is of great significance to be able to accurately model the timing of leaf senescence, especially for determining the autumnal pattern of the net ecosystem carbon exchange[10, 11].
The EGS simulated by our model are better agreed to the satellite-derived EGS, compared to those calculated by the original phenology model in IBIS (Fig 3). An early EGS was found in the boreal and cool regions, intermediate EGS in the temperate regions and late EGS in the warm regions. In terms of the spatial patterns of the mean absolute error (RA), our model outperformed the original model (Fig 4). The results indicated lower RA of our simulations in most of the boreal and cool regions, for which the RA was less than 10 days (Fig 4b). In contrast, the results of the original model delayed the timing of the EGS by 10–30 days compared with the MODIS EGS in the boreal and cool regions and predicted an earlier EGS of 30–90 days compared with the MODIS EGS in the woody savanna and open shrub areas of low latitudes (Fig 4a). Furthermore, the calibrated temperature threshold (TcritTm) in our phenology model exhibited obvious spatial variations in the Northern Hemisphere (Fig 5). The result indicated that the temperature threshold was approximately 7–9°C and exhibited an increasing trend from north to south in the Northern Hemisphere. In the same latitudinal zone, the temperature threshold (TcritTm) of grassland was lower than that of woody species.
Vegetation phenology serves a crucial function in regulating many ecosystem processes and is a key indicator of the biological responses to climate change. Predicting the impact of changing phenology on terrestrial ecosystems requires an accurate phenology model. In this study, we presented a novel large-scale temperature dominated phenology model and showed that this model provided more accurate prediction of EGS compared to the original phenology model. Our phenology model outperforms the original model by using the mean annual temperature to determine the minimum temperature threshold. Vegetation phenology is the optimization of the plant activity and reproduction resulting from natural selection. Plant species have adapted their temperature requirements to their local temperature environment[52–54]. Thus it is essential to integrate the physiological adaptation of plants to the local temperature into the phenology models and improve model performance at the global scale.
This study presented a novel large-scale temperature dominated model for predicting the end of the growing season and compared the performances of our model with the original phenology model which has been integrated into the Integrated Biosphere Simulator (IBIS). The results indicated that the novel large-scale temperature dominated phenology model explained most of the EGS variations over the Northern Hemisphere and greatly improves the accuracy compared with the original model. When spatially averaged, predictions of our phenology model exhibited very good agreement with mean annual dates of leaf senescence. We consider the novel large-scale temperature dominated model to be a primary tool for predicting leaf senescence.