Research Article
Spatial patterns and climate controls of seasonal variations in carbon fluxes in China's terrestrial ecosystems

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Abstract

Seasonal changes in CO2 exchange determine the strength and dynamics of the carbon budget in terrestrial ecosystems. Knowledge about seasonal and spatial variations in carbon fluxes (net ecosystem productivity (NEP), gross primary productivity (GPP), and ecosystem respiration (RE)) is thus essential to support accurate modeling of carbon flux dynamics. To the best of our knowledge, this study represents the first comprehensive evaluation of how carbon fluxes vary seasonally in different ecoregions in China. Using eddy covariance measurements from ChinaFLUX, we analyzed the spatial variations and climate controls of the phenological and physiological properties of NEP, GPP, and RE across China. Apart from the beginning and ending day of NEP (net carbon uptake), the phenological properties of the carbon fluxes varied significantly with latitude; however, there were no evident trends in the physiological properties of the carbon fluxes with latitude (apart from the annual values of GPP and RE, known as AGPP and ARE). The spatial variation in the physiological properties of GPP and RE was influenced by the precipitation patterns, while the spatial distribution of the phenological properties of GPP and RE was related to air temperature. Moreover, the spatial variation for the end of the growing season changed with the autumn mean soil temperatures. The factors that contributed to the spatial distribution in the annual NEP (ANEP) and annual GPP and RE (AGPP and ARE) were quite different. The mean daily GPP and RE were the main contributors to the spatial variations in AGPP and ARE, while the net carbon uptake period was the main contributor to the spatial variation in ANEP. In this study, we identified a series of ecological parameters and reference values for seasonal patterns that can be used to validate models that simulate changes in regional carbon fluxes.

Introduction

Carbon dioxide exchange between terrestrial ecosystems and the atmosphere varies seasonally with changes in meteorological conditions and the physiological activity of vegetation. Seasonal dynamics in carbon fluxes (net ecosystem productivity (NEP), gross primary productivity (GPP), and ecosystem respiration (RE)) reveal the information of the length and magnitude of the active periods of photosynthesis and respiration, which determine carbon sequestration in ecosystems (Fu et al., 2017; Gu et al., 2009; Xia et al., 2015; Zhou et al., 2016) and play an important role in simulations of the carbon cycle (Baldocchi et al., 2005; Falge et al., 2002b). Without a clear understanding of the mechanisms that drive the spatial distribution of the seasonal variations and characteristics of NEP, GPP, and RE in different ecoregions, we cannot have confidence in our ability to accurately evaluate the terrestrial ecosystem carbon budget, either regionally or globally.

Numerous researchers have examined the environmental controls that drive seasonal variations in carbon fluxes by directly testing the relationships between daily or annual carbon fluxes and environmental factors (Barr et al., 2007; Dass et al., 2016; Yu et al., 2008; Zhao et al., 2010). However, environment may indirectly influence carbon fluxes through seasonal characteristics, such as the growing season length and the amplitude of carbon uptake. Recently, researchers have turned their attention to the spatial and temporal patterns of the seasonal characteristics of carbon fluxes, and have attempted to explain the interannual and spatial variations in carbon fluxes and their relationships with environmental factors (Fu et al., 2017; Xia et al., 2015; Zhou et al., 2016). For instance, two studies have shown that air temperature affects the onset of both photosynthesis and net carbon uptake (Fu et al., 2017; Tanja et al., 2003). The growing season length (GSL) and the amplitude of GPP (GPPmax), both influenced by meteorological changes, adequately explain the interannual variability in GPP in most areas of North America and the spatial variation in GPP at the global scale (Xia et al., 2015). The meteorological changes are closely related to the interannual variability in NEP via their effect on the net carbon uptake period (CUP) and the maximum value of NEP (NEPmax) (Fu et al., 2017).

There are three important conclusions of the dynamics of terrestrial ecosystem carbon budgets in different regions. First, the seasonal variations in carbon fluxes present different seasonal dynamics in different climate zones (Barr et al., 2007; Carswell et al., 2002; Goulden et al., 2004; Greco and Baldocchi, 1996; Hutyra et al., 2007; Saleska et al., 2003). Second, the seasonal patterns in the carbon fluxes in specific biomes are affected by multiple factors, such as the leaf area index (LAI) and phenology (the growth, development, and fading) of plants (Baldocchi et al., 2001; Fu et al., 2009), and seasonal shifts in both the environmental conditions and supply of resources (radiation intensity, temperature, humidity, soil moisture, and nutrients) (Aubinet et al., 2001; Stoy et al., 2005; Zhang et al., 2010). Third, the effects of climate and soil on the interannual and spatial variability of NEP, GPP, and RE are mediated by plant phenology and the amplitude of carbon fluxes (Fu et al., 2017; Xia et al., 2015; Zhou et al., 2016).

At regional and global scales, ecosystems correspond to the large climatic region where climatic conditions are relatively uniform. As the climate changes, so do the components of the ecosystem. Based on climatic conditions and the prevailing plant formations determined by those conditions, the continents can be classified into numerous ecoregions (Bailey, 2002). The ecosystems in different ecoregions follow principles that are similar to those mentioned above, but the seasonal variations in ecosystem carbon fluxes are inevitably different because of differences in ecosystem components and structure, environmental conditions, and resource supply status. Thus, the seasonal variations in ecosystem carbon fluxes in individual ecoregions, either for a region, continent, or worldwide, should be distinctive, which may be determined by biogeographic mechanisms. That is, the geographic patterns of the seasonal variations in carbon fluxes may be modulated by coupled environmental conditions and ecosystem properties. Therefore, by studying the seasonal patterns in NEP, GPP, and RE in different regions and quantitatively analysing the spatial variability in the vegetation phenology and physiological activities, we can identify the fundamental parameters for simulations of spatial and temporal variations in regional carbon budgets. This type of study may also result in a new method that uses biogeographic mechanisms to assess regional carbon budgets.

Information about carbon fluxes, measured directly over the long-term using the eddy covariance technique (Baldocchi et al., 1988; Yu et al., 2014; Yu et al., 2013), provides both the data source for assessing spatial and temporal variations in terrestrial ecosystem carbon sequestration and the opportunity to investigate seasonal patterns in the NEP, GPP, and RE of terrestrial ecosystems at regional, continental, or global scales, which might eventually lead to new methods for assessing large-scale carbon fluxes. China is an important net carbon sink (Tang et al., 2018), which absorbs carbon at a rate of 0.19–0.26 Pg yr−1 (Piao et al., 2009). Given China's contribution to global carbon cycling, using the ChinaFLUX dataset, we characterized the seasonal variations in NEP, GPP, and RE in its main ecoregions. We extracted information about phenological (e.g., the start, end, and length of the carbon exchange period) and physiological (e.g., the maximum, mean, and annual values of daily carbon fluxes) properties that were related to the seasonal dynamics in ecosystem carbon fluxes, and then analyzed the spatial variations, and the factors behind changes, in the phenological and physiological properties of NEP, GPP, and RE.

Section snippets

Classification of ecoregions

Using the ecological region classification of China proposed by Fu et al. (2001) as a guide, we grouped China into ten ecoregions, namely tropical and seasonal rainforest, South Asian monsoon humid and semi-humid evergreen broad-leaved forest, subtropical evergreen broad-leaved forest, warm temperate humid and semi-humid deciduous broad-leaved forest, temperate humid coniferous and broad-leaved mixed forest, cold temperate humid coniferous forest, Qinghai-Tibet Plateau forest, Qinghai-Tibet

Seasonal variations in GPP, RE, and NEP

The seasonal patterns in GPP, RE, and NEP in the major ecoregions in China, obtained from the observation data, are shown in Fig. 3. For each ecoregion, the solid lines are the multi-year averaged values and reflect the average of the seasonal changes in GPP, RE, and NEP. The grey areas represent the interannual variability of the seasonal variations in GPP, RE, and NEP, which, to some degree, show both the sensitivity and the sensitive periods that the carbon fluxes respond to the interannual

Seasonal patterns in carbon fluxes for the major ecoregions

In this study, the seasonal variations and characteristics of GPP, RE, and NEP in terrestrial ecosystems across ten ecoregions in China were examined (Fig. 3, Table 1, Table 2, Table 3). The study sites consist of typical ecosystems that are distributed throughout these ecoregions in China, including meadow steppes, steppes, desert steppes, deserts, alpine meadows, and alpine meadow-steppe, which are distributed from the northeast China to the Qinghai-Tibet Plateau, and tropical seasonal rain

Declaration of Competing Interest

There are no conflicts of interest to declare.

Acknowledgements

This study was jointly supported by the National Key Research and Development Program of China (2016YFA0600104, 2016YFA0600103), National Natural Science Foundation of China (41671045, 31800406, 31600347), Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19020302), and the International Partnership Program of Chinese Academy of Sciences (121311KYSB20170004). We acknowledge all researchers who contributed to the eddy covariance flux measurements and provided valuable

References (56)

  • Y. Zhang et al.

    Respiration controls the unexpected seasonal pattern of carbon flux in an Asian tropical rain forest

    Atmos. Environ.

    (2010)
  • S. Zhou et al.

    Explaining inter-annual variability of gross primary productivity from plant phenology and physiology

    Agricultural and Forest Meteorology

    (2016)
  • A. Angert et al.

    Drier summers cancel out the CO2 uptake enhancement induced by warmer springs

  • M. Aubinet et al.

    Estimates of the annual net carbon and water exchange of forests: The EUROFLUX methodology

    Advances in Ecological Research

    (2000)
  • R.G. Bailey

    Ecoregion-Based Design for Sustainability

    (2002)
  • D.D. Baldocchi et al.

    Measuring biosphere-atmosphere exchanges of biologically related gases with micrometeorological methods

    Ecology

    (1988)
  • D. Baldocchi et al.

    Fluxnet: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities

    Bulletin of the American Meteorological Society

    (2001)
  • D.D. Baldocchi et al.

    Predicting the onset of net carbon uptake by deciduous forests with soil temperature and climate data: a synthesis of FLUXNET data

    International Journal of Biometeorology

    (2005)
  • A.G. Barr et al.

    Climatic controls on the carbon and water balances of a boreal aspen forest, 1994-2003

    Global Change Biology

    (2007)
  • F.E. Carswell et al.

    Seasonality in CO2 and H2O flux at an eastern Amazonian rain forest

    Journal of Geophysical Research

    (2002)
  • G. Churkina et al.

    Spatial analysis of growing season length control over net ecosystem exchange

    Glob. Chang. Biol.

    (2005)
  • P. Ciais et al.

    Europe-wide reduction in primary productivity caused by the heat and drought in 2003

    Nature

    (2005)
  • P. Dass et al.

    Environmental controls on the increasing GPP of terrestrial vegetation across northern Eurasia

    Biogeosciences

    (2016)
  • Y. Fracheboud et al.

    The Control of Autumn Senescence in European Aspen

    (2009)
  • B.J. Fu et al.

    Scheme of ecological regionalization in China

    Acta Ecol. Sin.

    (2001)
  • Y. Fu et al.

    Environmental influences on carbon dioxide fluxes over three grassland ecosystems in China

    Biogeosciences

    (2009)
  • M.L. Goulden et al.

    Exchange of carbon dioxide by a deciduous forest: Response to interannual climate variability

    Science

    (1996)
  • M.L. Goulden et al.

    Diel and seasonal patterns of tropical forest CO2 exchange

    Ecol. Appl.

    (2004)
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