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Annals of Forest Science

, 76:92 | Cite as

Precipitation mediates the temporal dynamics of net primary productivity and precipitation use efficiency in China’s northern and southern forests

  • Jian Sun
  • Tiancai ZhouEmail author
  • Wenpeng Du
  • Yanqiang Wei
Research Paper

Abstract

Key message

Precipitation mediates the dynamic of net primary productivity and precipitation use efficiency across the North-South Transect forests of China, which may result from an increase of productivity in warm temperate deciduous broad-leaved forests or a decrease of precipitation use efficiency in temperate coniferous broad-leaved mixed forests.

Context

Precipitation use efficiency (PUE), the ratio of net primary productivity (NPP) to annual precipitation, is one of the key factors that can clarify the response of forest ecosystem carbon and water cycles to ongoing climate change.

Aims

To investigate large-scale patterns of NPP and PUE, and to determine how NPP and PUE would respond to climate and soil variables across the North-South Transect forests (TNSTF) of China.

Methods

We revealed the spatial pattern dynamics of NPP and PUE in the TNSTF from 2000 to 2010 employing MOD17 NPP data and further explored the responses of NPP and PUE to environment factors across the TNSTF. Additionally, the temporal dynamics of NPP and PUE in different forest types and their dependencies on climate variation were investigated.

Results

The results indicated that NPP increased from 2000 to 2010 in most regions across the TNSTF. The spatial distribution pattern of NPP was mainly correlated with climate factors in the TNSTF rather than soil properties. Spatially, an increased trend of PUE (2000–2010) was found in the south and decreased PUE was revealed in the north of the TNSTF. In addition, the spatial distribution of PUE in the TNSTF was associated with both climate and soil factors. For different forests, only the NPP in warm temperate deciduous broad-leaved forests significantly increased (2000–2010, R2 = 0.33, P < 0.05) due to the increase in precipitation (R2 = 0.82, P < 0.0005). Moreover, only the PUE in temperate coniferous broad-leaved mixed forests presented a significantly decreasing trend (2000–2010, R2 = 0.38, P < 0.05), which was significantly negatively correlated with precipitation (R2 = 0.80, P < 0.0005).

Conclusion

Our findings demonstrated that climate governed the spatial distribution of NPP; in addition to the climate, soil properties also played an important role in shaping the spatial distribution of PUE. Our findings highlight that the dynamics of precipitation rather than those of temperature mediated the variations in NPP and PUE in forests across the TNSTF.

Keywords

Precipitation use efficiency Net primary production Climate Forest ecosystem The north-south transect China 

Notes

Funding information

This research was funded by the National Natural Science Foundation of China (grant no. 41871040, 41501057 and 41661144045), and West Light Foundation of the Chinese Academy of Sciences.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© INRA and Springer-Verlag France SAS, part of Springer Nature 2019

Authors and Affiliations

  • Jian Sun
    • 1
    • 2
  • Tiancai Zhou
    • 1
    • 3
    • 4
    Email author
  • Wenpeng Du
    • 1
    • 3
  • Yanqiang Wei
    • 5
  1. 1.Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  2. 2.State Key Laboratory of Urban and Regional Ecology, Research Center for Eco–environmental SciencesChinese Academy of SciencesBeijingChina
  3. 3.College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijingChina
  4. 4.Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  5. 5.Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhouPeople’s Republic of China

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