Vegetation structure and phenology primarily shape the spatiotemporal pattern of ecosystem respiration
Abstract Accurate estimation of terrestrial ecosystem respiration (TER) is essential for refining global carbon budgets. Current large-scale TER models rely on empirical structures derived from site-scale observations, often driven solely by hydrothermal factors. However, incorporating ecosystem-sca...
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Nature Portfolio
2025-03-01
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| Series: | Communications Earth & Environment |
| Online Access: | https://doi.org/10.1038/s43247-025-02240-1 |
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| author | Cenliang Zhao Wenquan Zhu |
| author_facet | Cenliang Zhao Wenquan Zhu |
| author_sort | Cenliang Zhao |
| collection | DOAJ |
| description | Abstract Accurate estimation of terrestrial ecosystem respiration (TER) is essential for refining global carbon budgets. Current large-scale TER models rely on empirical structures derived from site-scale observations, often driven solely by hydrothermal factors. However, incorporating ecosystem-scale information is critical for more accurate large-scale TER modeling. Such ecosystem-scale variables have not been well parameterized, since the mechanisms by which they affect TER remain unclear. To address this gap, here we developed a Causality constrained Interpretable Machine Learning model for TER estimation (named “CIML-TER”) which consider the ecosystem-scale information. CIML-TER exhibited higher estimation accuracy (reducing relative mean absolute error by approximately 15%) and overcame the “artificial discontinuities” phenomenon of traditional models. Meanwhile, we quantitatively revealed that although environmental factors, such as temperature and water, were still the dominant drivers of TER (contributing ~44.15% of global TER variability), biotic factors (e.g., vegetation structure, ~25.91%) and spatiotemporal variation factors (e.g., land cover and phenology, ~29.94%) were also critical. |
| format | Article |
| id | doaj-art-315292cef0e94e4e9ebd3add69c8638c |
| institution | OA Journals |
| issn | 2662-4435 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Earth & Environment |
| spelling | doaj-art-315292cef0e94e4e9ebd3add69c8638c2025-08-20T01:54:30ZengNature PortfolioCommunications Earth & Environment2662-44352025-03-016111510.1038/s43247-025-02240-1Vegetation structure and phenology primarily shape the spatiotemporal pattern of ecosystem respirationCenliang Zhao0Wenquan Zhu1State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal UniversityState Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal UniversityAbstract Accurate estimation of terrestrial ecosystem respiration (TER) is essential for refining global carbon budgets. Current large-scale TER models rely on empirical structures derived from site-scale observations, often driven solely by hydrothermal factors. However, incorporating ecosystem-scale information is critical for more accurate large-scale TER modeling. Such ecosystem-scale variables have not been well parameterized, since the mechanisms by which they affect TER remain unclear. To address this gap, here we developed a Causality constrained Interpretable Machine Learning model for TER estimation (named “CIML-TER”) which consider the ecosystem-scale information. CIML-TER exhibited higher estimation accuracy (reducing relative mean absolute error by approximately 15%) and overcame the “artificial discontinuities” phenomenon of traditional models. Meanwhile, we quantitatively revealed that although environmental factors, such as temperature and water, were still the dominant drivers of TER (contributing ~44.15% of global TER variability), biotic factors (e.g., vegetation structure, ~25.91%) and spatiotemporal variation factors (e.g., land cover and phenology, ~29.94%) were also critical.https://doi.org/10.1038/s43247-025-02240-1 |
| spellingShingle | Cenliang Zhao Wenquan Zhu Vegetation structure and phenology primarily shape the spatiotemporal pattern of ecosystem respiration Communications Earth & Environment |
| title | Vegetation structure and phenology primarily shape the spatiotemporal pattern of ecosystem respiration |
| title_full | Vegetation structure and phenology primarily shape the spatiotemporal pattern of ecosystem respiration |
| title_fullStr | Vegetation structure and phenology primarily shape the spatiotemporal pattern of ecosystem respiration |
| title_full_unstemmed | Vegetation structure and phenology primarily shape the spatiotemporal pattern of ecosystem respiration |
| title_short | Vegetation structure and phenology primarily shape the spatiotemporal pattern of ecosystem respiration |
| title_sort | vegetation structure and phenology primarily shape the spatiotemporal pattern of ecosystem respiration |
| url | https://doi.org/10.1038/s43247-025-02240-1 |
| work_keys_str_mv | AT cenliangzhao vegetationstructureandphenologyprimarilyshapethespatiotemporalpatternofecosystemrespiration AT wenquanzhu vegetationstructureandphenologyprimarilyshapethespatiotemporalpatternofecosystemrespiration |