Quantitative assessment of spatiotemporal variations and drivers of gross primary productivity in tropical ecosystems at higher resolution
Climate change significantly impacts vegetation gross primary productivity (GPP), yet uncertainties persist in the carbon cycle of tropical terrestrial ecosystems due to incomplete consideration of productivity drivers and lag effects. To address this, we developed a remote sensing-based process mod...
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Elsevier
2024-12-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843224006046 |
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| author | Ruize Xu Jiahua Zhang Fang Chen Bo Yu Shawkat Ali Hidayat Ullah Ali Salem Al-Sakkaf |
| author_facet | Ruize Xu Jiahua Zhang Fang Chen Bo Yu Shawkat Ali Hidayat Ullah Ali Salem Al-Sakkaf |
| author_sort | Ruize Xu |
| collection | DOAJ |
| description | Climate change significantly impacts vegetation gross primary productivity (GPP), yet uncertainties persist in the carbon cycle of tropical terrestrial ecosystems due to incomplete consideration of productivity drivers and lag effects. To address this, we developed a remote sensing-based process model by integrating high-resolution vegetation indices and multi-layer soil hydrological module, to simulate monthly GPP at a 30 m resolution across Hainan Island from 2000 to 2020. The finer GPP can capture more spatial details and show higher accuracy at site scales (R = 0.79 and NRMSE = 14.79 %). Trend analysis and Hurst exponent were used to reveal spatiotemporal dynamics and sustainability of GPP. Meanwhile, nonlinear Granger causality tests quantified both concurrent and lagged correlations between various environmental factors and GPP. The results indicated significant GPP increases across 98.5 % of vegetated areas, with an annual rise of 437.02 g C/m2, and a marked improvement in trends around 2011. Future projections suggest sustained high GPP sustainability (Hurst = 0.53), and reducing “positive-inconsistent” areas in the northeast and southwest is crucial for enhancing local carbon sinks. Furthermore, water availability, temperature, and radiation were primary drivers of GPP changes, affecting 53.55 %, 27.77 %, and 14.43 % of vegetated areas, respectively, with their compounded effects enhancing explanatory power by 35.84 %. Relative humidity dominated water availability impacts on GPP (10.02 % to 79.98 % variation), surpassing precipitation and soil moisture impacts. Lag effects were observed in 68.83 % of vegetated areas, with 1 to 4-month delays in responses to net solar radiation and surface temperature, especially in forest and shrubland ecosystems. This study provides deeper insights into fine-scale GPP simulations and analysis of climate interactions, which are crucial for effective carbon cycle management in tropical ecosystems. |
| format | Article |
| id | doaj-art-e7b5792614fe4e00aa997b872b4ed0fa |
| institution | DOAJ |
| issn | 1569-8432 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj-art-e7b5792614fe4e00aa997b872b4ed0fa2025-08-20T02:52:23ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322024-12-0113510424810.1016/j.jag.2024.104248Quantitative assessment of spatiotemporal variations and drivers of gross primary productivity in tropical ecosystems at higher resolutionRuize Xu0Jiahua Zhang1Fang Chen2Bo Yu3Shawkat Ali4Hidayat Ullah5Ali Salem Al-Sakkaf6Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, China; Remote Sensing and Digital Earth Research Center, College of Computer Science & Technology, Qingdao University, Qingdao 266071, ChinaKey Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; University of Chinese Academy of Sciences, Beijing 100049, China; Corresponding author at: No.9 Dengzhuang South Road, Haidian District, Beijing 100094, China.Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaRemote Sensing and Digital Earth Research Center, College of Computer Science & Technology, Qingdao University, Qingdao 266071, ChinaRemote Sensing and Digital Earth Research Center, College of Computer Science & Technology, Qingdao University, Qingdao 266071, ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, ChinaClimate change significantly impacts vegetation gross primary productivity (GPP), yet uncertainties persist in the carbon cycle of tropical terrestrial ecosystems due to incomplete consideration of productivity drivers and lag effects. To address this, we developed a remote sensing-based process model by integrating high-resolution vegetation indices and multi-layer soil hydrological module, to simulate monthly GPP at a 30 m resolution across Hainan Island from 2000 to 2020. The finer GPP can capture more spatial details and show higher accuracy at site scales (R = 0.79 and NRMSE = 14.79 %). Trend analysis and Hurst exponent were used to reveal spatiotemporal dynamics and sustainability of GPP. Meanwhile, nonlinear Granger causality tests quantified both concurrent and lagged correlations between various environmental factors and GPP. The results indicated significant GPP increases across 98.5 % of vegetated areas, with an annual rise of 437.02 g C/m2, and a marked improvement in trends around 2011. Future projections suggest sustained high GPP sustainability (Hurst = 0.53), and reducing “positive-inconsistent” areas in the northeast and southwest is crucial for enhancing local carbon sinks. Furthermore, water availability, temperature, and radiation were primary drivers of GPP changes, affecting 53.55 %, 27.77 %, and 14.43 % of vegetated areas, respectively, with their compounded effects enhancing explanatory power by 35.84 %. Relative humidity dominated water availability impacts on GPP (10.02 % to 79.98 % variation), surpassing precipitation and soil moisture impacts. Lag effects were observed in 68.83 % of vegetated areas, with 1 to 4-month delays in responses to net solar radiation and surface temperature, especially in forest and shrubland ecosystems. This study provides deeper insights into fine-scale GPP simulations and analysis of climate interactions, which are crucial for effective carbon cycle management in tropical ecosystems.http://www.sciencedirect.com/science/article/pii/S1569843224006046Gross primary productivityEnvironmental factorsRemote sensing-based process modelTime-lagged effectTropical vegetation |
| spellingShingle | Ruize Xu Jiahua Zhang Fang Chen Bo Yu Shawkat Ali Hidayat Ullah Ali Salem Al-Sakkaf Quantitative assessment of spatiotemporal variations and drivers of gross primary productivity in tropical ecosystems at higher resolution International Journal of Applied Earth Observations and Geoinformation Gross primary productivity Environmental factors Remote sensing-based process model Time-lagged effect Tropical vegetation |
| title | Quantitative assessment of spatiotemporal variations and drivers of gross primary productivity in tropical ecosystems at higher resolution |
| title_full | Quantitative assessment of spatiotemporal variations and drivers of gross primary productivity in tropical ecosystems at higher resolution |
| title_fullStr | Quantitative assessment of spatiotemporal variations and drivers of gross primary productivity in tropical ecosystems at higher resolution |
| title_full_unstemmed | Quantitative assessment of spatiotemporal variations and drivers of gross primary productivity in tropical ecosystems at higher resolution |
| title_short | Quantitative assessment of spatiotemporal variations and drivers of gross primary productivity in tropical ecosystems at higher resolution |
| title_sort | quantitative assessment of spatiotemporal variations and drivers of gross primary productivity in tropical ecosystems at higher resolution |
| topic | Gross primary productivity Environmental factors Remote sensing-based process model Time-lagged effect Tropical vegetation |
| url | http://www.sciencedirect.com/science/article/pii/S1569843224006046 |
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