Importance of the antecedent environmental factors’ memory effects on the temporal variation of terrestrial gross primary productivity
Quantitative estimation of temporal variation in ecosystem productivity is crucial for assessing the stability and sustainability of ecosystem carbon sinks. However, current assessments of temporal variation of gross primary productivity (GPP) suffer from inaccuracies due to oversight of the memory...
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Elsevier
2025-06-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X25004881 |
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| author | Weihua Liu Lili Feng Zhongen Niu Yan Lv Mengyu Zhang |
| author_facet | Weihua Liu Lili Feng Zhongen Niu Yan Lv Mengyu Zhang |
| author_sort | Weihua Liu |
| collection | DOAJ |
| description | Quantitative estimation of temporal variation in ecosystem productivity is crucial for assessing the stability and sustainability of ecosystem carbon sinks. However, current assessments of temporal variation of gross primary productivity (GPP) suffer from inaccuracies due to oversight of the memory effect of GPP on antecedent environmental and vegetation changes. By introducing memory effect into a time-dependent deep learning model, we investigated the responses of GPP to antecedent environmental and vegetation factors, and further simulated and analyzed the temporal trend and interannual variation of GPP at site and spatial scales. Our results indicate that (i) incorporating memory effect significantly improves the explanatory power of environmental and vegetation factors on GPP magnitude, trend, and interannual variation compared to the model ignoring memory effect; (ii) the memory effect length of GPP response to antecedent environmental and vegetation factors varies across different ecosystems, ranging from 4 to 11 months. Precipitation has a longer cumulative effect on GPP compared to temperature, shortwave radiation and VPD (Vapor Pressure Deficit) in most ecosystems. The impact of NDVI (Normalized Difference Vegetation Index) on GPP was stronger than environmental variables, emphasizing the significance of vegetation state in GPP simulation; (iii) the global terrestrial ecosystem GPP estimated by the deep learning model considering memory effect showed an increasing trend and significant interannual variation from 1983 to 2015. This study enhanced the understanding on the driving mechanisms of antecedent environmental and vegetation factors on GPP and provided a reference for modeling of carbon cycle process. |
| format | Article |
| id | doaj-art-1a405b5c24cd461bac78f29ee5ec9d54 |
| institution | DOAJ |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-1a405b5c24cd461bac78f29ee5ec9d542025-08-20T03:12:32ZengElsevierEcological Indicators1470-160X2025-06-0117511355810.1016/j.ecolind.2025.113558Importance of the antecedent environmental factors’ memory effects on the temporal variation of terrestrial gross primary productivityWeihua Liu0Lili Feng1Zhongen Niu2Yan Lv3Mengyu Zhang4College of JunCao Science and Ecology, Fujian Agriculture and Forestry University, Fuzhou 350002, ChinaResearch Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China; Corresponding author.School of Resources and Environmental Engineering, Ludong University, Yantai 264025, ChinaSchool of Civil Engineering and Geomatics, Shandong University of Technology, Zibo 255000, ChinaKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaQuantitative estimation of temporal variation in ecosystem productivity is crucial for assessing the stability and sustainability of ecosystem carbon sinks. However, current assessments of temporal variation of gross primary productivity (GPP) suffer from inaccuracies due to oversight of the memory effect of GPP on antecedent environmental and vegetation changes. By introducing memory effect into a time-dependent deep learning model, we investigated the responses of GPP to antecedent environmental and vegetation factors, and further simulated and analyzed the temporal trend and interannual variation of GPP at site and spatial scales. Our results indicate that (i) incorporating memory effect significantly improves the explanatory power of environmental and vegetation factors on GPP magnitude, trend, and interannual variation compared to the model ignoring memory effect; (ii) the memory effect length of GPP response to antecedent environmental and vegetation factors varies across different ecosystems, ranging from 4 to 11 months. Precipitation has a longer cumulative effect on GPP compared to temperature, shortwave radiation and VPD (Vapor Pressure Deficit) in most ecosystems. The impact of NDVI (Normalized Difference Vegetation Index) on GPP was stronger than environmental variables, emphasizing the significance of vegetation state in GPP simulation; (iii) the global terrestrial ecosystem GPP estimated by the deep learning model considering memory effect showed an increasing trend and significant interannual variation from 1983 to 2015. This study enhanced the understanding on the driving mechanisms of antecedent environmental and vegetation factors on GPP and provided a reference for modeling of carbon cycle process.http://www.sciencedirect.com/science/article/pii/S1470160X25004881Memory effectGross primary productivityTrendInterannual variationGlobal terrestrial ecosystem |
| spellingShingle | Weihua Liu Lili Feng Zhongen Niu Yan Lv Mengyu Zhang Importance of the antecedent environmental factors’ memory effects on the temporal variation of terrestrial gross primary productivity Ecological Indicators Memory effect Gross primary productivity Trend Interannual variation Global terrestrial ecosystem |
| title | Importance of the antecedent environmental factors’ memory effects on the temporal variation of terrestrial gross primary productivity |
| title_full | Importance of the antecedent environmental factors’ memory effects on the temporal variation of terrestrial gross primary productivity |
| title_fullStr | Importance of the antecedent environmental factors’ memory effects on the temporal variation of terrestrial gross primary productivity |
| title_full_unstemmed | Importance of the antecedent environmental factors’ memory effects on the temporal variation of terrestrial gross primary productivity |
| title_short | Importance of the antecedent environmental factors’ memory effects on the temporal variation of terrestrial gross primary productivity |
| title_sort | importance of the antecedent environmental factors memory effects on the temporal variation of terrestrial gross primary productivity |
| topic | Memory effect Gross primary productivity Trend Interannual variation Global terrestrial ecosystem |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X25004881 |
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