• Energy Research

Climate change affects vegetation growth around the world. It has been recognized that the effect of climate change on vegetation growth exhibits hysteresis. However, the duration and intensity of time-lag effect of climate factors on vegetation growth is still difficult to quantify. We analyzed the impacts of climate on vegetation growth in 32 major cities of China from 2010 to 2016. Vegetation growth conditions were characterized using enhanced vegetation index (EVI) datasets from Moderate Resolution Imaging Spectrometer (MODIS). The climate data were extracted from the Daily Value Data Set of China Surface Climate Data (V3.0), including precipitation (PRE; mm), air temperature (TEM; oC), sunshine duration (SSD; h), humidity (RHU; %), and evapotranspiration (EVP; mm). We used the vector autoregressive model (VAR) to analyze the lagged effects of climate factors on EVI, predict vegetation responses to future global changes, and validate its accuracy. Results showed that RHU had the longest (6.13 ± 1.96 months) and strongest (median 0.34 EVI per unit RHU in the first lag period) time-lag effect on EVI, while EVP had the shortest (3.45 ± 1.09 months) and weakest (median −0.02 EVI per unit EVP in the first lag period) time-lag effect on EVI. The time-lag effects of PRE and SSD on EVI were stronger in the south than in the north. Meanwhile, the EVI predicted by the VAR model was highly consistent with the observed EVI (root mean squared error, RMSE < 0.08), and the prediction accuracy generally improved by 23.43% compared with the EVI predicted by the multiple linear regression model (MLR). Our study highlights the necessity of considering time-lag effects when exploring vegetation-climate interaction. The methods developed in this study can be used to reveal the lagged effects of climatic factors on vegetation growth and improve prediction of EVI dynamics under climate change.

Climate change affects vegetation growth around the world. It has been recognized that the effect of climate change on vegetation growth exhibits hysteresis. However, the duration and intensity of time-lag effect of climate factors on vegetation growth is still difficult to quantify. We analyzed the impacts of climate on vegetation growth in 32 major cities of China from 2010 to 2016. Vegetation growth conditions were characterized using enhanced vegetation index (EVI) datasets from Moderate Resolution Imaging Spectrometer (MODIS). The climate data were extracted from the Daily Value Data Set of China Surface Climate Data (V3.0), including precipitation (PRE; mm), air temperature (TEM; oC), sunshine duration (SSD; h), humidity (RHU; %), and evapotranspiration (EVP; mm). We used the vector autoregressive model (VAR) to analyze the lagged effects of climate factors on EVI, predict vegetation responses to future global changes, and validate its accuracy. Results showed that RHU had the longest (6.13 ± 1.96 months) and strongest (median 0.34 EVI per unit RHU in the first lag period) time-lag effect on EVI, while EVP had the shortest (3.45 ± 1.09 months) and weakest (median −0.02 EVI per unit EVP in the first lag period) time-lag effect on EVI. The time-lag effects of PRE and SSD on EVI were stronger in the south than in the north. Meanwhile, the EVI predicted by the VAR model was highly consistent with the observed EVI (root mean squared error, RMSE < 0.08), and the prediction accuracy generally improved by 23.43% compared with the EVI predicted by the multiple linear regression model (MLR). Our study highlights the necessity of considering time-lag effects when exploring vegetation-climate interaction. The methods developed in this study can be used to reveal the lagged effects of climatic factors on vegetation growth and improve prediction of EVI dynamics under climate change.

AbstractVegetation growth is affected by past growth rates and climate variability. However, the impacts of vegetation growth carryover (VGC; biotic) and lagged climatic effects (LCE; abiotic) on tree stem radial growth may be decoupled from photosynthetic capacity, as higher photosynthesis does not always translate into greater growth. To assess the interaction of tree‐species level VGC and LCE with ecosystem‐scale photosynthetic processes, we utilized tree‐ring width (TRW) data for three tree species: Castanopsis eyrei (CE), Castanea henryi (CH, Chinese chinquapin), and Liquidambar formosana (LF, Chinese sweet gum), along with satellite‐based data on canopy greenness (EVI, enhanced vegetation index), leaf area index (LAI), and gross primary productivity (GPP). We used vector autoregressive models, impulse response functions, and forecast error variance decomposition to analyze the duration, intensity, and drivers of VGC and of LCE response to precipitation, temperature, and sunshine duration. The results showed that at the tree‐species level, VGC in TRW was strongest in the first year, with an average 77% reduction in response intensity by the fourth year. VGC and LCE exhibited species‐specific patterns; compared to CE and CH (diffuse‐porous species), LF (ring‐porous species) exhibited stronger VGC but weaker LCE. For photosynthetic capacity at the ecosystem scale (EVI, LAI, and GPP), VGC and LCE occurred within 96 days. Our study demonstrates that VGC effects play a dominant role in vegetation function and productivity, and that vegetation responses to previous growth states are decoupled from climatic variability. Additionally, we discovered the possibility for tree‐ring growth to be decoupled from canopy condition. Investigating VGC and LCE of multiple indicators of vegetation growth at multiple scales has the potential to improve the accuracy of terrestrial global change models.

AbstractVegetation growth is affected by past growth rates and climate variability. However, the impacts of vegetation growth carryover (VGC; biotic) and lagged climatic effects (LCE; abiotic) on tree stem radial growth may be decoupled from photosynthetic capacity, as higher photosynthesis does not always translate into greater growth. To assess the interaction of tree‐species level VGC and LCE with ecosystem‐scale photosynthetic processes, we utilized tree‐ring width (TRW) data for three tree species: Castanopsis eyrei (CE), Castanea henryi (CH, Chinese chinquapin), and Liquidambar formosana (LF, Chinese sweet gum), along with satellite‐based data on canopy greenness (EVI, enhanced vegetation index), leaf area index (LAI), and gross primary productivity (GPP). We used vector autoregressive models, impulse response functions, and forecast error variance decomposition to analyze the duration, intensity, and drivers of VGC and of LCE response to precipitation, temperature, and sunshine duration. The results showed that at the tree‐species level, VGC in TRW was strongest in the first year, with an average 77% reduction in response intensity by the fourth year. VGC and LCE exhibited species‐specific patterns; compared to CE and CH (diffuse‐porous species), LF (ring‐porous species) exhibited stronger VGC but weaker LCE. For photosynthetic capacity at the ecosystem scale (EVI, LAI, and GPP), VGC and LCE occurred within 96 days. Our study demonstrates that VGC effects play a dominant role in vegetation function and productivity, and that vegetation responses to previous growth states are decoupled from climatic variability. Additionally, we discovered the possibility for tree‐ring growth to be decoupled from canopy condition. Investigating VGC and LCE of multiple indicators of vegetation growth at multiple scales has the potential to improve the accuracy of terrestrial global change models.

Les activités humaines et le climat sont deux facteurs clés affectant les processus hydrologiques et d'érosion des sols. Il est très important de comprendre leurs impacts sur les rejets d'eau et le transport des sédiments pour le développement durable des bassins versants, en particulier dans les régions subtropicales où les précipitations et les charges de sédiments sont élevées. Nous avons ici comparé la dynamique à long terme des rejets d'eau et du transport des sédiments dans quatre grands bassins versants contigus de la Chine subtropicale et exploré l'importance des principaux facteurs d'influence, notamment le climat, les ressources naturelles telles que la géologie et les activités humaines. Des différences significatives ont été observées entre les bassins versants en termes de sédiments et de rejets d'eau (p < 0,001). La comparaison par paires entre les quatre bassins a démontré des différences significatives dans le module des sédiments entre 5 des 6 paires (p < 0,05). Le module des sédiments dans le bassin de Lishui était significativement plus élevé que ceux des autres bassins, principalement en raison de la présence substantielle de pentes raides dans la région montagneuse, sujette à l'érosion des sols. Temporellement, le transport des sédiments dans les quatre bassins était bien synchronisé, montrant des tendances à la baisse significatives avec des points de changement brusques (p < 0,001). En revanche, aucune tendance et aucun point de changement brusque n'ont été détectés dans les rejets d'eau, principalement influencés par les précipitations. Les activités humaines ont joué un rôle prédominant dans la réduction du transport des sédiments (80% à 102%) par rapport à celles du climat (-2% à 19%) à travers les quatre bassins. De plus, notre étude a également montré que la couverture terrestre avait divers impacts indépendants du bassin sur le changement du transport des sédiments. Grâce à des comparaisons entre bassins des changements à long terme dans le débit d'eau et le transport des sédiments, notre étude a révélé les similitudes et les différences dans leurs mécanismes d'entraînement, fournissant des informations précieuses pour la planification de l'utilisation des terres et la gestion des ressources en eau dans les grands bassins subtropicaux. Las actividades humanas y el clima son dos factores clave que afectan los procesos hidrológicos y de erosión del suelo. Comprender sus impactos en la descarga de agua y el transporte de sedimentos es muy importante para el desarrollo sostenible de las cuencas hidrográficas, particularmente en regiones subtropicales con altas precipitaciones y altas cargas de sedimentos. Aquí comparamos la dinámica a largo plazo de la descarga de agua y el transporte de sedimentos en cuatro grandes cuencas hidrográficas contiguas en China subtropical y exploramos la importancia de los principales factores que influyen, incluidos el clima, la dotación de la naturaleza, como la geología, y las actividades humanas. Se han observado diferencias significativas entre las cuencas en términos de sedimento y descarga de agua (p < 0.001). La comparación por pares entre las cuatro cuencas demostró diferencias significativas en el módulo de sedimento entre 5 de los 6 pares (p < 0.05). El módulo de sedimentos en la cuenca de Lishui fue significativamente más alto que en otras cuencas, principalmente debido a la presencia sustancial de pendientes pronunciadas en la región montañosa, que es propensa a la erosión del suelo. Temporalmente, el transporte de sedimentos en las cuatro cuencas estuvo bien sincronizado mostrando tendencias decrecientes significativas con puntos de cambio abruptos (p < 0.001). Por el contrario, no se detectaron tendencias y puntos de cambio bruscos en la descarga de agua, influenciados principalmente por la precipitación. Las actividades humanas desempeñaron un papel predominante en la reducción del transporte de sedimentos (80% a 102%) en comparación con las del clima (-2% a 19%) en las cuatro cuencas. Además, nuestro estudio también mostró que la cubierta terrestre tuvo varios impactos independientes de la cuenca en el cambio del transporte de sedimentos. A través de comparaciones entre cuencas de los cambios a largo plazo en la descarga de agua y el transporte de sedimentos, nuestro estudio reveló las similitudes y diferencias en sus mecanismos de conducción, proporcionando información valiosa para la planificación del uso de la tierra y la gestión de los recursos hídricos en grandes cuencas subtropicales. Human activities and climate are two key factors affecting hydrological and soil erosion processes. Understanding their impacts on water discharge and sediment transport is very important for sustainable development of watersheds, particularly in subtropical regions with high precipitation and high sediment loads. We here compared the long-term dynamics of water discharge and sediment transport in four large contiguous watersheds in subtropical China and explored the importance of the main influencing factors including climate, nature endowment such as geology, and human activities. Significant differences have been observed between watersheds in terms of sediment and water discharge (p < 0.001). Pairwise comparison among the four basins demonstrated significant differences in sediment modulus among 5 of the 6 pairs (p < 0.05). The sediment modulus in the Lishui Basin was significantly higher than those in other basins, mainly due to the substantial presence of steep slopes in the mountainous region, which is prone to soil erosion. Temporally, sediment transport in the four basins was well synchronized showing significant decreasing trends with abrupt change points (p < 0.001). In contrast, no trends and abrupt change points were detected in water discharge, mainly influenced by precipitation. Human activities played a predominant role to the reduction of sediment transport (80% to 102%) compared with those of climate (-2% to 19%) across the four basins. Additionally, our study also showed land cover had various basin-independent impacts on the change of sediment transport. Through cross-basin comparisons of the long-term changes in water discharge and sediment transport, our study revealed the similarities and differences in their driving mechanisms, providing valuable information for land use planning and water resource management in large subtropical basins. الأنشطة البشرية والمناخ عاملان رئيسيان يؤثران على العمليات الهيدرولوجية وتآكل التربة. يعد فهم آثارها على تصريف المياه ونقل الرواسب أمرًا مهمًا للغاية للتنمية المستدامة لمستجمعات المياه، لا سيما في المناطق شبه الاستوائية ذات الهطول المرتفع وأحمال الرواسب العالية. قارنا هنا الديناميكيات طويلة الأجل لتصريف المياه ونقل الرواسب في أربعة مستجمعات مياه متجاورة كبيرة في الصين شبه الاستوائية واستكشفنا أهمية العوامل المؤثرة الرئيسية بما في ذلك المناخ وهبات الطبيعة مثل الجيولوجيا والأنشطة البشرية. لوحظت اختلافات كبيرة بين مستجمعات المياه من حيث الرواسب وتصريف المياه (p < 0.001). أظهرت المقارنة الزوجية بين الأحواض الأربعة اختلافات كبيرة في معامل الرواسب بين 5 من 6 أزواج (P < 0.05). كان معامل الرواسب في حوض ليشوي أعلى بكثير من تلك الموجودة في الأحواض الأخرى، ويرجع ذلك أساسًا إلى الوجود الكبير للمنحدرات الحادة في المنطقة الجبلية، المعرضة لتآكل التربة. من الناحية الزمنية، كان نقل الرواسب في الأحواض الأربعة متزامنًا بشكل جيد مما يدل على اتجاهات تناقصية كبيرة مع نقاط تغير مفاجئة (p < 0.001). في المقابل، لم يتم الكشف عن أي اتجاهات ونقاط تغيير مفاجئة في تصريف المياه، متأثرة بشكل رئيسي بهطول الأمطار. لعبت الأنشطة البشرية دورًا بارزًا في الحد من انتقال الرواسب (80 ٪ إلى 102 ٪) مقارنة بالأنشطة المناخية (-2 ٪ إلى 19 ٪) عبر الأحواض الأربعة. بالإضافة إلى ذلك، أظهرت دراستنا أيضًا أن الغطاء الأرضي له تأثيرات مختلفة مستقلة عن الأحواض على تغير نقل الرواسب. من خلال مقارنات عبر الأحواض للتغيرات طويلة الأجل في تصريف المياه ونقل الرواسب، كشفت دراستنا عن أوجه التشابه والاختلاف في آليات قيادتها، مما يوفر معلومات قيمة لتخطيط استخدام الأراضي وإدارة الموارد المائية في الأحواض شبه الاستوائية الكبيرة.

Les activités humaines et le climat sont deux facteurs clés affectant les processus hydrologiques et d'érosion des sols. Il est très important de comprendre leurs impacts sur les rejets d'eau et le transport des sédiments pour le développement durable des bassins versants, en particulier dans les régions subtropicales où les précipitations et les charges de sédiments sont élevées. Nous avons ici comparé la dynamique à long terme des rejets d'eau et du transport des sédiments dans quatre grands bassins versants contigus de la Chine subtropicale et exploré l'importance des principaux facteurs d'influence, notamment le climat, les ressources naturelles telles que la géologie et les activités humaines. Des différences significatives ont été observées entre les bassins versants en termes de sédiments et de rejets d'eau (p < 0,001). La comparaison par paires entre les quatre bassins a démontré des différences significatives dans le module des sédiments entre 5 des 6 paires (p < 0,05). Le module des sédiments dans le bassin de Lishui était significativement plus élevé que ceux des autres bassins, principalement en raison de la présence substantielle de pentes raides dans la région montagneuse, sujette à l'érosion des sols. Temporellement, le transport des sédiments dans les quatre bassins était bien synchronisé, montrant des tendances à la baisse significatives avec des points de changement brusques (p < 0,001). En revanche, aucune tendance et aucun point de changement brusque n'ont été détectés dans les rejets d'eau, principalement influencés par les précipitations. Les activités humaines ont joué un rôle prédominant dans la réduction du transport des sédiments (80% à 102%) par rapport à celles du climat (-2% à 19%) à travers les quatre bassins. De plus, notre étude a également montré que la couverture terrestre avait divers impacts indépendants du bassin sur le changement du transport des sédiments. Grâce à des comparaisons entre bassins des changements à long terme dans le débit d'eau et le transport des sédiments, notre étude a révélé les similitudes et les différences dans leurs mécanismes d'entraînement, fournissant des informations précieuses pour la planification de l'utilisation des terres et la gestion des ressources en eau dans les grands bassins subtropicaux. Las actividades humanas y el clima son dos factores clave que afectan los procesos hidrológicos y de erosión del suelo. Comprender sus impactos en la descarga de agua y el transporte de sedimentos es muy importante para el desarrollo sostenible de las cuencas hidrográficas, particularmente en regiones subtropicales con altas precipitaciones y altas cargas de sedimentos. Aquí comparamos la dinámica a largo plazo de la descarga de agua y el transporte de sedimentos en cuatro grandes cuencas hidrográficas contiguas en China subtropical y exploramos la importancia de los principales factores que influyen, incluidos el clima, la dotación de la naturaleza, como la geología, y las actividades humanas. Se han observado diferencias significativas entre las cuencas en términos de sedimento y descarga de agua (p < 0.001). La comparación por pares entre las cuatro cuencas demostró diferencias significativas en el módulo de sedimento entre 5 de los 6 pares (p < 0.05). El módulo de sedimentos en la cuenca de Lishui fue significativamente más alto que en otras cuencas, principalmente debido a la presencia sustancial de pendientes pronunciadas en la región montañosa, que es propensa a la erosión del suelo. Temporalmente, el transporte de sedimentos en las cuatro cuencas estuvo bien sincronizado mostrando tendencias decrecientes significativas con puntos de cambio abruptos (p < 0.001). Por el contrario, no se detectaron tendencias y puntos de cambio bruscos en la descarga de agua, influenciados principalmente por la precipitación. Las actividades humanas desempeñaron un papel predominante en la reducción del transporte de sedimentos (80% a 102%) en comparación con las del clima (-2% a 19%) en las cuatro cuencas. Además, nuestro estudio también mostró que la cubierta terrestre tuvo varios impactos independientes de la cuenca en el cambio del transporte de sedimentos. A través de comparaciones entre cuencas de los cambios a largo plazo en la descarga de agua y el transporte de sedimentos, nuestro estudio reveló las similitudes y diferencias en sus mecanismos de conducción, proporcionando información valiosa para la planificación del uso de la tierra y la gestión de los recursos hídricos en grandes cuencas subtropicales. Human activities and climate are two key factors affecting hydrological and soil erosion processes. Understanding their impacts on water discharge and sediment transport is very important for sustainable development of watersheds, particularly in subtropical regions with high precipitation and high sediment loads. We here compared the long-term dynamics of water discharge and sediment transport in four large contiguous watersheds in subtropical China and explored the importance of the main influencing factors including climate, nature endowment such as geology, and human activities. Significant differences have been observed between watersheds in terms of sediment and water discharge (p < 0.001). Pairwise comparison among the four basins demonstrated significant differences in sediment modulus among 5 of the 6 pairs (p < 0.05). The sediment modulus in the Lishui Basin was significantly higher than those in other basins, mainly due to the substantial presence of steep slopes in the mountainous region, which is prone to soil erosion. Temporally, sediment transport in the four basins was well synchronized showing significant decreasing trends with abrupt change points (p < 0.001). In contrast, no trends and abrupt change points were detected in water discharge, mainly influenced by precipitation. Human activities played a predominant role to the reduction of sediment transport (80% to 102%) compared with those of climate (-2% to 19%) across the four basins. Additionally, our study also showed land cover had various basin-independent impacts on the change of sediment transport. Through cross-basin comparisons of the long-term changes in water discharge and sediment transport, our study revealed the similarities and differences in their driving mechanisms, providing valuable information for land use planning and water resource management in large subtropical basins. الأنشطة البشرية والمناخ عاملان رئيسيان يؤثران على العمليات الهيدرولوجية وتآكل التربة. يعد فهم آثارها على تصريف المياه ونقل الرواسب أمرًا مهمًا للغاية للتنمية المستدامة لمستجمعات المياه، لا سيما في المناطق شبه الاستوائية ذات الهطول المرتفع وأحمال الرواسب العالية. قارنا هنا الديناميكيات طويلة الأجل لتصريف المياه ونقل الرواسب في أربعة مستجمعات مياه متجاورة كبيرة في الصين شبه الاستوائية واستكشفنا أهمية العوامل المؤثرة الرئيسية بما في ذلك المناخ وهبات الطبيعة مثل الجيولوجيا والأنشطة البشرية. لوحظت اختلافات كبيرة بين مستجمعات المياه من حيث الرواسب وتصريف المياه (p < 0.001). أظهرت المقارنة الزوجية بين الأحواض الأربعة اختلافات كبيرة في معامل الرواسب بين 5 من 6 أزواج (P < 0.05). كان معامل الرواسب في حوض ليشوي أعلى بكثير من تلك الموجودة في الأحواض الأخرى، ويرجع ذلك أساسًا إلى الوجود الكبير للمنحدرات الحادة في المنطقة الجبلية، المعرضة لتآكل التربة. من الناحية الزمنية، كان نقل الرواسب في الأحواض الأربعة متزامنًا بشكل جيد مما يدل على اتجاهات تناقصية كبيرة مع نقاط تغير مفاجئة (p < 0.001). في المقابل، لم يتم الكشف عن أي اتجاهات ونقاط تغيير مفاجئة في تصريف المياه، متأثرة بشكل رئيسي بهطول الأمطار. لعبت الأنشطة البشرية دورًا بارزًا في الحد من انتقال الرواسب (80 ٪ إلى 102 ٪) مقارنة بالأنشطة المناخية (-2 ٪ إلى 19 ٪) عبر الأحواض الأربعة. بالإضافة إلى ذلك، أظهرت دراستنا أيضًا أن الغطاء الأرضي له تأثيرات مختلفة مستقلة عن الأحواض على تغير نقل الرواسب. من خلال مقارنات عبر الأحواض للتغيرات طويلة الأجل في تصريف المياه ونقل الرواسب، كشفت دراستنا عن أوجه التشابه والاختلاف في آليات قيادتها، مما يوفر معلومات قيمة لتخطيط استخدام الأراضي وإدارة الموارد المائية في الأحواض شبه الاستوائية الكبيرة.

# Vegetation growth responses to climate change: a cross-scale analysis of biological memory and time-lags using tree ring and satellite data The dataset includes tree-ring data for individual trees across three species, encompassing dimensionless tree-ring width (TRW) measurements, as well as data on the enhanced vegetation index (EVI), leaf area index (LAI), gross primary productivity (GPP), and various climate parameters. The TRW serves as an indicator of radial stem growth at the tree-species level. Remote sensing-based data of EVI, LAI and GPP were used to monitor ecosystem-scale canopy dynamics, leaf growth, and ecosystem carbon sequestration capacity, respectively. ## Description of the data and file structure 1. Climate_1956_2017.csv: The dataset includes the mean air temperature, mean maximum air temperature, mean minimum air temperature, mean sunshine duration, and total precipitation from 1956 to 2017 on a daily basis in the study area. *Notes*: Lat, Latitude; Lon, longitude; Elev, Elevation; MTEM, mean air temperature (ºC); MaxTEM, mean maximum air temperature (ºC); MinTEM, mean maximum air temperature (ºC); X20to20PRE, accumulated precipitation at 20-20 (mm); SSD, mean sunshine duration (h). 2. TRW_LF.csv: This dataset comprises data for each core of individual trees belonging to the Liquidambar formosana (LF), coded as LF_01A, where 'LF' denotes the tree species, '01' represents the tree number, and 'A' indicates the core sample number taken from each tree. The units for this tree-ring data are in 0.001mm. 3. TRW_CE.csv: This dataset comprises data for each core of individual trees belonging to the Castanopsis eyrei (CE), coded as CE_01A, where 'CE' denotes the tree species, '01' represents the tree number, and 'A' indicates the core sample number taken from each tree. The units for this tree-ring data are in 0.001mm. 4. TRW_CH.csv: This dataset comprises data for each core of individual trees belonging to the Castanea henryi (CH), coded as CH_01A, where 'CH' denotes the tree species, '01' represents the tree number, and 'A' indicates the core sample number taken from each tree. The units for this tree-ring data are in 0.001mm. 5. Dimensionless_TRW_data_of_the_three_tree_species.csv: Between October 2020 and July 2022, we sampled 25-29 mature and healthy trees per species, collecting one-to-two cores from each tree at 1.3 m above the ground using a 5.15 mm increment borer. The tree-ring cores were fixed, dried, polished, and visually cross-dated under a binocular microscope. We measured tree-ring width with the LINTAB™ 6 system to a 0.01-mm accuracy, covering data from 1957 to 2017. Standardization of tree-ring width data involved two phases. First, COFECHA software ensured the quality of cross-dating results by evaluating the synchronization of growth patterns across samples. Next, we used the detrend function from the dplR package in R to fit a modified negative exponential curve to each raw tree-ring series for detrending. Standardized indices were calculated by dividing the original ring widths by the fitted values and combining them into a single standardized chronology using a bi-weight robust mean to mitigate outlier influence. *Notes*: CE, Castanopsis eyrei; CH, Castanea henryi; LF, Liquidambar formosana. 6. EVI_MOD13Q1_16days.csv: The dataset consists of the enhanced vegetation index (EVI) for the study area, measured over 16-day periods. *Notes*: Start, date of start; End, date of start; EVI, enhanced vegetation index (unitless). 7. LAI_MCD15A2H_16days.csv: The dataset consists of the leaf area index (LAI) for the study area, measured over 16-day periods. To ensure a consistent time resolution for remote sensing-based vegetation indicators, the 8-day time periods of LAI was aligned with the 16-day time periods of EVI. This alignment was achieved by averaging LAI values from two consecutive 8-day periods. *Notes*: Start, date of start; End, date of start; LAI, leaf area index (m2/m2). 8. GPP_MOD17A2H_16days.csv: The dataset consists of the gross primary productivity (GPP) for the study area, measured over 16-day periods. To ensure a consistent time resolution for remote sensing-based vegetation indicators, the 8-day time periods of GPP was aligned with the 16-day time periods of EVI. This alignment was achieved by calculating GPP as the cumulative value of two consecutive 8-day periods. *Notes*: Start, date of start; End, date of start; GPP, gross primary productivity (kg C/m2). Vegetation growth is affected by past growth rates and climate variability. However, the impacts of vegetation growth carryover (VGC; biotic) and lagged climatic effects (LCE; abiotic) on tree stem radial growth may be decoupled from photosynthetic capacity, as higher photosynthesis does not always translate into greater growth. To assess the interaction of tree-species level VGC and LCE with ecosystem-scale photosynthetic processes, we utilized tree-ring width (TRW) data for three tree species: Castanopsis eyrei (CE), Castanea henryi (CH, Chinese chinquapin), and Liquidambar formosana (LF, Chinese sweet gum), along with satellite-based data on canopy greenness (EVI, enhanced vegetation index), leaf area index (LAI), and gross primary productivity (GPP). We used vector autoregressive models, impulse response functions, and forecast error variance decomposition to analyze the duration, intensity, and drivers of VGC and of LCE response to precipitation, temperature, and sunshine duration. The results showed that at the tree-species level, VGC in TRW was strongest in the first year, with an average 77% reduction in response intensity by the fourth year. VGC and LCE exhibited species-specific patterns; compared to CE and CH (diffuse-porous species), LF (ring-porous species) exhibited stronger VGC but weaker LCE. For photosynthetic capacity at the ecosystem scale (EVI, LAI, and GPP), VGC and LCE occurred within 96 days. Our study demonstrates that VGC effects play a dominant role in vegetation function and productivity, and that vegetation responses to previous growth states are decoupled from climatic variability. Additionally, we discovered the possibility for tree-ring growth to be decoupled from canopy condition. Investigating VGC and LCE of multiple indicators of vegetation growth at multiple scales has the potential to improve the accuracy of terrestrial global change models. The dataset includes tree-ring data for individual trees across three species, encompassing dimensionless tree-ring width (TRW) measurements, as well as data on the enhanced vegetation index (EVI), leaf area index (LAI), gross primary productivity (GPP), and various climate parameters. The TRW serves as an indicator of radial stem growth at the tree-species level. Remote sensing-based data of EVI, LAI and GPP were used to monitor ecosystem-scale canopy dynamics, leaf growth, and ecosystem carbon sequestration capacity, respectively. Dimensionless tree-ring width (TRW) measurements method: Between October 2020 and July 2022, we sampled 25-29 mature and healthy trees per species, collecting one-to-two cores from each tree at 1.3 m above the ground using a 5.15 mm increment borer. The tree-ring cores were fixed, dried, polished, and visually cross-dated under a binocular microscope. We measured tree-ring width with the LINTAB™ 6 system to a 0.01-mm accuracy, covering data from 1957 to 2017. Standardization of tree-ring width data involved two phases. First, COFECHA software ensured the quality of cross-dating results by evaluating the synchronization of growth patterns across samples. Next, we used the detrend function from the dplR package in R to fit a modified negative exponential curve to each raw tree-ring series for detrending. Standardized indices were calculated by dividing the original ring widths by the fitted values and combining them into a single standardized chronology using a bi-weight robust mean to mitigate outlier influence.

# Vegetation growth responses to climate change: a cross-scale analysis of biological memory and time-lags using tree ring and satellite data The dataset includes tree-ring data for individual trees across three species, encompassing dimensionless tree-ring width (TRW) measurements, as well as data on the enhanced vegetation index (EVI), leaf area index (LAI), gross primary productivity (GPP), and various climate parameters. The TRW serves as an indicator of radial stem growth at the tree-species level. Remote sensing-based data of EVI, LAI and GPP were used to monitor ecosystem-scale canopy dynamics, leaf growth, and ecosystem carbon sequestration capacity, respectively. ## Description of the data and file structure 1. Climate_1956_2017.csv: The dataset includes the mean air temperature, mean maximum air temperature, mean minimum air temperature, mean sunshine duration, and total precipitation from 1956 to 2017 on a daily basis in the study area. *Notes*: Lat, Latitude; Lon, longitude; Elev, Elevation; MTEM, mean air temperature (ºC); MaxTEM, mean maximum air temperature (ºC); MinTEM, mean maximum air temperature (ºC); X20to20PRE, accumulated precipitation at 20-20 (mm); SSD, mean sunshine duration (h). 2. TRW_LF.csv: This dataset comprises data for each core of individual trees belonging to the Liquidambar formosana (LF), coded as LF_01A, where 'LF' denotes the tree species, '01' represents the tree number, and 'A' indicates the core sample number taken from each tree. The units for this tree-ring data are in 0.001mm. 3. TRW_CE.csv: This dataset comprises data for each core of individual trees belonging to the Castanopsis eyrei (CE), coded as CE_01A, where 'CE' denotes the tree species, '01' represents the tree number, and 'A' indicates the core sample number taken from each tree. The units for this tree-ring data are in 0.001mm. 4. TRW_CH.csv: This dataset comprises data for each core of individual trees belonging to the Castanea henryi (CH), coded as CH_01A, where 'CH' denotes the tree species, '01' represents the tree number, and 'A' indicates the core sample number taken from each tree. The units for this tree-ring data are in 0.001mm. 5. Dimensionless_TRW_data_of_the_three_tree_species.csv: Between October 2020 and July 2022, we sampled 25-29 mature and healthy trees per species, collecting one-to-two cores from each tree at 1.3 m above the ground using a 5.15 mm increment borer. The tree-ring cores were fixed, dried, polished, and visually cross-dated under a binocular microscope. We measured tree-ring width with the LINTAB™ 6 system to a 0.01-mm accuracy, covering data from 1957 to 2017. Standardization of tree-ring width data involved two phases. First, COFECHA software ensured the quality of cross-dating results by evaluating the synchronization of growth patterns across samples. Next, we used the detrend function from the dplR package in R to fit a modified negative exponential curve to each raw tree-ring series for detrending. Standardized indices were calculated by dividing the original ring widths by the fitted values and combining them into a single standardized chronology using a bi-weight robust mean to mitigate outlier influence. *Notes*: CE, Castanopsis eyrei; CH, Castanea henryi; LF, Liquidambar formosana. 6. EVI_MOD13Q1_16days.csv: The dataset consists of the enhanced vegetation index (EVI) for the study area, measured over 16-day periods. *Notes*: Start, date of start; End, date of start; EVI, enhanced vegetation index (unitless). 7. LAI_MCD15A2H_16days.csv: The dataset consists of the leaf area index (LAI) for the study area, measured over 16-day periods. To ensure a consistent time resolution for remote sensing-based vegetation indicators, the 8-day time periods of LAI was aligned with the 16-day time periods of EVI. This alignment was achieved by averaging LAI values from two consecutive 8-day periods. *Notes*: Start, date of start; End, date of start; LAI, leaf area index (m2/m2). 8. GPP_MOD17A2H_16days.csv: The dataset consists of the gross primary productivity (GPP) for the study area, measured over 16-day periods. To ensure a consistent time resolution for remote sensing-based vegetation indicators, the 8-day time periods of GPP was aligned with the 16-day time periods of EVI. This alignment was achieved by calculating GPP as the cumulative value of two consecutive 8-day periods. *Notes*: Start, date of start; End, date of start; GPP, gross primary productivity (kg C/m2). Vegetation growth is affected by past growth rates and climate variability. However, the impacts of vegetation growth carryover (VGC; biotic) and lagged climatic effects (LCE; abiotic) on tree stem radial growth may be decoupled from photosynthetic capacity, as higher photosynthesis does not always translate into greater growth. To assess the interaction of tree-species level VGC and LCE with ecosystem-scale photosynthetic processes, we utilized tree-ring width (TRW) data for three tree species: Castanopsis eyrei (CE), Castanea henryi (CH, Chinese chinquapin), and Liquidambar formosana (LF, Chinese sweet gum), along with satellite-based data on canopy greenness (EVI, enhanced vegetation index), leaf area index (LAI), and gross primary productivity (GPP). We used vector autoregressive models, impulse response functions, and forecast error variance decomposition to analyze the duration, intensity, and drivers of VGC and of LCE response to precipitation, temperature, and sunshine duration. The results showed that at the tree-species level, VGC in TRW was strongest in the first year, with an average 77% reduction in response intensity by the fourth year. VGC and LCE exhibited species-specific patterns; compared to CE and CH (diffuse-porous species), LF (ring-porous species) exhibited stronger VGC but weaker LCE. For photosynthetic capacity at the ecosystem scale (EVI, LAI, and GPP), VGC and LCE occurred within 96 days. Our study demonstrates that VGC effects play a dominant role in vegetation function and productivity, and that vegetation responses to previous growth states are decoupled from climatic variability. Additionally, we discovered the possibility for tree-ring growth to be decoupled from canopy condition. Investigating VGC and LCE of multiple indicators of vegetation growth at multiple scales has the potential to improve the accuracy of terrestrial global change models. The dataset includes tree-ring data for individual trees across three species, encompassing dimensionless tree-ring width (TRW) measurements, as well as data on the enhanced vegetation index (EVI), leaf area index (LAI), gross primary productivity (GPP), and various climate parameters. The TRW serves as an indicator of radial stem growth at the tree-species level. Remote sensing-based data of EVI, LAI and GPP were used to monitor ecosystem-scale canopy dynamics, leaf growth, and ecosystem carbon sequestration capacity, respectively. Dimensionless tree-ring width (TRW) measurements method: Between October 2020 and July 2022, we sampled 25-29 mature and healthy trees per species, collecting one-to-two cores from each tree at 1.3 m above the ground using a 5.15 mm increment borer. The tree-ring cores were fixed, dried, polished, and visually cross-dated under a binocular microscope. We measured tree-ring width with the LINTAB™ 6 system to a 0.01-mm accuracy, covering data from 1957 to 2017. Standardization of tree-ring width data involved two phases. First, COFECHA software ensured the quality of cross-dating results by evaluating the synchronization of growth patterns across samples. Next, we used the detrend function from the dplR package in R to fit a modified negative exponential curve to each raw tree-ring series for detrending. Standardized indices were calculated by dividing the original ring widths by the fitted values and combining them into a single standardized chronology using a bi-weight robust mean to mitigate outlier influence.