Pub Date : 2026-03-01Epub Date: 2025-11-30DOI: 10.1016/j.agrformet.2025.110932
Hui Liu , Mingyu Wang , Pengle Cheng , Xiaodong Liu , Ying Huang
The increase in crop production has resulted in a significant increase in annual yield of crop straw. To analyze the impact of straw burning on air quality, this study integrates data on the burning of straw obtained from remote sensing satellites with meteorological data provided by meteorological satellites. Statistical analysis has been applied to analyze these data to identify patterns of the influence of straw burning pollutants on air quality. Experimental burnings were conducted to investigate the correlation between the volume of straw burning and the levels of particulate matter (PM). The findings demonstrate that under identical meteorological conditions, the impact of straw burning during the night is less pronounced than that of daytime burning, with pollutants dissipating more rapidly. Furthermore, the subsequent rainfall is found to mitigate the impact of straw burning on air quality. Consequently, the optimal strategy for minimizing the impact on air quality and accelerating the diffusion of pollutants is to conduct straw burning before predicted rainy weather and during nighttime on windy or sunny days.
{"title":"Meteorological drivers of air pollution impacts from straw burning in Henan Province, China","authors":"Hui Liu , Mingyu Wang , Pengle Cheng , Xiaodong Liu , Ying Huang","doi":"10.1016/j.agrformet.2025.110932","DOIUrl":"10.1016/j.agrformet.2025.110932","url":null,"abstract":"<div><div>The increase in crop production has resulted in a significant increase in annual yield of crop straw. To analyze the impact of straw burning on air quality, this study integrates data on the burning of straw obtained from remote sensing satellites with meteorological data provided by meteorological satellites. Statistical analysis has been applied to analyze these data to identify patterns of the influence of straw burning pollutants on air quality. Experimental burnings were conducted to investigate the correlation between the volume of straw burning and the levels of particulate matter (PM). The findings demonstrate that under identical meteorological conditions, the impact of straw burning during the night is less pronounced than that of daytime burning, with pollutants dissipating more rapidly. Furthermore, the subsequent rainfall is found to mitigate the impact of straw burning on air quality. Consequently, the optimal strategy for minimizing the impact on air quality and accelerating the diffusion of pollutants is to conduct straw burning before predicted rainy weather and during nighttime on windy or sunny days.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110932"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145625238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-12-04DOI: 10.1016/j.agrformet.2025.110957
Shuyuan Huang , Yujie Liu , Jiahao Chen , Ermei Zhang , Tao Pan
The configuration of phenology-based time windows, which determines how environmental variables are temporally aggregated, plays a pivotal role in crop yield estimation. However, the quantitative effects of different window configurations on model performance and uncertainty require further investigation. This study systematically assesses the effects of four window-configuration strategies (fixed, observation, rule-based, and sliding) on soybean yield estimation across the black soil regions of China and the USA. Multi-source remote sensing and meteorological datasets were integrated with three machine learning algorithms: RF, XGBoost, and LSTM. Results show that dynamic windows (observation, rule-based, and sliding) can better align environmental fluctuations with crop phenological stages, resulting in modest yet consistent improvements in accuracy compared to fixed windows. The LSTM–sliding window combination achieves the largest RMSE decrease (48.4-56.6%), followed by LSTM–rule-based windows (32.9-38.2%) and LSTM–observation windows (11.8-22.0%). A trade-off is identified: while sliding windows (SWs) provide the highest accuracy, they also show greater interannual variability, higher computational cost, and lower interpretability. In comparison, rule-based windows (RBWs) exhibit a moderate decline in accuracy but demonstrate lower inter-group variability, with ΔR² approximately one-third that of SW, offering more stable predictions. RBWs also exhibit better generalizability than observation windows, which rely on limited ground phenology data. Uncertainty decomposition reveals that, although the primary source of variation originates from input features and model structures, the configuration of the estimation window contributes approximately 11.9-13.7% to the total variation, indicating a secondary yet consistent factor influencing estimation stability. This study offers an analytical framework for quantifying the interactions among window design, algorithm type, and feature selection, thereby providing practical insights for future data-driven crop yield modeling.
{"title":"The influence of estimation window configuration on machine learning-based soybean yield estimation across black soil regions","authors":"Shuyuan Huang , Yujie Liu , Jiahao Chen , Ermei Zhang , Tao Pan","doi":"10.1016/j.agrformet.2025.110957","DOIUrl":"10.1016/j.agrformet.2025.110957","url":null,"abstract":"<div><div>The configuration of phenology-based time windows, which determines how environmental variables are temporally aggregated, plays a pivotal role in crop yield estimation. However, the quantitative effects of different window configurations on model performance and uncertainty require further investigation. This study systematically assesses the effects of four window-configuration strategies (fixed, observation, rule-based, and sliding) on soybean yield estimation across the black soil regions of China and the USA. Multi-source remote sensing and meteorological datasets were integrated with three machine learning algorithms: RF, XGBoost, and LSTM. Results show that dynamic windows (observation, rule-based, and sliding) can better align environmental fluctuations with crop phenological stages, resulting in modest yet consistent improvements in accuracy compared to fixed windows. The LSTM–sliding window combination achieves the largest RMSE decrease (48.4-56.6%), followed by LSTM–rule-based windows (32.9-38.2%) and LSTM–observation windows (11.8-22.0%). A trade-off is identified: while sliding windows (SWs) provide the highest accuracy, they also show greater interannual variability, higher computational cost, and lower interpretability. In comparison, rule-based windows (RBWs) exhibit a moderate decline in accuracy but demonstrate lower inter-group variability, with ΔR² approximately one-third that of SW, offering more stable predictions. RBWs also exhibit better generalizability than observation windows, which rely on limited ground phenology data. Uncertainty decomposition reveals that, although the primary source of variation originates from input features and model structures, the configuration of the estimation window contributes approximately 11.9-13.7% to the total variation, indicating a secondary yet consistent factor influencing estimation stability. This study offers an analytical framework for quantifying the interactions among window design, algorithm type, and feature selection, thereby providing practical insights for future data-driven crop yield modeling.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110957"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-09DOI: 10.1016/j.agrformet.2025.111011
Xiaojia Yuan , Chen Xu , Jingsong Zhang , Xue Wang , Jinglei Liao , Mingchao Du , Xianliang Zhang
Lumen traits (area and number) are critical for forest carbon sequestration and hydraulic function, yet their responses to climate and intraspecific competition (CI) along elevational gradients remain unclear. We analyzed lumen and stand inventory data from 39 Larix principis-rupprechtii trees across six plots in North China to evaluate the combined effects of climate and CI on earlywood and latewood formation.
At high elevations, earlywood lumen area represented 50–51 % of total lumen area and nearly 85 % of annual ring area. These earlywood lumens showed strong negative correlations with minimum temperature (Tmin), precipitation (PRE), and the Palmer Drought Severity Index (PDSI), indicating that their formation is constrained by both temperature and drought stress. At low elevations, the proportion of earlywood lumens declined to 48–49 %, and their climatic sensitivities weakened, with positive effects of maximum temperature (Tmax) primarily expressed in latewood traits. Increasing competition at high elevations reduced earlywood area in response to Tmax, while at low elevations it strengthened correlations of PDSI, PRE, Tmax, and mean temperature (Tmean) with latewood traits, and enhanced Tmin effects on earlywood structure. Extreme lumen traits exhibited clear climate–competition interactions: at high elevations, Tmin and Tmean promoted large earlywood lumens under stronger competition; at low elevations, competition amplified positive responses of small earlywood lumens to PDSI, PRE, Tmean, and Tmax, and increased Tmin sensitivity of large latewood lumens. Overall, earlywood formation is temperature-limited at high elevations, whereas latewood growth at low elevations is jointly regulated by temperature, drought, and competition. These findings clarify the regulatory role of climate–competition interactions in shaping xylem traits, thereby improving our understanding of forest adaptation under climate change.
{"title":"Elevation-dependent responses of xylem lumen traits to competition–climate interactions in temperate forests","authors":"Xiaojia Yuan , Chen Xu , Jingsong Zhang , Xue Wang , Jinglei Liao , Mingchao Du , Xianliang Zhang","doi":"10.1016/j.agrformet.2025.111011","DOIUrl":"10.1016/j.agrformet.2025.111011","url":null,"abstract":"<div><div>Lumen traits (area and number) are critical for forest carbon sequestration and hydraulic function, yet their responses to climate and intraspecific competition (CI) along elevational gradients remain unclear. We analyzed lumen and stand inventory data from 39 <em>Larix principis-rupprechtii</em> trees across six plots in North China to evaluate the combined effects of climate and CI on earlywood and latewood formation.</div><div>At high elevations, earlywood lumen area represented 50–51 % of total lumen area and nearly 85 % of annual ring area. These earlywood lumens showed strong negative correlations with minimum temperature (Tmin), precipitation (PRE), and the Palmer Drought Severity Index (PDSI), indicating that their formation is constrained by both temperature and drought stress. At low elevations, the proportion of earlywood lumens declined to 48–49 %, and their climatic sensitivities weakened, with positive effects of maximum temperature (Tmax) primarily expressed in latewood traits. Increasing competition at high elevations reduced earlywood area in response to Tmax, while at low elevations it strengthened correlations of PDSI, PRE, Tmax, and mean temperature (Tmean) with latewood traits, and enhanced Tmin effects on earlywood structure. Extreme lumen traits exhibited clear climate–competition interactions: at high elevations, Tmin and Tmean promoted large earlywood lumens under stronger competition; at low elevations, competition amplified positive responses of small earlywood lumens to PDSI, PRE, Tmean, and Tmax, and increased Tmin sensitivity of large latewood lumens. Overall, earlywood formation is temperature-limited at high elevations, whereas latewood growth at low elevations is jointly regulated by temperature, drought, and competition. These findings clarify the regulatory role of climate–competition interactions in shaping xylem traits, thereby improving our understanding of forest adaptation under climate change.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 111011"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-12-28DOI: 10.1016/j.agrformet.2025.110939
Yujie Liu , Paul Stoy , Housen Chu , Dave Y. Hollinger , Scott V. Ollinger , Andrew P. Ouimette , David J. Durden , Cove Sturtevant , Ben Lucas , Andrew D. Richardson
Long-term ecological data are essential for detecting impacts of climate change and other global change factors, and for making informed predictions about future change. However, long-term measurements are rarely replicated at the site level, which raises questions about their representativeness. We used a multiscale approach to evaluate the agreement of parallel observations from AmeriFlux and NEON (National Ecological Observatory Network) towers at Bartlett Experimental Forest, New Hampshire, USA. The two towers are separated by a horizontal distance of 93 m. We focused our analysis on standard meteorological variables; fluxes of CO2, sensible heat, and latent heat measured by eddy covariance; and phenology derived from PhenoCam imagery. Results suggest excellent agreement between AmeriFlux and NEON in meteorology and phenology, and good agreement in fluxes at the half-hourly scale. However, large disagreements in CO2 and latent heat fluxes occurred at the annual scale, with implications especially for the forest carbon balance. The AmeriFlux tower measurements indicate a site that is close to carbon-neutral (-8 ± 65 g C m-2 y-1, mean ± 1 SD), whereas the NEON tower measurements indicate a forest that is a carbon sink (-137 ± 10 g C m-2 y-1). Causes of this disagreement may include measurement height (26 m vs. 35 m), which resulted in different flux footprints being measured by the two towers, and differences in the flux measurement systems. Our results suggest the need for caution when attempting to merge long-term flux data from two different measurement platforms, and when using measurements from any one measurement platform to inform decision-making on issues related to carbon accounting or natural climate solutions.
长期生态数据对于探测气候变化和其他全球变化因素的影响以及对未来变化作出明智的预测至关重要。然而，长期测量很少在现场水平上复制，这就提出了关于它们的代表性的问题。我们使用多尺度方法来评估美国新罕布什尔州巴特利特实验森林AmeriFlux和NEON（国家生态观测站网络）塔平行观测结果的一致性。两座塔之间的水平距离为93米。我们将分析重点放在标准气象变量上；涡动相关测量的CO2通量、感热通量和潜热通量；和物候学来自于PhenoCam图像。结果表明，AmeriFlux和NEON在气象学和物候学上具有很好的一致性，在半小时尺度上的通量也有很好的一致性。然而，CO2和潜热通量在年尺度上存在较大差异，尤其对森林碳平衡有影响。AmeriFlux塔的测量结果表明该地点接近碳中性（-8±65 g C m-2 y-1，平均±1标准差），而NEON塔的测量结果表明森林是碳汇（-137±10 g C m-2 y-1）。造成这种差异的原因可能包括测量高度（26米对35米），这导致两个塔测量的通量足迹不同，以及通量测量系统的差异。我们的研究结果表明，在试图合并来自两个不同测量平台的长期通量数据时，以及在使用任何一个测量平台的测量结果为与碳核算或自然气候解决方案有关的问题的决策提供信息时，需要谨慎。
{"title":"A tale of two towers: comparing NEON and AmeriFlux data streams at Bartlett Experimental Forest","authors":"Yujie Liu , Paul Stoy , Housen Chu , Dave Y. Hollinger , Scott V. Ollinger , Andrew P. Ouimette , David J. Durden , Cove Sturtevant , Ben Lucas , Andrew D. Richardson","doi":"10.1016/j.agrformet.2025.110939","DOIUrl":"10.1016/j.agrformet.2025.110939","url":null,"abstract":"<div><div>Long-term ecological data are essential for detecting impacts of climate change and other global change factors, and for making informed predictions about future change. However, long-term measurements are rarely replicated at the site level, which raises questions about their representativeness. We used a multiscale approach to evaluate the agreement of parallel observations from AmeriFlux and NEON (National Ecological Observatory Network) towers at Bartlett Experimental Forest, New Hampshire, USA. The two towers are separated by a horizontal distance of 93 m. We focused our analysis on standard meteorological variables; fluxes of CO<sub>2</sub>, sensible heat, and latent heat measured by eddy covariance; and phenology derived from PhenoCam imagery. Results suggest excellent agreement between AmeriFlux and NEON in meteorology and phenology, and good agreement in fluxes at the half-hourly scale. However, large disagreements in CO<sub>2</sub> and latent heat fluxes occurred at the annual scale, with implications especially for the forest carbon balance. The AmeriFlux tower measurements indicate a site that is close to carbon-neutral (-8 ± 65 g C m<sup>-2</sup> y<sup>-1</sup>, mean ± 1 SD), whereas the NEON tower measurements indicate a forest that is a carbon sink (-137 ± 10 g C m<sup>-2</sup> y<sup>-1</sup>). Causes of this disagreement may include measurement height (26 m vs. 35 m), which resulted in different flux footprints being measured by the two towers, and differences in the flux measurement systems. Our results suggest the need for caution when attempting to merge long-term flux data from two different measurement platforms, and when using measurements from any one measurement platform to inform decision-making on issues related to carbon accounting or natural climate solutions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110939"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2026-01-03DOI: 10.1016/j.agrformet.2025.111003
Keyu Xiang , Bin Wang , De Li Liu , Chao Chen , Fei Ji , Fangzheng Chen , Shijin Yao , Siyi Li , Alfredo Huete , Yi Li , Qiang Yu
Drought is a principal determinant of yield variability in rain-fed wheat systems, with climate change expected to exacerbate both the frequency and severity of water deficits. However, knowledge gaps remain in quantifying (i) yield loss probability across different drought indices and (ii) the dynamic thresholds at which drought induces yield losses under divergent climate scenarios. A systematic quantification of these relationships is essential to improve the empirical foundation for risk assessment and adaptive strategies in water-limited agricultural systems. This study analyses future wheat yield loss probability and dynamic drought thresholds in southeastern Australia using the APSIM model and copula functions, comparing a soil water index (SPAWI) against a precipitation index (SPI). We found a higher future wheat yield loss probability for SPAWI-based drought (5–20% greater than for SPI), underscoring the limitation of rainfall-only indices by neglecting soil buffer effects during drought. Drought thresholds were higher for SPAWI than SPI, due to soil moisture buffering, and lower in wetter regions. Including CO2 fertilization increases yields and partially offsets drought impacts, lowering both loss probabilities and thresholds, while climate-model choice remains the dominant source of projected threshold shifts. Our analysis demonstrates that drought index selection influences yield-loss risk projections, and the quantified shifts in drought yield thresholds under climate change reveal key soil moisture buffering effects and CO2 mitigation potential. These findings provide evidence-based drought thresholds to guide adaptive management in dryland wheat cropping systems under climate change.
{"title":"Projecting shifts in drought-induced thresholds for wheat yield loss under climate change in southeastern Australia","authors":"Keyu Xiang , Bin Wang , De Li Liu , Chao Chen , Fei Ji , Fangzheng Chen , Shijin Yao , Siyi Li , Alfredo Huete , Yi Li , Qiang Yu","doi":"10.1016/j.agrformet.2025.111003","DOIUrl":"10.1016/j.agrformet.2025.111003","url":null,"abstract":"<div><div>Drought is a principal determinant of yield variability in rain-fed wheat systems, with climate change expected to exacerbate both the frequency and severity of water deficits. However, knowledge gaps remain in quantifying (i) yield loss probability across different drought indices and (ii) the dynamic thresholds at which drought induces yield losses under divergent climate scenarios. A systematic quantification of these relationships is essential to improve the empirical foundation for risk assessment and adaptive strategies in water-limited agricultural systems. This study analyses future wheat yield loss probability and dynamic drought thresholds in southeastern Australia using the APSIM model and copula functions, comparing a soil water index (SPAWI) against a precipitation index (SPI). We found a higher future wheat yield loss probability for SPAWI-based drought (5–20% greater than for SPI), underscoring the limitation of rainfall-only indices by neglecting soil buffer effects during drought. Drought thresholds were higher for SPAWI than SPI, due to soil moisture buffering, and lower in wetter regions. Including CO<sub>2</sub> fertilization increases yields and partially offsets drought impacts, lowering both loss probabilities and thresholds, while climate-model choice remains the dominant source of projected threshold shifts. Our analysis demonstrates that drought index selection influences yield-loss risk projections, and the quantified shifts in drought yield thresholds under climate change reveal key soil moisture buffering effects and CO<sub>2</sub> mitigation potential. These findings provide evidence-based drought thresholds to guide adaptive management in dryland wheat cropping systems under climate change.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 111003"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-12-02DOI: 10.1016/j.agrformet.2025.110956
Frankie Kiew , Ryuichi Hirata , Takashi Hirano , Guan Xhuan Wong , Joseph Wenceslaus Waili , Kim San Lo , Kaido Soosaar , Kuno Kasak , Ülo Mander , Lulie Melling
This study represents the first long-term investigation spanning from a tropical peat swamp forest (PSF) to its conversion into an oil palm plantation (OPP), offering valuable data for assessing carbon dioxide (CO2) dynamics across different conversion stages. The conversion of tropical peat swamp forests to oil palm plantations has significant implications for CO2 dynamics. However, ecosystem-scale studies investigating CO2 dynamics across different stages of land conversion are lacking. This study used the eddy covariance (EC) technique to measure the net ecosystem exchange (NEE) of CO2 above a tropical peat swamp forest in Sarawak, Malaysia, from 2011 until it was cleared in 2017 and ultimately converted into an OPP in 2018. Our study found that the removal of forest biomass during land preparation led to a substantial increase in annual NEE from 25 ± 179 (2011 to 2016) to 2732 ± 655 g C m−2 year−1 (2017 to 2019). This increase was attributed to an 83 % reduction in gross primary productivity (GPP) and a 14 % reduction in ecosystem respiration (Reco). The near-ground environmental conditions also significantly changed across the conversion stages, inducing drier conditions compared to the forest. These changes were found to affect the controlling factors of nighttime NEE during conversion, resulting in a negative relationship with both air temperature and vapor pressure deficit above canopy, in contrast to the typical relationship with groundwater level observed before conversion. The conversion is also found to cause significant reduction in overall ecosystem photosynthetic activity as evidenced by the reduction in maximum gross photosynthetic rate (Pmax), photosynthetic photon flux density (PPFD), quantum yeild (α), and dark respiration (REd). Although ecosystem-scale assessments of CO2 dynamics provide insights into how ecosystems respond to changes in relation to land conversion, it is crucial to assess other respiration components, such as soil respiration and aboveground woody debris, for a more comprehensive analysis.
这项研究代表了首次从热带泥炭沼泽森林（PSF）到其转化为油棕种植园（OPP）的长期调查，为评估不同转化阶段的二氧化碳（CO2）动态提供了有价值的数据。热带泥炭沼泽森林向油棕种植园的转变对二氧化碳动态具有重要意义。然而，在生态系统尺度上调查不同土地转化阶段二氧化碳动态的研究是缺乏的。本研究使用涡动相关（EC）技术测量了2011年至2017年马来西亚沙捞越热带泥炭沼泽森林上空二氧化碳的净生态系统交换（NEE），并最终在2018年将其转化为OPP。我们的研究发现，在整地过程中森林生物量的去除导致年NEE从25±179（2011 - 2016）大幅增加到2732±655 g C m−2（2017 - 2019）。这一增长归因于总初级生产力（GPP）下降83%和生态系统呼吸（Reco）下降14%。在整个转换阶段，近地环境条件也发生了显著变化，导致与森林相比更为干燥。这些变化影响了转换过程中夜间NEE的控制因子，导致其与冠层以上的气温和水汽压亏缺呈负相关，而与转换前观测到的地下水水位呈典型的负相关。这种转化还导致生态系统整体光合活性的显著降低，如最大总光合速率（Pmax）、光合光子通量密度（PPFD）、量子产率（α）和暗呼吸（REd）的降低。虽然生态系统尺度的二氧化碳动态评估提供了关于生态系统如何响应与土地转化有关的变化的见解，但评估其他呼吸成分（如土壤呼吸和地上木屑）对于更全面的分析至关重要。
{"title":"Carbon dioxide dynamics across three stages of tropical peatland conversion to oil palm plantations","authors":"Frankie Kiew , Ryuichi Hirata , Takashi Hirano , Guan Xhuan Wong , Joseph Wenceslaus Waili , Kim San Lo , Kaido Soosaar , Kuno Kasak , Ülo Mander , Lulie Melling","doi":"10.1016/j.agrformet.2025.110956","DOIUrl":"10.1016/j.agrformet.2025.110956","url":null,"abstract":"<div><div>This study represents the first long-term investigation spanning from a tropical peat swamp forest (PSF) to its conversion into an oil palm plantation (OPP), offering valuable data for assessing carbon dioxide (CO<sub>2</sub>) dynamics across different conversion stages. The conversion of tropical peat swamp forests to oil palm plantations has significant implications for CO<sub>2</sub> dynamics. However, ecosystem-scale studies investigating CO<sub>2</sub> dynamics across different stages of land conversion are lacking. This study used the eddy covariance (EC) technique to measure the net ecosystem exchange (NEE) of CO<sub>2</sub> above a tropical peat swamp forest in Sarawak, Malaysia, from 2011 until it was cleared in 2017 and ultimately converted into an OPP in 2018. Our study found that the removal of forest biomass during land preparation led to a substantial increase in annual NEE from 25 ± 179 (2011 to 2016) to 2732 ± 655 g C m<sup>−2</sup> year<sup>−1</sup> (2017 to 2019). This increase was attributed to an 83 % reduction in gross primary productivity (GPP) and a 14 % reduction in ecosystem respiration (<em>R</em><sub>eco</sub>). The near-ground environmental conditions also significantly changed across the conversion stages, inducing drier conditions compared to the forest. These changes were found to affect the controlling factors of nighttime NEE during conversion, resulting in a negative relationship with both air temperature and vapor pressure deficit above canopy, in contrast to the typical relationship with groundwater level observed before conversion. The conversion is also found to cause significant reduction in overall ecosystem photosynthetic activity as evidenced by the reduction in maximum gross photosynthetic rate (<em>P</em><sub>max</sub>), photosynthetic photon flux density (PPFD), quantum yeild (α), and dark respiration (<em>RE</em><sub>d</sub>). Although ecosystem-scale assessments of CO<sub>2</sub> dynamics provide insights into how ecosystems respond to changes in relation to land conversion, it is crucial to assess other respiration components, such as soil respiration and aboveground woody debris, for a more comprehensive analysis.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110956"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-12-01DOI: 10.1016/j.agrformet.2025.110933
Tuqiang Chen , Han Li , Jinhui Jeanne Huang
Urban forests play a critical role in regulating microclimates, sequestering carbon, and providing various ecosystem services. Due to urban land use changes and human activities, urban water and thermal environments have been significantly altered. This has made urban ecosystems more complex than natural ecosystems. However, our understanding of the magnitude, driving factors, and environmental response thresholds of carbon and water fluxes in urban forests remains limited. This study measured carbon and water fluxes in a semi-humid urban forest in China using eddy covariance technology over four consecutive growing seasons (May–October) from 2020 to 2023. Multi-year averages of gross primary production (GPP), evapotranspiration (ET), and water use efficiency (WUE) during the growing seasons were 1177.1 g C m⁻² yr⁻¹, 520.5 mm yr⁻¹, and 2.2 g C kg⁻¹ H₂O, respectively. Under non-drought conditions, canopy conductance (Gc), GPP, and ET were significantly (p < 0.05) higher than under drought conditions. Higher soil water content (SWC) partially alleviated the negative effects of high net radiation (Rn), air temperature (Ta), and vapor pressure deficit (VPD) on GPP and ET during droughts, although it was not the primary driver of their variability. Structural equation modeling revealed that under drought conditions, GPP was primarily regulated by atmospheric demand (e.g., VPD), whereas ET was primarily controlled by energy availability (e.g., Rn and Ta), with SWC exerting a positive influence on both GPP and ET. In contrast, under non-drought conditions, energy availability dominated the regulation of GPP and ET. Threshold analyses further revealed that GPP and ET responded nonlinearly to environmental drivers, initially increasing with Rn, Ta, and VPD but declining after reaching specific thresholds. These findings enhance our understanding of the mechanisms underlying carbon and water flux dynamics in urban forest ecosystems, particularly in the context of drying and warming conditions.
{"title":"Drivers and thresholds of carbon and water flux dynamics in a semi-humid urban forest ecosystem","authors":"Tuqiang Chen , Han Li , Jinhui Jeanne Huang","doi":"10.1016/j.agrformet.2025.110933","DOIUrl":"10.1016/j.agrformet.2025.110933","url":null,"abstract":"<div><div>Urban forests play a critical role in regulating microclimates, sequestering carbon, and providing various ecosystem services. Due to urban land use changes and human activities, urban water and thermal environments have been significantly altered. This has made urban ecosystems more complex than natural ecosystems. However, our understanding of the magnitude, driving factors, and environmental response thresholds of carbon and water fluxes in urban forests remains limited. This study measured carbon and water fluxes in a semi-humid urban forest in China using eddy covariance technology over four consecutive growing seasons (May–October) from 2020 to 2023. Multi-year averages of gross primary production (GPP), evapotranspiration (ET), and water use efficiency (WUE) during the growing seasons were 1177.1 <em>g</em> C m⁻² yr⁻¹, 520.5 mm yr⁻¹, and 2.2 <em>g</em> C kg⁻¹ H₂O, respectively. Under non-drought conditions, canopy conductance (Gc), GPP, and ET were significantly (<em>p</em> < 0.05) higher than under drought conditions. Higher soil water content (SWC) partially alleviated the negative effects of high net radiation (Rn), air temperature (Ta), and vapor pressure deficit (VPD) on GPP and ET during droughts, although it was not the primary driver of their variability. Structural equation modeling revealed that under drought conditions, GPP was primarily regulated by atmospheric demand (e.g., VPD), whereas ET was primarily controlled by energy availability (e.g., Rn and Ta), with SWC exerting a positive influence on both GPP and ET. In contrast, under non-drought conditions, energy availability dominated the regulation of GPP and ET. Threshold analyses further revealed that GPP and ET responded nonlinearly to environmental drivers, initially increasing with Rn, Ta, and VPD but declining after reaching specific thresholds. These findings enhance our understanding of the mechanisms underlying carbon and water flux dynamics in urban forest ecosystems, particularly in the context of drying and warming conditions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110933"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145658147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-12-15DOI: 10.1016/j.agrformet.2025.110977
Fernanda Leite Cunha , Otávio Camargo Campoe , Cléber Rodrigo de Souza , Isaira Leite & Lopes , Yann Nouvellon , Timothy Albaugh , David R. Carter , Rafael Rubilar , Isabel Deliberari , Rachel Cook , Joannès Guillemot , Guerric Le Maire , Jean-Paul Laclau , Jose Luiz Stape , Clayton Alcarde Alvares
Brazilian Eucalyptus and Pinus forests are the most productive forests worldwide. The growth rates of these intensively managed plantations depend strongly on environmental conditions and matching genotypes to local environments. Changing climates underscore the value of understanding the intricacies of how these plantations can fix high amounts of carbon (C) and grow so much wood. We measured the full C budgets of Eucalyptus and Pinus forests across climate gradients in Brazil, focusing on the rates of C uptake, the allocation of C to belowground roots and mycorrhizae, and stem growth. We found that gross primary production (GPP) varied more than sixfold across the climate conditions in Brazil. Maximum temperature was the main climatic driver of productivity, where extreme temperatures reduced fluxes to stem production while increasing fluxes to root production. Net ecosystem production varied with management and age across the sites. The ecophysiological investigation presented in this work is fundamental for understanding C partitioning behavior under extreme temperature conditions. In this way, our results provide tools for forest managers to support their decision-making processes as well as starting points for strategies to be implemented in projects aimed at mitigating the effects of climate change.
{"title":"Carbon fluxes and partitioning in Eucalyptus and Pinus plantations across a climatic gradient in Brazil","authors":"Fernanda Leite Cunha , Otávio Camargo Campoe , Cléber Rodrigo de Souza , Isaira Leite & Lopes , Yann Nouvellon , Timothy Albaugh , David R. Carter , Rafael Rubilar , Isabel Deliberari , Rachel Cook , Joannès Guillemot , Guerric Le Maire , Jean-Paul Laclau , Jose Luiz Stape , Clayton Alcarde Alvares","doi":"10.1016/j.agrformet.2025.110977","DOIUrl":"10.1016/j.agrformet.2025.110977","url":null,"abstract":"<div><div>Brazilian <em>Eucalyptus</em> and <em>Pinus</em> forests are the most productive forests worldwide. The growth rates of these intensively managed plantations depend strongly on environmental conditions and matching genotypes to local environments. Changing climates underscore the value of understanding the intricacies of how these plantations can fix high amounts of carbon (C) and grow so much wood. We measured the full C budgets of <em>Eucalyptus</em> and <em>Pinus</em> forests across climate gradients in Brazil, focusing on the rates of C uptake, the allocation of C to belowground roots and mycorrhizae, and stem growth. We found that gross primary production (GPP) varied more than sixfold across the climate conditions in Brazil. Maximum temperature was the main climatic driver of productivity, where extreme temperatures reduced fluxes to stem production while increasing fluxes to root production. Net ecosystem production varied with management and age across the sites. The ecophysiological investigation presented in this work is fundamental for understanding C partitioning behavior under extreme temperature conditions. In this way, our results provide tools for forest managers to support their decision-making processes as well as starting points for strategies to be implemented in projects aimed at mitigating the effects of climate change.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110977"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145753299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-12-13DOI: 10.1016/j.agrformet.2025.110991
Qian Li , Yuemin Yue , Lu Wang , Xiangkun Qi , Kelin Wang
Although previous studies have shown that bedrock composition regulates vegetation drought vulnerability, the variability in the response and recovery mechanisms of vegetation under different lithologic contexts remain unclear. Based on the record-breaking extreme drought that occurred in Southwest China in 2022, this study integrated multi-source remote sensing data to systematically assess productivity loss, vegetation recovery time, and their main controlling factors across karst regions (dolomite and limestone) and non-karst regions (clastic rocks). The results showed that vegetation in dolomite areas experienced the most severe productivity loss, maximum GPP (Gross Primary Productivity) loss of shrubland reached 494 kg C/m², 2.57 times higher than that in clastic rock regions, and the average recovery time after drought reached 5.08 months, 1.60 times longer than in clastic regions. Importance analysis indicated that WUE (Water Use Efficiency) was the key factor affecting vegetation recovery in dolomite and limestone regions, with importance values of 0.76 and 0.35, respectively; whereas, temperature was the dominant factor in clastic rocks region (importance value = 0.85). Although vegetation in limestone areas recovered slightly faster than in dolomite, it was still limited by weak WUE. Coupled analysis of WUE and SSM (Surface Soil Moisture) revealed that WUE decreases with greater water availability in limestone and dolomite areas but increases in clastic regions, reflecting a higher water-use responsiveness of vegetation on clastic bedrock. This indicates that the limited soil water-holding capacity in karst regions restricts the potential for efficient water use under high-moisture conditions.
虽然已有研究表明基岩组成调节植被干旱脆弱性，但不同岩性背景下植被响应和恢复机制的变异性尚不清楚。以2022年中国西南地区发生的破纪录极端干旱为背景，综合多源遥感数据，系统评价了岩溶区（白云岩和灰岩）和非岩溶区（碎屑岩）的生产力损失、植被恢复时间及其主控因素。结果表明：白云岩区植被生产力损失最为严重，灌丛植被GPP损失最大，达494 kg C/m²，是碎屑岩区GPP损失的2.57倍；干旱后平均恢复时间达5.08个月，是碎屑岩区GPP损失的1.60倍；重要性分析表明，水利用效率（WUE）是影响白云岩区和灰岩区植被恢复的关键因素，重要性值分别为0.76和0.35；而在碎屑岩区，温度是主导因素（重要值= 0.85）。尽管灰岩区植被恢复速度略快于白云岩区，但仍受WUE较弱的限制。WUE和SSM（表层土壤水分）耦合分析表明，灰岩和白云岩区WUE随水分有效度增大而减小，碎屑岩区WUE随水分有效度增大而增大，反映碎屑岩基岩上植被对水分利用的响应性较高。这表明喀斯特地区有限的土壤持水能力限制了高水分条件下有效利用水分的潜力。
{"title":"Bedrock controls vegetation resilience: Dominant role of lithology in the 2022 southern China drought","authors":"Qian Li , Yuemin Yue , Lu Wang , Xiangkun Qi , Kelin Wang","doi":"10.1016/j.agrformet.2025.110991","DOIUrl":"10.1016/j.agrformet.2025.110991","url":null,"abstract":"<div><div>Although previous studies have shown that bedrock composition regulates vegetation drought vulnerability, the variability in the response and recovery mechanisms of vegetation under different lithologic contexts remain unclear. Based on the record-breaking extreme drought that occurred in Southwest China in 2022, this study integrated multi-source remote sensing data to systematically assess productivity loss, vegetation recovery time, and their main controlling factors across karst regions (dolomite and limestone) and non-karst regions (clastic rocks). The results showed that vegetation in dolomite areas experienced the most severe productivity loss, maximum GPP (Gross Primary Productivity) loss of shrubland reached 494 kg C/m², 2.57 times higher than that in clastic rock regions, and the average recovery time after drought reached 5.08 months, 1.60 times longer than in clastic regions. Importance analysis indicated that WUE (Water Use Efficiency) was the key factor affecting vegetation recovery in dolomite and limestone regions, with importance values of 0.76 and 0.35, respectively; whereas, temperature was the dominant factor in clastic rocks region (importance value = 0.85). Although vegetation in limestone areas recovered slightly faster than in dolomite, it was still limited by weak WUE. Coupled analysis of WUE and SSM (Surface Soil Moisture) revealed that WUE decreases with greater water availability in limestone and dolomite areas but increases in clastic regions, reflecting a higher water-use responsiveness of vegetation on clastic bedrock. This indicates that the limited soil water-holding capacity in karst regions restricts the potential for efficient water use under high-moisture conditions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110991"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145753300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-01Epub Date: 2025-12-18DOI: 10.1016/j.agrformet.2025.110995
Shilin Chen , Hans Verbeeck , Louise Terryn , Wout Cherlet , Chang Liu , Mathias Disney , Yadvinder Malhi , Niall Origo , Joanne Nightingale , Kim Calders
Quantifying forest structure and aboveground biomass carbon (AGBC) dynamics over time is crucial for evaluating climate change impact on carbon stocks, and providing key insights into changes in the terrestrial carbon cycle. To date, the use of multi-temporal terrestrial laser scanning (TLS) to detect temporal dynamics of forest structure and AGBC remains largely unexplored. In this study, we demonstrate the use of bi-temporal TLS data to quantify fine-scale dynamics of forest structure and AGBC. A total of 831 live trees were extracted and manually aligned from two leaf-off datasets collected in a 1.4 ha area of temperate woodland (Wytham Woods, UK) in 2016 and 2022. Results indicated that, at the individual tree level, most trees exhibited positive growth in structural attributes between 2016 and 2022, including diameter at breast height (DBH, 60.2 % of trees), tree height (H, 75.8 %), crown projection area (CPA, 64.7 %), crown volume (CV, 60.5 %), and aboveground volume (V, 50.5 %). At the plot level, all structural attributes also increased, including basal area (1.8 m²/ha, 4.8 % growth), H (128.9 m/ha, 1.4 %), CPA (411.9 m²/ha, 3.0 %), DBH (1.5 m/ha, 1.1 %), CV (181.7 m³/ha, 0.3 %), and V (7.9 m³/ha, 1.0 %). The total AGBC of the study area saw a net carbon gain of 0.4 Mg C/ha/year over the six-year period. Notably, trees with DBH greater than 60 cm contributed over 40 % of the total AGBC. Moreover, our results reveal that branch dynamics play a crucial role in AGBC dynamics, underscoring the added value of TLS for tracking AGBC changes over time.
{"title":"Quantifying forest structural attributes and aboveground carbon dynamics with terrestrial laser scanning in a temperate deciduous forest","authors":"Shilin Chen , Hans Verbeeck , Louise Terryn , Wout Cherlet , Chang Liu , Mathias Disney , Yadvinder Malhi , Niall Origo , Joanne Nightingale , Kim Calders","doi":"10.1016/j.agrformet.2025.110995","DOIUrl":"10.1016/j.agrformet.2025.110995","url":null,"abstract":"<div><div>Quantifying forest structure and aboveground biomass carbon (AGBC) dynamics over time is crucial for evaluating climate change impact on carbon stocks, and providing key insights into changes in the terrestrial carbon cycle. To date, the use of multi-temporal terrestrial laser scanning (TLS) to detect temporal dynamics of forest structure and AGBC remains largely unexplored. In this study, we demonstrate the use of bi-temporal TLS data to quantify fine-scale dynamics of forest structure and AGBC. A total of 831 live trees were extracted and manually aligned from two leaf-off datasets collected in a 1.4 ha area of temperate woodland (Wytham Woods, UK) in 2016 and 2022. Results indicated that, at the individual tree level, most trees exhibited positive growth in structural attributes between 2016 and 2022, including diameter at breast height (DBH, 60.2 % of trees), tree height (H, 75.8 %), crown projection area (CPA, 64.7 %), crown volume (CV, 60.5 %), and aboveground volume (V, 50.5 %). At the plot level, all structural attributes also increased, including basal area (1.8 m²/ha, 4.8 % growth), H (128.9 m/ha, 1.4 %), CPA (411.9 m²/ha, 3.0 %), DBH (1.5 m/ha, 1.1 %), CV (181.7 m³/ha, 0.3 %), and V (7.9 m³/ha, 1.0 %). The total AGBC of the study area saw a net carbon gain of 0.4 Mg C/ha/year over the six-year period. Notably, trees with DBH greater than 60 cm contributed over 40 % of the total AGBC. Moreover, our results reveal that branch dynamics play a crucial role in AGBC dynamics, underscoring the added value of TLS for tracking AGBC changes over time.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"378 ","pages":"Article 110995"},"PeriodicalIF":5.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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