Agricultural and Forest Meteorology最新文献

{"title":"Refining water and carbon fluxes modeling in terrestrial ecosystems via plant hydraulics integration","authors":"Shanshan Sun ,&nbsp;Lingcheng Li ,&nbsp;Zong-Liang Yang ,&nbsp;Guiling Wang ,&nbsp;Nate G. McDowell ,&nbsp;Ashley M. Matheny ,&nbsp;Jian Wu ,&nbsp;Shiqin Xu ,&nbsp;Hui Zheng ,&nbsp;Miao Yu ,&nbsp;Dagang Wang","doi":"10.1016/j.agrformet.2024.110256","DOIUrl":"10.1016/j.agrformet.2024.110256","url":null,"abstract":"<div><div>Plant hydraulics substantially affects terrestrial water and carbon cycles by modulating water transport and carbon assimilation. Despite improved drought simulations in certain ecosystems through their integration into land surface models (LSMs), the broader application of plant hydraulics in diverse ecosystems and hydroclimates is still underexplored. In this study, we implemented the recently developed Noah-Multiparameterization Land Surface Model (Noah-MP LSM) equipped with a plant hydraulics scheme (Noah-MP-PHS) across 40 FLUXNET sites globally. Employing the Shuffled Complex Evolution-University of Arizona (SCE-UA) auto-calibration algorithm, we optimized key plant hydraulics parameters for these sites spanning eight vegetation types in both arid and humid climates. Noah-MP-PHS significantly improves the simulation of evapotranspiration (ET) and gross primary production (GPP) by better representing atmospheric and soil water stress compared to traditional soil hydraulic schemes (SHSs, such as Noah and CLM). The augmented Noah-MP-PHS models reduce surface flux overestimation and underestimation, exhibiting an average increase of 0.14 and 0.15 in Kling-Gupta Efficiency (KGE) compared to Noah and CLM, respectively. The explicit consideration of plant capacitance in PHS reveals substantial deep-layer and nocturnal root water uptake especially under dry conditions. We employed eXplainable Machine learning (XML) to quantify the model's relative sensitivity to newly introduced leaf-, stem- and root-related parameters in PHS. The sensitivity analysis reveals a rise in root parameter importance and a decline in leaf and stem parameters as conditions shift from humid to arid. These findings indicate that as aridity states vary, the most influential parameters affecting surface fluxes variation may change in parameter calibration for PHS applications. Our findings underscore the importance of incorporating plant hydraulics into LSMs to enhance simulations of terrestrial water and carbon dynamics. These findings are crucial for understanding ecosystem responses to global climate changes and guide the broader application of PHS at larger scales.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"359 ","pages":"Article 110256"},"PeriodicalIF":5.6,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142556206","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}

{"title":"Patterns of methane flux on different temporal scales and its environmental controls over a subtropical “floating blanket” wetland in southwest China","authors":"Yamei Shao ,&nbsp;Huizhi Liu ,&nbsp;Qun Du ,&nbsp;Yang Liu ,&nbsp;Jihua Sun","doi":"10.1016/j.agrformet.2024.110280","DOIUrl":"10.1016/j.agrformet.2024.110280","url":null,"abstract":"<div><div>Wetlands are the primary natural source of methane (CH₄) emissions to the atmosphere, however, the quantification of wetland CH₄ flux and net carbon budgets remains uncertain due to limited measurements and large variability across different types of wetlands. Based on continuous measurements using the eddy covariance (EC) technique over a “floating blanket” wetland in southwest China for a period of over three years (2018–2021), we examined the temporal variations of CH₄ flux and its environmental controls on different temporal scales. The results showed that this wetland acted as a sink for carbon dioxide (CO₂) while simultaneously serving as a source for CH₄. The annual CO₂ uptake and CH₄ emission was 155.9–221.2 g C-CO₂ m⁻² yr⁻¹ and 44.6–56.9 g C-CH₄ m⁻² yr⁻¹ during 2019–2021, respectively. The annual total carbon budget varied from -176.6 g C m⁻² yr⁻¹ to -99.0 g C m⁻² yr⁻¹. From half-hourly to monthly timescales, CH₄ flux was mainly controlled by water temperature with a positive correlation. There was a negative correlation between CH₄ flux and CO₂ flux, and the importance of CO₂ flux to CH₄ flux increased as the timescale extended. CH₄ flux exhibited a significant positive correlation with the ecosystem gross primary production (GPP) and respiration (Re) on daily and monthly timescales. In addition, the fraction of vegetation cover had a positive impact on CH₄ emissions. There was a significant variation in the fraction of vegetation cover with wind direction. The southwestern wind sector had the highest fraction of vegetation cover compared to other sectors, leading to the formation of the CH₄ emission hotspot. The cumulative CH₄ emissions in the southwestern wind sector were also higher than those in other sectors, accounting for around 58.13% of the annual total CH₄ emissions, while the cumulative CH₄ emissions in other wind sectors accounted for 5.21%–21.50%.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"359 ","pages":"Article 110280"},"PeriodicalIF":5.6,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142542188","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}

{"title":"Concurrent measurements of bark and xylem water contents in Malus pumila Mill. stems using improved flexible sensors","authors":"Xianglin Cheng ,&nbsp;Xiaofei Yan ,&nbsp;Zhongyi Wang ,&nbsp;Junhui Li ,&nbsp;Ricardo F. de Oliveira ,&nbsp;Taisheng Du ,&nbsp;Qiang Cheng","doi":"10.1016/j.agrformet.2024.110290","DOIUrl":"10.1016/j.agrformet.2024.110290","url":null,"abstract":"<div><div>The pattern of radial water transport in tree stems, specifically the interaction between bark and xylem, remains elusive because few measurement techniques are not capable of independently sensing bark water content (BWC) and xylem water content (XWC). To investigate the water variations in stem, two improved flexible sensors operating at 100 MHz and equipped with small interdigital-electrode (IE) probes were developed to measure BWC and XWC independently. The performances of the flexible sensors were tested under laboratory conditions. Software simulations and laboratory measurements were performed to evaluate the volume of sensitivity (VOS) and to assess the impact of variations in stem diameter (SD) on the sensors. Concurrent measurements of BWC and XWC were performed on three trees in <em>Malus pumila</em> Mill. (Red Fuji). The measurements revealed that the difference in predawn water content between the bark and xylem gradually increased as the water deficit intensified. The maximum daily variation of BWC from predawn to afternoon (MDV_BWC) was greater than that of the maximum daily variation of XWC from predawn to afternoon (MDV_XWC). In addition, the dehydration-rehydration loops exhibited a time lag between BWC and XWC under water deficit conditions, with earlier dehydration and rehydration of the bark than of the xylem. Concurrent measurements of BWC and XWC provide a new perspective for examining the pattern of stem radial water transport. However, the time lag between BWC and XWC might need to be validated in other tree species.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"359 ","pages":"Article 110290"},"PeriodicalIF":5.6,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541650","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}

{"title":"LiDAR insights on stand structure and topography in mountain forest wind extreme events: The Vaia case study","authors":"Michele Torresani ,&nbsp;Leonardo Montagnani ,&nbsp;Duccio Rocchini ,&nbsp;Vítězslav Moudrý ,&nbsp;Andrea Andreoli ,&nbsp;Camilla Wellstein ,&nbsp;Kenta Koyanagi ,&nbsp;Luca Da Ros ,&nbsp;Giovanni Bacaro ,&nbsp;Michela Perrone ,&nbsp;Chiara Salvatori ,&nbsp;Irene Menegaldo ,&nbsp;Enrico Guatelli ,&nbsp;Roberto Tognetti","doi":"10.1016/j.agrformet.2024.110267","DOIUrl":"10.1016/j.agrformet.2024.110267","url":null,"abstract":"<div><div>With climate change intensifying, forests globally are becoming more susceptible to extreme weather events, such as windstorms, which account for a significant share of Europe’s economic losses. The Vaia windstorm of late autumn 2018, striking Italy’s North-East alpine ecosystem, highlighted this vulnerability, toppling over 8.5 million cubic meters of timber and sparking debates on forest management’s role in mitigating such disasters. This study aims to evaluate the impact of structural and topographical characteristics on the damage caused by Vaia, using Airborne Light Detection And Ranging (LiDAR) data collected before the storm, in four heavily affected forest areas in the Italian Alps (Carezza in the Province of Bolzano-Bozen, Predazzo, Manghen, and Primiero in the Province of Trento). We analyzed structural metrics like forest height heterogeneity (HH), forest mean height, and density, alongside topographical features such as aspect, slope, and altitude, to discern their influence on the storm’s severity. Our results revealed that the most significant difference between affected and unaffected areas is forest mean height that was found higher in areas hit by the storm. Forest density played a lesser but important role, with denser areas experiencing more severe damage, though this was only significant in certain areas. Contrary to common assumptions, our analysis revealed that forest height heterogeneity (HH) did not have a significant effect on damage levels. The findings, consistent with previous research, revealed a significant association between specific aspects, particularly the South-East orientation, which aligned with the predominant wind direction during the Vaia storm, and an increased likelihood of damage. Both structural and topographical factors interact in complex ways to influence the outcome of such extreme events. The study emphasizes the dominant impact of the Vaia windstorm, noting that while managing forest height and density may help, the diverse topography complicates these efforts. Our study explicitly tested the effectiveness of using Airborne LiDAR data to explore forest structural and topographical factors that influenced Vaia storm damage. The achieved results demonstrate that LiDAR serves as a useful tool to field data, offering valuable insights for broader applications in this domain.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"359 ","pages":"Article 110267"},"PeriodicalIF":5.6,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Upgrading and validating a soil water balance model to predict stem water potential in vineyards","authors":"José M. Mirás-Avalos ,&nbsp;José M. Escalona ,&nbsp;Eva Pilar Pérez-Álvarez ,&nbsp;Pascual Romero ,&nbsp;Pablo Botia ,&nbsp;Josefa Navarro ,&nbsp;Nazareth Torres ,&nbsp;Luis Gonzaga Santesteban ,&nbsp;David Uriarte ,&nbsp;Diego S. Intrigliolo ,&nbsp;I. Buesa","doi":"10.1016/j.agrformet.2024.110281","DOIUrl":"10.1016/j.agrformet.2024.110281","url":null,"abstract":"<div><div>Efficient water management is pivotal for viticulture sustainability. Decision support tools can advise on how to optimize irrigation or on the feasibility of growing grapes in rainfed conditions, but reliable algorithms for assessing vine water status are required. In this context, the aim of the current study was to upgrade a soil water balance model specific for vineyards by incorporating meteorological, soil and vine vigor in equations that transform the fraction of transpirable soil water into midday stem water potential (Ψ_stem). The model's sensitivity to variations in the magnitude of input parameters was analyzed. Furthermore, the model was tested in a broad scope of Spanish vineyards with different grapevine cultivars (both red and white), rootstocks, plant age, soil and climatic conditions, and water regimes, totaling 129 scenarios. The model was only slightly sensitive to variations in the magnitude of most inputs, except for the fraction of transpirable water at which leaf stomatal conductance begin to decline. Moreover, the model satisfactorily reproduced the evolution of Ψ_stem over the growing season, although it slightly overestimated the measured Ψ_stem values, as the slopes of the fitted regression lines were lesser than 1 on most occasions, 76 out of 129. Nonetheless, the coefficients of determination for these relationships were greater than 0.9, except for 21 datasets. Mean errors averaged 0.024 ± 0.015 MPa, while root mean square errors averaged 0.27 ± 0.01 MPa. The index of agreement was greater than 0.75 in 51 datasets, with only three datasets showing an index of agreement lower than 0.5. Nevertheless, the deviations between observed and simulated Ψ_stem values did not alter the classification of the water stress undergone by grapevines. This upgraded model could constitute the core of a decision support system for water management in vineyards, applicable to both rainfed and irrigated conditions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"359 ","pages":"Article 110281"},"PeriodicalIF":5.6,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142542104","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}

{"title":"Analysis of scale-dependent spatial correlations of actual evapotranspiration measured by lysimeters","authors":"Xiao Lu ,&nbsp;Jannis Groh ,&nbsp;Alexander Graf ,&nbsp;Thomas Pütz ,&nbsp;Katrin Schneider ,&nbsp;Bingcheng Si ,&nbsp;Harry Vereecken ,&nbsp;Harrie-Jan Hendricks Franssen","doi":"10.1016/j.agrformet.2024.110288","DOIUrl":"10.1016/j.agrformet.2024.110288","url":null,"abstract":"<div><div>Accurate determination of actual evapotranspiration (ETa) is important in various research fields like hydrology, meteorology, ecology and agriculture. <em>In situ</em> ETa can be determined using weighing lysimeters and eddy covariance. However, despite being regarded as the most precise <em>in situ</em> method for measuring ETa, the information content of lysimeter measurements remains poorly understood. Here we examined the spatial correlations between ETa measured at different locations by lysimeter (ET-LYS) and at different locations by eddy covariance (ET-EC). This was done for the period 2015 - 2020 and the analysis was made for different spatial (range: 0 to 500 km) and temporal scales (range: 1 day to 1 year) using 23 lysimeters and 4 eddy covariance towers. We found that: (a) Same lysimeters at the plot scale show very high correlations of ET-LYS; (b) The Pearson correlation of daily standardized anomalies of ET-LYS between sites exhibit moderate to high correlations and were similar to that of ET-EC, indicating that lysimeter is generally as representative as EC regarding ETa, and can provide certain information at the landscape and larger regional scale. During winter, the spatial correlations for ET-LYS were smaller; (c) Wavelet analysis indicated that temporal correlations in ETa were strongest for distances in time around 12 months (yearly cycle) and less than three months. Spatial correlations were smaller under drought conditions (in the year 2018). Furthermore, combination of multiple ET-LYS from different sites improved the predictability of ET-LYS for another site, suggesting that ET-LYS can be predicted well using ET-LYS from different neighboring sites. Overall, lysimeter measurements can provide information at much larger scales compared to their small measurement area.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"359 ","pages":"Article 110288"},"PeriodicalIF":5.6,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142542105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Partitioning and driver analysis of eddy covariance derived N2O emissions from a grazed and fertilized pasture","authors":"Lena Barczyk ,&nbsp;Johan Six ,&nbsp;Christof Ammann","doi":"10.1016/j.agrformet.2024.110278","DOIUrl":"10.1016/j.agrformet.2024.110278","url":null,"abstract":"<div><div>Managed pastures are strong sources for the greenhouse gas nitrous oxide (N₂O) through various nitrogen (N) inputs. So far, chamber measurements have been used to quantify N₂O emissions and emissions factors of specific emissions sources like grazing cattle excreta. This study presents a three-year dataset of N₂O emissions from a grazed and fertilized pasture measured by eddy covariance (EC) in eastern Switzerland. N₂O fluxes were gap-filled and disaggregated into the emission sources (flux partitioning) by using random forest. The excreta N deposition in the pasture was estimated based on a cattle nitrogen budget approach using observed milk yield, body weight and feed intake of the cattle herd. Furthermore, a driver analysis was performed to quantify the relationship between N₂O emissions and predictor variables. The observed annual N₂O emissions amounted to 5.3 ± 0.8, 3.1 ± 0.5 and 4.4 ± 0.7 kg N₂O-N ha^-1 yr^-1 and were disaggregated into background, fertilizer and excreta related N₂O emissions with contributions of 27–46 %, 15–40 % and 30–51 %, respectively. Combining the excreta N₂O fluxes with the excreta N inputs resulted in an average emission factor (EF) for cattle excreta of 1.1 ± 0.5 %, that tends to be higher than the IPCC default value of 0.6 % for wet climates. While maximum N₂O emissions usually were observed after fertilizer application and under optimum soil moisture conditions as expected, distinct N₂O emission peaks also occurred during a longer drought period in summer and could be parametrised as a function of precipitation and previous grazing activity. Moreover, peak N₂O emissions occurred during the cold season at low temperatures and should be considered in future studies. Overall, we suggest that EC measurements under pasture conditions with subsequent flux partitioning by random forest are suitable for quantifying pasture N₂O emissions of different sources.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"359 ","pages":"Article 110278"},"PeriodicalIF":5.6,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing the closure period for improved accuracy of chamber-based greenhouse gas flux estimates","authors":"C-F. Johannesson ,&nbsp;J. Nordén ,&nbsp;H. Lange ,&nbsp;H. Silvennoinen ,&nbsp;K.S. Larsen","doi":"10.1016/j.agrformet.2024.110289","DOIUrl":"10.1016/j.agrformet.2024.110289","url":null,"abstract":"<div><div>Non-steady-state chambers are often used for greenhouse gas flux measurements, and while there are recommendations on how long to keep the chamber closed, it is less investigated to what extent the length of the chamber closure period affects the estimated flux rates and which closure periods may provide the most accurate linear and non-linear flux estimates. Previous studies have shown that the closure of non-steady-state chambers induces a non-linear concentration development inside the chamber, even across short chamber closure periods, and that both linear and non-linear flux estimates are impacted by the chamber closure period itself. Based on 3,159 individual soil CO₂ and CH₄ flux measurements, we analyzed how linear regression and <span><span>Hutchinson and Mosier (1981)</span></span> modeled flux estimates are affected by the length of the chamber closure period by increasing it in increments of 30 sec, with a minimum and maximum chamber closure period of 60 and 300 sec, respectively. Across all detected flux measurements, the effect of chamber closure period length varied between 1.4–8.0 % for linear regression estimates and between 0.4–17.8 % for Hutchinson–Mosier estimates, and the largest effect sizes were observed in high flux regions. While both linear regression and Hutchinson–Mosier based estimates decreased as the chamber closure period increased, we observed a clear convergence of flux estimates as shorter and longer chamber closure periods were used for linear regression and Hutchinson–Mosier based estimation, respectively. This suggests using closure periods as short as possible for linear regression flux estimation or ensuring long-enough closure periods to observe a stabilization of Hutchinson–Mosier flux estimates over time. This analysis was based on soil flux measurements, but because the perturbation of the concentration gradient is related to the non-steady-state chamber technique rather than the measured ecosystem component, our results have implications for all flux measurements conducted with non-steady-state chambers.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"359 ","pages":"Article 110289"},"PeriodicalIF":5.6,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of vegetation phenological carryover effects on plant autumn phenology under climate change","authors":"Huanhuan YUAN ,&nbsp;Jiabao YAN ,&nbsp;Ying LIU ,&nbsp;Jie PENG ,&nbsp;Xiaoyue WANG","doi":"10.1016/j.agrformet.2024.110284","DOIUrl":"10.1016/j.agrformet.2024.110284","url":null,"abstract":"<div><div>Vegetation phenological carryover effects refer to the influence of previous phenological events on the current or subsequent ones. These effects can modulate the responses of autumn phenology to climate change, but the magnitude and duration of this effect remain poorly understood. Therefore, we employed multiple remote sensing datasets from 1982 to 2018 in the Northern Hemisphere (&gt; 30°N) and partial correlation to investigate the influence of the carryover effect and environmental factors on the end of the growing season (EOS) over time. The importance of the variables in the projection score was used to quantify their relative importance. Our results showed that the previous year's EOS had a robust positive impact on the EOS for 40.02 % of the study area during 1982–2015, which was mainly located in the northern 50°N region. In contrast, the start of the growing season (SOS) was the main contributor to the EOS during 2001–2018, mainly at 40°N-50°N and in northern Russia. The carryover effect persisted into the subsequent year, but its strength and positive impacts varied dramatically in the next year. Concurrently, the mean correlation coefficient between climate factors and EOS rose from 0.20 to 0.22. Notably, the correlation coefficient for frost day frequency increased significantly (<em>P</em> &lt; 0.05) from 0.15 to 0.36, with its influence area expanding from 10.29 % to 11.85 % of the study area. Compared with climate factors, the phenological carryover effect was the dominant driver of the EOS for each vegetation type, accounting for 72.8 % and 44.23 % of the total pixels during 1982–2015 and 2001–2018, respectively. Our study reveals a cascade of ecological consequences that extend beyond the initial occurrence and emphasizes the interconnectedness of growth stages in the plant life cycle, providing valuable insights into the adaptability and vulnerability of plant communities.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"359 ","pages":"Article 110284"},"PeriodicalIF":5.6,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142519576","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}

{"title":"Evaluating the phase evolution of CMIP GCMs for agricultural climate-change impact assessments in China","authors":"Linlin Yao ,&nbsp;Qian Tan ,&nbsp;Guanhui Cheng ,&nbsp;Shuping Wang ,&nbsp;Bingming Chen","doi":"10.1016/j.agrformet.2024.110282","DOIUrl":"10.1016/j.agrformet.2024.110282","url":null,"abstract":"<div><div>The performance of general circulation models (GCMs) in the Coupled Model Intercomparison Project (CMIP) critically determines the reliability of climate-change impact assessments and has continuously progressed (e.g., from CMIP3, CMIP5 to CMIP6). It remains unclear whether this progression enhances the reliability in evaluating the effects of climate change on agricultural systems at a daily resolution, particularly concerning crop production. To address this question, the study selected AquaCrop as a crop model for large-scale agricultural impact assessment due to its compatibility, robustness, and simplicity. Subsequently, the study coupled AquaCrop with multiple GCMs from different CMIP phases: 9 from CMIP3, 14 from CMIP5, and 15 from CMIP6, and attributed GCM-driven crop yield simulations to GCM biases over China. According to the modeling results, the progression enhanced the simulation performance for daily precipitation and temperature. The impacts of CMIPs on assessment results exhibited variability across temporal scales and crop types, further modulated by water management practices. Overall, crop simulations across three CMIP phases revealed a reduction in cold and water stresses, a shortened growing period (particularly evident in CMIP6), and an underestimation of yields. The evolution of CMIP phases increased spatial-temporal correlations for maize (0.61 to 0.81), wheat (0.68 to 0.77), and rice (0.63 to 0.77), without significantly reducing yield biases. Yield biases in early growth period were primarily influenced by daily temperature fluctuations, while biases in latter growth period were correlated with precipitation and maximum temperature. Irrigation mitigated the crop model's sensitivity to precise daily precipitation data compared to rainfed systems. This comprehensive analysis suggests, when evaluating climate change impacts on agriculture—at least for Chinese crops—CMIP6 better captured regional and temporal yield distributions than earlier phases, despite potentially underestimating yields and growth periods in certain regions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"359 ","pages":"Article 110282"},"PeriodicalIF":5.6,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142519537","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}