Agricultural and Forest Meteorology最新文献_第7页

Seasonal patterns and hydrological regulations of root zone storage capacity across United States

IF 5.6 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-01-30 DOI: 10.1016/j.agrformet.2025.110428

Shuping Du , Shanhu Jiang , Liliang Ren , Yongwei Zhu , Hao Cui , Miao He , Chong-Yu Xu

Root zone storage capacity (S_r) represents the maximum subsurface storage accessible to plant roots. It is primarily influenced by water availability and water demand, thus exhibiting temporal change in response to climate variations. Previous studies have primarily focused on the spatial patterns of S_r across local to global scales; however, there remains a limited understanding of its temporal patterns, particularly in relation to seasonal changes. This work explores the seasonal behavior of S_r for wet and dry seasons and the hydrological regulation of seasonal S_r. We propose a seasonal modeling framework based on apportionment entropy, which considers the phase difference between water and energy. Within this framework, the PDM-FLEX hydrological model, an integration of the probability distributed model (PDM) with the FLEX lumped model, was employed to calculate catchment-scale S_r for each season across 671 catchments in the contiguous United States. Results show that: i) this framework can effectively capture seasonal S_r, with wet season S_r (an average of 564 mm) generally being smaller than dry season S_r (an average of 820 mm) for most catchments. In the west, plants routinely access deep water, leading to comparable S_r for both wet and dry seasons. Incorporating seasonal S_r into the hydrological model can improve simulation performance across time scales; ii) dry season S_r is more responsive to hydroclimatic control compared to wet season S_r, as plants in arid climates are more sensitive to water accessibility; and iii) during the wet season, low S_r relative to precipitation leads to an unresponsive hydrological reaction. However, during the dry season, a routine correlation between S_r and precipitation produces responsive hydrological behavior. These findings indicate that plants seasonally adapt their root systems and that these seasonal variations in S_r would have significant hydrological implications.

{"title":"Seasonal patterns and hydrological regulations of root zone storage capacity across United States","authors":"Shuping Du , Shanhu Jiang , Liliang Ren , Yongwei Zhu , Hao Cui , Miao He , Chong-Yu Xu","doi":"10.1016/j.agrformet.2025.110428","DOIUrl":"10.1016/j.agrformet.2025.110428","url":null,"abstract":"<div><div>Root zone storage capacity (S<sub>r</sub>) represents the maximum subsurface storage accessible to plant roots. It is primarily influenced by water availability and water demand, thus exhibiting temporal change in response to climate variations. Previous studies have primarily focused on the spatial patterns of S<sub>r</sub> across local to global scales; however, there remains a limited understanding of its temporal patterns, particularly in relation to seasonal changes. This work explores the seasonal behavior of S<sub>r</sub> for wet and dry seasons and the hydrological regulation of seasonal S<sub>r</sub>. We propose a seasonal modeling framework based on apportionment entropy, which considers the phase difference between water and energy. Within this framework, the PDM-FLEX hydrological model, an integration of the probability distributed model (PDM) with the FLEX lumped model, was employed to calculate catchment-scale S<sub>r</sub> for each season across 671 catchments in the contiguous United States. Results show that: i) this framework can effectively capture seasonal S<sub>r</sub>, with wet season S<sub>r</sub> (an average of 564 mm) generally being smaller than dry season S<sub>r</sub> (an average of 820 mm) for most catchments. In the west, plants routinely access deep water, leading to comparable S<sub>r</sub> for both wet and dry seasons. Incorporating seasonal S<sub>r</sub> into the hydrological model can improve simulation performance across time scales; ii) dry season S<sub>r</sub> is more responsive to hydroclimatic control compared to wet season S<sub>r</sub>, as plants in arid climates are more sensitive to water accessibility; and iii) during the wet season, low S<sub>r</sub> relative to precipitation leads to an unresponsive hydrological reaction. However, during the dry season, a routine correlation between S<sub>r</sub> and precipitation produces responsive hydrological behavior. These findings indicate that plants seasonally adapt their root systems and that these seasonal variations in S<sub>r</sub> would have significant hydrological implications.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"363 ","pages":"Article 110428"},"PeriodicalIF":5.6,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143056797","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}

引用次数: 0

Impact of 38-year integrated nutrient management on soil carbon sequestration and greenhouse gas emissions of a rice-wheat cropping system

IF 5.6 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-01-30 DOI: 10.1016/j.agrformet.2025.110415

Manjeet Kaur , G.S. Dheri , S.S. Walia , O.P. Choudhary

Integrating chemical fertilizers and organic manures is critical for improving soil health, increasing crop production, and mitigating the adverse environmental effects of the rice-wheat cropping system (RWCS). Numerous attempts have been made to evaluate the influence of integrated nutrient management (INM) on both crop yields and greenhouse gas (GHG) emissions during a single crop growing season. However, few studies have quantified the impact across an entire rotation cycle in this cropping system, considering the CO₂ uptake due to soil carbon (C) sequestration and saving of chemical fertilizer in INM practices. Therefore, the study was conducted to quantify the effects of 38 years of INM in rice-wheat cropping system on C sequestration and GHG emissions. Five treatment combinations of fertilizer nutrients (NPK) alone and their partial substitution (25 % N) with organic sources either through farmyard manure (FYM) or wheat cut straw (WCS) or green manuring (GM) in rice, and only chemical fertilizers at different levels in succeeding wheat crop were studied for two years (2019–20 and 2020–21). The results showed that substituting 25 % fertilizer N with organic materials (FYM/WCS/GM) in rice and using 25 % less NPK in wheat for 38 years significantly improved soil properties, including SOC sequestration, and increased crop yield (except WCS). INM increased the GHG emissions over chemical fertilization (100 % NPK), but the GHGI (greenhouse gas intensity) was equivalent, except for the usage of WCS in RWCS. Overall, in RWCS, INM via substituting 25 % fertilizer N with FYM/GM in rice and applying 75 % NPK in wheat had lower GHGI than only chemical fertilizer application, indicating the advantages of these amendments for increasing soil health, crop production, and climate change mitigation. Further research is required to determine the correlation between the mineralization patterns of added organic amendments, soil C fractions during critical crop growth stages, and GHG emissions.

{"title":"Impact of 38-year integrated nutrient management on soil carbon sequestration and greenhouse gas emissions of a rice-wheat cropping system","authors":"Manjeet Kaur , G.S. Dheri , S.S. Walia , O.P. Choudhary","doi":"10.1016/j.agrformet.2025.110415","DOIUrl":"10.1016/j.agrformet.2025.110415","url":null,"abstract":"<div><div>Integrating chemical fertilizers and organic manures is critical for improving soil health, increasing crop production, and mitigating the adverse environmental effects of the rice-wheat cropping system (RWCS). Numerous attempts have been made to evaluate the influence of integrated nutrient management (INM) on both crop yields and greenhouse gas (GHG) emissions during a single crop growing season. However, few studies have quantified the impact across an entire rotation cycle in this cropping system, considering the CO<sub>2</sub> uptake due to soil carbon (C) sequestration and saving of chemical fertilizer in INM practices. Therefore, the study was conducted to quantify the effects of 38 years of INM in rice-wheat cropping system on C sequestration and GHG emissions. Five treatment combinations of fertilizer nutrients (NPK) alone and their partial substitution (25 % N) with organic sources either through farmyard manure (FYM) or wheat cut straw (WCS) or green manuring (GM) in rice, and only chemical fertilizers at different levels in succeeding wheat crop were studied for two years (2019–20 and 2020–21). The results showed that substituting 25 % fertilizer N with organic materials (FYM/WCS/GM) in rice and using 25 % less NPK in wheat for 38 years significantly improved soil properties, including SOC sequestration, and increased crop yield (except WCS). INM increased the GHG emissions over chemical fertilization (100 % NPK), but the GHGI (greenhouse gas intensity) was equivalent, except for the usage of WCS in RWCS. Overall, in RWCS, INM via substituting 25 % fertilizer N with FYM/GM in rice and applying 75 % NPK in wheat had lower GHGI than only chemical fertilizer application, indicating the advantages of these amendments for increasing soil health, crop production, and climate change mitigation. Further research is required to determine the correlation between the mineralization patterns of added organic amendments, soil C fractions during critical crop growth stages, and GHG emissions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"363 ","pages":"Article 110415"},"PeriodicalIF":5.6,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143057189","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}

引用次数: 0

Drought-induced water use patterns in epiphytic ferns and orchids of the Hainan tropical cloud forest, South China

IF 5.6 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-01-30 DOI: 10.1016/j.agrformet.2025.110400

Liangyu Wen , Dexu Zhang , Chuchu Xiao , Guang Feng , Ewuketu Linger , Wenxing Long

Understanding how epiphytic vascular plants respond to drought is essential for elucidating the potential mechanisms that may contribute to their resilience in the context of global climate change. Despite numerous studies have estimated tropical epiphytic vascular plants’ water source and use efficiency, their response to drought induced water scarcity poorly understood. We conducted an in-situ water reduction control experiment (i.e., controlling rain and fog water, each with three treatments) on epiphytic vascular plant communities in a biodiverse hotspots region of Hainan tropical cloud forest. We then investigated the water sources and water use efficiency (WUE) of epiphytic vascular plants under different drought gradients. We found a significant seasonal variation in water sources: 63 %–67 % in the dry season (November to April of the next year) and 64 %–70 % in the wet season (May to October) came from fog and rain, respectively In the wet season, epiphytic ferns utilized 39 % fog and 61 % rain, while orchids utilized 31 % fog and 69 % rain. Ferns absorbed significantly more fog water than orchids under all drought gradients. In the dry season, 63 % of the water in epiphytic ferns and 64 % in orchids originated from fog, while 37 % and 36 % from rain for ephiphytic ferns and orchids respectively. The WUE of ferns was significantly higher than that of orchids under all drought gradients. These findings reveal that both epiphytic vascular plant communities and epiphytic taxa display selective and complementary water uptake strategies, with distinct differences in water use strategy between epiphytic ferns and orchids.

{"title":"Drought-induced water use patterns in epiphytic ferns and orchids of the Hainan tropical cloud forest, South China","authors":"Liangyu Wen , Dexu Zhang , Chuchu Xiao , Guang Feng , Ewuketu Linger , Wenxing Long","doi":"10.1016/j.agrformet.2025.110400","DOIUrl":"10.1016/j.agrformet.2025.110400","url":null,"abstract":"<div><div>Understanding how epiphytic vascular plants respond to drought is essential for elucidating the potential mechanisms that may contribute to their resilience in the context of global climate change. Despite numerous studies have estimated tropical epiphytic vascular plants’ water source and use efficiency, their response to drought induced water scarcity poorly understood. We conducted an <em>in-situ</em> water reduction control experiment (<em>i.e.,</em> controlling rain and fog water, each with three treatments) on epiphytic vascular plant communities in a biodiverse hotspots region of Hainan tropical cloud forest. We then investigated the water sources and water use efficiency (WUE) of epiphytic vascular plants under different drought gradients. We found a significant seasonal variation in water sources: 63 %–67 % in the dry season (November to April of the next year) and 64 %–70 % in the wet season (May to October) came from fog and rain, respectively In the wet season, epiphytic ferns utilized 39 % fog and 61 % rain, while orchids utilized 31 % fog and 69 % rain. Ferns absorbed significantly more fog water than orchids under all drought gradients. In the dry season, 63 % of the water in epiphytic ferns and 64 % in orchids originated from fog, while 37 % and 36 % from rain for ephiphytic ferns and orchids respectively. The WUE of ferns was significantly higher than that of orchids under all drought gradients. These findings reveal that both epiphytic vascular plant communities and epiphytic taxa display selective and complementary water uptake strategies, with distinct differences in water use strategy between epiphytic ferns and orchids.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"363 ","pages":"Article 110400"},"PeriodicalIF":5.6,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143056791","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}

引用次数: 0

Impacts of Spartina alterniflora invasion on coastal carbon cycling within a native Phragmites australis-dominated wetland

IF 5.6 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-01-30 DOI: 10.1016/j.agrformet.2025.110405

Ying Huang , Jiangtao Wang , Pengfei Wu , Zheng Duan , Xiuzhen Li , Jianwu Tang

Despite its significance for climate adaptation, the impact of non-native Spartina alterniflora on coastal blue carbon cycling remains unclear. While it is generally reported that S. alterniflora invasion increases the soil organic carbon (SOC) stock along China's coastlines from tropical to subtropical climate zones, some cases, such as the Jiuduansha wetland in the Yangtze River estuary, show a different pattern. To clarify the impacts of S. alterniflora invasion on carbon cycling within a native Phragmites australis-dominated wetland, a comprehensive study was conducted in the Yangtze River estuary, employing a multidisciplinary approach that integrated eddy covariance (EC) measurements, soil and water sampling, and satellite remote sensing. The EC measurements revealed that three marshes (S. alterniflora saltmarsh, native Phragmites australis saltmarsh, and P. australis freshwater marsh) functioned as net carbon sinks annually, with S. alterniflora saltmarsh capturing 822.57 g C m⁻² yr⁻¹, which was 86.13 % and 54.27 % higher than P. australis saltmarsh (NEE=−441.93 g C m⁻² yr⁻¹) and P. australis freshwater marsh (NEE=−533.21 g C m⁻² yr⁻¹), respectively. This suggests that enhanced lateral carbon fluxes from the wetland to the estuary underlie the higher primary production but lower SOC storage observed in S. alterniflora wetlands. This possibility is further supported by higher satellite-derived dissolved organic carbon concentrations in the tidal creeks adjacent to S. alterniflora compared to those near P. australis marshes, which were significantly correlated with satellite-derived non-photosynthetic vegetation fractional cover. This study underscores the role of non-native S. alterniflora in facilitating carbon transfer from the atmosphere to the estuary, in contrast to native P. australis, and highlights that effective S. alterniflora management is beneficial for the synergistic enhancement of wetland restoration, conservation, and carbon sequestration.

{"title":"Impacts of Spartina alterniflora invasion on coastal carbon cycling within a native Phragmites australis-dominated wetland","authors":"Ying Huang , Jiangtao Wang , Pengfei Wu , Zheng Duan , Xiuzhen Li , Jianwu Tang","doi":"10.1016/j.agrformet.2025.110405","DOIUrl":"10.1016/j.agrformet.2025.110405","url":null,"abstract":"<div><div>Despite its significance for climate adaptation, the impact of non-native <em>Spartina alterniflora</em> on coastal blue carbon cycling remains unclear. While it is generally reported that <em>S. alterniflora</em> invasion increases the soil organic carbon (SOC) stock along China's coastlines from tropical to subtropical climate zones, some cases, such as the Jiuduansha wetland in the Yangtze River estuary, show a different pattern. To clarify the impacts of <em>S. alterniflora</em> invasion on carbon cycling within a native <em>Phragmites australis</em>-dominated wetland, a comprehensive study was conducted in the Yangtze River estuary, employing a multidisciplinary approach that integrated eddy covariance (EC) measurements, soil and water sampling, and satellite remote sensing. The EC measurements revealed that three marshes (<em>S. alterniflora</em> saltmarsh, native <em>Phragmites australis</em> saltmarsh, and <em>P. australis</em> freshwater marsh) functioned as net carbon sinks annually, with <em>S. alterniflora</em> saltmarsh capturing 822.57 g C m<sup>−2</sup> yr<sup>−1</sup>, which was 86.13 % and 54.27 % higher than <em>P. australis</em> saltmarsh (NEE=−441.93 g C m<sup>−2</sup> yr<sup>−1</sup>) and <em>P. australis</em> freshwater marsh (NEE=−533.21 g C m<sup>−2</sup> yr<sup>−1</sup>), respectively. This suggests that enhanced lateral carbon fluxes from the wetland to the estuary underlie the higher primary production but lower SOC storage observed in <em>S. alterniflora</em> wetlands. This possibility is further supported by higher satellite-derived dissolved organic carbon concentrations in the tidal creeks adjacent to <em>S. alterniflora</em> compared to those near <em>P. australis</em> marshes, which were significantly correlated with satellite-derived non-photosynthetic vegetation fractional cover. This study underscores the role of non-native <em>S. alterniflora</em> in facilitating carbon transfer from the atmosphere to the estuary, in contrast to native <em>P. australis</em>, and highlights that effective <em>S. alterniflora</em> management is beneficial for the synergistic enhancement of wetland restoration, conservation, and carbon sequestration.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"363 ","pages":"Article 110405"},"PeriodicalIF":5.6,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143072236","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}

引用次数: 0

Seasonal vapor pressure deficit and temperature effects on carbon dioxide and water dynamics in a prevalent crop rotation in the northern Great Plains

IF 5.6 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-01-27 DOI: 10.1016/j.agrformet.2025.110425

Craig W. Whippo, Nicanor Z. Saliendra, Mark A. Liebig, David W. Archer

A spring wheat (Triticum aestivum L.) -corn (Zea mays L.) -soybean (Glycine max (L.) Merr.) rotation has become widespread in dry-land cropping systems in the northern Great Plains of the United States. But this region experiences extreme variability in climate, which is projected to increase in the future, and little is known about how seasonal weather changes impact this crop rotation in terms of carbon and water balances. To address this research gap, we analyzed micrometeorological and eddy covariance measurements through two rotations of spring wheat-corn-soybean in a no-till, rainfed field managed according to prevailing local practices near Mandan, ND USA. Using linear regression models, we found a negative correlation between vapor pressure deficit (VPD) and soil water content, which explained 84 % of the variation in net-ecosystem production (NEP) and 64 % of the variation in gross ecosystem production (GEP). Results also indicated that evapotranspiration (ET) across dormant and growing seasons among three crops (i.e., six crop-seasons) was mainly determined by VPD during the dormant season but a threshold ET was attained as VPD increased between growing seasons. Elevated temperatures during the dormant season explained 88 % of the variability in ecosystem respiration during the dormant season. These results imply that anticipated increases in evaporative demand due to elevated temperatures and/or low humidity in conjunction with soil drought may necessitate wider adoption of conservation agricultural practices that enhance soil moisture recharge during the dormant season.

{"title":"Seasonal vapor pressure deficit and temperature effects on carbon dioxide and water dynamics in a prevalent crop rotation in the northern Great Plains","authors":"Craig W. Whippo, Nicanor Z. Saliendra, Mark A. Liebig, David W. Archer","doi":"10.1016/j.agrformet.2025.110425","DOIUrl":"10.1016/j.agrformet.2025.110425","url":null,"abstract":"<div><div>A spring wheat (<em>Triticum aestivum</em> L.) -corn (<em>Zea mays</em> L.) -soybean (<em>Glycine</em> max (L.) Merr.) rotation has become widespread in dry-land cropping systems in the northern Great Plains of the United States. But this region experiences extreme variability in climate, which is projected to increase in the future, and little is known about how seasonal weather changes impact this crop rotation in terms of carbon and water balances. To address this research gap, we analyzed micrometeorological and eddy covariance measurements through two rotations of spring wheat-corn-soybean in a no-till, rainfed field managed according to prevailing local practices near Mandan, ND USA. Using linear regression models, we found a negative correlation between vapor pressure deficit (VPD) and soil water content, which explained 84 % of the variation in net-ecosystem production (NEP) and 64 % of the variation in gross ecosystem production (GEP). Results also indicated that evapotranspiration (ET) across dormant and growing seasons among three crops (i.e., six crop-seasons) was mainly determined by VPD during the dormant season but a threshold ET was attained as VPD increased between growing seasons. Elevated temperatures during the dormant season explained 88 % of the variability in ecosystem respiration during the dormant season. These results imply that anticipated increases in evaporative demand due to elevated temperatures and/or low humidity in conjunction with soil drought may necessitate wider adoption of conservation agricultural practices that enhance soil moisture recharge during the dormant season.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"363 ","pages":"Article 110425"},"PeriodicalIF":5.6,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143050574","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}

引用次数: 0

Extreme hydroclimates amplify the biophysical effects of advanced green-up in temperate China

IF 5.6 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-01-27 DOI: 10.1016/j.agrformet.2025.110421

Lingxue Yu , Ye Liu , Miaogen Shen , Zicheng Yu , Xuan Li , Huanjun Liu , Vincent Lyne , Ming Jiang , Chaoyang Wu

Vegetation phenology modulates climate by altering energy and water exchange between the land and atmosphere. However, how extreme hydroclimatic conditions modify these phenology-climate feedbacks is still poorly understood. In this study, we used a land–atmosphere-coupled Weather Research and Forecasting model to explore the impacts of advanced green-up on air temperature under different hydroclimate conditions across temperate China and to Mechanistic analysis elucidate the underlying biophysical mechanisms. By imposing a 14-day earlier green-up in line with recent satellite observations, we found that under mean climate conditions, an earlier leaf-out induces immediate surface cooling of 0.14 °C during green-up and a lagging 0.02 °C warming during senescence averaged for temperate China. Extremely humid conditions amplify the cooling effects to 0.18 °C during green-up, extending this cooling into the senescence period. Conversely, under extremely arid conditions, earlier green-up cools air temperature by 0.09 °C, and amplified senescence warming to 0.16 °C. Mechanism analysis revealed that evapotranspiration-dominated non-radiative processes drive immediate cooling during green-up while radiation and circulation process dominates the delayed but opposite warming/cooling effects during senescence in extremely arid/humid hydroclimates. Given the projected continuation of warming trends and increased frequency of extreme climatic events, it is imperative to incorporate the biophysical effects of vegetation phenology into local climate adaptation strategies.

植被物候通过改变陆地与大气之间的能量和水分交换来调节气候。然而，人们对极端水文气候条件如何改变这些物候-气候反馈仍知之甚少。在本研究中，我们利用陆地-大气耦合天气研究与预报模型，探讨了在中国温带不同水文气候条件下，提前返青对气温的影响，并通过机制分析阐明了其背后的生物物理机制。根据最近的卫星观测结果，我们将返青期提前了14天，结果发现，在平均气候条件下，返青期提前落叶会立即导致地表降温0.14 °C，而衰老期平均升温0.02 °C。在极度潮湿的条件下，返青期的降温效应扩大到 0.18 °C，并将降温效应延续到衰老期。相反，在极端干旱条件下，较早的返青期会使气温降低 0.09 °C，并将衰老期的升温效应放大到 0.16 °C。机理分析表明，以蒸腾作用为主的非辐射过程驱动了返青期的直接降温，而在极端干旱/潮湿的水文气候条件下，辐射和环流过程主导了衰老期延迟但相反的升温/降温效应。鉴于气候变暖的趋势预计将持续，极端气候事件的发生频率也将增加，因此必须将植被物候的生物物理效应纳入当地的气候适应战略。

{"title":"Extreme hydroclimates amplify the biophysical effects of advanced green-up in temperate China","authors":"Lingxue Yu , Ye Liu , Miaogen Shen , Zicheng Yu , Xuan Li , Huanjun Liu , Vincent Lyne , Ming Jiang , Chaoyang Wu","doi":"10.1016/j.agrformet.2025.110421","DOIUrl":"10.1016/j.agrformet.2025.110421","url":null,"abstract":"<div><div>Vegetation phenology modulates climate by altering energy and water exchange between the land and atmosphere. However, how extreme hydroclimatic conditions modify these phenology-climate feedbacks is still poorly understood. In this study, we used a land–atmosphere-coupled Weather Research and Forecasting model to explore the impacts of advanced green-up on air temperature under different hydroclimate conditions across temperate China and to Mechanistic analysis elucidate the underlying biophysical mechanisms. By imposing a 14-day earlier green-up in line with recent satellite observations, we found that under mean climate conditions, an earlier leaf-out induces immediate surface cooling of 0.14 °C during green-up and a lagging 0.02 °C warming during senescence averaged for temperate China. Extremely humid conditions amplify the cooling effects to 0.18 °C during green-up, extending this cooling into the senescence period. Conversely, under extremely arid conditions, earlier green-up cools air temperature by 0.09 °C, and amplified senescence warming to 0.16 °C. Mechanism analysis revealed that evapotranspiration-dominated non-radiative processes drive immediate cooling during green-up while radiation and circulation process dominates the delayed but opposite warming/cooling effects during senescence in extremely arid/humid hydroclimates. Given the projected continuation of warming trends and increased frequency of extreme climatic events, it is imperative to incorporate the biophysical effects of vegetation phenology into local climate adaptation strategies.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"363 ","pages":"Article 110421"},"PeriodicalIF":5.6,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143044828","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}

引用次数: 0

Significant roles of snow and vegetation cover in modulating altitudinal gradients of land surface temperature over Asia high mountains 积雪和植被在调节亚洲高山地表温度海拔梯度方面的重要作用

IF 5.6 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-01-27 DOI: 10.1016/j.agrformet.2025.110406

Hongbo Zhang , Fan Zhang , Lun Luo , Wei Yan , Longhui Zhang , Ziying Li

The land surface temperature gradient (LSTG) serves as a key indicator of mountain thermal patterns that critically influences hydrological and ecological processes in mountainous regions. However, our understanding of LSTG across the Asian high mountains (AHM) is limited due to sparse observations and unexplored influences of surface characteristic heterogeneity within the grid used for LSTG calculation. Using a novel gridded dataset of monthly LSTG with improved local reliability, this study firstly uncovers significant spatiotemporal variations in AHM LSTGs. Then, employing an explainable machine learning approach coupled with surface energy balance analyses, we investigate the effects of ten environmental factors, including sub-grid gradients of snow, cloud, and vegetation cover. Our results reveal that spatial variations of annual LSTGs are predominantly driven by downward longwave radiation and sub-grid snow cover gradient index (SGI), with SGI dominating during cold months (April‒November) due to the substantial cooling effects of snow at higher elevations. Seasonally, three distinct LSTG patterns are detected: Spring-unimodal (21.0% of the study area), characterized by a single peak in spring; Summer-unimodal (25.2%), with a single peak in summer; and Spring-Autumn-bimodal (34.6%), showing two peaks in spring and autumn. These patterns are closely linked to local snow cover dynamics, with SGI playing a critical role in shaping the Spring-unimodal and Spring-Autumn-bimodal patterns through snow-albedo feedback, while surface net radiation primarily drives the Summer-unimodal pattern. Interannually, most of the significant LSTG trends are decreasing, mainly attributed to accelerated snow cover depletion at higher elevations, while increased vegetation cover gradient is the main contributor to increasing LSTGs. These findings highlight the importance of considering fine-scale surface heterogeneity in understanding mountain climate dynamics. The results also inform future research on integrating LSTG into ecological, agricultural, and hydrological models to better predict climate change impacts on high-mountain ecosystems.

{"title":"Significant roles of snow and vegetation cover in modulating altitudinal gradients of land surface temperature over Asia high mountains","authors":"Hongbo Zhang , Fan Zhang , Lun Luo , Wei Yan , Longhui Zhang , Ziying Li","doi":"10.1016/j.agrformet.2025.110406","DOIUrl":"10.1016/j.agrformet.2025.110406","url":null,"abstract":"<div><div>The land surface temperature gradient (LSTG) serves as a key indicator of mountain thermal patterns that critically influences hydrological and ecological processes in mountainous regions. However, our understanding of LSTG across the Asian high mountains (AHM) is limited due to sparse observations and unexplored influences of surface characteristic heterogeneity within the grid used for LSTG calculation. Using a novel gridded dataset of monthly LSTG with improved local reliability, this study firstly uncovers significant spatiotemporal variations in AHM LSTGs. Then, employing an explainable machine learning approach coupled with surface energy balance analyses, we investigate the effects of ten environmental factors, including sub-grid gradients of snow, cloud, and vegetation cover. Our results reveal that spatial variations of annual LSTGs are predominantly driven by downward longwave radiation and sub-grid snow cover gradient index (SGI), with SGI dominating during cold months (April‒November) due to the substantial cooling effects of snow at higher elevations. Seasonally, three distinct LSTG patterns are detected: Spring-unimodal (21.0% of the study area), characterized by a single peak in spring; Summer-unimodal (25.2%), with a single peak in summer; and Spring-Autumn-bimodal (34.6%), showing two peaks in spring and autumn. These patterns are closely linked to local snow cover dynamics, with SGI playing a critical role in shaping the Spring-unimodal and Spring-Autumn-bimodal patterns through snow-albedo feedback, while surface net radiation primarily drives the Summer-unimodal pattern. Interannually, most of the significant LSTG trends are decreasing, mainly attributed to accelerated snow cover depletion at higher elevations, while increased vegetation cover gradient is the main contributor to increasing LSTGs. These findings highlight the importance of considering fine-scale surface heterogeneity in understanding mountain climate dynamics. The results also inform future research on integrating LSTG into ecological, agricultural, and hydrological models to better predict climate change impacts on high-mountain ecosystems.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"363 ","pages":"Article 110406"},"PeriodicalIF":5.6,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143050723","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}

引用次数: 0

Seasonal precipitation variability controls shallow soil water drought events across the southwestern United States

IF 5.6 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-01-25 DOI: 10.1016/j.agrformet.2025.110403

Trevor T. McKellar, Michael A. Crimmins

The semi-arid climate of the Southwestern United States (‘Southwest’) presents unique challenges for quantifying drought conditions due to annual potential evapotranspiration being significantly greater than annual precipitation. Southwestern vegetation is adapted to seasonal soil water recharge for primary productivity, with recharge delays potentially resulting in drought impacts. Understanding how delays in seasonal precipitation timing and magnitude create soil water anomalies is key for characterizing drought dynamics in Southwestern soils; however, the lack of long-term, reliable soil water datasets have restricted this effort to a local scale. Here, we couple sophisticated soil water modeling, site-specific soil information, and spatially continuous, high resolution meteorological data to create a soil water dataset for the purpose of characterizing shallow drought onset and cessation patterns in Southwestern soils. Daily matric potential at 10 cm and 30 cm was simulated from 1979 to 2020 at 240 locations throughout 4 Major Land Resource Areas (MLRA). Historical matric potential anomaly time series were percent ranked from 0 to 100 %, with consecutive days below the 15th percentile quantified as drought events. Drought events were categorized by duration and analyzed by onset and cessation season. Results showed that short-term droughts (60 – 270 days) were frequent, and typically resulted from delayed or slowed starts to the MLRAs major modal precipitation season. Long-term droughts (>270 days) were infrequent and occurred only during specific years, requiring below average anomalies in one or more consecutive rainy seasons. Long-term droughts were more likely to occur in MLRAs with unimodal precipitation distributions, due to soil water anomalies likely remaining unresolved until the following rainy season. MLRAs with bimodal precipitation distributions made long-term drought development difficult as consecutive below average rainy seasons were needed. With expected changes in Southwestern climate over the coming decades, understanding how changing precipitation patterns will impact shallow soil drought development is key for future impact assessment and mitigation.

{"title":"Seasonal precipitation variability controls shallow soil water drought events across the southwestern United States","authors":"Trevor T. McKellar, Michael A. Crimmins","doi":"10.1016/j.agrformet.2025.110403","DOIUrl":"10.1016/j.agrformet.2025.110403","url":null,"abstract":"<div><div>The semi-arid climate of the Southwestern United States (‘Southwest’) presents unique challenges for quantifying drought conditions due to annual potential evapotranspiration being significantly greater than annual precipitation. Southwestern vegetation is adapted to seasonal soil water recharge for primary productivity, with recharge delays potentially resulting in drought impacts. Understanding how delays in seasonal precipitation timing and magnitude create soil water anomalies is key for characterizing drought dynamics in Southwestern soils; however, the lack of long-term, reliable soil water datasets have restricted this effort to a local scale. Here, we couple sophisticated soil water modeling, site-specific soil information, and spatially continuous, high resolution meteorological data to create a soil water dataset for the purpose of characterizing shallow drought onset and cessation patterns in Southwestern soils. Daily matric potential at 10 cm and 30 cm was simulated from 1979 to 2020 at 240 locations throughout 4 Major Land Resource Areas (MLRA). Historical matric potential anomaly time series were percent ranked from 0 to 100 %, with consecutive days below the 15th percentile quantified as drought events. Drought events were categorized by duration and analyzed by onset and cessation season. Results showed that short-term droughts (60 – 270 days) were frequent, and typically resulted from delayed or slowed starts to the MLRAs major modal precipitation season. Long-term droughts (>270 days) were infrequent and occurred only during specific years, requiring below average anomalies in one or more consecutive rainy seasons. Long-term droughts were more likely to occur in MLRAs with unimodal precipitation distributions, due to soil water anomalies likely remaining unresolved until the following rainy season. MLRAs with bimodal precipitation distributions made long-term drought development difficult as consecutive below average rainy seasons were needed. With expected changes in Southwestern climate over the coming decades, understanding how changing precipitation patterns will impact shallow soil drought development is key for future impact assessment and mitigation.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"363 ","pages":"Article 110403"},"PeriodicalIF":5.6,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143031345","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}

引用次数: 0

Separating leaf area index from plant area index using semi-supervised classification of digital hemispheric canopy photographs: A case study of dryland vegetation

IF 5.6 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-01-24 DOI: 10.1016/j.agrformet.2025.110395

Jake Eckersley , Caitlin E. Moore , Sally E. Thompson , Michael Renton , Pauline F. Grierson

Leaf area index (LAI) describes the main plant surface area for gas exchange. Accurate LAI measurements are integral to effective hydrological, ecological, and climate modelling. LAI is commonly modelled using canopy gap fraction measurements from optical sensors. In woody vegetation, however, the wood to total plant area ratio (

α

) must also be estimated to convert plant area index (PAI) to LAI. Historically, estimating

α

required destructive harvests and is a potential source of LAI error. In this study, we present a theoretical framework for estimating LAI from digital hemispheric canopy photography by correcting for

α

within each image using semi-supervised pixel classification. We apply this framework to 201 images collected in semi-arid Australian vegetation (overstorey LAI range 0–5) to explore potential sources of error from: image classification, LAI model implementation, and differences in

α

among vegetation types. Leaf, wood, and canopy gap (sky) pixels were classified using a random forest (RF) algorithm with 87.7 ± 0.01 % accuracy (mean ± standard error) under overcast skies but 81.3 ± 0.01 % under clear sky conditions where leaf and wood pixel classification was inconsistent. LAI estimates using the proposed approach had a strong linear relationship to PAI (r² ≥ 0.97). However, the proportional contribution of woody material to canopy gap fraction was zenith angle dependent. Allowing

α

to vary by zenith and azimuth angle when calculating LAI resulted in estimates 10–17 % higher than widely used PAI conversion methods. The zenith angle distribution of

α

also differed among co-occurring vegetation types. Allowing the PAI to LAI regression slope to vary based on the dominant genus reduced PAI conversion error by ∼2 % (p < 0.001). Quantifying

α

variability within canopies and between vegetation types using the method outlined here can reduce on-ground LAI measurement uncertainty.

{"title":"Separating leaf area index from plant area index using semi-supervised classification of digital hemispheric canopy photographs: A case study of dryland vegetation","authors":"Jake Eckersley , Caitlin E. Moore , Sally E. Thompson , Michael Renton , Pauline F. Grierson","doi":"10.1016/j.agrformet.2025.110395","DOIUrl":"10.1016/j.agrformet.2025.110395","url":null,"abstract":"<div><div>Leaf area index (<em>LAI</em>) describes the main plant surface area for gas exchange. Accurate <em>LAI</em> measurements are integral to effective hydrological, ecological, and climate modelling. <em>LAI</em> is commonly modelled using canopy gap fraction measurements from optical sensors. In woody vegetation, however, the wood to total plant area ratio (<span><math><mi>α</mi></math></span>) must also be estimated to convert plant area index (<em>PAI</em>) to <em>LAI</em>. Historically, estimating <span><math><mi>α</mi></math></span> required destructive harvests and is a potential source of <em>LAI</em> error. In this study, we present a theoretical framework for estimating <em>LAI</em> from digital hemispheric canopy photography by correcting for <span><math><mi>α</mi></math></span> within each image using semi-supervised pixel classification. We apply this framework to 201 images collected in semi-arid Australian vegetation (overstorey <em>LAI</em> range 0–5) to explore potential sources of error from: image classification, <em>LAI</em> model implementation, and differences in <span><math><mi>α</mi></math></span> among vegetation types. Leaf, wood, and canopy gap (sky) pixels were classified using a random forest (RF) algorithm with 87.7 ± 0.01 % accuracy (mean ± standard error) under overcast skies but 81.3 ± 0.01 % under clear sky conditions where leaf and wood pixel classification was inconsistent. <em>LAI</em> estimates using the proposed approach had a strong linear relationship to <em>PAI</em> (<em>r<sup>2</sup></em> ≥ 0.97). However, the proportional contribution of woody material to canopy gap fraction was zenith angle dependent. Allowing <span><math><mi>α</mi></math></span> to vary by zenith and azimuth angle when calculating <em>LAI</em> resulted in estimates 10–17 % higher than widely used <em>PAI</em> conversion methods. The zenith angle distribution of <span><math><mi>α</mi></math></span> also differed among co-occurring vegetation types. Allowing the <em>PAI</em> to <em>LAI</em> regression slope to vary based on the dominant genus reduced <em>PAI</em> conversion error by ∼2 % (<em>p</em> < 0.001). Quantifying <span><math><mi>α</mi></math></span> variability within canopies and between vegetation types using the method outlined here can reduce on-ground <em>LAI</em> measurement uncertainty.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"363 ","pages":"Article 110395"},"PeriodicalIF":5.6,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143026521","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}

引用次数: 0

Dominant grasses buffer the fluctuation of plant productivity to long-term grazing pressure in a desert steppe grassland

IF 5.6 1区农林科学 Q1 AGRONOMY

Agricultural and Forest Meteorology

Pub Date : 2025-01-24 DOI: 10.1016/j.agrformet.2025.110420

Feng Zhang, Shaoyu Li, Jiahua Zheng, Bin Zhang, Jing Wang, Jirong Qiao, Jiaqing Xing, Zhongwu Wang, Zhiguo Li, Guodong Han, Mengli Zhao

Grazing by livestock can influence the diversity and productivity of plants in an ecosystem, as well as the relationship between productivity and diversity. Furthermore, these effects or their relationship can be strongly influenced by variation in the intensity of grazing as well as external environmental conditions, such as rainfall amount. We used observations over an 18-year period in a desert steppe grassland in Inner Mongolia to evaluate how different intensities of grazing influenced productivity, diversity and the underlying mechanism of their relationship through time. Increasing intensity of grazing led to decreased species richness, primarily via the loss of subordinate and rare species, and a decrease in aboveground net primary productivity [ANPP: g m^-2], primarily due to a reduction in dominant species (especially the forb species, A. frigida). We found a positive association between diversity and productivity in most experimental years (14 out of 18 years), with the slope being strongest in wetter years. This suggests that their positive relationship may be affected by precipitation. We used a random forest model to show that variation in ANPP was mainly driven by variation in dominant species, not species richness. Dominant species may be the key driver in regulating plant primary productivity in these species-poor, water-limited grassland ecosystems, and that less intense grazing may be an appropriate management regime to balance ecosystem functions and herder's income.

{"title":"Dominant grasses buffer the fluctuation of plant productivity to long-term grazing pressure in a desert steppe grassland","authors":"Feng Zhang, Shaoyu Li, Jiahua Zheng, Bin Zhang, Jing Wang, Jirong Qiao, Jiaqing Xing, Zhongwu Wang, Zhiguo Li, Guodong Han, Mengli Zhao","doi":"10.1016/j.agrformet.2025.110420","DOIUrl":"10.1016/j.agrformet.2025.110420","url":null,"abstract":"<div><div>Grazing by livestock can influence the diversity and productivity of plants in an ecosystem, as well as the relationship between productivity and diversity. Furthermore, these effects or their relationship can be strongly influenced by variation in the intensity of grazing as well as external environmental conditions, such as rainfall amount. We used observations over an 18-year period in a desert steppe grassland in Inner Mongolia to evaluate how different intensities of grazing influenced productivity, diversity and the underlying mechanism of their relationship through time. Increasing intensity of grazing led to decreased species richness, primarily via the loss of subordinate and rare species, and a decrease in aboveground net primary productivity [ANPP: g m<sup>-2</sup>], primarily due to a reduction in dominant species (especially the forb species, <em>A. frigida</em>). We found a positive association between diversity and productivity in most experimental years (14 out of 18 years), with the slope being strongest in wetter years. This suggests that their positive relationship may be affected by precipitation. We used a random forest model to show that variation in ANPP was mainly driven by variation in dominant species, not species richness. Dominant species may be the key driver in regulating plant primary productivity in these species-poor, water-limited grassland ecosystems, and that less intense grazing may be an appropriate management regime to balance ecosystem functions and herder's income.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"363 ","pages":"Article 110420"},"PeriodicalIF":5.6,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143031201","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}

引用次数: 0