Agricultural and Forest Meteorology最新文献

{"title":"Improving the simulation of maize growth using WRF-Crop model based on data assimilation and local maize characteristics","authors":"Lun Bao ,&nbsp;Lingxue Yu ,&nbsp;Entao Yu ,&nbsp;Rongping Li ,&nbsp;Zhongquan Cai ,&nbsp;Jiaxin Yu ,&nbsp;Xuan Li","doi":"10.1016/j.agrformet.2025.110478","DOIUrl":"10.1016/j.agrformet.2025.110478","url":null,"abstract":"<div><div>Global climate change presents a significant challenge to the sustainable development goal of eradicating hunger. Accurate assessment or projection of crop yields is crucial for ensuring food security at both global and regional levels in a changing environment. However, traditional crop models may introduce significant uncertainties due to lack of the intensified feedbacks between crop vegetation and climate systems. In this study, we coupled dynamic crop model (Noah-MP-Crop) with the Weather Research and Forecasting (WRF) model (WRF-Crop) based on data assimilation and local maize characteristics to simulate dynamic maize growth and subsequent yield at Jilin Province, China. We utilized in-site phenological observation data to refine the model's cumulative growing degree days (GDDs), and employed leaf mass assimilation to enhance the accuracy of crop phenology cycles. Our findings suggest that refining the model's GDDs thresholds and incorporating data assimilation leads to better alignment with MODIS-observed Leaf area index (LAI), evapotranspiration (ET), and gross primary productivity (GPP), with a reduction in the mean absolute error of 41.2 %, 14.1 %, and 27.5 %, respectively. The in-site eddy covariance flux observation data on soil moisture (layer 1 R = 0.9) and GPP (R = 0.82) also support our results. With the improvement of the maize growth cycles, the adjusted WRF-Crop model exhibited significantly improved accuracy in simulating maize yield, averaging 10,140 kg/ha in Jilin Province. This represents an approximate 9.26 % increase in accuracy compared to the default model configuration. Therefore, the dynamic crop-coupled WRF-Crop model showcases substantial potential for regional crop yield estimation and predictions, featuring dynamic downscaling capabilities through the incorporation of interactions between crops and the atmosphere.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"365 ","pages":"Article 110478"},"PeriodicalIF":5.6,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529526","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":"Does high resolution in situ xylem and atmospheric vapor isotope data help improve modeled estimates of ecohydrological partitioning?","authors":"Christian Birkel ,&nbsp;Dörthe Tetzlaff ,&nbsp;Ann-Marie Ring ,&nbsp;Chris Soulsby","doi":"10.1016/j.agrformet.2025.110467","DOIUrl":"10.1016/j.agrformet.2025.110467","url":null,"abstract":"<div><div>Ecohydrological partitioning of rainfall into different sources of evaporated and transpired water is crucial to quantify water balance impacts from land cover change. However, resolving ecohydrological partitioning into component fluxes can be ambiguous and uncertain, even where detailed, small-scale measurements are available. To constrain ecohydrological fluxes at the scale of an individual tree in an urban setting, we combined hydrometeorological, sap flow, soil water and high-resolution in situ plant xylem and atmospheric vapor stable isotope measurements over the growing season from April to October 2022. These data were integrated with parsimonious tracer-aided conceptual modeling. The data helped isolate temporal patterns of shifting preferential fractionation in xylem and atmospheric vapor from δ¹⁸O to δ²H mainly depending on air temperature and relative humidity. Modeling high-resolution in situ isotope data revealed the dominant local influence of interception, soil evaporation and transpired water sources on atmospheric vapor particularly during dry periods, whereas wet periods were driven by more variable non-local moisture sources. Additionally, modeling tree water storage did not explain the highly variable and more depleted xylem isotope data compared to enriched and fractionated soil water. Despite volumetrically constrained (within transpiration measurement uncertainty bounds) ecohydrological partitioning, the atmospheric vapor isotope data showed that fine-scale variations of interception and soil evaporation vapor sources can have nuanced impacts on the atmospheric vapor mixture. The comparison of a more complex conceptualization of modeled soil storages (three soil storages) with a minimalist two-storage model indicated the notoriously difficult isotopic discrimination of root water uptake depths. Nonetheless, the combination of soil moisture, transpiration and high-resolution in situ isotope measurements with modeling helped enhance our understanding of plot-scale vegetation-mediated urban hydrological processes.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"365 ","pages":"Article 110467"},"PeriodicalIF":5.6,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526958","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":"Can the eco-evolutionary optimality concept predict steady-state vegetation? An evaluation and comparison of four models","authors":"Dameng Zhang,&nbsp;Yuting Yang,&nbsp;Ajiao Chen","doi":"10.1016/j.agrformet.2025.110470","DOIUrl":"10.1016/j.agrformet.2025.110470","url":null,"abstract":"<div><div>The Eco-Evolutionary Optimality (EEO) theory posits that vegetation adopts specific growth strategies, co-evolving with the environment to achieve a steady state. The EEO models, by capturing the mechanistic interactions between vegetation and the environment while maintaining simplicity, hold promise in simulating vegetation at steady states. In this study, four EEO models (the Eagleson model, the Yang–Medlyn model, the VOM, and the P model) were selected for evaluation and comparison of their performance across 44 undisturbed flux sites globally. Overall, all four models effectively reproduced key variables such as fraction of vegetation cover, evapotranspiration, and gross primary production across most sites, with the Yang–Medlyn and P models demonstrating superior performance. Variability in model performance across different plant functional types was observed, with poorer performance generally noted at shrub sites, while forest and savanna sites exhibited better performance. Analysis across precipitation and temperature gradients revealed better model performance under wetter or warmer conditions. Furthermore, variations in model sensitivity to climate factors were evident, with outputs generally exhibiting higher sensitivity to precipitation and atmospheric CO₂ concentration compared to temperature and vapor pressure deficit. Sensitivity tended to be higher in arid regions compared to relatively humid regions. These findings underscore the capability of EEO models to simulate steady-state vegetation with minimal or no parameter calibration, demonstrating satisfactory performance across diverse environmental conditions.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"365 ","pages":"Article 110470"},"PeriodicalIF":5.6,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526959","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":"Inter-comparison of soybean models for the simulation of evapotranspiration in a humid continental climate","authors":"Evandro H. Figueiredo Moura da Silva ,&nbsp;Kritika Kothari ,&nbsp;Elizabeth Pattey ,&nbsp;Rafael Battisti ,&nbsp;Kenneth J. Boote ,&nbsp;Sotirios V. Archontoulis ,&nbsp;Santiago Vianna Cuadra ,&nbsp;Babacar Faye ,&nbsp;Brian Grant ,&nbsp;Gerrit Hoogenboom ,&nbsp;Qi Jing ,&nbsp;Fábio R. Marin ,&nbsp;Claas Nendel ,&nbsp;Budong Qian ,&nbsp;Ward Smith ,&nbsp;Amit Kumar Srivastava ,&nbsp;Kelly R. Thorp ,&nbsp;Nilson A. Vieira Junior ,&nbsp;Montserrat Salmerón","doi":"10.1016/j.agrformet.2025.110463","DOIUrl":"10.1016/j.agrformet.2025.110463","url":null,"abstract":"<div><div>Accurate simulation of evapotranspiration (ET) with crop models is essential for improving agricultural water management and yield forecasting. Few studies have evaluated multiple soybean [<em>Glycine</em> max (L.) Merr.] models for simulating ET under conditions of low evaporative demand that is characteristic for a warm-summer humid continental climate. Six soybean crop models, encompassing 15 different modeling approaches, were evaluated for ET simulation and compared against eddy covariance data collected over five growing seasons in Ottawa, Canada. Models were first calibrated with phenology, in-season growth, and yield data, followed by calibration with measured ET and soil water content (SWC) data during the second step. After initial calibration, simulated daily ET was higher on average than measured ET, particularly during full canopy cover (normalized bias, nBias = 17.1 to 49.2% depending on the model). Following the second calibration, simulated daily ET was closer to measured values, but bias remained (nBias = 5.9 to 52.1% during full canopy). The ensemble median reduced uncertainty in the simulation of daily ET compared to most models, but DNDC remained the top-ranking model (nRMSE = 0.7 mm <em>d</em>⁻¹, nBias = 11.2%). The MONICA model was most accurate simulating cumulative ET (RMSE = 39.9 mm, nBias = 11.3%), whereas the CROPGRO models excelled simulating SWC (RMSE= 0.04 to 0.05 m³ m⁻³, nBias = 0.10 to 0.9% depending on soil depth). This study was instrumental in evaluating the best ET methodologies and parameters in soybean models. However, there was bias across the models compared to measured eddy covariance ET in a humid environment. The results reveal the need to further investigate possible biases in ET estimates by eddy covariance over soybean canopies, and to review the role of night-time dew contributions to ET in process-based models.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"365 ","pages":"Article 110463"},"PeriodicalIF":5.6,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143519901","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":"Integrating LUCC and forest aging to project and attribute subtropical forest NEP in Zhejiang Province under four SSP-RCP scenarios","authors":"Zihao Huang ,&nbsp;Xuejian Li ,&nbsp;Fangjie Mao ,&nbsp;Lei Huang ,&nbsp;Yinyin Zhao ,&nbsp;Meixuan Song ,&nbsp;Jiacong Yu ,&nbsp;Huaqiang Du","doi":"10.1016/j.agrformet.2025.110462","DOIUrl":"10.1016/j.agrformet.2025.110462","url":null,"abstract":"<div><div>Net ecosystem productivity (NEP) serves as a key indicator of the ecosystem carbon balance. However, the combined effects of various drivers, particularly land use/cover change (LUCC) and forest aging, on NEP remain uncertain, leading to uncertainties in regional and global future NEP simulations. This study integrated Future Land Uses Simulation (FLUS), System Dynamic (SD), and optimized Integrated Terrestrial Ecosystem Carbon-budget (InTEC) models to account for future LUCC and its induced changes in forest age structure into future forest NEP simulations. Taking the Zhejiang Province as the study area, we applied four SSP-RCP scenarios (i.e., SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5) to simulate its subtropical forest NEP from 1980 to 2100. Our simulations indicate that the forests existing in 2020 will function as a carbon sink from 2020 to 2060 but will transition to a carbon source from 2060 to 2100, primarily due to the gradual aging of existing forests and the combined influences of climate and CO₂ changes. Nonetheless, after considering LUCC such as afforestation, the overall cumulative NEP will continue to increase after 2060. By 2100, cumulative forest carbon sinks from 2020 will reach 631.74 Tg C under SSP1–2.6, 681.75 Tg C under SSP2–4.5, 586.41 Tg C under SSP3–7.0, and 601.28 Tg C under SSP5–8.5. Among these contributions, aging forests existing in 2020 with climate and CO₂ changes account for 27.04 % to 63.30 % of cumulative NEP. Climate change exerts a negative impact ranging from -47.39 % to -14.39 %, while CO₂ fertilization has a positive contribution of 6.31 % to 73.79 %. Regarding LUCC, afforestation/reforestation contributes significantly, accounting for 43.66 % to 53.65 %, whereas deforestation has a negative impact of -22.77 % to -10.49 %. Additionally, continuous regeneration further supports NEP growth, contributing 12.85 % to 34.77 %. Finally, Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to elucidate the interactions between these factors. The analysis revealed that future LUCC has significant positive impacts on forest NEP whereas forest aging has significant negative impacts. These findings are crucial for understanding the future carbon cycle of subtropical forests and informing adaptation strategies in response to global climate change.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"365 ","pages":"Article 110462"},"PeriodicalIF":5.6,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143507295","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":"The spatiotemporal variations in ecosystem photosynthetic quantum yield and their drivers","authors":"Liyao Yu ,&nbsp;Xiangzhong Luo ,&nbsp;Ruiying Zhao ,&nbsp;Tin W. Satriawan ,&nbsp;Jiaqi Tian","doi":"10.1016/j.agrformet.2025.110466","DOIUrl":"10.1016/j.agrformet.2025.110466","url":null,"abstract":"<div><div>The quantum yield (<em>α</em>) of photosynthesis represents the maximum light use efficiency (LUE) as indicated by the initial slope of photosynthetic light response curves. <em>α</em> is an important variable in LUE-based models which are widely used to simulate gross primary productivity (GPP) from regional to global scales. However, the spatiotemporal variations in <em>α</em> at the ecosystem scale remain elusive despite its importance. Here, we leveraged long-term eddy-covariance observations from 90 sites globally and examined the spatiotemporal variations in <em>α</em> and their drivers, using statistical and machine learning approaches. We found significant spatial variability in <em>α</em> across and within biomes, primarily driven by atmospheric vapor pressure deficit (VPD) and soil moisture variations. Meanwhile, the temporal changes in <em>α</em> are primarily driven by the negative effect of VPD, which weakens the positive effects of elevated CO₂ and leaf area index (LAI). Our results highlight the dominant role of VPD in controlling the spatiotemporal variations of <em>α</em> and the unneglectable impacts of soil moisture, CO₂, and LAI on <em>α</em>. These new results provide insights for improving the representation of <em>α</em> in LUE-based models for GPP simulations.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"365 ","pages":"Article 110466"},"PeriodicalIF":5.6,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487767","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":"A compact spectroscopic analyzer for simultaneous measurement of N2O, CH4, and CO2 fluxes from soils","authors":"Zetong Niu ,&nbsp;Longfei Yu ,&nbsp;Zhimei Liu ,&nbsp;Lifang Wu ,&nbsp;Dingxi Chen ,&nbsp;Xiaoqing Cui ,&nbsp;Tingjung Lin ,&nbsp;Yin Wang","doi":"10.1016/j.agrformet.2025.110460","DOIUrl":"10.1016/j.agrformet.2025.110460","url":null,"abstract":"<div><div>Nitrous oxide (N₂O), methane (CH₄), and carbon dioxide (CO₂) are three major greenhouse gases (GHG), contributing more than 90% of global warming effects. Across land ecosystems, the source and sink patterns of these GHGs exhibit significant spatial and temporal variability. Field measurements of soil-atmosphere exchange fluxes provide valuable evidence for understanding local GHG dynamics and serve as a complement to comprehensive GHG assessments. While a lot of laboratory-based instruments can facilitate the determination of all three GHGs, few commercially available devices balance precision and portability for <em>in situ</em> flux measurements in remote regions. Here, we present a newly developed GHG analyzer (HT8850) based on a dual-laser spectroscopic system, which determines N₂O, CH₄, CO₂ and H₂O concurrently. With a size of 47 cm * 36 cm * 18 cm, a weight of 14.8 kg, and a power consumption below 100 W, this instrument maintains a good balance between portability/budget and precision/stability. With standard gas measurements in the laboratory, we found that the HT8850 has reasonable accuracy and fast response with an inflow rate of 0.5 L min^-1. Based on the Allan deviation analysis, the 1σ-detection limits under static operation are 1.11 ppb, 2.38 ppb, 0.39 ppm and 6.95 ppm for N₂O, CH₄, CO₂ and H₂O measurements with a 10-second averaging time, respectively. In field application with the soil flux chamber, the analyzer demonstrated good potential in quantifying fluxes for the soil-atmosphere exchange of all three GHGs. Therefore, this compact and integrated spectroscopic analyzer offers a versatile solution for scientists interested in field flux measurements, likely contributing to the further development of <em>in situ</em> applications for GHG flux measurements.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"365 ","pages":"Article 110460"},"PeriodicalIF":5.6,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487766","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":"Climate-driven shifts in suitable areas of Alternaria leaf blotch (Alternaria mali Roberts) on apples: Projections and uncertainty analysis in China","authors":"Bin Chen ,&nbsp;Gang Zhao ,&nbsp;Qi Tian ,&nbsp;Linjia Yao ,&nbsp;Genghong Wu ,&nbsp;Jing Wang ,&nbsp;Qiang Yu","doi":"10.1016/j.agrformet.2025.110464","DOIUrl":"10.1016/j.agrformet.2025.110464","url":null,"abstract":"<div><div>Apple production in China faces significant threats from Alternaria leaf blotch (ALB), a disease potentially exacerbated by climate change through shifts in its distribution and severity. However, the impacts of future climate change on ALB distribution remain insufficiently explored. We collected ALB occurrence data from orchard surveys, public databases, and the literature. Using five species distribution models (SDMs), we examined the relationship between environmental variables and ALB occurrence, and assessed its potential distribution under different climate change scenarios. The analysis used five Global Climate Models (GCMs) from the CMIP6 dataset, with a baseline period (1970–2000) and projections for the 2030s, 2050s, 2070s, and 2090s, based on four shared socioeconomic pathways (SSP126, SSP245, SSP370, and SSP585). The SDMs showed high reliability, with average values for the area under the receiver operating characteristic curve exceeding 0.96 and the true skill statistic exceeding 0.86. During the baseline period, ALB-suitable areas were primarily concentrated in the Bohai Bay, Loess Plateau, and Old Course of the Yellow River apple-planting regions. By the 2090s, under the SSP126, these areas were projected to decrease by 8.89 %. In contrast, under the SSP245, SSP370, and SSP585 scenarios, they were expected to increase by 4.89 %, 21.30 %, and 23.22 %, respectively, with a northwestward shift of 137 to 263 kms and an elevation increase of 288 to 680 m. Additionally, our findings indicated that GCMs contribute 42.2 % of the uncertainty in predictions, while SDMs and scenarios contribute 31.5 % and 8.28 %, respectively. This research highlights the importance of using multiple models and scenarios to enhance the accuracy of disease distribution predictions under changing climatic conditions. By identifying potential future hotspots and suitable areas of ALB, the study provides critical insights for safeguarding apple production in China against the impacts of climate change.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"364 ","pages":"Article 110464"},"PeriodicalIF":5.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479762","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":"Overstory and understory leaves warm faster than air in evergreen needleleaf forests","authors":"Keenan Ganz ,&nbsp;Christopher J. Still ,&nbsp;Bharat Rastogi ,&nbsp;L. Monika Moskal","doi":"10.1016/j.agrformet.2025.110456","DOIUrl":"10.1016/j.agrformet.2025.110456","url":null,"abstract":"<div><div>The limited homeothermy hypothesis states that leaves maintain their temperature within an optimal range for photosynthesis by increasing transpiration during warm conditions. Under limited homeothermy, plants may offset thermal stress caused by climate change. If this hypothesis is true, we should observe: 1) leaf temperature increasing slower than air temperature and 2) leaves cooler than air during warm conditions. We tested these predictions with an energy balance model for evergreen needleleaf forest sites in the National Ecological Observatory Network. A key feature of our model was its vertical stratification of the canopy, which allowed us to analyze vertical gradients in canopy temperature. This feature is especially important given that prior work has focused on the tops of forest canopies. Our results do not support limited homeothermy at any canopy position. In all canopy strata, leaf temperature increased faster than air and periods with leaves cooler than air were rare. In such cases, cooling was due to emitted radiation, not transpiration. But, when water was abundant, transpiration could produce mildly homeothermic behavior. We attribute these results to the needle-like shape of leaves in our study sites. This leaf shape increases boundary layer conductance and causes heat gain from surrounding air to overpower heat loss from transpiration when leaves are cooler than air. Our results indicate that needleleaf forests cannot avert thermal stress in a warming world. Thermal limits on photosynthesis and non-linear increases in respiration with temperature may weaken the role of evergreen forests as a global carbon sink.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"364 ","pages":"Article 110456"},"PeriodicalIF":5.6,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465327","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":"No recovery of soil respiration four years after fire and post-fire management in a Nordic boreal forest","authors":"Julia Kelly ,&nbsp;Stefan H. Doerr ,&nbsp;Johan Ekroos ,&nbsp;Theresa S. Ibáñez ,&nbsp;Md. Rafikul Islam ,&nbsp;Cristina Santín ,&nbsp;Margarida Soares ,&nbsp;Natascha Kljun","doi":"10.1016/j.agrformet.2025.110454","DOIUrl":"10.1016/j.agrformet.2025.110454","url":null,"abstract":"<div><div>The long-term carbon storage capacity of the boreal forest is under threat from the increasing frequency and intensity of wildfires. In addition to the direct carbon emissions during a fire, the burnt forest often turns into a net carbon emitter after fire, leading to large additional losses of carbon over several years. Understanding how quickly forests recover after a fire is therefore vital to predicting the effects of fire on the forest carbon balance. We present soil respiration and CH₄ fluxes, soil chemistry, microclimate and vegetation survey data from the first four years after a wildfire in a <em>Pinus sylvestris</em> forest in Sweden. This is an understudied part of the boreal biome where forest management decisions interact with disturbances to affect forest growth. We analysed how fire severity and post-fire salvage-logging affected soil carbon fluxes. The fire did not affect soil CH₄ uptake. However, soil respiration was significantly affected by the presence or absence of living trees after the fire and post-fire forest management. Tree mortality due to the high-severity fire, or the salvage-logging of living trees after low-severity fire, led to immediate and significant decreases in soil respiration. Salvage-logging of dead trees after high-severity fire did not alter soil respiration compared to when the dead trees were left standing. However, it did significantly slow the regrowth of understory vegetation. Our results highlight that the impact of salvage-logging on the soil carbon fluxes depends on fire severity but that logging always slows the natural recovery of vegetation after fire. The soil CO₂ fluxes did not show signs of recovery at any of the burnt sites during the first four years since the fire.</div></div>","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"364 ","pages":"Article 110454"},"PeriodicalIF":5.6,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465329","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}