Search Results (138)

The temperate evergreen needleleaf forest (ENF), primarily composed of Mongolian Scots pine (Pinus sylvestris var. mongolica), plays a pivotal role in the “The Great Green Wall” Shelterbelt Project in northern China as a major species for windbreak and sand fixation. Solar-induced chlorophyll fluorescence (SIF) has emerged as a revolutionary remote sensing signal for quantifying photosynthetic activity and gross primary production (GPP) at the ecosystem scale. Meanwhile, eddy covariance (EC) technology has been widely employed to obtain in situ GPP estimates. Although a linear relationship between SIF and GPP has been reported in various ecosystems, it is mainly derived from satellite SIF products and flux-tower GPP observations, which are often difficult to align due to mismatches in spatial and temporal resolution. In this study, we analyzed synchronous high-frequency SIF and EC-derived GPP measurements from a Mongolian Scots pine plantation during the seasonal transition (August–December). The results revealed the following. (1) The ENF acted as a net carbon sink during the observation period, with a total carbon uptake of 100.875 gC·m⁻². The diurnal dynamics of net ecosystem exchange (NEE) exhibited a “U”-shaped pattern, with peak carbon uptake occurring around midday. As the growing season progressed toward dormancy, the timing of CO₂ uptake and release gradually shifted. (2) Both GPP and SIF peaked in September and declined thereafter. A strong linear relationship between SIF and GPP (R² = 0.678) was observed, consistent across both diurnal and sub-daily scales. SIF demonstrated higher sensitivity to light and environmental changes, particularly during the autumn–winter transition. Cloudy and rainy conditions significantly affect the relationship between SIF and GPP. These findings highlight the potential of canopy SIF observations to capture seasonal photosynthesis dynamics accurately and provide a methodological foundation for regional GPP estimation using remote sensing. This work also contributes scientific insights toward achieving China’s carbon neutrality goals. Full article

Integrating green spaces into urban designs and planning for ecosystem services has become vital; however, in creating these spaces, the growth phase is often overlooked. This study provides insight into the changing energy and carbon dioxide (CO₂) fluxes in a developing forest, “The Forestias” project in Thailand. The eddy covariance technique was applied to determine real-time surface energies and CO₂ fluxes from December 2021 to September 2023. The results suggest that under fast growing conditions of the green areas, the diurnal latent energy flux corresponded with the area gained. This effect was supported by increasing evapotranspiration through the byproduct of canopy gas exchange. Consequently, the influence of green areas on lowering the average ambient temperature compared with the urban non-green surroundings was observed. In terms of CO₂ flux dynamics, the increasing efficacy of photosynthesis was parallel with the growing forest canopy. Changes in flux dynamics due to urban green areas show their potential as a mitigation tool for moderating ambient air temperatures. Moreover, they can serve as a carbon sink within tropical cities and provide a pivotal contribution in reaching carbon neutrality. Full article

Purple soil, predominantly found in the Sichuan Basin of China with a favorable climate, is renowned for its fertility, making it an ideal soil for citrus cultivation. To investigate the effect of citrus plantation on the acidification characteristics of purple soil, we selected one field where citrus trees coexist with varying ages of 3, 10, and 50 years. The soil is a neutral purple soil developed from Jurassic Shaximiao Formation mudstone. A total of 138 soil samples were collected at different depths (0–20, 20–40, and 40–60 cm) beneath the canopies of these citrus trees for physicochemical property analysis. Our results indicate that citrus cultivation caused significant spatial variability in the purple soil acidity within the same field. The pH values of these soils varied from 3.97 to 7.90. The degree of soil acidification under the citrus canopies adheres to the following order: 10-year-old > 50-year-old > 3-year-old citrus trees. Soil pH values were negatively correlated with the contents of N, P, and K available in the soil, particularly exhibiting a significantly negative correlation with these soil fertility indicators under the canopy of the 10-year-old citrus at p < 0.01, suggesting that the intensive fertilizer application typical in citrus plantations accelerated soil acidification. Additionally, soil acidification was associated with an increase in the exchangeable Al³⁺ (from 0 to 7.03 cmol kg⁻¹) and a decrease in the exchangeable Ca²⁺ (from 25.07 to 6.48 cmol kg⁻¹), exchangeable Mg²⁺ (from1.53 to 0.62 cmol kg⁻¹), base saturation (from 100% to 53.4%), and effective cation exchange capacity (from 24.3 to 13.1 cmol kg⁻¹).The acidification of the purple soil enhanced the extractability of metal elements, increasing the bioavailability of essential plant nutrients, such as Fe, Mn, Cu, Zn, and Ni, as well as enhancing the mobility of harmful heavy metals like Pb and Cd. In conclusion, unlike the widespread acidification observed in Oxisols or Ultisols at the field scale, citrus cultivation caused varying degrees of acidification within purple soil at this scale. This variability in soil acidification at the field scale of purple soil can lead to a series of soil degradation problems and should be given due attention in the management of citrus and similar high-economic-value fruit trees. Full article

Soil moisture is a core climate variable in land surface processes and has a strong influence on the energy balance and water exchange between the land surface–vegetation–atmosphere columns. However, the low spatial resolution of soil moisture remote sensing products cannot satisfy the requirements of research and applications based on hydro-meteorological and eco-hydrological simulations and the management of water resources at the watershed scale. A feasible solution is to downscale soil moisture products derived from microwave remote sensing, which often requires the support of auxiliary variables. Meanwhile, during the validation process of remote sensing products, the spatial scales between in situ observations and remote sensing pixel retrievals are inconsistent; thus, in situ observations should be translated to ground truths at a pixel scale via reasonable upscaling methods. Many auxiliary variables can serve as proxies in the scaling of soil moisture, although few studies have analyzed their feasibility and application conditions. In this paper, a SiB2 (Simple Biosphere Model-II) simulation for the Daman superstation from 1 May to 30 September 2013, was employed to calculate seven auxiliary variables related to soil moisture: ATIs and ATIc (Apparent Thermal Inertias based on surface soil temperature and canopy temperature), E (Evaporation), E/ET_a (Ratio of Evaporation and Actual Evapotranspiration), E/ET_p (Ratio of Evaporation and Potential Evapotranspiration), EF (Evaporative Fraction) and AEF (Actual Evaporative Fraction). The applicability of these variables was then evaluated via a correlation analysis between the variables and soil moisture. The results indicated that E is highly sensitive to soil moisture at Phase I (R² ≥ 0.67), whereas ATIs is the greatest indicator of soil moisture at Phase II (R² ≥ 0.51). Considering both the correlation and computability of these auxiliary variables, the EF (R² ≥ 0.56) and AEF (R² ≥ 0.54) are recommended as proxies for Phase I, while ATIs (R² ≥ 0.51) is also recommended for Phase II. Full article

The comprehension of seasonal patterns of evapotranspiration (ET), as well as the interactive response to environmental factors, holds paramount importance for illuminating the intricate interaction within the carbon–water cycle of desert riparian forest ecosystems. Nonetheless, the driving mechanism behind ET changes is complex, and different components show significant differences in response to the same factor. Moreover, water resources are scarce in the region, and sustainable water resources management in arid regions usually aims to maximize transpiration (T) and minimize evaporation (E); therefore, reasonable calculation of ET components is urgent to effectively assess water resources consumption and improve water use efficiency. This discussion assessed the suitability and reliability of different methods for partitioning ET within the desert oasis in Northwestern China, calculated water use efficiency (WUE), and explored the differences in the response patterns of ET, transpiration (T), and WUE to environmental elements of constructive Populus euphratica forests in this region during the growing season. Continuous measurements of meteorological, soil, and vegetation factors were collected from 2014 to 2021 to facilitate this investigation. This study demonstrated that the underlying water use efficiency (uWUE) method effectively partitions ET into vegetation T and soil evaporation (E). Seasonal variations in ET and T were predominantly driven by temperature (Ta), radiation (Rn), soil moisture, and leaf area index (LAI). In addition, the exchange of water and carbon across different scales was governed by distinct regulatory mechanisms, where canopy-level WUE (WUEc) primarily depended on climatic conditions, while ecosystem-level WUE (WUEe) was more strongly influenced by vegetation structural characteristics. This study provided valuable insights into the ET characteristics, influencing factors, and water–carbon consumption mechanisms of desert vegetation in arid regions, and the conclusions of the discussion may provide theoretical insights for policymakers and ecosystem managers interested in preserving the ecological balance of arid regions. Full article

The exchange of water, sediment, and nutrients in wetlands occurs through a complex network of channels and overbank flow. Although optical sensors can map channels at high resolution, they fail to identify narrow intermittent channels colonized by vegetation. Here we demonstrate an innovative application of rapid-repeat interferometric synthetic aperture radar (InSAR) to study hydrologic connectivity and tidal influences in Louisiana’s coastal wetlands, which can provide valuable insights into water flow dynamics, particularly in vegetation-covered and narrow channels where traditional optical methods struggle. Data used were from the airborne UAVSAR L-band sensor acquired for the Delta-X mission. We applied interferometric techniques to rapid-repeat (~30 min) SAR imagery of the southern Atchafalaya basin acquired during two flights encompassing rising-to-high tides and ebbing-to-low tides. InSAR coherence is used to identify and differentiate permanent open water channels from intermittent channels in which flow occurs underneath the vegetation canopy. The channel networks at rising and ebbing tides show significant differences in the extent of flow, with vegetation-filled small channels more clearly identified at rising-to-high tide. The InSAR phase change is used to identify locations on channel banks where overbank flow occurs, which is a critical component for modeling wetland hydrodynamics. This is the first study to use rapid-repeat InSAR to monitor tidal impacts on water flow dynamics in wetlands. The results show that the InSAR method outperforms traditional optical remote sensing methods in monitoring water flow in vegetation-covered wetlands, providing high-resolution data to support hydrodynamic models and critical support for wetland protection and management. Full article

The global shortage of high-quality forage has significantly constrained the development of animal husbandry. Leveraging the complementary effects of forage rapeseed and hairy vetch intercropping can enhance forage yield and quality; however, the underlying mechanisms of overyielding in forage rapeseed–hairy vetch intercropping systems remain unclear. Over two years of field experiments, three cropping systems—rapeseed sole cropping, hairy vetch sole cropping, and rapeseed–hairy vetch intercropping—were investigated to assess the effects of intercropping on root and stem morphology, canopy light distribution, leaf photosynthetic physiology, and nitrogen metabolism. Our results demonstrated that intercropping increased forage biomass and crude protein yield by 14.3–20.0% and 30.7–92.8%, respectively, compared to sole cropping. Intercropping significantly enhanced root biomass, increasing lateral root biomass by 81% compared to rapeseed sole cropping. It also improved stem anatomical traits, including the cortex area (58.8–80.7%), cortex thickness (25.1–38.3%), number of vascular bundles (18.0–37.3%), vascular bundle length (17.8–18.4%), vascular bundle perimeter (6.7–18.7%), vascular bundle area (34.6–63.9%), and stem breaking strength (25.7–76.6%). Additionally, intercropping optimized vertical canopy light interception, reduced the activity of antioxidant enzymes (CAT, POD, SOD) and reactive oxygen species (ROS) accumulation, and enhanced the activities of glutamine synthetase and nitrate reductase, stomatal traits, and photosynthetic rates in the leaves of both crops. Structural equation modeling revealed that, in the intercropping system, improved population lodging resistance directly promoted nitrogen metabolism and leaf photosynthetic rates, ultimately increasing population biomass. In summary, rapeseed–hairy vetch intercropping improved canopy light distribution, strengthened rapeseed stem anatomy and root penetration, and enhanced population lodging resistance, leaf photosynthetic physiology, and nitrogen metabolism, thereby boosting forage biomass and quality. The supportive role of rapeseed in the intercropping system elucidates the overyielding mechanisms of rapeseed–hairy vetch intercropping, offering a theoretical framework for optimizing forage production systems worldwide. Full article

Water use efficiency (WUE) plays a pivotal role in connecting the carbon and water cycles and represents the amount of water used by plants or ecosystems to achieve carbon sequestration. The response of WUE to climate warming and its underlying mechanisms remain unclear. Here, we examined the effects of varying levels of warming on carbon fluxes, water fluxes, and WUE in an alpine peatland, with Blysmus sinocompressus and Carex secbrirostris as dominant species. Open-top chambers were utilized to simulate two levels of warming: low-level warming (TL) and high-level warming (TH). The carbon dioxide and water fluxes were monitored over a growing season (June to September). Gradient warming significantly decreased both gross primary productivity (GPP) and net ecosystem carbon exchange (NEE); GPP was 10.05% and 13.31% lower and NEE was 21.00% and 30.00% lower in the TL and TH treatments, respectively, than in the control. Warming had no significant effect on soil evaporation, and plant transpiration and evapotranspiration were 36.98% and 23.71% higher in the TL treatment than in the control, respectively; this led to decreases of 31.38% and 28.17% in canopy water use efficiency (WUEc) and ecosystem water use efficiency (WUEe), respectively. Plant transpiration was the main factor affecting both WUEe and WUEc in response to warming. The findings underscore the essential function of water fluxes in regulating WUE and enhance our understanding of carbon–water coupling mechanisms under climate change. Full article

The interaction between forests and precipitation plays a crucial role in the material cycling of forest ecosystems. Atmospheric deposition and rainfall leaching promote the transfer of heavy metals to the forest floor, while canopy exchange may potentially slow this process. Therefore, studying heavy metal fluxes and their influencing factors, along with canopy rainfall partitioning, is essential for understanding forest material cycling. We conducted a year-long experiment to examine the dynamics of chromium (Cr), cadmium (Cd), and lead (Pb) concentrations and fluxes in four types of forests (Cunninghamia lanceolata plantations, Castanopsis carlesii plantations, Cas. carlesii natural forests, and Cas. carlesii secondary forests) located in the subtropical regions of southeast China. Results showed that (1) the annual mean concentrations of Cr, Cd, and Pb were 167.6, 13.8, and 6180.5 μg L⁻¹ in the throughfall and 204.7, 28.4, and 2251.1 μg L⁻¹ in the stemflow, respectively, and the annual fluxes of Cr, Cd, and Pb through throughfall were 29.3, 2.4, and 847.7 g ha⁻¹, respectively, and were 1.7, 0.2, and 12.7 g ha⁻¹ through stemflow, respectively; (2) the concentrations of these heavy metals associated with throughfall did not vary between forest types, but their fluxes were highest in Cas. carlesii natural forests; (3) Cr concentration and flux were higher during the rainy than dry seasons, while Cd and Pb concentrations and fluxes showed an opposite trend. Overall, our results indicate that the fluxes of heavy metals along with rainfall partitioning were highest in natural forests and are primarily controlled by meteorological factors, indicating that the conversion of natural forests to other forest types will substantially change the fluxes of heavy metals along with hydrological processes. These results will contribute to a better understanding of the natural fluxes of heavy metals in forest ecosystems and are valuable for sustainable forest management, particularly in the context of forest type transformation. Full article

Gross primary productivity (GPP), the primary driver of carbon accumulation, governs the sequestration of atmospheric CO₂ into biomass. However, GPP cannot be measured directly, as photosynthesis and respiration are simultaneous. At canopy level in plot-scale studies, GPP can be estimated through the closed chamber-based measurements of net ecosystem exchange (NEE) and ecosystem respiration (Reco). This technique is cost-effective and widely used in small-scale studies with short vegetation, but measurements are periodic-based and require temporal interpolations. The rectangular hyperbolic model (RH) was the basis of this study, developing two temperature-dependent factors following a linear and exponential shift in GPP when the temperature oscillates from the optimum for vegetation performance. Additionally, a water table depth (WTD)-dependent model and an exponential model were tested. In the peak season, modified RH models showed the best performance, while for the rest of the year, the best model varied for each subplot. The statistical results demonstrate the limitations of assuming the light-use efficiency as a fixed shape mechanism (using only one model). Therefore, a multi-model approach with the best performance model selected for each period is proposed to improve GPP estimations for peatlands. Full article

Accurately predicting grapevine yield and quality is critical for optimising vineyard management and ensuring economic viability. Numerous studies have reported the complexity in modelling grapevine yield and quality due to variability in the canopy structure, challenges in incorporating soil and microclimatic factors, and management practices throughout the growing season. The use of multimodal data and machine learning (ML) algorithms could overcome these challenges. Our study aimed to assess the potential of multimodal data (hyperspectral vegetation indices (VIs), thermal indices, and canopy state variables) and ML algorithms to predict grapevine yield components and berry composition parameters. The study was conducted during the 2019/20 and 2020/21 grapevine growing seasons in two South Australian vineyards. Hyperspectral and thermal data of the canopy were collected at several growth stages. Simultaneously, grapevine canopy state variables, including the fractional intercepted photosynthetically active radiation (fiPAR), stem water potential (Ψ_stem), leaf chlorophyll content (LCC), and leaf gas exchange, were collected. Yield components were recorded at harvest. Berry composition parameters, such as total soluble solids (TSSs), titratable acidity (TA), pH, and the maturation index (IMAD), were measured at harvest. A total of 24 hyperspectral VIs and 3 thermal indices were derived from the proximal hyperspectral and thermal data. These data, together with the canopy state variable data, were then used as inputs for the modelling. Both linear and non-linear regression models, such as ridge (RR), Bayesian ridge (BRR), random forest (RF), gradient boosting (GB), K-Nearest Neighbour (KNN), and decision trees (DTs), were employed to model grape yield components and berry composition parameters. The results indicated that the GB model consistently outperformed the other models. The GB model had the best performance for the total number of clusters per vine (R² = 0.77; RMSE = 0.56), average cluster weight (R² = 0.93; RMSE = 0.00), average berry weight (R² = 0.95; RMSE = 0.00), cluster weight (R² = 0.95; RMSE = 0.13), and average berries per bunch (R² = 0.93; RMSE = 0.83). For the yield, the RF model performed the best (R² = 0.97; RMSE = 0.55). The GB model performed the best for the TSSs (R² = 0.83; RMSE = 0.34), pH (R² = 0.93; RMSE = 0.02), and IMAD (R² = 0.88; RMSE = 0.19). However, the RF model performed best for the TA (R² = 0.83; RMSE = 0.33). Our results also revealed the top 10 predictor variables for grapevine yield components and quality parameters, namely, the canopy temperature depression, LCC, fiPAR, normalised difference infrared index, Ψ_stem, stomatal conductance (g_s), net photosynthesis (P_n), modified triangular vegetation index, modified red-edge simple ratio, and ANT_gitelson index. These predictors significantly influence the grapevine growth, berry quality, and yield. The identification of these predictors of the grapevine yield and fruit composition can assist growers in improving vineyard management decisions and ultimately increase profitability. Full article

Canopy architecture is fundamental to productivity in grapevines. This research focused on evaluating the impact of opening canopies on the capture of photosynthetically active radiation, photosynthetic activity, and berries’ physicochemical properties in Cabernet Sauvignon grapevines. A completely randomised design was used to compare open and closed canopies, with ten replicates per treatment (20 vines in total), during the vegetative growth period and after harvest. The key measurements included photon flux density (PFD), daily light integral (DLI), photosynthetic rate (PR), stomatal conductance (SC), intercellular CO₂ concentration (IC), leaf area (LA), transpiration, ambient CO₂ concentration, and temperature. Additionally, we assessed berry quality variables, such as total soluble solids (TSS), glucose/fructose ratio, total titratable acidity (TTA), pH, TSS/TTA, and total phenols (TP). During vegetative growth, PFD, DLI, PR, IC, and LA increased significantly (p ≤ 0.05), whereas after harvest, only PR and IC showed variation Closed canopies increased water use efficiency (CO₂/H₂O) by 62.5%, while the temperature was higher in open canopies. Opening canopy increased contacts, gaps and visible sky and reduced leaf area index. Berries from open canopies showed higher TSS, glucose-fructose, pH, TSS/TTA and TP contents. Opening canopy is essential for improving light interception, photosynthetic efficiency, and fruit quality in Cabernet Sauvignon grapevine cultivated in northern Mexico. Full article

Canopy–atmospheric water vapor output resistance (g_s) is a key parameter in researching forest canopy transpiration. It is important for quantifying the water vapor exchange in forest ecosystems. However, the method by which g_s is determined has been controversial, and it cannot precisely represent water vapor exchange. This study aimed to develop a model to quantify the water vapor resistance between the canopy and the atmosphere in Platycladus orientalis (P. orientalis) forests using sap flow and meteorological factors monitoring data. The resistance model was constructed using the relationship between canopy stomatal resistance (g_c) and aerodynamic resistance (g_a) from the mechanism perspective, and sap flow data and measurements of meteorological variables were used to model the stomatal and aerodynamic resistance of the canopy. The results indicate that the canopy-atmospheric water vapor output resistance was closer to the measured values and showed a unimodal curve in the diurnal scale, and this change could provide more accurate measurements of tree transpiration. At the same time, the canopy-atmospheric water vapor output resistance was strongly influenced by wind speed and PAR when 0.2 m/s < u < 0.4 m/s (R² = 0.871, p < 0.01). The stomatal and aerodynamic resistance were also both strongly influenced by wind speed, with the proposed model achieving a high degree of fit (R² = 0.949, p < 0.01), providing a new tool for analyzing forest transpiration. This research provides a new perspective and technical reference for clarifying the mechanism of forest canopy water output. Full article

‘Xinomavro’ (V. vinifera L.) is an important native red wine grape variety in Northern Greece, particularly in PDO (protected designation of origin) regions. Despite its significance, there is limited research on the effects of pruning type and severity on ‘Xinomavro’ vine physiology, yield, and berry quality across diverse environmental conditions. This study aimed to address this knowledge gap and provide growers with crucial information for optimizing vineyard management practices. The study was conducted over two consecutive years (2016 and 2017) in a vineyard in Thessaloniki, Northern Greece. Four treatments (B12: 12 buds on 6 spurs, B24: 24 buds on 12 spurs, M12: 12 buds on 2 canes, and M24: 24 buds on 4 canes) combining two bud load levels (12 or 24 count nodes) and two pruning types (short spurs or long canes) were applied to ‘Xinomavro’ vines in a complete block randomized design. The vine water status, gas exchange, canopy characteristics, yield components, and berry composition were measured. Bud load and pruning type significantly influenced vine canopy development, microclimate, and yield components. Short pruning with high bud load (B24) resulted in denser canopies and higher yields, whereas cane pruning (M12 and M24) led to more open canopies and improved berry quality indicators. Treatment effects on berry composition were inconsistent across years but showed a tendency for higher anthocyanin and total phenol content in cane-pruned vines. This study demonstrates that pruning type (short or long fruiting units) may have a greater impact on vine growth, yield, and berry composition than bud load alone in ‘Xinomavro’ vines. Cane pruning appears to be a more effective strategy for achieving vine balance and potentially improving grape quality under given experimental conditions. Full article

In the maize-soybean intercropping system, varying degrees of maize leaf shading are an important factor that reduces the uniformity of light penetration within the soybean canopy, altering the soybean canopy structure. Quantitative analysis of the relationship between the soybean canopy structure and canopy photosynthesis helps with breeding shade-tolerant soybean varieties for intercropping systems. This study examined the canopy structure and photosynthesis of intercropped soybeans during the shading stress period (28 days before the corn harvest), the high light adaptation period (15 days after the corn harvest), and the recovery period (35 and 55 days after the corn harvest), using a field high-throughput phenotyping platform and a plant gas exchange testing system (CAPTS). Additionally, indoor shading experiments were conducted for validation. The results indicate that shade-tolerant soybean varieties (STV varieties) have significantly higher yields than shade-sensitive soybean varieties (SSV varieties). This is attributable to the STV varieties having a larger top area, lateral width, and lateral external rectangular area. Compared to the SSV varieties, the four top areas of the STV varieties are, on average, 52.09%, 72.05%, and 61.37% higher during the shading stress, high light adaptation, and recovery periods, respectively. Furthermore, the average maximum growth rates (GRs) for the side mean width (SMW) and side rectangle area (SRA) of the STV varieties are 62.92% and 22.13% in the field, and 83.36% and 55.53% in the indoor environment, respectively. This results in a lower canopy overlap in STV varieties, leading to a more uniform light distribution within the canopy, which is reflected in higher photosynthetic rates (Pn), apparent quantum efficiency, and whole-leaf photosynthetic potential (WLPP) for the STV varieties, thereby enhancing their adaptability to shading stress. Above-ground dry matter accumulation was higher in STV varieties, with more assimilates stored in the source and sink, promoting assimilate accumulation in the grains. These results provide new insights into how the superior canopy structure and photosynthesis of shade-tolerant soybean varieties contribute to increased yield. Full article