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Proper management and accounting of forest carbon requires good knowledge of how disturbances and climate affect the carbon dynamics of different stand types. We have investigated such relationships by measuring, over a 5-year period (2003–2007), the net ecosystem productivity (NEP), gross ecosystem productivity (GEP) and ecosystem respiration (ER) of 26 forest sites in Canada using the eddy covariance technique. The study included black spruce, jack pine, Douglas-fir, aspen, boreal mixedwood and white pine forest ecosystems ranging in age from 1- to 153-years. The dataset included six chronosequences (one afforested plantation, three harvested and two burned).Following planting, the afforested white pine stands quickly became carbon sinks and offset initial carbon losses after 4 years. Depending on forest type, the other forest stands were carbon sources for 10–18 years following a disturbance, offset initial carbon losses after 19–47 years, and showed net total gains ranging from 38 to 86 Mg C ha−1 at 80 years. Peak NEP ranged from 0.9 to 2.9 Mg C ha−1 year−1 at ages of 35–55 years except for the afforested white pine where it was 6.9 Mg C ha−1 year−1 at 15–20 years. Stepwise regression and Pearson correlation analyses indicated that the GEP and ER of mature stands (>70 years old) were driven mainly by climate, while fluxes of young stands (

stage of the vegetation determines the radiative budget, energy balance partitioning, evapotranspiration and carbon dioxide flux. Here, we synthesize energy balance measurements from across the western boreal zone of North America as a function of stand age following fire. The data are from 22 sites in Alaska, Saskatchewan and Manitoba collected between 1998 and 2004 for a 150-year forest chronosequence. The summertime albedo immediately after a fire is about 0.05, increasing to about 0.12 for a period of about 30 years and then averaging about 0.08 for mature coniferous forests. A mature deciduous (aspen) forest has a higher summer albedo of about 0.16. Wintertime albedo decreases from a high of 0.7 for 5- to 30-year-old forests to about 0.2 for mature forests (deciduous and coniferous). Summer net radiation normalized to incoming solar radiation is lower in successional forests than in more mature forests by about 10%, except for the first 1–3 years after fire. This reduction in net radiative forcing is about 12–24 W m−2 as a daily average in summer (July). The summertime daily Bowen ratio exceeds 2 immediately after the fire, decreasing to about 0.5 for 15-year-old forests, with a wide range of 0.3–2 for mature forests depending on the forest type and soil water status. The magnitude of these changes is relatively large and may affect local, regional and perhaps global climates. Although fire has always determined stand renewal in these forests, increased future area burned could further alter the radiation balance and energy partitioning, causing a cooling feedback to counteract possible warming from carbon dioxide released by boreal fires.

Abstract: Light detection and ranging (lidar) is becoming an increasingly popular technology among scientists for the development of predictive models of forest biophysical variables. However, before this technology can be [...]

Aboveground biomass (AGB) is a vital indicator for studying carbon sinks in forest ecosystems. Semiarid forests harbor substantial carbon storage but received little attention due to the high spatial–temporal heterogeneity that complicates the modeling of AGB in this environment. This study assessed the performance of different data sources (annual monthly time-series radar was Sentinel-1 [S1]; annual monthly time series optical was Sentinel-2 [S2]; and single-temporal airborne light detection and ranging [LiDAR]) and seven prediction approaches to map AGB in the semiarid forests on the border between Gansu and Qinghai Provinces in China. Five experiments were conducted using different data configurations from synthetic aperture radar backscatter, multispectral reflectance, LiDAR point cloud, and their derivatives (polarimetric combination indices, texture information, vegetation indices, biophysical features, and tree height- and canopy-related indices). The results showed that S2 acquired better prediction (coefficient of determination [R2]: 0.62–0.75; root mean square error [RMSE]: 30.08–38.83 Mg/ha) than S1 (R2: 0.24–0.45; RMSE: 47.36–56.51 Mg/ha). However, their integration further improved the results (R2: 0.65–0.78; RMSE: 28.68–35.92 Mg/ha). The addition of single-temporal LiDAR highlighted its structural importance in semiarid forests. The best mapping accuracy was achieved by XGBoost, with the metrics from the S2 and S1 time series and the LiDAR-based canopy height information being combined (R2: 0.87; RMSE: 21.63 Mg/ha; relative RMSE: 14.45%). Images obtained during the dry season were effective for AGB prediction. Tree-based models generally outperformed other models in semiarid forests. Sequential variable importance analysis indicated that the most important S1 metric to estimate AGB was the polarimetric combination indices sum, and the S2 metrics were associated with red-edge spectral regions. Meanwhile, the most important LiDAR metrics were related to height percentiles. Our methodology advocates for an economical, extensive, and precise AGB retrieval tailored for semiarid forests. [ABSTRACT FROM AUTHOR]

The globally increasing frequency of extreme drought events exacerbates the contradiction between the supply of water and the demand for high-quality urban greening. However, the mechanism of the response of urban shrubs to drought stress remains unclear. In this study, three typical urban shrubs (Euonymus japonicus, golden vicary [Ligustrum × vicaryi], and Japanese purple barberry [Berberis thunbergii var. atropurpurea]) that are used for greening in northern China were exposed to three levels of water (full irrigation, natural rain-fed, and extreme drought) in different periods of the growing season (April to May, June to July, and August to September) to investigate the responses of leaf water potential and photosynthetic parameters. The main results were as follows: (1) all the leaf water potentials (Ψ) and photosynthetic parameters (Pn) showed a typical linear relationship along the water gradient in the middle of the growing season. Extreme drought decreased the photosynthetic rates by 1.26~11.03 μmol·m−2·s−1 compared with the irrigated groups. However, the responses were less pronounced in the early and late growing seasons. (2) Different shrubs responded with different intensities and mechanisms. B. thunbergii var. atropurpurea showed clear anisohydric behavior throughout the whole growing season, while L. × vicaryi and E. japonicus showed stronger isohydric behavior during the early and late growing seasons. These findings are important to improve the sustainability of maintenance of ornamental plants from the scope of the efficient utilization of urban water resources. [ABSTRACT FROM AUTHOR]

Through photosynthesis, forests absorb annually large amounts of atmospheric CO2. However, they also release CO2 back through respiration. These two, opposite in sign, large fluxes determine how much of the carbon is stored or released back into the atmosphere. The mean seasonal cycle (MSC) is an interesting metric that associates phenology and carbon (C) partitioning/allocation analysis within forest stands. Here, we applied the 3D-CMCC-FEM model and analyzed its capability to represent the main C-fluxes, by validating the model against observed data, questioning if the sink/source mean seasonality is influenced under two scenarios of climate change, in five contrasting European forest sites. We found the model has, under current climate conditions, robust predictive abilities in estimating NEE. Model results also predict a consistent reduction in the forest's capabilities to act as a C-sink under climate change and stand-aging at all sites. Such a reduction is predicted despite the number of annual days as a C-sink in evergreen forests increasing over the years, indicating a consistent downward trend. Similarly, deciduous forests, despite maintaining a relatively stable number of C-sink days throughout the year and over the century, show a reduction in their overall annual C-sink capacity. Overall, both types of forests at all sites show a consistent reduction in their future mitigating potential. [ABSTRACT FROM AUTHOR]

Among the essential tools to address global environmental information requirements are the Earth-Observing (EO) satellites with free and open data access. This paper reviews those EO satellites from international space programs that already, or will in the next decade or so, provide essential data of importance to the environmental sciences that describe Earth's status. We summarize factors distinguishing those pioneering satellites placed in space over the past half century, and their links to modern ones, and the changing priorities for spaceborne instruments and platforms. We illustrate the broad sweep of instrument technologies useful for observing different aspects of the physio-biological aspects of the Earth's surface, spanning wavelengths from the UV-A at 380 nanometers to microwave and radar out to 1 m. We provide a background on the technical specifications of each mission and its primary instrument(s), the types of data collected, and examples of applications that illustrate these observations. We provide websites for additional mission details of each instrument, the history or context behind their measurements, and additional details about their instrument design, specifications, and measurements. [ABSTRACT FROM AUTHOR]

The Brazilian Pampa biome has natural pastures that have been used for centuries for cattle grazing. This is considered a sustainable system because it combines the conservation of natural vegetation and high-quality meat production, protecting the biome from commercial agriculture's advances. However, whether it is a source or a sink of carbon dioxide (CO2) has yet to be evaluated. Hence, this study aimed to quantify the net ecosystem exchange (NEE) of the CO2 of a natural pasture of the Pampa biome used for livestock production. The experimental area is located in a subtropical region of southern Brazil, where eddy covariance (EC) measurements were conducted from 2015 to 2021 in a rotational cattle grazing system. The seven months of the warm season (September to March) were characterized as CO2 absorbers, while the five months of the cold season (April to August) were CO2 emitters. Throughout the six years and with complete data, the ecosystem was an absorber of atmospheric CO2, with an average value of −207.6 g C m−2 year−1. However, the significant interannual variability in NEE was observed, with cumulative values ranging from −82.0 to −385.3 g C m−2 year−1. The results suggest the coupling of climatic conditions to pasture management can be the factor that modulated the NEE interannual variability. The cattle raising system on the natural pastures of the Pampa absorbs CO2, which is further evidence of its sustainability and need for conservation. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is increasing the occurrence of wildfires, especially in northern high latitudes, leading to a shift in land surface climate. This study aims to determine the predominant climatic effects of fires in boreal forests to assess their impact on vegetation composition, surface albedo, and snow dynamics. The influence of fire-induced changes on Earth's radiative forcing is investigated, while considering variations in burn severity and postfire vegetation structure. Six burn sites are explored in central Alaska's boreal region, alongside six control sites, by utilizing Moderate Resolution Imaging Spectroradiometer (MODIS)-derived albedo, Leaf Area Index (LAI), snowmelt timing data, AmeriFlux radiation, National Land Cover Database (NLCD) land cover, and Monitoring Trends in Burn Severity (MTBS) data. Key findings reveal significant postfire shifts in land cover at each site, mainly from high- to low-stature vegetation. A continuous increase in postfire surface albedo and negative surface shortwave forcing was noted even after 12 years postfire, particularly during the spring and at high-severity burn areas. Results indicate that the cooling effect from increased albedo during the snow season may surpass the warming effects of earlier snowmelt. The overall climate impact of fires depends on burn severity and vegetation composition. [ABSTRACT FROM AUTHOR]

Forest transpiration plays a vital role in the regional water budget and water supply security of the semi-arid Loess Plateau of northwest China. A thorough understanding and accurate predictions of the variation in the transpiration of forests with important tree species, e.g., Armeniaca sibirica (L.) Lam., are critical for land and water management. Owing to the extreme climatic seasonality and interannual variability, detailed information on the seasonal variation in the transpiration of Armeniaca sibirica plantations and its response to climatic and soil moisture/temperature fluctuations is limited. Therefore, in this study, the sap flux density and meteorological and soil moisture/temperature conditions were continuously monitored during the growing season (May to October) in 2019–2020. The results show the four following features: (1) The mean daily transpiration of the Armeniaca sibirica plantation was 0.31 mm·day−1; (2) the daily transpiration varied nonlinearly with increasing potential evapotranspiration (PET). Transpiration first increased rapidly until reaching the PET threshold of 4 mm·day−1 and then slowly increased within the PET range of 4–8.5 mm·day−1, but thereafter, it decreased slightly when PET exceeded 8.5 mm·day−1; (3) the daily forest transpiration varied with increasing relative extractable soil water content (REW) and soil temperature (ST) following a saturated exponential function; i.e., it first increased until reaching a threshold of 0.5 of REW or 14 °C of ST, but thereafter tended to stabilize; (4) models for estimating the daily forest transpiration were established. According to these models, PET had the greatest limiting effect (32.17%) on forest transpiration during the observation period, while REW and ST showed lower limits at 7.03% and 3.87%, respectively. The findings of this study are useful for understanding and managing the hydrological effects of forests in the semi-arid Loess Plateau as a typical dryland with seasonal droughts. [ABSTRACT FROM AUTHOR]

Understanding developments in the trunk sap flow of prevalent tree species within the hilly areas of the Haihe River basin is imperative for ecosystem conservation. Nevertheless, the changes in sap flow of local trees and their response to environmental factors remain elusive. This study focuses on seven dominant tree species in the hilly area of the Haihe River basin and analyzed the relationship between tree sap flow rate and environmental factors at different time scales (hourly and daily). Our findings suggested: (1) Regardless of the time scale, total solar irradiance played a primary role in influencing sap flow rate. Conversely, as the time scale grew, the associations between most soil factors and sap flow rate enhanced, while those with meteorological factors declined. Notably, soil temperature exerted a more profound influence on sap flow rate than soil moisture and conductivity. (2) At the hourly scale, the sap flow rate of each species had a lag effect of 1–2 h with vapour pressure deficit, relative humidity and temperature, and 1 h or no lag effect with total solar irradiance and wind speed. (3) The response model of sap flow rate and environmental factors showed that, except for Pinus tabuliformis Carr., other tree species fit well at various time scales (R2 ≥ 0.59). As the time scale of most tree species increased from hourly scale to daily scale, the fit gradually weakened. Concurrently, considering the time-lag effect, the accuracy of the model has been improved, and the fitting accuracy of Koelreuteria paniculata Laxm. and Pinus tabuliformis Carr. has been significantly improved. [ABSTRACT FROM AUTHOR]

The choice of basil (Ocimum basilicum L.) genotypes determines key attributes such as yield, flavor, and adaptability, contributing significantly to the overall success and sustainability of basil cultivation practices. As the primary aim of this study, seven basil accessions were characterized for both their growth performance and biochemical profile of volatile compounds, enabling the differentiation among distinct chemotypes. As secondary objectives, growth performance and production were evaluated under natural solar radiation conditions (SR100) and with a 30% reduction in solar radiation using a net (SR70). Light use efficiency (LUE) determination revealed the plants' biomass production capability under different solar radiation (SR) conditions. Genotypes A, B, C, and G were characterized by a high levels of linalool, which is typically associated with the "pesto" sauce smell. Lemon basil D exhibited a different chemotype due to the presence of neral and geranial. E and F displayed a different chemotype due to the higher concentration of α-bergamotene. The total fresh harvested biomass was significantly higher in SR70 than SR100 conditions. The second harvest in both SR conditions was the most productive one, while genotype E under SR70 displayed the highest yield. The landraces D and E showed the highest LUE values, indicating their capability in converting the solar radiation into fresh biomass. Plants grown in SR70 conditions registered significantly higher values of plant height, number of branches, and leaf weight. This work aimed to provide valuable insights into the selection of basil genotypes suitable for sustainable agriculture. Conversely, it lays the basis for cultivation aspects pertaining to the crop's adaptability in peri-urban, marginal lands, which are characterized by limited solar radiation. [ABSTRACT FROM AUTHOR]

Understanding how forest ecosystems respond to environmental factors, particularly in the context of global climate change, is essential for devising effective mitigation strategies. This study focuses on quantifying the interaction between forest ecosystems and atmospheric gases. To achieve our objectives, we are using the eddy covariance (EC) flux method to measure air turbulence and gas concentrations above the forest canopy at the Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) in southern Estonia. We apply a flux footprint (FFP) model to describe the spatial extent and position of the surface area contributing to the turbulent flux measurements. The FFP analysis provides valuable insights into the long-term changes in SMEAR Estonia, the FFP and its relationship with forest management and land use changes. Our findings reveal that the FFP area varies from year to year due to changes in wind speed and direction, affecting the contribution of different land cover elements to the overall FFP. The average changes in the FFP area at a height of 30 meters were approximately 4.9%, while those at a height of 70 meters were only 1.6%. Moreover, human activities, such as thinning and clear-cutting, influence the growing stock and increment of forest stands. [ABSTRACT FROM AUTHOR]

Human impact on natural ecosystems has significantly increased in recent decades. As a result, the structure and functioning of ecosystems are seriously altered. This in turn affects regional weather and climate conditions through changes in the radiation, water, and carbon balance of ecosystems. Investigating the process of natural ecosystem restoration after disturbances is an important issue in the context of climate change. During monitoring observations of greenhouse gas (GHG) fluxes in a reforestation area in the Chechen Republic, new experimental data on their seasonal variability were obtained, and their sensitivity to changes in environmental conditions was assessed. Forest restoration and land reclamation are essential components of the low-carbon development and decarbonization strategy of the world economy. Observations of GHG fluxes were conducted in the reclaimed area, which was planted with tree seedlings. One year of eddy covariance flux measurements (May 2022–June 2023) demonstrated that CO2 uptake by the reforestation area in a humid continental climate with hot summers and cold winters is determined by the moisture conditions of the growing season. The cumulative net ecosystem exchange (NEE) for the entire measurement period at the carbon farm was 613.7 gC·m−2. The uptake of CO2 by the reforestation area was observed only due to active seedling growth during periods of sufficient soil moisture (May 2023). During this time, total NEE uptake was 48.7 gC·m−2. Sensible and latent heat fluxes were also dependent on weather conditions, primarily on incoming solar radiation and moisture conditions. For the successful implementation of climate projects aimed at the creation of artificial forest ecosystems with high CO2 uptake capacity, it is essential to develop appropriate hydro-meliorative measures that ensure a sufficient amount of available soil moisture. [ABSTRACT FROM AUTHOR]

As an important aspect of plant water consumption, nocturnal water use (En) behavior provides reliable information on the effect of plantation carbon and water budgets at stand and regional scales. Therefore, quantifying En and its environmental and stomatal controlling mechanisms is urgent to establish adaptation strategies for plantation management in semiarid regions. With the help of the sap flow technique, our study investigated the seasonal variations in canopy transpiration and canopy conductance in a Caragana korshinskii Kom plantation. Environmental variables were measured concurrently during the growing seasons of 2020 and 2021. The results indicated that the average En values were 0.10 mm d−1 and 0.09 mm d−1, which accounted for 14% and 13% of daily water use, respectively, over two years. The proportions of nocturnal transpiration (Tn) to En were approximately 49.76% and 54.44%, while stem refilling (Re) accounted for 50.24% and 45.56% of En in 2020 and 2021, respectively, indicating that C. korshinskii was able to draw on stored stem water to support transpiration. En was predominantly affected by nocturnal canopy conductance (Gc–n), air temperature (Ta–n) and wind speed (u2-n). In contrast, Gc–n and Ta–n explained the highest variation in Tn and nocturnal vapor pressure (VPDn), and u2-n explained the highest variation in Re. Total effects of the five environmental and stomatal variables explained 50%, 36% and 32% of En, Tn and Re variation, respectively. These findings could enable a better understanding of nocturnal water use dynamics and their allocation patterns in C. korshinskii plantations on the Bashang Plateau. Moreover, our results reveal the water use strategies of artificial shrubs and highlight the importance of incorporating nocturnal water use processes into large-scale ecohydrological models in semiarid regions. [ABSTRACT FROM AUTHOR]

The biodiversity, including the diversity of autotrophic organisms of mostly plant species, assembled in vegetation patches and its impact on the course of ecosystem processes is still a key subject of research in natural sciences around the world. Certain aspects of the relationship between biodiversity and CO2 release processes have been studied only in some natural and semi-natural ecosystems (semi-natural ecosystems such as meadow or grasslands). In contrast, very little is known about the biotic parameters related to natural processes and the functioning of novel ecosystems. This study was performed on post-black coal mining heaps. The studied sites were established on carboniferous mineral material. Among the considered biotic parameters, the vegetation plant species composition, soil organic matter, soil enzymatic activity, soil fauna presence, and the plant species biomass were studied. The aim of the research was to analyse the influence of the selected biotic factors on the CO2 release from the mineral material of black coal mining heaps' novel ecosystems. The range of CO2 release at the analysed sites was 0.00158–1.21462 [g CO2/m2/h]. The activity of soil enzymes such as dehydrogenase, acid phosphatase, and basic phosphatase was positively correlated with the amount of CO2 released, however, there was no correlation between urease activity and CO2 emissions from the soil. In our study, a comparison of the soil organic matter developed under the vegetation types studied and CO2 release (rate) showed a dependence on vegetation type. The amount of biomass was not linearly correlated with CO2 release from the soil. The presence of soil fauna displayed a positive effect on CO2 release. [ABSTRACT FROM AUTHOR]

Eucalyptus plantation forests in southern China provide not only the economic value of producing timber, but also the ecological value service of absorbing carbon dioxide and releasing oxygen. Based on the theory of spatial colonial modeling, this paper proposes a new method for 3D reconstruction of tree terrestrial LiDAR point clouds for determining the aboveground carbon stock of eucalyptus monocotyledons, which consists of the main steps of tree branch and trunk separation, skeleton extraction and optimization, 3D reconstruction, and carbon stock calculation. The main trunk and branches of the tree point clouds are separated using a layer-by-layer judgment and clustering method, which avoids errors in judgment caused by sagging branches. By optimizing and adjusting the skeleton to remove small redundant branches, the near-parallel branches belonging to the same tree branch are fused. The missing parts of the skeleton point clouds were complemented using the cardinal curve interpolation algorithm, and finally a real 3D structural model was generated based on the complemented and smoothed tree skeleton expansion. The bidirectional Hausdoff distance, average Hausdoff distance, and F distance were used as evaluation indexes, which were reduced by 0.7453 m, 0.0028 m, and 0.0011 m, respectively, and the improved spatial colonization algorithm enhanced the accuracy of the reconstructed tree 3D structural model. To verify the accuracy of our method to determine the carbon stock and its related parameters, we cut down 41 eucalyptus trees and destructively sampled the measurement data as reference values. The R2 of the linear fit between the reconstructed single-tree aboveground carbon stock estimates and the reference values was 0.96 with a CV(RMSE) of 16.23%, the R2 of the linear fit between the trunk volume estimates and the reference values was 0.94 with a CV(RMSE) of 19.00%, and the R2 of the linear fit between the branch volume estimates and the reference values was 0.95 with a CV(RMSE) of 38.84%. In this paper, a new method for reconstructing eucalyptus carbon stocks based on TLS point clouds is proposed, which can provide decision support for forest management and administration, forest carbon sink trading, and emission reduction policy formulation. [ABSTRACT FROM AUTHOR]

Forest ecosystems in the mid-latitudes of the Northern Hemisphere are significantly affected by frequent extreme weather events. How different forest ecosystems respond to these changes is a major challenge. This study aims to assess differences in the response of daily net ecosystem exchange (NEE) of CO2 and latent heat flux (LE) between different boreal and temperate ecosystems and the atmosphere to extreme weather events (e.g., anomalous temperature and precipitation). In order to achieve the main objective of our study, we used available reanalysis data and existing information on turbulent atmospheric fluxes and meteorological parameters from the global and regional FLUXNET databases. The analysis of NEE and LE responses to high/low temperature and precipitation revealed a large diversity of flux responses in temperate and boreal forests, mainly related to forest type, geographic location, regional climate conditions, and plant species composition. During the warm and cold seasons, the extremely high temperatures usually lead to increased CO2 release in all forest types, with the largest response in coniferous forests. The decreasing air temperatures that occur during the warm season mostly lead to higher CO2 uptake, indicating more favorable conditions for photosynthesis at relatively low summer temperatures. The extremely low temperatures in the cold season are not accompanied by significant NEE anomalies. The response of LE to temperature variations does not change significantly throughout the year, with higher temperatures leading to LE increases and lower temperatures leading to LE reductions. The immediate response to heavy precipitation is an increase in CO2 release and a decrease in evaporation. The cumulative effect of heavy precipitations is opposite to the immediate effect in the warm season and results in increased CO2 uptake due to intensified photosynthesis in living plants under sufficient soil moisture conditions. [ABSTRACT FROM AUTHOR]

Photosynthetically active radiation (PAR) is the 400–700 nm portion of the solar radiation spectrum that photoautotrophic organisms including plants, algae, and cyanobacteria use for photosynthesis. PAR is a key variable in global ecosystem and Earth system modeling, playing a prominent role in carbon and water cycling. Alongside air temperature, water availability, and atmospheric CO2 concentration, PAR controls photosynthesis and consequently biomass productivity in general. The management of agricultural and horticultural crops, forests, grasslands, and even grasses at sports venues is a non-exhaustive list of applications for which an accurate knowledge of the PAR resource is desirable. Modern agrivoltaic systems also require a good knowledge of PAR in conjunction with the variables needed to monitor the co-located photovoltaic system. In situ quality-controlled PAR sensors provide high-quality information for specific locations. However, due to associated installation and maintenance costs, such high-quality data are relatively scarce and generally extend over a restricted and sometimes non-continuous period. Numerous studies have already demonstrated the potential offered by surface radiation estimates based on satellite information as reliable alternatives to in situ measurements. The accuracy of these estimations is site-dependent and is related, for example, to the local climate, landscape, and viewing angle of the satellite. To assess the accuracy of PAR satellite models, we inter-compared 11 methods for estimating 30 min surface PAR based on satellite-derived estimations at 33 ground-based station locations over several climate regions in Europe, Africa, and South America. Averaged across stations, the results showed average relative biases (relative to the measurement mean) across methods of 1 to 20%, an average relative standard deviation of 25 to 30%, an average relative root mean square error of 25% to 35% and a correlation coefficient always above 0.95 for all methods. Improved performance was seen for all methods at relatively cloud-free sites, and quality degraded towards the edge of the Meteosat Second Generation viewing area. A good compromise between computational time, memory allocation, and performance was achieved for most locations using the Jacovides coefficient applied to the global horizontal irradiance from HelioClim-3 or the CAMS Radiation Service. In conclusion, satellite estimations can provide a reliable alternative estimation of ground-based PAR for most applications. [ABSTRACT FROM AUTHOR]

This study investigates the occurrence and characteristics of low‐level jets (LLJs) up to 200 m above sea level in the North Sea area, specifically in the southernmost part of the basin, at the entrance of the English Channel. Using a short‐range Doppler lidar installed in Dunkerque Port, on the northern coast of France, wind profiles were recorded for 4 years and analyzed statistically. LLJs were detected on more than 11,000 of the 10‐min average wind profiles (5% of time), with similar jet core height and core speed distributions as in other sites in the southern North Sea area, and a similar annual cycle. However, there were differences in the core directions and the daily cycle, with afternoon northeastly jets being the most frequent in Dunkerque, whereas southwesterly nocturnal jets were dominant in the other North Sea sites. This suggests that wind channeling in the Dover Strait is likely a major factor for LLJ formation in Dunkerque region. The study also examined the conditions of LLJ occurrence using European Centre for Medium‐Range Weather Forecast (ECMWF) reanalysis v5 and ultrasonic anemometer data, but the different types of LLJs sharing the same core direction and occurrence conditions made it difficult to quantify specific jet formation mechanisms. This is the first experimental study on the North Sea shore, and at the entrance of the English Channel, providing valuable insights into the LLJ behavior in the region. [ABSTRACT FROM AUTHOR]

Waterlogging and soil salinity issues can be handled using surface or subsurface drainage networks, soil bed elevation, and soil and crop management patterns. A properly operating and maintained drainage system is important for both rural and urban inhabitants to protect lives and property from flooding and high groundwater levels, enhance health conditions, and safeguards water purity, soil salinity, and waterlogging. It also supports and increases crop yields and consequently rural incomes. This study assessed the maintenance condition of the main surface drains (Baloza and ELFarama) located in the Tina Plain (50,000 acres) and a portion of the Southeast El-Kantara regions (25,000 acres) in North Sinai, Egypt, based on the values of the Discharge Capacity Ratio (DCR) and Manning's roughness (n). Ten measurement locations at the drain cross-section were used in the investigation. For the ELFarama Drain, the average values of n and DCR were found to be 0.029 and 86.2%, and for the Baloza Drain, they were 0.032 and 78.6%, respectively. Compared to the design values, the actual Manning's roughness was higher, indicating that the drainage canals' capacities had been reduced and that their upkeep was inadequate. In both drains, sedimentation is present and they need to be maintained, according to the hydrographic surveying results for the actual cross-sections compared to the planned cross-sections. A methodology for the channel maintenance method is presented. For removing vegetation and dredging sediment, a long-boom mechanical hydraulic excavator with a bucket is suggested and to be conducted every two years. To the results of this study, the amount of weed infestation in vegetated channels is the main factor that affects Manning's roughness coefficient value. It is now easier to calculate the proportion of weeds that are submerged in vegetated channels using echo-sound sonar technology. The DCR is an affordable and simple methodology to assess the channel maintenance status for sustainable agriculture. [ABSTRACT FROM AUTHOR]

Soil respiration is an important component of the global carbon cycle and is highly responsive to disturbances in the environment. Human impacts on the terrestrial ecosystem lead to changes in the environmental conditions, and following this, changes in soil respiration. Predicting soil respiration and its changes under future climatic and land-use conditions requires a clear understanding of the processes involved. The observation of CO2 fluxes was conducted at an urban grassland, where plants were removed and respiration from bare soil was measured. Nine soil respiration models were applied to describe the temperature dependence of heterotrophic soil respiration. Modified models were suggested, including a linear relationship of the temperature sensitivity and base respiration coefficients with soil temperature at various depths. We demonstrate that modification improves the simulated soil respiration. The exponential and logistic models with linear dependences on the model parameters from the soil temperatures were the best models describing soil respiration fluxes. Variability of the apparent temperature sensitivity coefficient (Q10) was demonstrated, depending on the model used. The Q10 value can be extremely high and does not reflect the actual relationships between soil respiration and temperature. Our findings have important implications for better understanding and accurately assessing the carbon cycling characteristics of terrestrial ecosystems in response to climate change in a temporal perspective. [ABSTRACT FROM AUTHOR]

Wetlands are important CO2 sinks and methane sources, and their seasonality and phenological cycle play an essential role in understanding the carbon budget. However, given the spatial heterogeneity of wetland landscapes and the coarser spatial resolution of satellites, the phenological retrievals of wetlands are challenging. Here we examined the phenology of wetlands from 30 m harmonized Landsat/Sentinel-2 (LandSent30) and 500 m MODIS satellite observations using the ground phenology network PhenoCam as a benchmark. This study used all 11 available wetland PhenoCam sites (about 30 site years), covering diverse wetland types from different climate zones. We found that the LandSent30-based phenology results were in overall higher consistency with the PhenoCam results compared to MODIS, which could be related to the better explanation capacity of LandSent30 data in the heterogeneous landscapes of wetlands. This also means that the LandSent30 has an advantage over the 500 m MODIS regarding wetland vegetation phenological retrievals. It should be noted that the LandSent30 did not show a greatly improved performance, which could be related to the specificity and complexity of the wetlands landscape. We also illustrated the potential effects of the location and observation direction of PhenoCam cameras, the selection of Region of Interest (ROI), as well as the landscape composition of the site. Overall, this study highlights the complexity of wetland phenology from both ground and remote sensing observations at different scales, which paves the road for understanding the role of wetlands in global climate change and provides a basis for understanding the real phenological changes of wetland surfaces. [ABSTRACT FROM AUTHOR]

Rice is China's main crop and its output accounts for 30% of the world's total annual rice production. Rice growth status is closely related to chlorophyll content (called Soil and Plant Analyzer Development (SPAD) values). The determination of a SPAD value is of great significance to the health status of rice, agricultural irrigation and regulated fertilization. The traditional SPAD value measurement method is not only time-consuming, laborious and expensive but also causes irreparable damage to vegetation. The main aim of the present study is to obtain a SPAD value through the inversion of hyperspectral remote sensing images. In order to achieve this purpose, the hyperspectral image of rice at different growth stages at the canopy scale was first acquired using a hyperspectral imaging instrument equipped with a drone; the spectral characteristics of the rice canopy at different growth stages were analyzed and combined with a ground-level measured SPAD value, the bands with high correlation between the SPAD values and the spectra of the rice canopy at different fertility stages were selected. Subsequently, we combined the spectral characteristics with the continuous projection algorithm to extract the characteristic band and used the PLS method in MATLAB software to analyze and calculate the weight of each type of spectral value and the corresponding canopy SPAD value; we then used the wavelength corresponding to the spectral value with the highest weight as the used band. Secondly, the four methods of univariate regression, partial least squares (PLS) regression, support vector machine (SVM) regression and back propagation (BP) neural network regression are integrated to establish the estimation model of the SPAD value of rice canopy. Finally, the models are used to map the SPAD values of the rice canopy. Research shows that the model with the highest decision coefficient among the four booting stage models is "booting stage-SVR" (R2 = 0.6258), and the model with the highest decision coefficient among the four dairy maturity models is "milk-ripe stage-BP" (R2 = 0.6716), all of which can meet the requirement of accurately retrieving the SPAD value of rice canopy. The above results can provide a technical reference for the accurate, rapid and non-destructive monitoring of chlorophyll content in rice leaves and provide a core band selection basis for large-scale hyperspectral remote sensing monitoring of rice. [ABSTRACT FROM AUTHOR]

Chrysanthemum morifolium Ramat., known as Hangbaiju (HBJ), is a high-value edible, medicinal product where the flowers are infused in hot water and drunk as tea. Its quality and efficacy are closely related to its geographical origin. Consequently, it is vulnerable to fraudulent substitution by other lower-value Chrysanthemum products. In this study, cultivation (variety and different growth stages) and isotopic fractionation between the flower, stem, and leaf were studied. Samples from four different HBJ varieties were characterized using stable isotopes (δ13C, δ15N, δ2H, δ18O, %C, and %N) across three producing regions in Zhejiang province, China. The results showed that there were no significant differences in stable isotopic compositions for different HBJ varieties, but there were significant differences for different plant tissues (flower, stem, leaf, etc.). Furthermore, the stable isotopic composition altered dramatically at different growth stages. The δ15N (r = 0.6809) and δ2H (r = 0.6102) correlations between stems and leaves (SL) and flowers (F) of HBJ were relatively good, the δ13C correlation (r = 0.2636) between SL and F was weak, but δ18O correlation (r = 0.01) had almost no correlation. A supervised multivariate statistical model (partial least squares discriminant analysis, PLS-DA) was used to discriminate three different producing regions with high accuracy (66.7%, 66.7%, and 100%, respectively). Our findings show that stable isotopes combined with multivariate statistical analysis provide an effective method for the geographical identification of HBJ. [ABSTRACT FROM AUTHOR]

To assess the degree to which it has met its commitments under the Paris Agreement, Morocco is called upon to carry out carbon assessments and transparent evaluations. Within the forestry sector, little is known about the role of Morocco's forests in contributing to carbon uptake. With this aim, we applied for the first time in the literature the 3-PG model to Cedrus atlantica ((Endl.) Manetti ex Carrière, 1855), which represents about 131,800 ha of Morocco's forest area (i.e., Azrou forest). Through the Differential Evolution-Markov Chains (DE-MC) we tested and assessed the sensitivity and calibrated the 3-PG model. This process-based model provided significant results regarding the carbon sequestration capacity. The results showed the following: i. Parameters related to stand properties, canopy structure, and processes, as well as biomass partitioning, are the most important or sensitive for the performance of the model; ii. The DE-MC method optimized the values of the 3-PG parameters which was confirmed by the means of the Gelman–Rubin convergence test; iii. According to the predictions of the calibrated 3-PG, the Net Primary Production in the pure Azrou forest varies between 0.35 and 8.82 tC. ha − 1. yr − 1 , it is equal in average to 5.48 tC. ha − 1. yr − 1 , which given the total area corresponds to 7918 tC. ha − 1 . [ABSTRACT FROM AUTHOR]

Stellera chamaejasme (Thymelaeaceae) is amongst the worst invasive species of the alpine grasslands on the Qinghai–Tibet Plateau; timely and effective monitoring is critical for its prevention and control. In this study, by using high spatial resolution Planet imagery, an optimal approach was explored to improve the discrimination of S. chamaejasme from surrounding communities, integrated with TWINSAPN technique, Transformed divergence and image classification algorithms. Results demonstrated that there were obvious spectral conflicts observed among the TWINSPAN ecological communities, owing to the inconsistency of S. chamaejasme coverage within the communities. By determining the threshold of spectral separability, the adjustment of ecological classification produced spectrally separated S. chamaejasme communities and native species communities. The sensitive index characterizing the spectra of S. chamaejasme contributes to its discrimination; moderate or good classification accuracy was obtained by using four machine learning algorithms, of which Random Forest achieved the highest accuracy of S. chamaejasme classification. Our study suggests the distinct phenological feature of S. chamaejasme provides a basis for the detection of the toxic weed, and the establishment of communities using the rule of spectral similarity can assist the accurate discrimination of invasive species. [ABSTRACT FROM AUTHOR]

The MODIS Aqua and Terra Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) time series acquired during nearly two decades (2000 to 2020) covering the area burned by the Camp Fire (California) in 2018 is investigated in this study by using the multifractal detrended fluctuation analysis in relation to the recovery process of vegetation after fire. In 2008, the same area was partially burned by two wildfires, the BTU Lightning Complex Fire and the Humboldt Fire. Our results indicate that all vegetation index time series are featured by six- and twelve-month modulating periodicities, with a larger spectral content at longer periods for two-fire-affected sites. Furthermore, two fires cause an increase of the persistence of the NDVI and EVI time series and an increase of the complexity, suggesting that the recovery process of vegetation dynamics of fire-affected sites is characterized by positive feedback mechanisms, driving the growth-generating phenomena, which become even more effective in those sites affected by two fires. [ABSTRACT FROM AUTHOR]