Methodological advancement in deriving primary productivity and ecosystem respiration fluxes across different biomes.

In this paper, we introduce a methodology that can improve the estimations of Gross Primary Productivity (GPP) and ecosystem Respiration (Reco) processes at a regional scale. This method is based on a satellite data-driven approach which is suitable for regions like India where there exists a serious shortage of ground-based observations of biospheric carbon fluxes (e.g., Eddy Covariance (EC) flux measurements). We relied on the Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance for capturing vegetation dynamics in the Light-Use Efficiency (LUE)-based vegetation model. Further, we utilised recently available satellite-based Solar-Induced Fluorescence (SIF) and other variables such as Soil Moisture (SM) and Soil Temperature (ST) to refine the predictions of GPP and Reco. The methodology involves establishing a relationship between SIF and GPP for different vegetation classes over India. The SIF-GPP relationship established across the biomes was then used to correct the GPP fluxes simulated by the LUE-based model. Similarly, the ecosystem respiration estimations by the model have undergone refinement by incorporating ST and SM information. This innovative method shows remarkable potential to improve biospheric CO2 uptake and release, especially for in situ data-constrained regions like India. • SIF-based information is introduced to a light-use efficiency-based vegetation model. • SIF-GPP relationship is established for major biomes across India. • SM and ST information is incorporated into the Reco simulations in the model.

Physiological dynamics dominate the relationship between solar-induced chlorophyll fluorescence and gross primary productivity along the nitrogen gradient in cropland.

Solar-induced chlorophyll fluorescence (SIF) has been found to be robustly correlated with gross primary productivity (GPP) based on satellite datasets. However, it is unclear whether nitrogen affects the relationship between SIF and GPP at the canopy scale. Here, seasonal dynamics of SIF, GPP, vegetation physiology and canopy structure were measured synchronously throughout growing season along the nitrogen gradient in a rice paddy of China's subtropical region. Our results found that the slope of SIF against GPP was not constant, showing an increasing trend from low to high nitrogen levels. The sensitivity of SIF to nitrogen was larger than that of GPP. Nitrogen enrichment versus deficiency had asymmetrical effects on the SIF-GPP relationship. The steeper slope of SIF against GPP under high nitrogen level was mainly attributed to the promotion of canopy fluorescence efficiency (ΦF) rather than the variation of canopy fluorescence escape probability (Fesc). These results emphasize the vital role of nitrogen in exploring mechanisms underlying SIF dynamics and decoding GPP from SIF.

Quantifying effects of cold acclimation and delayed springtime photosynthesis resumption in northern ecosystems.

Land carbon dynamics in temperate and boreal ecosystems are sensitive to environmental change. Accurately simulating gross primary productivity (GPP) and its seasonality is key for reliable carbon cycle projections. However, significant biases have been found in early spring GPP simulations of northern forests, where observations often suggest a later resumption of photosynthetic activity than predicted by models. Here, we used eddy covariance-based GPP estimates from 39 forest sites that differ by their climate and dominant plant functional types. We used a mechanistic and an empirical light use efficiency (LUE) model to investigate the magnitude and environmental controls of delayed springtime photosynthesis resumption (DSPR) across sites. We found DSPR reduced ecosystem LUE by 30-70% at many, but not all site-years during spring. A significant depression of LUE was found not only in coniferous but also at deciduous forests and was related to combined high radiation and low minimum temperatures. By embedding cold-acclimation effects on LUE that considers the delayed effects of minimum temperatures, initial model bias in simulated springtime GPP was effectively resolved. This provides an approach to improve GPP estimates by considering physiological acclimation and enables more reliable simulations of photosynthesis in northern forests and projections in a warming climate.

[Connotation of distal bleeding based on modern pathophysiological mechanism and application of Huangtu Decoction for acute coronary syndrome complicated with acute upper gastrointestinal hemorrhage in critical care medicine].

Huangtu Decoction, first recorded in Essentials from the Golden Cabinet(Jin Kui Yao Lue) from ZHANG Zhong-jing in Han dynasty, is used to treat distal bleeding. It is mainly treated for the syndrome of failing to control blood with spleen-yang deficiency. The connotation of distal bleeding is more extensive, including not only upper gastrointestinal bleeding in the traditional sense such as peptic ulcer bleeding, gastrointestinal tumors, gastric mucosal lesions, vascular dysplasia, esophagogastric variceal bleeding, and pancreatic and biliary tract injury, but also other anorectal diseases such as part colon and rectal cancer swelling or polyps, hemorrhoids, and anal fissure and other parts of bleeding such as epistaxis, thrombocytopenia, functional uterine bleeding, threatened abortion, and unexplained hematuria. Distal bleeding also involves syndromes of failing to keep part deficient and cold fluids in interior, such as nocturia, enuresis, clear nose, sweating, cold tears, and leucorrhea, and excessive gastrointestinal bleeding caused by anti-plate and anticoagulant drugs, unexplained positive in the fecal occult blood test, and other modern clinical new problems. The indications of Huangtu Decoction include not only lower blood, defecation before blood, distant blood, hematemesis, epistaxis, and other diseases in traditional Chinese medicine, but also three types of clinical manifestations including bleeding, deficiency syndrome, and stagnant heat syndrome. In the clinic, Huangtu Decoction can be used to treat acute upper gastrointestinal bleeding, acute coronary syndrome complicated with acute upper gastrointestinal bleeding, bleeding events caused by excessive antiplatelet and anticoagulant drugs, unexplained positive in the fecal occult blood test, gastrointestinal tumor with bleeding, thrombocytopenia, and other acute and critical diseases. The dosage of Cooking Stove Earthkey, Rehmanniae Radix, and Asini Corii Colla in Huangtu Decoction is the key to hemostasis.

Evaluating gross primary productivity over 9 ChinaFlux sites based on random forest regression models, remote sensing, and eddy covariance data.

Accurate modeling of Gross Primary Productivity (GPP) in terrestrial ecosystems is a major challenge in quantifying the carbon cycle. Many light use efficiency (LUE) models have been developed, but the variables and algorithms used for environmental constraints in different models vary importantly. It is still unclear whether the models can be further improved by machine learning methods and the combination of different variables. Here, we have developed a series of RFR-LUE models, which used the random forest regression (RFR) algorithm based on variables of LUE models, to explore the potential of estimating site-level GPP. Based on remote sensing indices, eddy covariance and meteorological data, we applied RFR-LUE models to evaluate the effects of different variables combined on GPP on daily, 8-day, 16-day and monthly scales, respectively. Cross-validation analyses revealed performances of RFR-LUE models varied significantly among sites with R2 of 0.52-0.97. Slopes of the regression relationship between simulated and observed GPP ranged from 0.59 to 0.95. Most models performed better in capturing the temporal changes and magnitude of GPP in mixed forests and evergreen needle-leaf forests than in evergreen broadleaf forests and grasslands. Performances were improved at the longer temporal scale, with the average R2 for four-time resolutions of 0.81, 0.87, 0.88, and 0.90, respectively. Additionally, the importance of the variables showed that temperature and vegetation indices were critical variables for RFR-LUE models, followed by radiation and moisture variables. The importance of moisture variables was higher in non-forests than in forests. A comparison with four GPP products indicated that RFR-LUE model predicted GPP better matcher observed GPP across sites. The study provided an approach to deriving GPP fluxes and evaluating the extent to which variables affect GPP estimation. It may be used for predicting vegetation GPP at the regional scales and for calibration and evaluation of land surface process models.

Land use efficiency of functional urban areas: Global pattern and evolution of development trajectories.

The application of last-generation spatial data modelling, integrating Earth Observation, population, economic and other spatially explicit data, enables insights into the sustainability of the global urbanisation processes with unprecedented detail, consistency, and international comparability. In this study, the land use efficiency indicator, as developed in the Sustainable Development Goals, is assessed globally for the first time at the level of Functional Urban Areas (FUAs). Each FUA includes the city and its commuting zone as inferred from statistical modelling of available spatial data. FUAs represent the economic area of influence of each urban centre. Hence, the analysis of land consumption within their boundary has significance in the fields of spatial planning and policy analyses as well as many other research areas. We utilize the boundaries of more than 9,000 FUAs to estimate the land use efficiency between 1990 and 2015, by using population and built-up area data extracted from the Global Human Settlement Layer. This analysis shows how, in the observed period, FUAs in low-income countries of the Global South evolved with rates of population growth surpassing the ones of land consumption. However, in almost all regions of the globe, more than half of the FUAs improved their land use efficiency in recent years (2000-2015) with respect to the previous decade (1990-2000). Our study concludes that the spatial expansion of urban areas within FUA boundaries is reducing compactness of settlements, and that settlements located within FUAs do not display higher land use efficiency than those outside FUAs.

Cone-Beam CT and Image Fusion-Guided Percutaneous Recanalization of Occluded Central Venous Stent.

We describe an 81-year-old man with end-stage renal disease and central venous occlusion who was referred for dialysis access creation. This case illustrates a novel percutaneous image fusion-guided recanalization of an occluded right subclavian vein and brachiocephalic vein stent in a patient with limited remaining dialysis access sites. (Level of Difficulty: Advanced.).

Continuous Lighting and High Daily Light Integral Enhance Yield and Quality of Mass-Produced Nasturtium (Tropaeolum majus L.) in Plant Factories.

Nasturtium (Tropaeolum majus L.), as a medicinal plant, has a high phenolic content in its leaves and flowers. It is often used in salads as a dietary vegetable. Attracting strong demand, it could be a good candidate crop for a plant factory with artificial lighting (PFAL) that can achieve the mass production of high-quality crops with high productivity by regulating environmental conditions such as light. In this study, two experiments were conducted to investigate the effects of continuous lighting (CL) and different daily light integrals (DLIs) under CL on the growth, secondary metabolites, and light use efficiency (LUE) of nasturtium, all of which are essential in the successful cultivation in PFALs. In Experiment 1, two lighting models, the same DLI of 17.3 mol m-2 d-1 but different light periods (24 and 16 h) with different light intensities (200 and 300 µmol m-2 s-1, respectively), were applied to nasturtium. The results showed that leaf production, secondary metabolites, and LUE were higher under the 24-h CL treatment than under the 16-h non-CL treatment. In Experiment 2, three DLI levels (17.3, 25.9, and 34.6 mol m-2 d-1) under the CL condition were applied. The results showed that the growth parameters were positively correlated with the DLI levels under CL. The lowest DLI had the highest LUE. We conclude that the mass production of nasturtium under CL in PFALs is feasible, and the yield increases as DLI increases from 17.3 to 34.6 mol m-2 d-1 under CL without causing physiological stress on plants.

Seasonal variation in photosynthetic rates and satellite-based GPP estimation over mangrove forest.

In view of increasing anthropogenic influences and global changes, quantification of carbon assimilation through photosynthesis has gained tremendous significance. Precise estimation of Gross Primary Productivity (GPP) is essential for several ecosystem models and is typically done using coarser scale satellite data. The mangrove ecosystem, which offers significant protection to the coastal environment, is one of the critical habitats from a global change point of view. Light use efficiency (LUE) was measured using diurnal in situ photosynthetic rate observations for 13 dominant mangrove species for 3 seasons at each of the three mangrove dominant test-sites situated along the east and west coast of India. Variations in photosynthetic rates among these species were studied for 3 seasons that indicated varying responses of mangrove ecosystem at each site. Among all species, Rhizophora mucronata and Sonneratia apetala indicated higher values at two of the test-sites. IRS Resourcesat-2 LISS-IV datasets were used for the estimation of GPP. Mean GPP for all the sites varied from 1.2 to 7.7 g C m-2 day-1 with maximum value of 14.4 g C m-2 day-1. Mean values of GPP varied across the sites, based on its maximum LUE values and available photosynthetically active radiation (PAR). The results provide GPP values at much better spatial resolution for a threatened habitat like mangroves that typically survive in a narrow habitat along the coasts.

[On the name and authorship of Yi Lüe Zheng Wu Gai Lun].

Yi Lüe Zheng Wu Gai Lun(, Introduction of Corrections to Summaries on Medicine) was written around 1545, the 24th year during Emperor Jiajing's reign in the Ming Dynasty, now it has the only copy extant. Some errors and mistakes happened about this book name and its author in some history books and bibliographies: some reference books describe Yi Lüe Zheng Wu Gai Lun and Yi Lüe Zheng Wu (, Corrections to Summaries on Medicine) as two different books, with their own writer Li Xiang and Li Hanyi respectively. In fact, there is only one book, Yi Lüe Zheng Wu Gai Lun and Yi Lüe Zheng Wu is same book. The author is Li Xiang, but Hanyi is his courtesy name that misunderstood as a different person.

Monitoring tropical forests under a functional perspective with satellite-based vegetation optical depth.

Monitoring ecosystem functions in forests is a priority in a climate change scenario, as climate-induced events may initially alter the functions more than slow-changing attributes, such as biomass. The ecosystem functional properties (EFPs) are quantities that characterize key ecosystem processes. They can be derived by point observations of gas and energy exchanges between the ecosystems and the atmosphere that are collected globally at FLUXNET flux tower sites and upscaled at ecosystem level. The properties here considered describe the ability of ecosystems to optimize the use of resources for carbon uptake. They represent functional forest information, are dependent on environmental drivers, linked to leaf traits and forest structure, and influenced by climate change effects. The ability of vegetation optical depth (VOD) to provide forest functional information is investigated using 2011-2014 satellite data collected by the Soil Moisture and Ocean Salinity mission and using the EFPs as reference dataset. Tropical forests in Africa and South America were analyzed, also according to ecological homogeneous units. VOD jointly with water deficit information explained 93% and 87% of the yearly variability in both flux upscaled maximum gross primary productivity and light use efficiency functional properties, in Africa and South America forests respectively. Maps of the retrieved properties evidenced changes in forest functional responses linked to anomalous climate-induced events during the study period. The findings indicate that VOD can support the flux upscaling process in the tropical range, affected by high uncertainty, and the detection of forest anomalous functional responses. Preliminary temporal analysis of VOD and EFP signals showed fine-grained variability in periodicity, in signal dephasing, and in the strength of the relationships. In selected drier forest types, these satellite data could also support the monitoring of functional dynamics.

Assessment of five satellite-derived LAI datasets for GPP estimations through ecosystem models.

Ecosystem models have been widely used for obtaining gross primary productivity (GPP) estimations at multiple scales. Leaf area index (LAI) is a critical variable in these models for describing the vegetation canopy structure and predicting vegetation-atmosphere interactions. However, the uncertainties in LAI datasets and the effects of their representation on simulated GPP remain unclear, especially over complex terrain. Here, five most popular datasets, namely the Long-term Global Mapping (GLOBMAP) LAI, Global LAnd Surface Satellite (GLASS) LAI, Geoland2 version 1 (GEOV1) LAI, Global Inventory Monitoring and Modeling System (GIMMS) LAI, and Moderate Resolution Imaging Spectroradiometer (MODIS) LAI, were selected to examine the influences of LAI representation on GPP estimations at 95 eddy covariance (EC) sites. The GPP estimations from the Boreal Ecosystem Productivity Simulator (BEPS) model and the Eddy Covariance Light Use Efficiency (EC-LUE) model were evaluated against EC GPP to assess the performances of LAI datasets. Results showed that MODIS LAI had stronger linear correlations with GLASS and GEOV1 than GIMMS and GLOMAP at the study sites. The GPP estimations from GLASS LAI had a better agreement with EC GPP than those from other four LAI datasets at forest sites, while the GPP estimations from GEOVI LAI matched best with EC GPP at grass sites. Additionally, the GPP estimations from GLASS and GEOVI LAI presented better performances than the other three LAI datasets at crop sites. Besides, the results also showed that complex terrain had larger discrepancies of LAI and GPP estimations, and flat terrain presented better performances of LAI datasets in GPP estimations. Moreover, the simulated GPP from BEPS was more sensitive to LAI than those from EC - LUE, suggesting that LAI datasets can also lead to different uncertainties in GPP estimations from different model structures. Our study highlights that the satellite-derived LAI datasets can cause uncertainties in GPP estimations through ecosystem models.

Exploring the spatial relationship between airborne-derived red and far-red sun-induced fluorescence and process-based GPP estimates in a forest ecosystem.

Terrestrial gross primary productivity (GPP) plays an essential role in the global carbon cycle, but the quantification of the spatial and temporal variations in photosynthesis is still largely uncertain. Our work aimed to investigate the potential of remote sensing to provide new insights into plant photosynthesis at a fine spatial resolution. This goal was achieved by exploiting high-resolution images acquired with the FLuorescence EXplorer (FLEX) airborne demonstrator HyPlant. The sensor was flown over a mixed forest, and the images collected were elaborated to obtain two independent indicators of plant photosynthesis. First, maps of sun-induced chlorophyll fluorescence (F), a novel indicator of plant photosynthetic activity, were successfully obtained at both the red and far-red peaks (r2 = 0.89 and p < 0.01, r2 = 0.77 and p < 0.01, respectively, compared to top-of-canopy ground-based measurements acquired synchronously with the overflight) over the forested study area. Second, maps of GPP and absorbed photosynthetically active radiation (APAR) were derived using a customised version of the coupled biophysical model Breathing Earth System Simulator (BESS). The model was driven with airborne-derived maps of key forest traits (i.e., leaf chlorophyll content (LCC) and leaf area index (LAI)) and meteorological data providing a high-resolution snapshot of the variables of interest across the study site. The LCC and LAI were accurately estimated (RMSE = 5.66 µg cm-2 and RMSE = 0.51 m2m-2, respectively) through an optimised Look-Up-Table-based inversion of the PROSPECT-4-INFORM radiative transfer model, ensuring the accurate representation of the spatial variation of these determinants of the ecosystem's functionality. The spatial relationships between the measured F and modelled BESS outputs were then analysed to interpret the variability of ecosystem functioning at a regional scale. The results showed that far-red F is significantly correlated with the GPP (r2 = 0.46, p < 0.001) and APAR (r2 = 0.43, p < 0.001) in the spatial domain and that this relationship is nonlinear. Conversely, no statistically significant relationships were found between the red F and the GPP or APAR (p > 0.05). The spatial relationships found at high resolution provide valuable insight into the critical role of spatial heterogeneity in controlling the relationship between the far-red F and the GPP, indicating the need to consider this heterogeneity at a coarser resolution.

Testing of Automated Photochemical Reflectance Index Sensors as Proxy Measurements of Light Use Efficiency in an Aspen Forest.

Commercially available autonomous photochemical reflectance index (PRI) sensors are a new development in the remote sensing field that offer novel opportunities for a deeper exploration of vegetation physiology dynamics. In this study, we evaluated the reliability of autonomous PRI sensors (SRS-PRI) developed by METER Group Inc. as proxies of light use efficiency (LUE) in an aspen (Populus tremuloides) forest stand. Before comparisons between PRI and LUE measurements were made, the optical SRS-PRI sensor pairs required calibrations to resolve diurnal and seasonal patterns properly. An offline diurnal calibration procedure was shown to account for variable sky conditions and diurnal illumination changes affecting sensor response. Eddy covariance measurements provided seasonal gross primary productivity (GPP) measures as well as apparent canopy quantum yield dynamics (α). LUE was derived from the ratio of GPP to absorbed photosynthetically active radiation (APAR). Corrected PRI values were derived after diurnal and midday cross-calibration of the sensor's 532 nm and 570 nm fore-optics, and closely related to both LUE (R² = 0.62, p < 0.05) and α (R² = 0.72, p < 0.05). A LUE model derived from corrected PRI values showed good correlation to measured GPP (R² = 0.77, p < 0.05), with an accuracy comparable to results obtained from an α driven LUE model (R² = 0.79, p < 0.05). The automated PRI sensors proved to be suitable proxies of light use efficiency. The onset of continuous PRI sensors signifies new opportunities for explicitly examining the cause of changing PRI, LUE, and productivity over time and space. As such, this technology represents great value for the flux, remote sensing and modeling community.

Performance of a two-leaf light use efficiency model for mapping gross primary productivity against remotely sensed sun-induced chlorophyll fluorescence data.

Estimating terrestrial gross primary production is an important task when studying the carbon cycle. In this study, the ability of a two-leaf light use efficiency model to simulate regional gross primary production in China was validated using satellite Global Ozone Monitoring Instrument - 2 sun-induced chlorophyll fluorescence data. The two-leaf light use efficiency model was used to estimate daily gross primary production in China's terrestrial ecosystems with 500-m resolution for the period from 2007 to 2014. Gross primary production simulated with the two-leaf light use efficiency model was resampled to a spatial resolution of 0.5° and then compared with sun-induced chlorophyll fluorescence. During the study period, sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf light use efficiency model exhibited similar spatial and temporal patterns in China. The correlation coefficient between sun-induced chlorophyll fluorescence and monthly gross primary production simulated by the two-leaf light use efficiency model was significant (p<0.05, n=96) in 88.9% of vegetated areas in China (average value 0.78) and varied among vegetation types. The interannual variations in monthly sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf light use efficiency model were similar in spring and autumn in most vegetated regions, but dissimilar in winter and summer. The spatial variability of sun-induced chlorophyll fluorescence and gross primary production simulated by the two-leaf light use efficiency model was similar in spring, summer, and autumn. The proportion of spatial variations of sun-induced chlorophyll fluorescence and annual gross primary production simulated by the two-leaf light use efficiency model explained by ranged from 0.76 (2011) to 0.80 (2013) during the study period. Overall, the two-leaf light use efficiency model was capable of capturing spatial and temporal variations in gross primary production in China. However, the model needs further improvement to better simulate gross primary production in summer.

Deconvolution of pigment and physiologically related photochemical reflectance index variability at the canopy scale over an entire growing season.

The sensitivity of the photochemical reflectance index (PRI) to leaf pigmentation and its impacts on its potential as a proxy for light-use efficiency (LUE) have recently been shown to be problematic at the leaf scale. Most leaf-to-leaf and seasonal variability can be explained by such a confounding effect. This study relies on the analysis of PRI light curves that were generated at the canopy scale under natural conditions to derive a precise deconvolution of pigment-related and physiologically related variability in the PRI. These sources of variability were explained by measured or estimated physiologically relevant variables, such as soil water content, that can be used as indicators of water availability and canopy chlorophyll content. The PRI mainly reflected the variability in the pigment content of the canopy. However, the corrected PRI, which was obtained by subtracting the pigment-related seasonal variability from the PRI measurement, was highly correlated with the upscaled LUE measurements. Moreover, the sensitivity of the PRI to the leaf pigment content may mask the PRI versus LUE relationship or result in an artificial relationship that reflects the relationship of chlorophyll versus LUE, depending on the species phenology.

Optimizing illumination in the greenhouse using a 3D model of tomato and a ray tracer.

Reduction of energy use for assimilation lighting is one of the most urgent goals of current greenhouse horticulture in the Netherlands. In recent years numerous lighting systems have been tested in greenhouses, yet their efficiency has been very difficult to measure in practice. This simulation study evaluated a number of lighting strategies using a 3D light model for natural and artificial light in combination with a 3D model of tomato. The modeling platform GroIMP was used for the simulation study. The crop was represented by 3D virtual plants of tomato with fixed architecture. Detailed data on greenhouse architecture and lamp emission patterns of different light sources were incorporated in the model. A number of illumination strategies were modeled with the calibrated model. Results were compared to the standard configuration. Moreover, adaptation of leaf angles was incorporated for testing their effect on light use efficiency (LUE). A Farquhar photosynthesis model was used to translate the absorbed light for each leaf into a produced amount of carbohydrates. The carbohydrates produced by the crop per unit emitted light from sun or high pressure sodium lamps was the highest for horizontal leaf angles or slightly downward pointing leaves, and was less for more upward leaf orientations. The simulated leaf angles did not affect light absorption from inter-lighting LED modules, but the scenario with LEDs shining slightly upward (20(°)) increased light absorption and LUE relative to default horizontal beaming LEDs. Furthermore, the model showed that leaf orientation more perpendicular to the string of LEDs increased LED light interception. The combination of a ray tracer and a 3D crop model could compute optimal lighting of leaves by quantification of light fluxes and illustration by rendered lighting patterns. Results indicate that illumination efficiency increases when the lamp light is directed at most to leaves that have a high photosynthetic potential.

Relationship between photochemical reflectance index and leaf ecophysiological and biochemical parameters under two different water statuses: towards a rapid and efficient correction method using real-time measurements.

The use of the photochemical reflectance index (PRI) as a promising proxy of light use efficiency (LUE) has been extensively studied, and some issues have been identified, notably the sensitivity of PRI to leaf pigment composition and the variability in PRI response to LUE because of stress. In this study, we introduce a method that enables us to track the short-term PRI response to LUE changes because of photosynthetically active radiation (PAR) changes. The analysis of these short-term relationships between PRI and LUE throughout the growing season in two species (Quercus robur L. and Fagus sylvatica L.) under two different soil water statuses showed a clear change in PRI response to LUE, which is related to leaf pigment content. The use of an estimated or approximated PRI0, defined as the PRI of perfectly dark-adapted leaves, allowed us to separate the PRI variability due to leaf pigment content changes and the physiologically related PRI variability over both daily (PAR-related) and seasonal (soil water content-related) scales. The corrected PRI obtained by subtracting PRI0 from the PRI measurements showed a good correlation with the LUE over both of the species, soil water statuses and over the entire growing season.

Actualización sobre la enfermedad de Peyronie / Update on Peyronie´s disease

La enfermedad de Peyronie es un trastorno de la túnica albugínea del pene caracterizada por la formación de placas fibrosas que conlleva a curvaturas patológicas del mismo. El presente artículo tiene como objetivo revisar los nuevos conceptos y los avances en los tratamientos, tanto quirúrgicos como no quirúrgicos, los orales o intralesionales, para manejar adecuadamente al paciente o para seguir un tratamiento que conlleve la mejoría de la sintomatología y de la calidad de vida de los hombres que padecen esta enfermedad. La enfermedad de Peyronie es un trastorno que no es tan infrecuente en la población masculina, que se acompaña de disfunción eréctil, una de las alteraciones que genera más consultas urológicas.

Peyronie’s disease, it is a disorder of the tunica albuginea of the penis, characterized by the formation of fibrotic plates that cause pathological curvatures of this organ. The present article aims to update new concepts, and advances in the both surgical and non surgical oral or intralesional treatments, in order to manage adequately the patient, or to follow a treatment that would improve their symptomatology and the quality of life. Peyronie’s disease is a disorder, not so infrequent in the masculine population which accompanies erectile dysfunction, one of the disorders that seen in urological services.