Recent studies report an increase in vegetation greenness in mid‐to‐high northern latitudes. This increase is observed in leaf‐out data in Europe and North America since the 1950s and in satellite ...data since the 1980s. Increased vegetation greenness is potentially a factor contributing to a land CO2 sink. Various causes for increased vegetation greenness are suggested, but their relative importance is uncertain. In the present study, the effect of climate and CO2 fertilization on increased vegetation greenness and the land CO2 sink are investigated. The study is organized as follows: (1) A model is used to simulate monthly global normalized difference vegetation index (NDVI) fields for 1901–2006. The model is derived from NDVI, precipitation, and temperature data for 1982–1999. The modeled fields, referred to as reconstructed vegetation index (RVI), are tested back in time on phenological data (1950s–1990s) and forward in time on Moderate Resolution Imaging Spectrometer (MODIS) data (2001–2006). The RVI represents the response of NDVI to variations in climate. (2) Residuals between RVI and NDVI are analyzed for associations with variations in downwelling solar radiation, nitrogen deposition, satellite‐related artifacts, and CO2 fertilization. CO2 fertilization was the only factor that improved RVI modeling. (3) The effect of climate variations and CO2 fertilization on the land CO2 sink, as manifested in the RVI, is explored with the Carnegie Ames Stanford Assimilation (CASA) model. Climate (temperature and precipitation) and CO2 fertilization each explain approximately 40% of the observed global trend in NDVI for 1982–2006. For 1901–2006, estimated trends in NDVI related to CO2 fertilization are four to five times larger than climate‐related trends. CASA simulations indicate that the CO2 fertilization effect on vegetation greenness contributes about 0.7 Pg C per year to the recent land CO2 sink. This is a conservative estimate and is likely larger. This effect of CO2 fertilization would be a large component of the land carbon sink. In the supporting information the RVI is used as a common standard to fuse MODIS and advanced very high resolution radiometer (AVHRR) NDVI data. This fusion compares well with SeaWiFS data.
Key Points
It is the first realistic simulation of monthly NDVI for the 20th century
It is the first evidence of CO2 fertilization derived from satellite data
The model can be used to fuse AVHRR and MODIS data
For three forest canopies (a sparse, boreal needleleaf; a temperate broadleaf; and a dense, tropical, broadleaf stand) light-use efficiency (LUE) is found to be 6-33% higher when sky radiance is ...dominated by diffuse rather than direct sunlight. This enhancement is much less than that reported previously for both crops (110%; Choudbury, 2001 ) and moderately dense temperate woodland (50-180%). We use the land-surface scheme JULES to interpret the observed canopy response. Once sunflecks and leaf orientation are incorporated explicitly into the scheme, our simulations reproduce convincingly the overall level of canopy gross photosynthetic product (GPP), its enhancement with respect to diffuse sunlight and the mean 15% reduction in productivity observed during the afternoon due to stomatal closure. The LUE enhancement under diffuse sunlight can be explained by sharing of the canopy radiation-load, which is reduced under direct sky radiance. Once sunflecks are accounted for the advantage of implementing more sophisticated calculations of stomatal conductance (e.g. Ball-Berry and SPA submodels) is less obvious even for afternoon assimilation. Empirical relations are developed between observed carbon flux and the environmental variables total downwelling shortwave radiation (SW), canopy temperature (T) and the fraction of diffuse sky radiance (fDIF). These relations allow us to gauge the impact of increased/reduced insolation on GPP and net ecosystem exchange (NEE). Overall the three stands appear to be fairly stable within global trends and typical interannual variability (SW changing by <15%). Greatest sensitivity is exhibited by the boreal site, Zotino, where NEE falls by 9±4% for a 15% reduction in SW.
To obtain specific information about cattle in extensive production systems, the usual labor intensive work done by the farmer to find and visit cattle herds in large pastures can be replaced by ...using UAVs. UAVs are capable of assessing traits in cows, like distinguishing individuals and postures. Although these traits and the detection of cattle, do not represent resilience and efficiency directly, these may contain information associated to resilience. We performed a feasibility study of remotely sensed imagery (using datasets from satellites, manned aircrafts, and UAVs), and deep learning techniques to detect, count, identify and characterize posture of individual cows in grassland production systems. With these techniques, we focused on : (1) automatic detection of cattle locations and animal counting; (2) cow postures like standing, grazing or lying; and (3) individual cow identification. Data were collected during three field trials in the Netherlands and Poland. Artificial Intelligence was used to classify the objects (cattle) in the drone imagery. Classification accuracies of >95% were obtained for detecting cows. Accuracies of ~91% were obtained for identifying individual cows, and accuracies of ~88% were obtained for cow postures. These results make camera-mounted drones a promising new technology for monitoring extensive beef production systems.
The realistic simulation of key components of the land-surface hydrological cycle – precipitation, runoff, evaporation and transpiration, in general circulation models of the atmosphere – is crucial ...to assess adverse weather impacts on environment and society. Here, gridded precipitation data from observations and precipitation and runoff fields from reanalyses were tested with satellite derived global vegetation index data for 1982–2010 and latitudes between 45° S and 45° N. Data were obtained from the Climate Research Unit (CRU), the Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Monitoring Mission (TRMM; analysed for 1998–2010 only) and precipitation and runoff reanalyses were obtained from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), the European Centre for Medium-Range Weather Forecasts (ECMWF) and the NASA Global Modelling and Assimilation Office (GMAO). Annual land-surface precipitation was converted to annual potential vegetation net primary productivity (NPP) and was compared to mean annual normalised difference vegetation index (NDVI) data measured by the Advanced Very High Resolution Radiometer (AVHRR; 1982–1999) and Moderate Resolution Imaging Spectroradiometer (MODIS; 2001–2010). The effect of spatial resolution on the agreement between NPP and NDVI was investigated as well. The CRU and TRMM derived NPP agreed most closely with the NDVI data. The GPCP data showed weaker spatial agreement, largely because of their lower spatial resolution, but similar temporal agreement. MERRA Land and ERA Interim precipitation reanalyses showed similar spatial agreement to the GPCP data and good temporal agreement in semi-arid regions of the Americas, Asia, Australia and southern Africa. The NCEP/NCAR reanalysis showed the lowest spatial agreement, which could only in part be explained by its lower spatial resolution. No reanalysis showed realistic interannual precipitation variations for northern tropical Africa. Inclusion of runoff in the NPP prediction resulted only in marginally better agreement for the MERRA Land reanalysis and slightly worse agreement for the NCEP/NCAR and ERA Interim reanalyses.
We present a method and results for a model of the interaction of waveform Light Detection And Ranging (LiDAR) with a three-dimensional vegetation canopy. The model is developed from the FLIGHT ...radiative transfer model based on Monte Carlo simulations of photon transport. Foliage is represented by structural properties of leaf area, leaf-angle distribution, crown dimensions and fractional cover, and the optical properties of leaves, branch, shoot and ground components. The model represents multiple scattering of light within the canopy and with the ground surface, simulates the return signal efficiently at multiple wavebands and includes the effects of topography. LiDAR-emitted pulse and spatial and temporal sampling characteristics of the instrument are explicitly modelled. Agreement is found between the integrated waveform energy and directly derived bidirectional reflectance factors from FLIGHT (root mean square error < 0.01), and between simulated and observed Ice, Cloud and land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) waveforms for a complex forest site. A sensitivity analysis gives expected effects of canopy parameters on the waveform, and indicates potential for retrieval of the canopy properties of fractional cover and leaf area, in addition to height. Where canopy and ground pulses can be separated, an index derived from the waveform shows theoretical retrieval of vertically projected plant area index with correlation coefficient R
2
= 0.87.
The upgrades of the CMS and ATLAS experiments for the high luminosity phase of the Large Hadron Collider will employ precision timing detectors based on Low Gain Avalanche Detectors (LGADs). We ...present a suite of results combining measurements from the Fermilab Test Beam Facility, a beta source telescope, and a probe station, allowing full characterization of the HPK type 3.1 production of LGAD prototypes developed for these detectors. We demonstrate that the LGAD response to high energy test beam particles is accurately reproduced with a beta source. We further establish that probe station measurements of the gain implant accurately predict the particle response and operating parameters of each sensor, and conclude that the uniformity of the gain implant in this production is sufficient to produce full-sized sensors for the ATLAS and CMS timing detectors.
Background Environmental psychological factors such as mood states can modify and trigger an organic response; depressive disorder is considered a risk factor for oncological development, leading to ...alterations both in the genesis and in the progression of the disease. Some authors have identified that personality relates to mood since a high score in neuroticism is associated with intense and long-lasting emotions of stress and therefore with the development of depressive behaviors. The objective of this study was to analyze the relationship between personality and depression in skin cancer patients. Methods A total of forty-seven clinically and histopathologically diagnosed patients were scheduled for an hour-long interview, during which they provided informed consent and sociodemographic information. The psychological questionnaires applied were the revised Eysenck Personality Questionnaire and the clinical questionnaire for the diagnosis of the depressive syndrome. Results The patient's mean age was 66.5 years (SD + or - 12.4) and the majority were diagnosed with basal cell carcinoma (70.2%). The frequency of anxious/depressive symptoms was 42.5%, with an increase in depression scores in the female gender (p < 0.001). Furthermore, a difference was found in the neuroticism dimension related to gender, with higher values in women (p = 0.002). Depressive symptomatologic portraits were correlated with the dimensions of neuroticism (p < 0.001, r = 0.705), psychoticism (p = 0.003, r = 0.422) and lying (p = 0.028, r = - 0.321). Conclusions Our results support the hypothesis that personality dimensions are related to the presence of anxiety/depressive symptomatology in patients with skin cancer, especially in the female gender. Highlighting the need for future research that delves into the implications at the psychological level, the quality of life, and the biological mechanisms that link personality and depressive symptoms in the development and evolution of skin cancer. Keywords: Personality dimensions, Anxiety, Depression, Skin cancer
•The surface tension and density of binary mixtures of 1-nonanol + n-alkane were measured.•The intermolecular interactions for the 1-nonanol + n-alkane mixtures were discussed.•The deviation of the ...surface tension decreases as the temperature increases, but only in the 1-nonanol + n-octane mixture.•The volume of excess was determined, and a crossing of isotherms was observed for the mixture of 1-nonanol + n-octane.
We present the density and surface tension of binary mixtures n-octane, n-nonane and n-decane with 1-nonanol in the entire composition range at atmospheric pressure. The surface tension is measured from 293.15 K to 313.15 K while the density is measured from 293.15 to 323.15 K. Densities are obtained from a vibrating tube densimeter and surface tensions are from a drop volume tensiometer. Excess molar volumes and surface tension deviations are calculated from the experimental measurements and they are represented using Redlich-Kister type equations. Surface entropy and enthalpy are calculated using the temperature dependence of the surface tension.
We present new coarse resolution (0.5° × 0.5°) vegetation height and vegetation-cover fraction data sets between 60° S and 60° N for use in climate models and ecological models. The data sets are ...derived from 2003-2009 measurements collected by the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat), the only LiDAR instrument that provides close to global coverage. Initial vegetation height is calculated from GLAS data using a development of the model of Rosette et al. (2008) with with further calibration on desert sites. Filters are developed to identify and eliminate spurious observations in the GLAS data, e.g. data that are affected by clouds, atmosphere and terrain and as such result in erroneous estimates of vegetation height or vegetation cover. Filtered GLAS vegetation height estimates are aggregated in histograms from 0 to 70 m in 0.5 m intervals for each 0.5° × 0.5°. The GLAS vegetation height product is evaluated in four ways. Firstly, the Vegetation height data and data filters are evaluated using aircraft LiDAR measurements of the same for ten sites in the Americas, Europe, and Australia. Application of filters to the GLAS vegetation height estimates increases the correlation with aircraft data from r = 0.33 to r = 0.78, decreases the root-mean-square error by a factor 3 to about 6 m (RMSE) or 4.5 m (68% error distribution) and decreases the bias from 5.7 m to -1.3 m. Secondly, the global aggregated GLAS vegetation height product is tested for sensitivity towards the choice of data quality filters; areas with frequent cloud cover and areas with steep terrain are the most sensitive to the choice of thresholds for the filters. The changes in height estimates by applying different filters are, for the main part, smaller than the overall uncertainty of 4.5-6 m established from the site measurements. Thirdly, the GLAS global vegetation height product is compared with a global vegetation height product typically used in a climate model, a recent global tree height product, and a vegetation greenness product and is shown to produce realistic estimates of vegetation height. Finally, the GLAS bare soil cover fraction is compared globally with the MODIS bare soil fraction (r = 0.65) and with bare soil cover fraction estimates derived from AVHRR NDVI data (r = 0.67); the GLAS tree-cover fraction is compared with the MODIS tree-cover fraction (r = 0.79). The evaluation indicates that filters applied to the GLAS data are conservative and eliminate a large proportion of spurious data, while only in a minority of cases at the cost of removing reliable data as well. The new GLAS vegetation height product appears more realistic than previous data sets used in climate models and ecological models and hence should significantly improve simulations that involve the land surface.
To investigate the effect of biofertilizers on the growth and yield of Eucalyptus grandis seedlings, greenhouse experiments were performed applying fertilizers based on agricultural byproducts, ...inoculated with nitrogen-fixing bacteria of the genera Azotobacter spp and Azospirillum spp. For the biofertilizers formulation, a nitrogen-fixing bacteria consortium was inoculated, and the experimental design was a 2 × 2 × 2 factorial arrangement, the factors were nitrogen source (NS: chicken manure), source of carbon (CS: eucalyptus leaf litter) and source of micronutrients (RS: rhizospheric soil) with two dose levels, inoculated with a consortium of Azotobacter spp and Azospirillum spp. The optimal time production of the best biofertilizers was 30 days, with the highest density of Azospirillum (9.23 × 10
6
CFU·g
−1
) and Azotobacter (19.3 × 10
6
CFU·g
−1
), and total nitrogen contents in the range of 2.15-5.64%, released into the biofertilizers with chicken manure and bioaugmented with the bacterium consortium. The treatment with the highest dose of biofertilizer, 500 g, showed the most significant effect on seedling development, increasing growth, stimulating rooting and the highest increase in leaf number. The results show that biofertilizers contributed to Eucalyptus grandis crop yield, and biofertilizers are proposed as an alternative for implementing sustainable soil management in the forest sector.
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