Estimates Of Production Research Articles

Onshore wind in Portugal: History, supporting policies, economic viability and future perspectives

Onshore wind energy is currently playing a crucial role in Europe’s decarbonization efforts. Among other European countries, Portugal is recognized as a successful example of large-scale wind energy implementation thanks to its supportive policies in the 00 s. However, the government's financial support for onshore wind technologies has faced criticism, with accusations that feed-in tariffs were set too high and that farm owners were overpaid for their energy production. As the end of feed-in tariff regimes approaches for onshore wind farms in Portugal, it is unclear whether farm owners will choose to pursue repowering and life extension strategies, or opt to shut down operations. The present paper provides a techno-economic assessment to onshore wind farms in Portugal to assess their historical financial performance based on power production estimates and applicable feed-in tariff legal regimes. Based on the estimated investment costs, farm yield and established feed-in tariffs, the results suggest that there is no evidence of exceptional profits in onshore wind projects in Portugal. The results also suggest significant economic benefits for Portugal in prioritizing future investments in onshore wind, by pointing towards a strategic focus on life extension and repowering strategies as key components of this forward-looking approach.

The Role of Soil Microbial Consortia in Sustainable Cereal Crop Residue Management.

The global escalation in cereal production, essential to meet growing population demands, simultaneously augments the generation of cereal crop residues, estimated annually at approximately 3107 × 106 Mg/year. Among different crop residue management approaches, returning them to the soil can be essential for various ecological benefits, including nutrient recycling and soil carbon sequestration. However, the recalcitrant characteristics of cereal crop residues pose significant challenges in their management, particularly in the decomposition rate. Therefore, in this review, we aim to summarize the influence of different agricultural practices on enhancing soil microbial decomposer communities, thereby effectively managing cereal crop residues. Moreover, this manuscript provides indirect estimates of cereal crop residue production in Northern Europe and Lithuania, and highlights the diverse roles of lignocellulolytic microorganisms in the decomposition process, with a particular focus on enzymatic activities. This review bridges the knowledge gap and indicates future research directions concerning the influence of agricultural practices on cereal crop residue-associated microbial consortia.

AKURASI ESTIMASI PRODUKSI PADI DENGAN METODE NDVI BERDASARKAN SENTINEL-2 DI KABUPATEN TANAH LAUT KALIMANTAN SELATAN

Remote sensing is a technology that is very useful in every step of the planning process and has been used in developed countries and several regions in developing countries. The aim of this research is to interpret rice production in Tanah Laut Regency using the NDVI method based on Sentinel-2 and determine the accuracy of rice production estimates in Tanah Laut Regency using the NDVI method based on Sentinel-2. Research methods include preparation, measurement principles, data collection, radiometric correction, geometric correction, creating a vegetation index, determining the best vegetation index, estimating rice production, accuracy testing, image analysis, and rice production potential. The result of this research is a rice production estimation model of y = 0.341 + 4.319 NDVI. The NDVI estimation results in Tanah Laut Regency range from 1.36 t ha-1 to 3.36 t ha-1 with an average production of 2.67 t ha-1. The results of the analysis show that there is no real difference at the 95% confidence level between the results of the NDVI estimation of rice production using Sentinel-2 imagery and the results of the field survey of rice production based on a coefficient of determination (R2) of 0.749 and a standard error (SE) of 0.29 t ha-1.

Oxygen production from dissociation of Europa’s water-ice surface

Jupiter’s moon Europa has a predominantly water-ice surface that is modified by exposure to its space environment. Charged particles break molecular bonds in surface ice, thus dissociating the water to ultimately produce H2 and O2, which provides a potential oxygenation mechanism for Europa’s subsurface ocean. These species are understood to form Europa’s primary atmospheric constituents. Although remote observations provide important global constraints on Europa’s atmosphere, the molecular O2 abundance has been inferred from atomic O emissions. Europa’s atmospheric composition had never been directly sampled and model-derived oxygen production estimates ranged over several orders of magnitude. Here, we report direct observations of H2+ and O2+ pickup ions from the dissociation of Europa’s water-ice surface and confirm these species are primary atmospheric constituents. In contrast to expectations, we find the H2 neutral atmosphere is dominated by a non-thermal, escaping population. We find 12 ± 6 kg s−1 (2.2 ± 1.2 × 1026 s−1) O2 are produced within Europa’s surface, less than previously thought, with a narrower range to support habitability in Europa’s ocean. This process is found to be Europa’s dominant exogenic surface erosion mechanism over meteoroid bombardment.

Использование геномной оценки в совершенствовании продуктивных качеств коров голштинской породы

Abstract. Purpose of the study is analysis of productive and reproductive qualities of the Holstein cattle of the Tyumen region in comparison with the leading American enterprises using genomic selection. Materials and methods. Zootechnical, statistical and economic methods were used. As part of the work, the tasks were solved to consider the growth and development of replacement young animals; the main indicators of reproduction of heifers and cows of the main herd were analyzed; the milk productivity of cows and first-calf heifers was estimated according to the primary accounting data; a zootechnical assessment of sires used in the economy was carried out; the results of the genomic assessment were compared with the actual milk production. The scientific novelty of the work lies in the fact that genotyping was carried out in the conditions of a large industrial complex, because the use of genomic evaluation was not widely used in farms in the Russian Federation. Research results. The indicators of the intensity of growth of replacement young animals grown in the conditions of the Evika-Agro enterprise correspond to the world standards of the breed, and in some cases exceed them. The intensity of growing heifers allows for earlier insemination, which also contributes to early calving - 98% of animals calve up to 25 months of age. Estimates of milk production are largely consistent with those of advanced farms in the United States. “Evika-Agro” LLC uses outstanding sires from the world’s gene pool to improve economically useful traits, thereby accelerating the rate of selection. Analysis of the genomic assessment showed a significant discrepancy between the genetic basis of milk production and the actual level of milk production. This is most noticeable in the lifetime earnings index ($ 682) and the average increase in milk per lactation (916.2 kg) between the worst and best heifers in the sample.

Nematode production in artificial ponds: a long-term perspective

Summary Nematodes are the most abundant multicellular animals on Earth and play an important role as intermediaries in energy fluxes. However, estimations of nematode biomass turnover and secondary production have been poorly defined for decades and it is difficult to reach a consensus about the importance of nematodes for ecosystem functioning. Here we monitored monthly the nematode species composition, abundance and biomass over 3-10 years in a set of artificial urban ponds, and we used different allometric models to estimate biomass turnover and secondary production. During the first 3 years of colonisation of the pond bottom, the nematode community was rather species-poor and mostly composed of small bacterivorous species (Monhysterids); however, the community quickly reached impressive numbers (up to 21 million individuals m−2) achieving a maximum annual production of 3.8-11.6 gC m−2 year−1 depending on the allometric model used for estimation. However, over the long-term (3-10 years), abundance and community structure eventually became dramatically altered by anoxic events occurring in one pond, dampening nematode production to low levels (0.3-0.6 gC m−2 year−1) without clear resilience. The comparison of models helped us to formulate general recommendations in order to popularise the use of nematode secondary production as a useful ecosystem diagnostic tool. Overall, results indicated that under good conditions of oxygenation nematodes are a highly productive component of the zoobenthos of ponds. We also discussed the consequences of this finding for sustainable pond aquaculture, as nematodes constitute an important local and nutritive resource for juveniles of economically important fish, such as carp and tilapia.

Modeling of Cotton Yield Estimation Based on Canopy Sun-Induced Chlorophyll Fluorescence

Cotton yield estimation is of great practical significance to producers, allowing them to make rational management decisions. At present, crop yield estimation methods mainly comprise traditional agricultural yield estimation methods, which have many shortcomings. As an ideal “probe” for detecting crop photosynthesis, sun-induced chlorophyll fluorescence (SIF) can directly reflect the dynamics of actual crop photosynthesis and has the potential to predict crop yield, in order to realize cotton yield estimation based on canopy SIF. In this study, we set up field trials with different nitrogen fertilizer gradients. The changes of canopy SIF and the physiological parameters of cotton in different growth periods were analyzed. To investigate the effects of LAI and AGB on canopy SIF estimation of cotton yield, four algorithms, Ada Boost (Adaptive Boosting), Bagging (Bootstrap Aggregating), RF (Random Forest), and BPNN (Backpropagation Neural Network), were used to construct cotton yield estimation models based on the SIF and SIFy (the normalization of SIF by incident photosynthetically active radiation) for different time and growth periods. The results include the following: (1) The effects of the leaf area index (LAI) and aboveground biomass (AGB) on cotton canopy SIF and cotton yield were similar. The correlation coefficients of LAI and AGB with cotton yield and SIF were significantly positively correlated with each other starting from the budding period, reaching the maximum at the flowering and boll period, and decreasing at the boll period; (2) In different monitoring time periods, the R2 of the cotton yield estimation model established based on SIF and SIFy showed a gradual increase from 10:00 to 14:00 and a gradual decrease from 15:00 to 19:00, while the optimal observation time was from 14:00 to 15:00. The R2 increased with the progression of growth from the budding period to the flowering and boll period and decreased at the boll period, while the optimum growth period was the flowering and boll period; (3) Compared to SIF, SIFy has a superior estimation of yield. The best yield estimation model based on the RF algorithm (R2 = 0.9612, RMSE = 66.27 kg·ha−1, RPD = 4.264) was found in the canopy SIFy of the flowering and boll period at 14:00–15:00, followed by the model utilizing the Bagging algorithm (R2 = 0.8898) and Ada Boost algorithm (R2 = 0.8796). In summary, SIFy eliminates the effect of PAR (photosynthetically active radiation) on SIF and can further improve the estimation of SIF production. This study provides empirical support for SIF estimation of cotton yield and methodological and modeling support for the accurate estimation of cotton yield.

The economic value of human milk from three cohort studies in Friuli Venezia Giulia, Italy

BackgroundThe Mothers’ Milk Tool, developed and launched by the Australian National University and Alive & Thrive in 2022, allows to estimate the volume and value of breastmilk using prevalence rates of breastfeeding by month of age from birth to 36 months. The objective of this study was to obtain these estimates for three cohort studies conducted in a region of Italy.MethodsBreastfeeding data from three cohort studies carried out in 1999, 2007 and 2016, with follow-up to 12, 24 and 36 months of 842, 400 and 265 children, respectively, were entered into the downloadable version of the tool. Breastfeeding rates charts and tables with estimates of breastmilk production and value for breastfeeding of children aged 0–36 months were produced.ResultsThe rates of initiation of breastfeeding were similar in the three cohorts, while the rates of any breastfeeding at subsequent ages increased over the years. The volumes and values of breastmilk per child increased accordingly, from around 130 L (13,000 USD) in 1999, to 200 L (20,000 USD) in 2007, to 226 L (22,600 USD) in 2016. The percentage of lost breastmilk decreased from 67.7% to 55.4% to 43.7%, respectively. Overall, the 1507 mothers of the three cohorts produced an estimated 250,000 L of breastmilk for their children aged 0–36 months. At 100 USD per litre, this would add up to around 25 million USD.ConclusionsOur study shows that the Mothers’ Milk Tool can be used to estimate per child volumes and values of breastmilk produced and lost at local levels, and to provide simple indicators of the effects of breastfeeding interventions using the percentage of lost breastmilk, where datasets on rates of breastfeeding by month of age are available. The results of such studies can be used to advocate for better and adequately funded programmes for the protection, promotion and support of breastfeeding.

Improved estimation of gross primary production with NIRvP by incorporating a phenophase scheme for temperate deciduous forest ecosystems

NIRvP, the product of the remotely sensed near infrared reflectance of vegetation (NIRv) and photosynthetically active radiation (PAR), has been demonstrated to be a good proxy for terrestrial gross primary productivity (GPP) due to their strong theoretical correlation. Currently, a linear relationship with a constant slope parameter (k) is used to estimate GPP with NIRvP. However, this parameter may vary with plant phenology, potentially leading to uncertainty in GPP estimation. In this study, we hypothesized that considering the influence of phenology on k could improve the accuracy of GPP estimation. To test this hypothesis, we used pair measurements of ground eddy covariance-derived GPP and satellite-derived NIRvP across nine temperate deciduous forest sites, and compared the modeling results of two parameterization schemes: one with a constant k throughout the entire growing season (termed the global scheme) and another with dynamic k parameters across different phenophases (e.g., greenup, mature and senescence phases; termed the phenophase scheme). Our results show that relative to the global scheme, the phenophase scheme significantly improved GPP estimation with a reduction in bias by 63.71 ± 16.46%, 53.71 ± 26.17% and 32.96 ± 32.07% in the greenup, maturity and senescence phases across all study sites, respectively. Moreover, the efficiency of this improvement is meaningful in terms of the Akaike Information Criterion (AIC). Further regression analysis revealed that k varies with phenophase, which can be attributed to variations in photosynthetic capacity and canopy optical properties due to leaf aging and canopy structure development. These findings collectively improve our understanding of the influence of phenology on the GPP-NIRvP relationship and emphasize the effectiveness of using the phenophase-dependent k parameterization scheme, which would ultimately contribute to improving the accuracy of GPP estimation in temperate forest ecosystems.

A Bayesian spatially explicit estimation of daily egg production: application to anchovy in the Bay of Biscay

Biomass estimates of fish resources by the daily egg production method (DEPM) are sensitive to the high variability of the daily egg production ( P0) and egg mortality (Z) in space. This work presents a Bayesian approach to estimate these parameters. A prior distribution of Z based on literature serves to overcome the biologically implausible Z estimates that can result from frequentist approaches. In addition to the classical estimation of a single P0 over the spawning area, the Bayesian framework allows also the modelling of egg densities in space, by including either spatial random effects, smoothing functions, or kriging like models, providing insights into the spatial variability of P0. The Bayesian approach was applied to the Bay of Biscay anchovy DEPM surveys. Results showed that this Bayesian approximation solved the implausible Z problem resulting in tighter credible intervals of both P0 and Z. Overall, spatial models outperformed the non-spatial model in terms of goodness of fit and resulted in slightly different total production estimates across models for each year, with a moderate decrease on uncertainty estimates.

How much can performance measures explain of the between-cow variation in enteric methane?

Enteric CH4 produced from dairy cows contributes to the greenhouse gas emission from anthropogenic sources. Recent studies have shown that the selection of lower CH4 emitting cows is possible, but this would be simpler if performance measures already recorded on farm could be used, instead of measuring gas emission from individual cows. These performance measures could be used for selection of low emitting cows. The aim of this analysis was to quantify how much of the between-cow variation in CH4 production can be explained by variation in performance measures. A data set with 3 experiments, a total of 149 lactating dairy cows with repeated measures, was used to estimate the between-cow variation (the variation between cow estimates) for performance and gas measures from GreenFeed. The cow estimates were obtained with a linear mixed model with the diet within period effect as a fixed effect and the cow within experiment as a random effect. The cow estimates for CH4 production were first regressed on the performance and gas measures individually, and then performance and CO2 production measures were grouped in 3 subsets for principal component analysis and principal component regression. The variables that explained most of the between-cow variation in CH4 production were DMI (R2 = 0.44), among the performance measures, and CO2 production (R2 = 0.61), among gas measures. Grouping the measures increased the R2 to 0.53, when only performance measures were used, and to 0.66, when CO2 production was added to the significant performance measures. We found the marginal improvement to be insufficient to justify the use of grouped measures rather than an individual measure, since the latter avoid over fitting and simplify the model. Investigation of other measures that can be explored to increase explanatory power of between-cow variation in CH4 production is briefly discussed. Finally, the use of residual CH4 as a measure for CH4 efficiency could be considered by using either DMI or CO2 production as the sole predicting variables.

Organic Input to Titan's Subsurface Ocean Through Impact Cratering.

Titan has an organic-rich atmosphere and surface with a subsurface liquid water ocean that may represent a habitable environment. In this work, we determined the amount of organic material that can be delivered from Titan's surface to its ocean through impact cratering. We assumed that Titan's craters produce impact melt deposits composed of liquid water that can founder in its lower-density ice crust and estimated the amount of organic molecules that could be incorporated into these melt lenses. We used known yields for HCN and Titan haze hydrolysis to determine the amount of glycine produced in the melt lenses and found a range of possible flux rates of glycine from the surface to the subsurface ocean. These ranged from 0 to 1011 mol/Gyr for HCN hydrolysis and from 0 to 1014 mol/Gyr for haze hydrolysis. These fluxes suggest an upper limit for biomass productivity of ∼103 kgC/year from a glycine fermentation metabolism. This upper limit is significantly less than recent estimates of the hypothetical biomass production supported by Enceladus's subsurface ocean. Unless biologically available compounds can be sourced from Titan's interior, or be delivered from the surface by other mechanisms, our calculations suggest that even the most organic-rich ocean world in the Solar System may not be able to support a large biosphere.

Comparison of nonlinear functions to describe lactation curves for cumulative milk production in buffalo.

The aim of this study was to examine the suitability of different growth functions (linear, sinusoidal, Gompertz, Schumacher and Richards) to fit cumulative milk production data from buffalo cows. Cumulative milk production at each day in milk was calculated from two published datasets reporting (i) fortnightly test-day milk yield records of the first lactation of Murrah buffalo that had calved during 1977-2012 and (ii) the first lactation records of Jaffarabadi buffalo collected from history-cum-pedigree registers for each quinquennium between 1991 and 2010. Each function was fitted to the lactation curves using nonlinear regression procedures. The Richards and sinusoidal equations provided the smallest root mean square error values, Akaike's and Bayesian information criteria and, therefore, the best fit for the cumulative lactation curves for milk yield. The Richards equation appeared to provide the most accurate estimate of the cumulative milk production at peak milk yield. Sinusoidal and flexible classical growth functions are appropriate to describe cumulative milk production curves and estimate lactation traits in buffalo.

Nectar Characteristics and Honey Production Potential of Five Rapeseed Cultivars and Two Wildflower Species in South Korea

The growing beekeeping industry in South Korea has led to the establishment of new honey plant complexes. However, studies on honey production from each species are limited. This study aimed to assess the honey production potential of various Brassica napus cultivars and two wildflower species. The nectar characteristics of B. napus varied significantly among the cultivars. Absolute sugar concentrations differed among the cultivars, but sugar composition ratios were similar. In contrast, the amino acid content remained relatively uniform regarding percentage values, irrespective of the absolute concentrations. Estimations of honey potential production per hectare (kg/ha) resulted in the following ranking among cultivars: ‘JM7003’ (107.1) > ‘YS’ (73.0) > ‘JM7001’ (63.7) > ‘TL’ (52.7) > ‘TM’ (42.4). The nectar volume of Pseudolysimachion rotundum var. subintegrum and Leonurus japonicus increased during the flowering stage. P. rotundum var. subintegrum was sucrose-rich and L. japonicus was sucrose-dominant. Both species predominantly contained phenylalanine, P. rotundum var. subintegrum had glutamine as the second most abundant amino acid, and L. japonicus had tyrosine. The honey production potential was 152.4 kg/ha for P. rotundum var. subintegrum and 151.3 kg/ha for L. japonicus. These findings provide a basis for identifying food resources for pollinators and selecting plant species to establish honey plant complexes.

Synthesis of NaA Zeolite: Conventional Route and Green Route

The research describes a sustainable approach for the synthesis of zeolite NaA using kaolin as an alternative source of silica. The main objective of this research was to prepare NaA zeolite using metakaolin derived from kaolin from the state of Rio Grande do Norte, Brazil, as an alternative source of silica, reducing the production cost and evaluating its thermal stability. In addition, a study of the thermal stability of the zeolite and cost estimates for zeolite production were carried out. Traditional methods of zeolite synthesis, mainly through hydrothermal processes, are often associated with high costs, waste generation, and negative environmental impacts. This work addresses these concerns by exploring a more sustainable approach. The kaolin used in the study was characterized by X-ray diffraction, energy-dispersive X-ray fluorescence spectroscopy, infrared spectroscopy, and thermogravimetry. These techniques help confirm the composition and properties of the raw material. NaA zeolite was synthesized by replacing sodium silicate with metakaolin using the hydrothermal synthesis method. The NaA zeolite was characterized by XRD and IR, which helped verify its purity and structural order. The study's results demonstrated that kaolin waste mainly consists of kaolinite, which suggests that it can be effectively used as a source of silica. Furthermore, the research successfully produced low-cost NaA zeolite in a relatively short synthesis time, achieving high purity and structural order. The study highlights the potential of using kaolin waste as a sustainable source of silica for zeolite production, helping to minimize environmental impacts and reduce processing costs compared to traditional methods. This work presents a promising and sustainable method for producing NaA zeolite from kaolin waste, which has the potential to contribute to cost reduction, waste reduction, and improved environmental sustainability in zeolite production processes. This research is aligned with the broader goals of reducing the ecological footprint of industrial processes while maintaining product quality and efficiency.

Copepod egg production estimates are biased by female mortality

AbstractEgg production rate (EPR, eggs ♀−1d−1) is a key measure of the nutritional state of metazoans such as copepods. Chlorophyll concentration is most often used to index responses of copepod vital rates to ambient food, but the fits to EPR are often poor. A known but unexplored bias in EPR estimates is the interaction between lifetime reproductive schedules of adult females and their mortality. We examined this interaction for Pseudodiaptomus forbesi, an abundant sac‐spawning calanoid copepod, in the San Francisco Estuary (SFE), USA. The reproductive schedule of P. forbesi comprises a latent period followed by a generally steady rate of clutch production. We used a Bayesian approach to analyze data from two studies which included 141 individual estimates of proportion ovigerous, eggs per clutch, and mortality from 28 sampling events. Proportion ovigerous contributed 95% of the variation in EPR. Mortality was 0.01–0.73 d−1 by one method and ~ 20% higher by another. When mortality was high, most females were young, few were past the latent stage, and ~ 25% were ovigerous. Proportion ovigerous up to 75% occurred only with mortality > ~0.1 d−1. Adjusting for mortality increased estimates of proportion ovigerous by 3%–88% (median 36%) and allowed for a relationship with chlorophyll, which could not be fitted to the raw data. However, the adjustments increased uncertainty. Given the large effort required, we recommend that others investigate this phenomenon for other species and environments before this adjustment should be recommended for estimating copepod egg production.

Genetic parameters, trends, and inbreeding in a honeybee breeding program for royal jelly production and behavioral traits

An economically sustainable production of royal jelly (RJ) requires the use of genetics specifically improved for this very demanding trait. The French Royal Jelly Association has developed since 2010 a selection plan for that purpose, based on a collective data recording system and the initial seedstock of five French beekeepers. The aim of this study was to evaluate the efficiency of this collective breeding program, a decade after its concrete start. We considered three different genetic models to describe the phenotypes, hereafter named the Colony, Worker, and Queen Models. We showed that when the size and the structure of the dataset are insufficient to fit a Colony Model, fitting a Queen Model gives more understandable results for practical use of the estimated breeding values than the Worker Model. Regarding genetic parameters, we estimated moderate to high heritability values for all traits, regardless of the genetic model. Under a Queen Model, heritability estimates of RJ production were 0.19 ± 0.09 and 0.35 ± 0.13 for first and second harvests, respectively; the estimates were 0.76 ± 0.08, 0.29 ± 0.09, and 0.22 ± 0.08, respectively, for the calmness, gentleness, and spring development of the colony. We also proved that the breeding program is efficient, increasing the production at second harvest of 3.5% per year on average. Attention must, however, be paid to the evolution of inbreeding in this very small breeding population. Few genetic correlations were significantly different from zero between the traits, due to large standard errors of our estimates. It is, however, worth to note that the trends were generally favorable between all traits, which appears encouraging to improve production and behavioral traits jointly in the breeding program.

Employment and occupational prospects and Lifelong Learning in Greece

The present paper addresses employment and occupational prospects in Greece, in the period 2011-2022, highlighting the dynamic, stagnant and declining occupations and it also addresses employment and occupational prospects in the near future (2022-2030). The role that Lifelong Learning can play in an environment of abrupt changes is also discussed. The study reveals that in the period 2011-2022, the total employment rates in Greece increased by 1.0%, with the creation of 43,002 new jobs. A large number of jobs was created for general and keyboard clerks, health professionals and information and communication technology professionals but on the other hand, a large number of jobs were destructed. Therefore, the employment and occupational prospects in Greece in the near future require further attention. The estimates presented in this paper concern the time period 2022-2030, in a two-digit occupation code and they are derived from the application of the Oxford model (Oxford Global Economic Model - GEM), which is managed by NKUA, in the framework of its eLearning program. In this time period, according to relevant estimates, the total employment rates in Greece are expected to decrease by 3.4%, with a loss of 143,998 jobs in total. This negative development, that is expected to take place in an environment of increased production (estimates of the Oxford model), indicate a paradox that is a period of economic growth which is not followed by the creation of new jobs (jobless growth). In light of this evidence, employment and occupational prospects and Lifelong learning are interlinked and often considered a favored topic for researchers, practitioners, policy makers and politicians. As occupations, dynamic, stagnant or declining, include certain tasks and skills, their evolution (and mainly in the dynamic ones) provide the necessary information areas in which long term strategy of Lifelong Learning should target. However, there seems to be a distance between policy, strategy and action. The paper suggests a more careful mapping of the job market, the lifelong learning programmes and the trainees’ prospective profiles. It also addresses the need to focus on those who rarely participate in lifelong learning programmes and are considered to also be the dropout rates from formal educational processes.

Atmospheric Δ14C in the northern and southern hemispheres over the past two millennia: Role of production rate, southern hemisphere westerly winds and ocean circulation changes

The variations of atmospheric Δ14C over the past two millennia are classically attributed to changes in its production rate in the upper atmosphere, which in turn is related to changes in solar activity and the Earth's magnetic field. However, the potential contribution of atmospheric and oceanic circulation changes during this period has not been precisely quantified. This has been achieved here using a coupled climate model simulating explicitly the evolution of the different carbon isotopes, driven by a new estimate of 14C production derived from 10Be measurements, and using different production rates for each hemisphere. Our results confirm that changes in global and hemispheric atmospheric Δ14C are primarily driven by changes in production rate. The very good agreement between our results and observed atmospheric Δ14C also highlights the strong consistency of current interpretations of 10Be and 14C measurements. By contrast, the interhemispheric difference in atmospheric Δ14C is controlled by changes in the intensity of southern hemisphere westerly winds (SHWW) that impact atmosphere-ocean exchange and the upwelling of 14C depleted water masses in the Southern Ocean. Changes in deep water formation in both hemispheres or open ocean polynyas in the Southern Ocean only have a small impact on atmospheric Δ14C over that period. When driven by changes in the SHWW proportional to three existing reconstructions of the Southern Annular Mode (SAM) index, the model reproduces some key characteristics of the observed interhemispheric Δ14C gradient. These include the low values in the 15th century and the peak in the 16th century, but there are also clear differences between the experiments and Δ14C observations. This suggests that while SAM reconstructions capture some robust features in the centennial variability, large uncertainties remain.

Evaluation of three contrasting models in estimating primary production from ocean color remote sensing using long-term time-series data at oceanic and coastal sites

Accurate estimates of depth-integrated Net Primary Production (NPP, mg C m−2 d−1) and the creation of a robust climate data record of NPP for the global oceans are essential goals of the ocean color remote sensing community. Here, we take advantage of in situ NPP measurements from three long-term time-series sites, the HOT (Hawaii Ocean Time-series), BATS (Bermuda Atlantic Time-series Study) and CARIACO (Ocean Time-Series Program from the Cariaco basin), spanning over 30 years to evaluate three contrasting models in estimating NPP from ocean color remote sensing. These models for NPP estimation include the Absorption-based Model (AbPM), which relies on phytoplankton absorption coefficient, the Vertically Generalized Production Model (VGPM), which centers on chlorophyll-a concentration, and the Carbon-based Productivity Model (CbPM) centering on phytoplankton carbon. In addition to the accuracy of NPP estimation from these models, we laid great emphasis on evaluating their skills in capturing the monthly to seasonal variations and interannual trends in NPP at the three sites. Comparison with in situ NPP at all three long-term sites (∼20 years) showed that AbPM yielded the highest coefficient of determination (R2 = 0.67) and the lowest uncertainties (Bias = 0.03 and unbiased root mean square difference = 0.17). Seasonal and interannual variations apparent in the in situ NPP time-series records were best captured by AbPM. These results showcase the robust capabilities of AbPM and its superiority for global carbon cycling and climate change studies, largely because it takes into account optical and photosynthetic parameters of local phytoplankton.